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1

Influence of exogenous application of triacontanol on

various morpho-physiological and biochemical attributes

of sunflower (Helianthus annuus L.) under saline

conditions

By

Robina Aziz

M. Phil. (Botany)

A thesis submitted in partial fulfillment of the requirements

for the degree of

DOCTOR OF PHILOSOPHY

IN BOTANY

DEPARTMENT OF BOTANY University of Agriculture

Faisalabad

2015

3

DECLARATION “I hereby declare that the contents of the thesis, entitled ‘‘Influence of exogenous

application of triacontanol on various morpho-physiological and biochemical

attributes of sunflower (Helianthus annuus L.) under saline conditions’’ are product

of my own research and no part has been copied from any published source (except

the references, standard mathematical or genetic models/equation/formulae etc.). I

further declare that this work has not been submitted for award of any other

diploma/degree. The University may take action if the information provided is

found inaccurate at any stage”.

Robina

Aziz

Reg. No. 2003-

ag-510

TO,

THE CONTROLLER OF EXAMINATIONS,

UNIVERSITY OF AGRICULTURE,

FAISALABAD.

4

We, the supervisory committee, certify that the contents and form of

this thesis submitted by Robina Aziz D/O Abdul Aziz, Reg. # 2003-

ag-510 have been found satisfactory, and recommend that it be

processed for evaluation by the external examiner(s) for the award of

the degree.

SUPERVISORY COMMITTEE

CHAIRMAN : ________________________________

(Dr. Muhammad Shahbaz)

MEMBER :

_________________________________

(Dr. Muhammad Arfan)

MEMBER :

_________________________________

(Dr. Bushra Sadia)

DEDICATIONS

5

To ALLAH &

The Holy Prophet Hazrat MUHAMMAD

Peace be Upon Him &

My Parent Whose always supported me through

prayers, affections and care

ACKNOWLEDGMENTS All my praises and appreciations are for Almighty ALLAH for bestowing upon me

the wisdom and great potential for successful accomplishment of this manuscript. I

offer my humblest salutations upon the Holy Prophet MUHAMMAD (Peace Be

Upon Him), who is forever, a source of illumination of souls for all mankind.

It is a sense of immense pleasure to express my heartiest gratitude to my esteemed

supervisor Dr. Muhammad Shahbaz, Assistant Professor, University of

Agriculture, Faisalabad. Without his guidance, proper direction and support, it

would have never been possible for me to complete my Ph.D work and manuscript.

I am also greatly thankful to my supervisory committee, Dr. Muhammad Arfan,

Lecturer, Department of Botany, University of Agriculture, Faisalabad and Dr.

Bushra Sadia, Assistant Professor, Department of University of Agriculture,

6

Faisalabad for their guidance and kind cooperation provided during the course of

my study.

This is a great opportunity to thank to Prof. Dr. Abdul Wahid, Chairman

Department of Botany, University of Agriculture, Faisalabad, under whose

headship my research proved to be a smooth job and I am also thankful to my all

respectable teachers for their guidance.

I extend my thanks to all fellows, juniors and seniors to being good with me. I am

very thankful to our lab attendant Mr. Mahboob for providing me research

apparatus at a time. I have a special thanks to my best friends for their love,

affections and best wishes.

I have no words to thanks my loving and gorgeous parents, dearest brothers and

sisters who always wish to see me successful and prosperous. I never can pay for

their endless love and care. I am also thankful to all family child for their innocent

love and prayers.

I gratefully acknowledge the financial support by Higher Education Commission

for my Ph.D studies (PIN. No. 117-7760-BM7-132). I am thankful to all members

of HEC dealing with my indigenous scholarship. They always sent me funds well

in time and have a good behavior.

Robina Aziz

CONTENTS

Chapter

No. TITLE

Page

No.

Acknowledgments

List of tables

List of figures

ABSTRACT

7

1 INTRODUCTION 1

2 REVIEW OF LITERATURE 9

3 MATERIALS AND METHODS 35

4 RESULTS 41

5 DISCUSSION 104

6 GENERAL DISCUSSION 114

7 SUMMARY 120

8 LITERATURE CITED 122

DETAILED CONTENTS

1.

INTRODUCTION…………………………………………………...……………

…..…..1

2. REVIEW OF

LITERATURE………………………………………………………..…..9

2.1 Causes of

salinity……………………………………………………………………....…9

2.2 Effects of salinity on

plants……………………………………………….…………....10

2.2.1 Primary

effects………………………………………………………………................11

2.2.1.1 Osmotic

stress……………………………………………………..............................11

2.2.1.2 Ionic

stress………………………………………………………...……..…………..12

8

2.2.2 Salt induced secondary

effects………………………………………………...……....13

2.2.2.1 Oxidative

stress……………………………………………..………………….…….13

2.2.2.2 Nutritional

imbalance…………………………………………………..……...…..…14

2.2.2.3 Hormonal

inbalance………………………………………………………….............15

2.2.2.4 Osmoprotectant

production…………………………..………………………….…...16

2.3 Triacontanol

(TRIA)………………………………………………………….…….…..17

2.3.1 Physiological activity of

TRIA………………………………………………………...18

2.3.2 Mode of action of

TRIA……………………………………………...…………….….19

2.3.3 TRIA role in

plants……………………………………………………………........…21

2.3.3.1 Role of TRIA on morphological

attributes…………………………………….…..21

2.3.3.2 Effect of TRIA on physiological and biochemical

attributes………...………….. 22

2.3.3.3 TRIA and yield

attributes……………………………………………………… .…...23

2.3.4. TRIA and abiotic

stress……………………………………………………………. ....25

2.3.5 Role of TRIA under salinity

stress……………………………………………….. …...26

2.3.5.1

Presowing……………………………………………………………..............

..........26

9

2.3.5.2 Foliar application of

TRIA………………………………………………….... .…….27

2.3.5.3 Root-growing medium application……………………………………...……

…...30

2.4

Sunflower………………………………………………………………………..……

...31

2.4.1 Importance of

sunflower……………………………………...…………..……………31

2.4.1.1 Nutritional aspects of

sunflower…………………..…………………………...….....31

2.4.1.2 Economic

importance……………………………………………………………...32

2.4.1.3 Sunflower and Salinity

stress……………………………………………….....……..33

3.0 MATERIAL AND

METHODS……………………………..……….…………….......35

3.1 Meteorological

data…………...…….……………………………………………..…...35

3.2 Experiment

……………………………………………………………..…………...….35

3.3 Water relations

parameters…………………………………………..……………......36

3.3.1 Leaf water potential (Ψw)

…………………………………………………………….36

3.3.2 Leaf osmotic potential (Ψs)

……………………………………………….…...….…..36

3.3.3 Leaf turgor potential (Ψp)………………………

…………………………......………36

3.3.4 Relative water content (RWC)………………

………………………………...….…...36

10

3.4 Gas exchange

attributes……………………………………………..………..….........37

3.5 Chlorophyll

fluorescence…………………………………………………….......….....37

3.6 Photosynthetic

pigments…………………………………………………….......….…37

3.7 Mineral

nutrients…………………………………………………..………...…….…..38

3.8 Determination of Sodium (Na+ ), Potassium (K+ ) and Calcium (Ca2+)

………….....38

3.8.1 Chloride (Cl-) determination

……………....................................................................38

3.9

Osmolytes…………………………………………………………………..…....…

…..38

3.9.1 Leaf free proline content

……………………………………………...……….38

3.9.2 Glycinebetaine (GB)

content……………………………..…………………....39

3.9.3 Total soluble proteins

………………………………………….……………....39

3.10 Antioxidents determination

………………………………………………………..…39

3.10.1 Peroxidase (POD) and Catalase (CAT)

………………………………..….…39

3.10.2 Superoxide Dismutase (SOD)

……………………………………..………....40

3.10.3Glutathione reductase (GR)

…………………………………………………..40

3.11 Yield

attributes………………………………………………………………......….…40

11

3.12 Statistical

analysis…………………………………...………………….…....……..…40

4.0

RESULTS……………………………………………………..……………….…..

……41

4.1 Shoot fresh

weight…………………………………………….……………………........41

4.2 Root fresh

weight……………………………………………….……………..................41

4.3 Shoot dry

weight………………………………………………….……………………...45

4.4 Root dry

weight…………………………………………………..…………………..….45

4.5 Shoot

length………………………………………………..…………………...……......45

4.6 Root

length………………………………………………………………..……………..49

4.7 Water potential

(Ψw)…………………………………………….……………................49

4.8 Leaf osmotic potential

(Ψs)……………………………………….…..............................49

4.9 Leaf turgor

potential…………………………………………………………….…….....53

4.10 Relative water contents

(RWC)………………………………………...........................53

4.11 Chlorophyll

a…………………..……………………………………………….………57

4.12 Chlorophyll

b…..…………………………………………………………….................57

4.13 Chlorophyll a/b

ratio……..……………………………………………..........................57

12

4.14 Net CO2 assimilation rate

(A)……..……………………………………………………57

4.15 Transpiration rate

(E)……..…………………………………………….........................62

4.16 Stomatal conductance

(gs)……………...…………………………………….………....62

4.17 Sub-stomatal CO2 concentration

(Ci)…………………………………………………62

4.18 Ci/Ca

ratio……...…………….…….................................................................................62

4.19 Water use efficiency

(A/E)…..……………………………………………………....….68

4.20 Non-photochemical quenching

(qN)………..………………………………………...68

4.21 Photochemical quenching

(qP)……..……………………………………….................68

4.22 Non-photochemical quenching excition

(NPQ)…………………………….………..…72

4.23 Electron transport rate

(ETR)……………………………………………..….................72

4.24 Efficiency of photosystem II

(Fv/Fm)…………………………………………………...72

4.25 Free

proline………………………………………………………………………….....72

4.26 Glycinebetaine (GB)………………………………………

……………………….…78

4.27 Total soluble

protein………………………………………………………………..…78

4.28 Activity of peroxidases

(POD)…………………………………….…………………..78

4.29 Activity of Catalase

(CAT)…………………………………………………...…...…..82

13

4.30 Activity of superoxide dismutase

(SOD)…………………………………….…..........82

4.31 Activity of Glutathione reductase

(GR)……………………………………….....…...85

4.32 Shoot Na+

.……………………………………………………………...........................85

4.33 Root

Na+………………………………………………………………...........................85

4.34 Shoot

K+…………………………………………………………...................................90

4.35 Root

K+………………………………………………………………………………....90

4.36 Shoot

Ca2+…………………………………………………………………….……...…90

4.37 Root

Ca2+………………………………………………………..……………………...94

4.38 Shoot

Clˉ……………………………………………………..………………................94

4.39 Root

Clˉ…………………..…………………………………………………………..…97

4.40 Number of achenes

/plant….….……………………………..………….................…97

4.41 Achene yield

/plant…...……………………………………....……………………....97

4.42 100-achene

weight…..………………………………………………………...............101

5.

DISCUSSION………………………………………………………………………

…...104

6. GENERAL

DISCUSSION…………………………………………………..…………114

14

CONCLUSIONS………………………………………………………….…

….…118

FUTURE

PROSPECTS............................................................................................119

7.

SUMMARY..................................................................................................................

......120

8. LITERATURE

CITED…………………………………………………………….......122

LIST OF TABLES

Title

No. Title

Page

No.

4.1

Mean squares from analysis of variance of data for growth and

water relations attributes of sunflower (Helianthus annuus L.)

cultivars when plants were treated with foliar application of

triacontanol at different growth stages under saline conditions.

42

4.2

Mean squares from analysis of variance of data for water

relations, chlorophyll contents and gas exchange attributes of

sunflower (Helianthus annuus L.) cultivars when plants were

treated with foliar application of triacontanol at different growth

stages under saline conditions.

54

4.3

Mean squares from analysis of variance of data for gas exchange

attributes and chlorophyll florescence of sunflower (Helianthus

annuus L.) cultivars when plants were treated with foliar

65

15

application of triacontanol at different growth stages under

saline conditions.

4.4

Mean squares from analysis of variance of data for leaf free

proline, glycinebetaine, total soluble proteins, activities of POD,

CAT, SOD and GR of sunflower (Helianthus annuus L.)

cultivars when plants were treated with foliar application of

triacontanol at different growth stages under saline stress.

76

4.5

Mean squares from analysis of variance of data for shoots and

roots mineral nutrients and yield attributes of sunflower

(Helianthus annuus L.) cultivars when plants were treated with

foliar application of triacontanol at different growth stages under

saline conditions.

88

4.6

Comparison of all attributes of sunflower (Helianthus annuus L.)

cultivars with respect to the foliar application of triacontanol

levels at different growth stages under saline conditions.

103

LIST OF FIGURES

Figure

No. Figure Name

Page

No.

3.1 Materological data during the conduction of experiments

in 2012. 35

4.1 a

Shoot fresh weight of sunflower (Helianthus annuus L.)

cultivars when plants were treated with foliar application

of triacontanol at different growth stages under saline

conditions.

43

4.1 b

Shoot fresh weight comparison of two sunflower

(Helianthus annuus L.) cultivars when plants were

treated with foliar application of triacontanol at different

growth stages under saline conditions.

43

4.2 a

Root fresh weight of sunflower (Helianthus annuus L.)



conditions.

44

Root fresh weight comparison of two sunflower


16

4.2 b treated with foliar application of triacontanol at different


44

4.3 a

Shoot dry weight of sunflower (Helianthus annuus L.)



conditions.

46

4.3 b

Shoot dry weight comparison of two sunflower




46

4.4 a

Root dry weight of sunflower (Helianthus annuus L.)



conditions.

47

4.4 b

Root dry weight comparison of two sunflower




47

4.5 a

Shoot length of sunflower (Helianthus annuus L.)



conditions.

48

4.5 b

Shoot length comparison of two sunflower (Helianthus


application of triacontanol at different growth stages

under saline conditions.

48

4.6 a

Root length of sunflower (Helianthus annuus L.)



conditions.

50

4.6 b

Root length comparison of two sunflower (Helianthus




50

4.7 a

Leaf water potential of sunflower (Helianthus annuus

L.) cultivars when plants were treated with foliar



51

Leaf water potential comparison of two sunflower

17

4.7 b




51

4.8 a

Leaf osmotic potential of sunflower (Helianthus annuus




52

4.8 b

Leaf osmotic potential comparison of two sunflower




52

4.9 a

Leaf turgur pressure of sunflower (Helianthus annuus




55

4.9 b

Leaf turgor pressure comparison of two sunflower




55

4.10 a

Leaf relative water contents of sunflower (Helianthus




56

4.10 b

Leaf relative water content comparison of two sunflower




56

4.11 a

Chlorophyll a of sunflower (Helianthus annuus L.)



conditions.

58

4.11 b

Chlorophyll a comparison of two sunflower (Helianthus




58

4.12 a

Chlorophyll b of sunflower (Helianthus annuus L.)



conditions.

59

18

4.12 b

Chlorophyll b comparison of two sunflower (Helianthus




59

4.13 a

Chlorophyll a/b ratio of sunflower (Helianthus annuus




60

4.13 b

Chlorophyll a/b ratio comparison of two sunflower




60

4.14 a

Net CO2 assimilation rate of sunflower (Helianthus




61

4.14 b

Net CO2 assimilation rate comparison of two sunflower




61

4.15 a

Transpiration rate of sunflower (Helianthus annuus L.)



conditions.

63

4.15 b

Transpiration rate comparison of two sunflower




63

4.16 a

Stomatal conductance of sunflower (Helianthus annuus




64

4.16 b

Stomatal conductance comparison of sunflower




64

4.17 a

Sub-stomatal CO2 concetration of sunflower (Helianthus




66

19

4.17 b

Sub-stomatal CO2 concentration comparison of

sunflower (Helianthus annuus L.) cultivars when plants

were treated with foliar application of triacontanol at

different growth stages under saline conditions.

66

4.18 a

Ci/Ca ratio of sunflower (Helianthus annuus L.) cultivars

when plants were treated with foliar application of

triacontanol at different growth stages under saline

conditions.

67

4.18 b

Ci/Ca ratio comparison of two sunflower (Helianthus




67

4.19 a

Water use efficiency of sunflower (Helianthus annuus




69

4.19 b

Water use efficiency comparison of two sunflower




69

4.20 a

Co-efficient of non-photochemical quenching (qN) of




70

4.20 b

Co-efficient of non-photochemical quenching (qN)

comparison of two sunflower (Helianthus annuus L.)



conditions.

70

4.21 a

Photochemical quenching (qP) of PSII of sunflower




71

4.21 b

Photochemical quenching (qP) of PSII comparison of

two sunflower (Helianthus annuus L.) cultivars when

plants were treated with foliar application of triacontanol

at different growth stages under saline conditions.

71

4.22 a

Non-photochemical qauencing (NPQ) of sunflower



20

growth stages under saline conditions. 73

4.22 b

Non-photochemical qauencing (NPQ) comparison of




73

4.23 a

Electron transport rate (ETR) of sunflower (Helianthus




74

4.23 b

Electron transport rate (ETR) comparison of two




74

4.24 a

Efficiency of PSII (Fv/Fm) of sunflower (Helianthus




75

4.24 b

Efficiency of PSII (Fv/Fm) comparison of two sunflower




75

4.25 a

Free proline content of sunflower (Helianthus annuus




77

4.25 b

Free proline content comparison of two sunflower




77

4.26 a

Glycinebetaine content of sunflower (Helianthus annuus




79

4.26 b

Glycinebetaine content comparison of two sunflower




79

Total soluble protein of sunflower (Helianthus annuus


21

4.27 a application of triacontanol at different growth stages


80

4.27 b

Total soluble protein comparison of two sunflower




80

4.28 a

Activity of peroxidase (POD) enzyme of sunflower




81

4.28 b

Activity of peroxidase (POD) enzyme comparison of




81

4.29 a

Activity of catalase (CAT) enzyme of sunflower




83

4.29 b

Activity of catalase (CAT) enzyme comparison of two




83

4.30 a

Activity of superoxide dismutase (SOD) of sunflower




84

4.30 b

Activity of superoxide dismutase (SOD) comparison of




84

4.31 a

Activity of glutathione reductase (GR) of two sunflower




86

4.31 b

Activity of glutathione reductase (GR) comparison of




86

Shoot sodium content of sunflower (Helianthus annuus


22

4.32 a application of triacontanol at different growth stages


87

4.32 b

Shoot sodium content comparison of two sunflower




87

4.33 a

Root sodium content of sunflower (Helianthus annuus




89

4.33 b

Root sodium content comparison of two sunflower




89

4.34 a

Shoot potassium content of sunflower (Helianthus




91

4.34 b

Shoot potassium content comparison of two sunflower




91

4.35 a

Root potassium content of sunflower (Helianthus annuus




92

4.35 b

Root potassium content comparison of two sunflower




92

4.36 a

Shoot calcium content of sunflower (Helianthus annuus




93

4.36 b

Shoot calcium content comparison of two sunflower




93

Root calcium content of sunflower (Helianthus annuus

23

4.37 a




95

4.37 b

Root calcium comparison of two sunflower (Helianthus




95

4.38 a

Shoot chloride content of sunflower (Helianthus annuus




96

4.38 b

Shoot chloride content comparison of two sunflower




96

4.39 a

Root chloride content of sunflower (Helianthus annuus




98

4.39 b

Root chloride content comparison of two sunflower


treated with foliar application triacontanol at different


98

4.40 a

Number of achene per plant of two sunflower




99

4.40 b

Number of achene per plant comparison of two


were treated with foliar application triacontanol at


99

4.41 a

Achene yield per plant of two sunflower (Helianthus


application triacontanol at different growth stages under

saline conditions.

100

4.41 b

Achene yield per plant comparison of two sunflower




100

4.42 a

100-achene weight of two sunflower (Helianthus annuus


24

application triacontanol at different growth stages under

saline conditions.

102

4.42 b 100-achene weight comparison of two sunflower




102

ABSTRACT

In the light of potential role of newly introduced potential growth regulator

triacontanol (TRIA) under saline regimes, experiments were performed on two

sunflower cultivars SMH-907 and SMH-917. Both sunflower cultivars were grown

in sand medium supplemented with full strength Hoagland’s nutrient solution under

control (0 mM NaCl) and saline (150 mM NaCl) conditions. Three TRIA levels [0

(water spray), 50 and 100 μM] were applied as foliar spray at three growth stages

i.e. vegetative, flowering and veg. + flowering stages. Imposition of salinity

potentially reduced shoot and root biomass (fresh and dry weights) and their

lengths, chlorophyll pigments (Chl. a and b), gas exchange attributes (net CO2

assimilation rate (A), stomatal conductance (gs), sub-stomatal conductance (Ci),

Ci/Ca ratio, water use efficiency (WUE) ), electron transport rate (ETR), enzyme

activity of peroxidases (POD) and superoxide dismutase (SOD), shoot and root K+

and Ca2+ contents and yield attributes (number of achenes per plant, achene yield

per plant and 100-achene weight) while enhanced accumulation of proline,

glycinbetaine and shoot and root Na+ and Clˉ contents in both sunflower cultivars

(SMH-907 and SMH-917) at three growth stages. Salt stress did not alter the chl.

a/b ratio, transpiration rate (E), co-efficient of non-photochemical quenching (qN),

photochemical quenching (qP), non-photochemical quenching exiton (NPQ),

efficiency of PS II (Fv/Fm), total soluble protein and activity of catalase (CAT) in

both sunflower cultivar. Foliar applied TRIA enhanced the growth attributs, water

potential, turgor potential, chlorophyll pigments (chl. a and b), net CO2 assimilation

rate (A), stomatal conductance (gs), water use efficiency (WUE), chlorophyll

fluorescence, free proline, glycinebetaine, activity of peroxidases (POD),

superoxide dismutase (SOD), glutathione reductase (GR), shoot and root K+ and

Ca2+ contents and yield while osmotic potential, NPQ and shoot and root Na+ and

Clˉ contents declined in both sunflower cultivars. The TRIA level 50 μM was more

25

effective in enhancing A and shoot Ca2+ in both sunflower cultivars at flowering

and veg. + flowering stages. Overall TRIA was more effective when applied

flowering and veg. + flowering growth stages. Of both cultivars the cv. SMH-917

showed more sensitivity in osmotic potential, chl. a, chl. b, A, WUE and shoot Na+

contents under saline conditions.

26

Chapter 1

INTRODUCTION

Soil microbial biomass, microbial population and soil enzymes activity play

important function in soil. Soil microbial biomass defined by Jenkinson and Ladd

(1981) is the living constituent of soil organic matter, excluding roots of plants and

soil animals having size greater than 5 x 103 µm3. It comprises numerous bacterial

and fungal species along with larger soil microorganisms including protozoa, algae

and yeast. Assessment of soil microbial biomass provides a mean of estimating the

response of microbes to the changes in soil management operations (McGrath et

al., 1995; Dai et al., 2004). For sustainable agro-ecosystem, soil microbial biomass

and biological productivity are most essential (Singh and Ghoshal, 2010). Soil

microbial biomass comprises only 2-6 % of organic matter, but being highly

mobile constituent it plays key role in nutrient cycling (Anderson and Domsch,

1980) and it help in flow of energy (Bardegu et al., 1997; Kang et al., 2012). It acts

as soil ecological marker due to its active involvement in nutrient release and soil

structure formation (Smith and Paul, 1990). Microbial biomass plays a vital role in

enzymes activity so it acts as best indicator of changes taking place in soil

(Gonzales et al., 2007). However, continuous application of anthopogenic

chemicals exerts lethal effect on soil microorganisms and microbial biomass.

Vischetti et al. (2002) reported 20% decrease in microbial biomass carbon by the

application of 50% dose of imazamox. Perucci et al. (2000) observed injurious

effect of rimsulfuron and imazethapyr herbicide on soil microbes when applied at

field and ten times of field rates. El-Ghamry et al. (2000) applied four levels of

chlorsulfuron herbicide (control, 0.01, 0.1 and 1.0 μg g-1) to see its effect on

27

microbial biomass carbon and observed significant decline in it during initial 10

days where herbicide was applied at 0.1 and 1 μg/g than control (Ljiljana et al.,

2011).

Soil microorganisms perform essential functions in soil so act as marker of

soil quality (Bolter et al., 2002; Scholter et al., 2003). Soil microbes cause

degradation of pesticides by producing enzymes and help in regulating soil

enzymes activity (Speir and Ross 1978; Chaudhry et al., 2008). Herbicides exert

harmful effect on soil microorganisms and cause disturbance in soil functions viz.

decomposition of organic matter and nitrogen transformations (Hutsch, 2001).

Bacteria are single celled microorganisms and present in abundant quantity

in soil (Schulz and Jørgensen, 2001) and reproduce very fast and become double

within each twenty minutes (Eagon, 1962). They perform essential functions in soil

such as nitrification, nitrogen fixation, organic matter decomposition and convert

organic phosphorus into inorganic form. Allievi and Gigliotti (2001) noticed death

of bacteria due to sulfonyl urea herbicide. Bromoxynil herbicide resulted decrease

in nitifying bacteria due to severe sensitivity of these bacteria to this herbicide

(Ratnayak and Audus, 1987; Edward et al., 1993). Pampalha and Oliveira (2006)

also confirmed suppression in ammonium oxidizing bacteria due to bromoxynil.

Actinomycetes being facultative anaerobe produce enzymes that assist in

lignin degradation and compost formation (Holt et al., 1994). Actinomycetes have

the ability of degrading recalcitrant (Crawford, 1978; Warren, 1996; Jererat and

Tokiwa, 2001). They are important source of enzymes and save the plants from

phytopathogens (Alderson et al., 1993; Doumbou et al., 2002). Omar and Abdel-

28

Sater (2000) observed restricted population of bacteria and actinomycetes by the

application of high dose of bromoxynil herbicide.

Fungi help in promoting root branches and enhance nutrients uptake

because of their large surface area. Myccorrhizal fungi help plants in phosphorus

uptake. Fungi protect plants from drought and diseases through their hyphae.

Fungal hyphae help in binding the soil particles, therefore increase pore space and

water retention. Fungi also liberate phosphatase enzymes in soil (Singh and Dileep,

2005. Ayansino and Oso (2005) observed 40% decline in fungal population by

atrazine application. Application of combined mixture of bromoxynil and

prosulfuron (1ppm and 100ppm) showed 43 % and 96% decline respectively, in

fungi population (Pampulha and Oliveria, 2006). Herbicides harm physiologically

to soil microorganisms by creating alteration in biosynthetic mechanism (Milosevic

and Govidarica, 2002). Nutrients mineralization and enzymes activity in the soil

are badly affected by herbicides application and indicate signal of stress (Anderson

and Domsch, 1980; Lupwayi et al., 2006).

Enzyme activity is the only way which can describe the general condition of

soil microbial population (Margesin and Schinner, 1997; Liang et al., 2003).

Nutrient transformations in soils are carried out by the enzymes because they

convert the nutrients into plant available forms (Degens, 1998; Gainfreda et al.,

2002; Gainfreda and Ruggiero, 2006). Soil bound enzymes play vital role in the

transfer of substrates to cells and produce intermediate metabolites that help in

mediating cleave-off of larger molecules of substrate (Rao et al., 2010). The

29

activity of soil enzymes help in the restoration and recovery of pesticides polluted

soils (Nannipieri and Bollag, 1991; Sutherland et al., 2002). Biochemical reactions

in soil are carried out due to catalytic activity of soil enzymes (Kiss et al., 1978)

and continuous synthesis, accumulation and decomposition of enzymes in soil play

vital role in nutrient transformations (Tabatabai, 1994).

Generally, the soil urease originates from microbes (Pollaco, 1977) and

plants and exists as intra and extracellular enzyme (Mobley and Hausinger, 1989).

Urease enzyme is involved in the hydrolysis of urea to ammonium. Sarathchandra

et al. (1984) observed urease activity in many fungi and bacteria. He et al. (1976)

observed 10-30% inhibition in urea hydrolysis by phenyl urea herbicides (linuron,

diuron and monuron). Chlorothalanil application exhibited 37.7% decline in the

activity of urease (Yu et al., 2011). Niu et al. (2011) observed inhibition in urease

activity by applying higher dose of chlorpyrifos. Punitha et al. (2012) reported

considerable inhibition in the activity of urease and phosphatase enzymes due to

acetamiprid application.

Dehydrogenase occurs in all microbial cells, so it is considered as a marker

of microbial activity (Quilchano and Maranon, 2002; Stepniewska and Wolinska,

2005) and is used for the measurement of electron transfer during carbon substrate

utilization, therefor, reflects cumulative biological activity in soil (Locke and

Zabolowicz, 2004). It causes oxidation of organic matter by transferring electrons

and protons from the substrate to acceptor (Glinski and Stepniewski, 1985). Being

an integral part of soil microorganisms, the dehydrogenases act as indicators of soil

30

microbial activity (Beyer et al., 1992; Berzezinska et al., 1998). Dehydrogenase

activate the metabolic activity of facultative anaerobes under oxygen deficient

conditions (Galstian and Awungian, 1974). Researchers (Saha et al., 2012) reported

55 % increase in the activity of dehydrogenase by field rate application of alachlor,

while 5 times and 10 times higher doses exhibited 58 % and 59 % increase,

respectively in the activity of said enzyme. Radiojevic et al. (2012) noticed 42.7%

decrease in dehydrogenase activity by nicosulfuron herbicide @ 3.0 µg g-1.

Combined mixture of bromoxynil + prosulfuron showed 80 % inhibition in

dehydrogenase activity (Pampalha and Oloveria, 2006). Pandey and Singh (2006)

recorded 17% decrease in dehydrogenase activity by Quinalphos application.

Fonofos application @ 1.0 mg kg-1fonofos resulted 5-21 % decline, while ten times

higher application rate showed 44 % reduction in the activity of this enzyme than

control (Stepniewska et al., 2007).

Phosphatase changes the organic phosphorus into inorganic form and makes

it available to plants (Schneider et al., 2001) and are added in soil due to active

exudation or through cell lyses (Tadano et al., 1993). Phosphatase help in ester

bond hydrolysis and attachment of phosphorus to the carbon (C-O-P bonds) of soil

organic matter which in turn release inorganic phosphorus from roots and other

organic materials (Harrison, 1983). The impact of herbicide on soil enzymes is a

key factor which describes the potential toxicity of herbicide in soil (Quilchano and

Maranon, 2002). Sannio and Gianfreda (2001) reported 98% reduction in the

activity of phosphatase enzyme due to glyphosate application. Voets et al. (1974)

noticed 61.8% decline in alkaline phosphatase activity due to atrazine application.

31

Punitha et al. (2010) observed 74% decreases in alkaline phosphates activity due to

acetamipred application.

Main reasons for low crop production in Pakistan are water deficiency,

imbalanced use of fertilizers and infestation of weeds. Shah et al. (2005) reported

20 - 45 % drop in wheat yield due to weeds. Because of high reproduction

potential, weeds fight with major crop for space, nutrients and water. Differeny

methods (mechanical and chemical) are used for weed control. But due to

unavailability of labour at the time of need, the use of chemicals has become

inevitable.

Buctril super (bromoxynil) is a post emergence herbicide used for

controlling broad leaf weeds in wheat (Cupples et al., 1995). It blocks the electron

transport in photosystem-II, during photosynthesis. In Pakistan this herbicide is

being used most frequently for weeds control in wheat. Intensive application of this

herbicide created anxiety in scientists. Despite usefullness of this herbicide it exerts

toxic effect on soil microbes. Different processes (mineralization and nitrification

etc.) depend on balanced equilibrium among different groups of soil

microorganisms. Few studies highlighted the injurious effects of buctril super on

soil enzymes and microbes (Maria et al., 2008). As in Pakistan this herbicide is

being used most frequently in wheat fields, but data are scarce about the effect of

this herbicide on soil microbial activities and soil health. This study was conducted

with the following objectives:

32

1. Quantification of the effect of different levels of Buctril super herbicide on

microbial biomass carbon, microbial biomass nitrogen and microbial

biomass phosphorus.

2. Determination of Buctril super herbicide effect on soil urease, alkaline

phosphatase and dehydrogenase enzymes activity.

3. Evaluation of Buctril super effects on soil bacteria, fungi and

actinomycetes.

33

Chapter 2

REVIEW OF LITERATURE

Sustainable agriculture mainly depends on the extensive use of

agrochemicals comprising of fertilizers and pesticides. Anthropogenic chemicals

addition left injurious effect on beneficial soil organisms, soil enzymes activity and

on physical and chemical properties of soil. Microorganisms are involved in

organic matter decomposition, nutrient cycling, nitrogen transformation and are

also helpful in degrading the pesticides added to the soil. Many studies stated that

only ˂ 0.3 % part of the applied pesticide had reached to the target pests and 99.7

% goes to the soil environment leading to its direct contact with soil

microorganisms ultimately causing the death of soil microbes. Due to this, soil

loses its potential for sustainable crop production. Rapidly increasing anxiety

regarding soil pollution has highlighted the addition of consciousness and use of

different products that do not have any harmful effect on soil microbes, enzymes

activities and will not pollute the environment. This review covers the recent

information about the effect of herbicides on microbial biomass, microbial

population, enzymes activities biochemical process in soil such as nitrification,

nitrogen fixation, phosphate solubilization, organic matter decomposition.

Microorganisms perform much important function in soil. Fungi convert

dead organic matter in to their biomass, CO2 and organic acids. They also cause

breakdown of organic matter containing very hard woody material. Fungi obtain

nutrients from organic matter and immobilize them and keep them in soil. They

have the capacity to decompose highly resistant compounds such as proteins,

34

cellulose and lignin. Actinomycetes also play vital role in degradation of all types

of highly complex organic substances such as polysaccharides, fats and proteins as

well as humus. All the residues are initially attacked by bacteria and fungi and then

by actinomycetes because of their low growth and activity. Different enzymes

perform different function in soil. Urease acts as a catalyst during the hydrolysis of

urea to carbon dioxide and ammonia. This mechanism of reaction is based on the

development of carbamate as intermediate. Dehydrogenase is involved in

biological oxidation of soil organic matter because it transfers H+ from substrate to

acceptors. Phosphatases help in catalyzing the hydrolysis of organic form of

phosphorus to inorganic phosphorus and made it available to plants for subsequent

use. Bromoxynil (3,5-dibromo-4-hydroxybenzonitrile) is commonly used post-

emergence herbicide in order to control broad leave weeds in wheat (Triticum

aestivum L.). About 18000 to 22000 tons of bromoxynil herbicide was being

applied annually in United States of America (Gianessi and Cressida, 2000).

Because of ban on atrazine herbicide usage, bromoxynil herbicide is being used as

alternate promoting it extensive use in future. Repeated use of bromoxynil

herbicide exerted potential toxic effect on soil environment (Follak et al., 2005).

These herbicides are highly toxic for soil microbes. Ma et al. (2007) experienced

deleterious effect of bromoxynil herbicide on algae during the examination of the

effect of six herbicides on five aquatic algae. Detectable quantity of bromoxynil

herbicide was found in blood plasma of 19.3 % people of Canada living in rural

areas (Semchuk et al., 2003). From one day to few months the half life of

bromoxynil herbicide in soil has been reported by (Golovleva et al., 1988; Kjaer et

al., 2003). Physico-chemical characteristics of soil such as air, moisture,

35

temperature, organic matter contents and pH affect bromoxynil biodegradation in

soil (Perucci et al., 2000). Soil microorganisms such as Desulfitobacterium

chlororespirans use chlorohydroxybenzoate under well aerated conditions as

electron acceptor for their growth (Sanford et al., 1996). Bromoxynil like

brominated compounds are susceptible to degradation under anaerobic environment

and Desulfitobacterium chlororespirans cause their mineralization/degradation in

such environment. Holtze et al. (2008) conducted an experiment using pure culture

of bacteria and observed that bacteria attack on the nitrile group of bromoxynil

herbicides. But the substituent site in their molecule has a great effect on their

biodegradation through enzymes that causes nitrile transformation. Soil

microorganisms that are involved in bromoxynil degradation synthesize enzymes of

two types including nitrilase which convert nitriles to their relevant acids (Dale and

Hampson, 1995) and nitrile hydratase which transform nitriles into amides (Věková

et al., 1995). Cleaning of this herbicide from soil through soil microorganisms is

inevitable. If the herbicide is capable of stimulating enzymes production that have

the potential to detoxify the herbicide then quick degradation of herbicide will take

(Gainfreda and Rao, 2002).

2.1 EFFECT OF HERBICIDES ON MICROBIAL BIOMASS

Microbial biomass consisting of bacteria, fungi, actinomycetes and other

soil microorganisms can be employed for the quantification of the mass of the

living fraction of soil organic matter. In soil, the microbial biomass takes part in

soil organic matter decomposition for the production of nutrients and carbon

dioxide (CO2) and increase their availability to plants (Cookson et al., 2008).

36

The soil microbial biomass consists of living portion of the soil organic

matter, without plant roots and soil microorganisms having more than 5 mm3 size.

It includes several species of actinomycetes, bacteria and fungus as well as yeast,

algae and protozoa. Estimation of soil microbial biomass (carbon, nitrogen and

phosphorus) gives the idea about the collective response of microbial diversity

towards the alteration in the soil management processes (McGrath et al., 1995; Dai

et al., 2004). Microbial biomass consists of 2-6 % of soil organic matter but

because of being extremely mobile component of soil organic matter, it performs

main function in nutrients transformations (Anderson and Domsch, 1980). Soil

microbial biomass consists of considerable amount of essential elements including

nitrogen, phosphorus, carbon and calcium (Bardgett et al., 1997). It serves as

ecological indicator of soil due to its active participation in nutrients

transformations and because of key role in the formation of soil structure (Smith

and Paul 1990). Organic matter transformation mediated by soil microbial biomass

has confirmed that it acted as a supply of essential nutrients in soil with low

nutrients (Kang et al., 2012).

During organic matter decomposition, the soil microbial biomass act as a

major driving force and is oftenly used as primary indicator of changes in soil

physico-chemical properties as a result of anthropogenic chemicals induced stress

in the soil environment (Baaru et al., 2007). Soil microorganisms comprise about

quarter of whole living biomass of the earth and carry out essential nutrients

transformations and influence accessibility of nutrients as well as soil quality and

37

health (Mungendi et al., 2007). Therefore, agro-ecosystem productivity is mainly

dependent on microbial biomass activity (Friedel et al., 1996).

Many studies described positive as well as injurious impacts of different

herbicides on soil microbial biomass. Different researchers found that application

of four levels of chlorsulfuron herbicide (control, 0.01, 0.1 and 1 μg g-1) showed

significant decrease in microbial biomass carbon and nitrogen during initial 10 days

in soils where herbicide was applied at 0.1 and 1 μg/g as compared to the control

and they also observed substantial increase in C:N ratio in herbicide treated soil

than untreated soil. Various studies (Perucci et al., 2000) confirmed that

rimsulfuron and imazethapyr herbicides are harmful for soil microorganisms and

soil biochemical properties when applied at recommended and ten times

recommended doses and they also found considerable effect on alkaline

phosphatase activity. To see the effect of benfluralin and imazamox herbicides on

microbial biomass in three soil types scientists (Vischetti et al., 2002) found

substantial decrease (20 %) in microbial biomass carbon due to imazamox when

the concentration of the applied herbicide was about 50 % of the initial dose. While

seeing the effect of different concentrations of atrazine on microbial biomass,

dehydrogenase and urease activity, researchers noticed obvious increase in

microbial and biochemical parameters in soil treated with atrazine after prolonged

incubation. Different researchers conducted an incubation experiment for three

weeks using three soil types to investigate the effect of higher doses of glyphosate,

2, 4-dichlorophenoxy acetic acid and metsulfuron-methyl on soil microbial biomass

and found that metsulforan methyl has less toxic effect on microbial biomass as

38

compared to 2,4-dichlorophenoxyacetic acid and glyphosate (Makoi and

Ndakidemi, 2010). According to some studies (Singh and Ghoshal, 2010) soil

microbial biomass and biological productivity are most essential for sustainable

agro-ecosystem and they observed that MBC and MBN were more where herbicides

and amendments were added together as compared to herbicides alone. So the

combination of organic soil amendments with herbicide is helpful in maintaining

soil fertility on sustainable basis.

Many studies documented inhibitory effect of nicosulfuron herbicide (0.3, 1.5

and 3 mg/kg of soil) on dehydrogenase activity and microbial biomass carbon and

argued that this inhibition was transitory and depends on rate of application and

period of activity (Nweke et al., 2010). Various studies highlighted the adverse

effects of different herbicides (carbofuron, ehion and hexaconazole) on soil

microbial community even up to 61% reduction in their population with

concomitant decrease in biomass carbon (Ingram et al., 2005). Application of pre

and post emergence herbicides including fenoxaprop-P-ethyl, pendimethalin,

metribuzin and tralkoxydim showed 10-100 time decrease in soil microorganisms

population as a consequence microbial biomass decreased (Khalid et al., 2001).

Baboo et al. (2013) observed significant decline in microbial biomass carbon due to

the application of butachlor herbicide (@1kg/ha), pyrozosulfuron (@25 g/ha),

paraquot (@200g /l) and glyphosate (@360 g/l).

39

2.2 EFFECT OF HERBICIDES ON MICROBIAL POPULATION

Soil microorganisms function as soil quality sign because of their major role

in various soil functions (Scholter et al., 2003). Bacteria, fungi and actinomycetes

are considered as most important soil microorganisms because they play very

important role in organic matter decomposition and nutrient cycling. All species of

actinomycetes are facultative anaerobe except few one (Actinomycetes meyeri) and

show excellent growth under anaerobic environments. Actinomycetes manufacture

enzymes that can degrade different agrochemicals added in the soil and protect the

crop from insects and for controlling weeds. Actinomycetes also have the ability of

degrading lignin, cellulose. They are essential component of compost (Holt et al.,

1994). Fungi contribute about 10-20 % of total soil microbial population in soil.

The carbon use efficiency of fungus is high so they have the ability of storing and

recycling of carbon. Arbuscular mycorhizal fungi produce amino polysaccharide

(glomalin) which surrounds the soil particles and help in soil structure formation.

Fungi can also restore and reprocess nitrogen and phosphorus in soil and enhance N

and P extraction from soil (Hoorman, 2011).

Baxter and Cummings (2006) reported that in the absence of available

carbon, bromoxynil degradation by bacteria reduced markedly. Soil microbial

population showed both qualitative and quantitative variation to bromoxynil

application depending on the accessibility of organic carbon. Soil microorganisms

enhance the ability of plants to get phosphorus from soil through different

mechanisms such as changing sorption equilibria that can result in enhanced

transfer of orthophosphate ion in soil solution, by stimulating roots growth, by

40

producing harmones or through facilitating the mobility of organic phosphorus by

microbial decomposition (Seeling and Zasoski, 1993) or through induction of

different metabolic processes which help in solubilizing inorganic phosphorus from

soil (Ricardson et al., 2011).

Microorganisms are also helpful in degrading the pesticides added to the

soil. Pimentel (1995) found that less than 0.3 % part of the applied chemical

reached to the target organism and 99.7 % goes to the soil ecosystem leading its

exposure to soil microbial ecology. Soil organisms that have the capability of

degrading aromatic nitriles manufacture two types of enzymes (i) nitrilase that

convert nitriles to their analogous nitrile hydratase or nitrile hydratase. (ii) nitrile

hydratase that cause conversion of nitrile group to amide group (Cycon et al.,

2010). But addition of herbicide in soil affect the formation of these enzymes

ultimately stopping the degradation of nitrile herbicides (Dale et al., 1993). Omar

(1994) experienced significant inhibition in osmophilic fungi due to soil application

of bromoxynil and profenophos herbicides (0.3 ppm and 6 ppm), while complete

death of osmophilic fungi in agar medium was documented in some studies.

Similarly, selecron insecticide mixed in agar medium (0.9 ppm and 4.5 ppm)

showed considerable decline in osmophilic fungi and aspergilli population. The

inhibitory effect of insecticide and herbicide was similar on the population of fungi

(Nicholson and Hirsch, 1998). Researchers, while evaluating the effect of

herbicides combinations (chlorfenvinophos, aldicarb, benomyl and glyphosate) on

soil bacteria observed slight increase in bacterial population and high speed of

substrate utilization by bacteria in treated soil as compared to untreated soil (Black

41

et al., 1998). During an experiment to see glyphosate herbicide impact on soil

microbial community using culture media and soil, different scientists (Busse et al.,

2001) observed glyphosate toxicity to bacterial and fungal population in culture

media and also increased concentration of glyphosate showed significant inhibition

in bacterial population. Some studies (Digrak and Kazaniki, 2001) reported

increase in bacterial population and no effect on other soil microbes in soil treated

with organophosphorus insecticide (isofenphos) in contrast to untreated soil. Omar

and Abdel-Sater (2000) reported enhancement in actinomycetes and bacterial

population at field rate application of bromoxynil while decreased population of

bacteria and actinomycetes due to higher application rate was reported in earlier

studies. However, herbicide application exhibited appreciable inhibition in the

population of fungi. Recommended dose of some herbicides resulted enhanced

alkaline phosphatase activity while higher rate resulted low activity of said enzyme.

Allison and Cupples (2005) found that Some bacteria (Desulfitobacterium

cholorospirans) use the applied herbicide as a source of carbon and energy and

cause debromination of bromoxynil herbicide (3,5-dibromo-4-hydroxy

benzonitrile) and its metabolites (3,5-dibromohydroxy benzoate) and use both of

these as electron acceptor for their development and growth. By the application of

5.5 mg kg-1 to 22 mg kg-1 of butachlor (n-butoxymethyl-chloro-2’,6’

diethylacetnilide) herbicide, Min et al. (2001) reported stimulation in fermentative

and sulfate reducing bacteria, whereas, suppression in acetogenic bacterial

population (Ratcliff et al., 2006) Some studies reported increase in bacterial

population by applying higher dose (100x field rate) of glyphosate herbicide. In an

incubation study for ten weeks to see the impact of brominal (herbicide) and

42

selecron (insecticide) on the population of bacteria, fungi and actinomycetes.

Researches (Omar and Abdel Sattar 2001) observed considerable promotion in the

population of actinomycetes and bacteria at field application rate while suppression

in the growth of these microbes at five times of the recommended rates was

noticed. However, both application rates of herbicides and insecticides

significantly inhibited fungi population. They also reported 41% and 31% decline

in bacterial population during first and second week, respectively by 0.6 and 3.0 µg

g-1 soil dose of herbicide. However, during second week this rate of herbicide

resulted 43.3 and 62.0 % decrease in fungi population. Some soil microorganism

cause decomposition of the applied herbicide and act as biological indicator of

changes in soil due to herbicide application. Some species of microbes serve as bio-

herbicides and some bacterial species such as azotobacter is highly sensitive to the

soil applied herbicide. So it is a best indicator of soil biological value (Milosevic et

al., 2002). Various studies (Milesovic and Govedarica, 2002) reported significant

increase in actinomycetes and fungi population but 5-7% and 2-18% decrease in

total microbial and azotobacter population, respectively by applying 1.6 L/ha dose

of dimethenamide (Frontier) herbicide indicating that the herbicide was used as a

biogenous source by actinomycetes and fungi. Findings of (Ayansina and Oso,

2005) revealed that the effect of combined mixture of atrazine and metolachlor

herbicides and atrazine alone on soil organisms when applied at field rate and 1.5

recommended rate showed considerable decrease in microbial population and even

caused removal of some microbial species. Literature reported strong negative

effect of metsulfuron-methyl on aerobic heterotrophic bacteria and actinomycetes

but its impact on fungi was not obvious suggesting that fungi must be added in

43

large quantity in the soil polluted with metsulfuron-methyl for its rapid degradation

into less toxic substances (He et al., 2006). Nevertheless, some researcher (Araujo

et al., 2003) reported increase in the number of actinomycetes and fungi due to

glyphosate application (2.16 mg glyphosate /kg soil). Combined mixture of

bromoxynil and prosulfuron herbicides with 1ppm and 100 ppm concentrations

exhibited 43% and 96 % inhibition in fungi population, whereas, 33% and 90%

decrease in ammonium oxidizing bacteria and 91% decrease in actinomycetes as

compared to control (Nanniprie and Bollag, 1991). Some studies reported decline

in microbial population after 1st application of chlorothalanil, but they reported

recovery of microbes after 3rd and 4th application because of the adjustment of soil

microorganism to the herbicide (Tu, 1992). The persistence of herbicide in soil is

directly related to soil composition. Generally, soils with high clay and organic

matter have the capacity of binding herbicide to soil. Therefore, the herbicide gets

adsorbed with clay ultimately prolonging its persistence and exposure to soil

microbial population (Curran et al., 1992). Microbial population showed

suppressed growth due to high concentration of cotrazine herbicide (Nweke at al.,

2007). Different researchers while studying the influence of chlorothalonil and

chlorpyrifos on soil microbial population (bacteria, fungi and actinomycetes)

noticed significant inhibition in microbial population (Chen et al., 2011). Various

metabolites of the pesticides also exert injurious effects on biochemical activity and

soil organisms (Xiaoqiang et al., 2008). Different studies (Singh et al., 2005; Chen

et al., 2011; Grenni et al., 2009) highlighted the detrimental effects of pesticide

metabolites during the assessment of dehydrogenase activity in different soils

(Singh and Wright 2002; Grenni et al., 2009; Chen et al., 2011). Dehydrogenase

44

being intracellular enzyme represents the catabolic capability of microbes

concerned with carbon turnover, therefore, any type of trouble in carbon substrates

mineralization by microorganisms due to added pesticides may needs investigation

(Nannipieri et al., 1990).

Sebiomo et al. (2011) while evaluating the effect of atrazine, primeextra,

paraquat and glyphosate on soil microbial population and dehydrogenase activity

found suppression in microbial (bacterial, fungal and actinomycetes) population. In

an experiment to quantify the effect of glyphosate on soil microbial community,

Weaver et al. (2007) found that glyphosate has not significantly affected the

microbial community, even when applied higher than recommended rates.

However, 19 % reduction in soil hydrolytic activity was observed where glyphosate

was applied three folds of the recommended rate. They concluded that glyphosate

has little and temporary effects on the soil microbial community, even if applied at

greater than field application rates.

Autotrophic nitrifiers are very sensitive to herbicides. Literature highlighted

the toxic effect of sulfonyl urea herbicides on autotrophic nitrifiers by inhibiting

their amino acid assimilation ability (Allievi ang Giglioti, 2001). Other

investigations revealed about 90% and 33% decline in the population of ammonium

oxidizing bacteria by 100ppm and 1 ppm concentration of bromoxynil herbicide

(Pampalha and Oliveria, 2006) hence hampering nitrification process and

ultimately causing decline in nitrate nitrogen. Chang et al. (2011) observed decline

in the population of ammonium oxidizing bacteria due to five herbicides (atrazine,

45

dicambia-4, flumeturon, metolachlor, sulfentrazone) by using 0 µg g-1, 10 µg g-1,

100 µg g-1 and 1000 µg g-1 of each herbicide. Opposite to that, stimulation in the

activity of ammonium oxidizers due to acetachlor herbicide during initial days of

treatment has been reported in some studies (Li et al., 2008). Nitrification being

vital process of worldwide nitrogen cycle, involve ammonium oxidizing bacteria as

well as ammonium oxidizing Archaea. Different studies (Hernandez et al., 2011)

reported inhibition in the activities of ammonium oxidizing bacteria by simazine

herbicide (50 µg g-1soil) leading to entire inhibition in nitrification process.

Contrary to that, some studies (Kanungo et al., 1995) observed stimulation in

Azotobactor and Azospirillum population due to repeated application of carbofuron

and enhancement in anaerobic nitrogen fixing bacteria due to repeated application

of anilofos herbicide.

Ingram and Pullin (1974) while studying the persistence of bromoxynil

(applied @1.12 kg ha-1 a.i.) in three different soil types (sand, clay loam and peat),

the herbicide residues detected were 0.91 mgl-1 in clay 0.53 mgl-1 in peat and 0.35

mgl-1 in sandy soil and turn down below the level of detection after 28 days in clay,

after 44 days in peat and after 14 days in sand. They observed inverse relationship

between decline rate and clay content. Same was the case with organic matter

content of the soil and rate of decline. Degradation of pesticide in soil is carried out

by the combination of biological and chemical actions (Wu and Nofzigar, 1999).

Previous investigations (Nielsen et al., 2007) observed the formation of highly

persistent products from the transformation of bromoxynil (3,5-dibromo-4-

hydroxybenzonitrile) and Ioxynil (3,5-dichlorobenzamide) herbicides. Related

46

process to the conversion of BAM (2, 6-dibromobenzamide) from dichlobenil (2,6-

dibromobenzonitrile) herbicide can be predictable because bromoxynil is analogue

of dichlobenil and their degradation is carried out by nitrile hydrates and amidase

enzymes. A biodegradation experiment in which cultured Variovorax sp. that is

commonly found in soil was used. Results indicated the complete transformation of

bromoxynil and ioxynil to their amides within 2-5 days. Further degradation of

amides and formation of products of degradation up to 18 days were not observed.

Variovorax sp. is capable of degrading only non halogenated benzamide. So

halogenated substituents including meta-I. meta-Br causes hindrance in amides

degradation. Desorption studies showed that low concentration of the herbicides

resulted higher desorption as compared to higher concentration. Bromoxynil is one

of the herbicide which is being used all over the world for weed control. It is being

used in Pakistan under the brand name Buctril Super. Microbial degradation of

bromoxynil by different species of bacteria including Azospirillum baraselense,

Klebelense pneumoneae, Azotobacter chrooccum ,Pseudomonas cepacia,

Pseudomonas fluorescence, Bacillus subtilus and Bacillus polymixa and two

species of fungi , Trichoderma viride and Trichoderma harzianum (Askar et al.,

2007) reported that the bromoxynil residues percentage from the bacteria enriched

media ranged from 29.51 -71.94 , 18.89 - 43.88 , 9.82 - 35.07 , 3.47- 31.90 and

1.80 - 19.24 % respectively after 3, 7, 14, 21 and 28 days of incubation. While the

bromoxynil residues from fungi enriched media were 45.61 - 60.26 ,12.25 - 30.56 ,

6.48 - 20.63, 1.25 - 10.49 and 0.63 - 1.56 after 3, 7, 14, 21 and 28 days of

incubation respectively. It is obvious that during the first phase there was faster loss

of bromoxynil as compared to the second phase. So they concluded that these

47

microbes should be used as bio-control agents while applying bromoxynil for the

control of weeds to save the soil health. Soil microorganisms are involved in the

degradation of pesticides (Chowdhury at al., 2008) and they affect their behavior

and fate. They also produce enzymes which causes degradation of the applied

pesticides. Rosenbrock et al. (2004) reported readily degradation of bromoxynil in

soil and they found 63% mineralization of bromoxynil in soil within 84 days.

2.3 EFFECT OF HERBICIDES ON SOIL ENZYMES

Enzymes perform numerous important functions in soil and facilitate

nutrient availability. Soil enzymes exhibit particular and peculiar characteristics

and acquire resistant against different agents that cause their deactivation such as

irradiation, temperature, protease existence. Thus in most cases no change in the

activity of soil enzymes occur after their exposure to those agents (Gainfreda et al.,

2002: Gainfreda and Ruggiero, 2006). Because of their immediate response the soil

bound enzymes play vital role in the transfer of available substrates and make them

available to cells. Soil bound enzymes produce intermediate metabolites that

mediate cleavage of larger molecules of substrate (Gianfreda et al., 2010). Some

researchers observed active involvement of soil enzyme in pollutants degradation

including herbicides and pesticides thus they help in the restoration and recovery of

soils polluted with pesticides (Nannipieri et al., 1990). Different enzymes perform

different functions. Urease causes hydrolysis of urea. Nitrogen transformations in

soil are carried out by urease enzymes. As a nitrogenous source, urea fertilizer is

applied and urease enzyme causes the hydrolysis of urea to ammonium. Literature

(Cervelli et al., 1976) reported significant inhibition (10-30%) in urea hydrolysis

due to phenyl urea herbicides (linuron, diuron and monuron) through competitive

48

and non competitive behavior. Higher dose of chlorpyrifos (100 mg/kg and 500

mg/kg) resulted significant inhibition in urease activity (Niu et al., 2011). Urease

play important role in decomposition of urea into carbon (CO2) dioxide and

ammonia (NH3) therefore, urea consumption rate is directly related to the activity

of urease. Chlorothalanil and mancozeb fungicides (10 x FR) exerted lethal effect

on urease activity but chlorothalanil was less toxic as compared to mancozeb (Yu et

al., 2011). Some studies (Yang et al., 2006) reported positive impacts of furadan

and chlorimuron-ethyl on the activity of urease and found 46.9% and 39.3%

stimulation due to chlorimuron-ethyl, while, Yang et al. (2006) reported increase of

about 21% to 12.7% due to furadan in the activity of said enzyme. Some studies

revealed increase in urease and dehydrogenase activity due to different rates of

different (butachlor, pyrozosulfuron, paraquot and glyphosate) herbicides (Baboo et

al., 2013). Ingram et al. (2005) observed severe injurious effects of diazinon and

imidacloprid on ammonium oxidizing bacteria (Proteus vulgaris) which produce

urease enzyme with concomitant suppression in urease activity.

Dehydrogenase causes oxidation of organic matter by the transfer of both

electrons and protons between substrates and acceptors. These phenomena are basic

component of soil microorganism’s respiration (Schinner et al., 1995). As these

phenomina are integral component of respiration pathway of soil microbial

community. Research about dehydrogenase activity in soil is inevitable because it

provide indication of soil capability to assist many essential biochemical reactions

which are compulsory for maintaining soil health and quality. Dehydrogenase also

acts as marker of microbial redox system and can be used for the measurement of

http://europepmc.org/abstract/MED/17044522/?whatizit_url_Chemicals=http://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI%3A34611

49

soil microorganism’s oxidative activity (Trevors, 1984). Dehydrogenase is often

used for the measurement of any interruption due the addition of anthropogenic

chemicals and heavy metals in soil (Wilke, 1991; Frank and Malkoms, 1993).

Dehydrogenase also indicates kind and importance of soil pollution. Soil polluted

with paper and pulp industry effluents exhibit pronounced activity of

dehydrogenase, while soil contaminated with fly ash exhibit suppressed

dehydrogenase activity (Siddaramappa et al., 1994; Pitchel and Hayes, 1990). Soil

characteristics such as soil temperature and soil water contents indirectly influence

dehydrogenase activity by affecting soil redox potential. Oxygen deficiency in soil

causes activation of facultative anaerobes to start metabolic activities by the

involvement of dehydrogenase enzyme by using Fe+++ as acceptor of electron

(Galstian and Awungian, 1974). Literature reported negative as well as positive

effects of herbicides on dehydrogenase activity in soil. Some studies (Saha et al.,

2012) reported 55 % increase in dehydrogenase activity by field rate application of

alachlor herbicide after 42 days, while 5 FR and 10 FR of alachlor herbicide

showed 58 % and 59 % increase, respectively in the activity of said enzyme (Saha

et al., 2012). Mayanglambam et al. (2005) observed obvious inhibition (30%) in

dehydrogenase activity due to quinalphos application after 15 days and recovery of

dehydrogenase after 90 days because of ability of soil microorganisms to

counteract the impact of added chemical stress in hostile conditions. The activity of

dehydrogenase enzyme was negatively related with phosphatase but positively

correlated with proteolysis and nitrification (Skujins, 1973) while dehydrogenase

activity is positively correlated with humus (Kobus, 1974). High dose of triazophos

to paddy soil showed substantial decrease in dehydrogenase activity (Xie et al.,

50

2004). Substantial decrease (42.7%) in dehydrogenase activity due to nicosulfuron

herbicide (3.0 µg g-1) was recorded in some studies (Radiojevic et al., 2012). While

some studies (Stepniewska et al., 2007) highlighted 5-21% and 17-44% inhibition

in dehydrogenase activity due to 1mg kg-1 and 10 times higher rate of fonofos,

respectively as compared to control. In field, the activities of enzymes decreased

significantly due to metribuzin and linuron herbicides (Niemi at al., 2009) and this

decrease in enzymes activity was because of mortality of weeds due to these

herbicides application (Kang et al., 2012). Pronounced increase in dehydrogenase

activity due to diazinin and linuron herbicides and mancozeb fungicide when

applied at maximum predicted environment conditions (PEC) and five times of

PEC in loamy sand soil as compared to sandy loam soil was supported by Cycon et

al. (2010). Incubation experiment on the effect of endosulfuron on soil organic

matter and enzymes activity in soil with different physico-chemical properties

reported inhibition in dehydrogenase and alkaline phosphatase activities due to

endosulfuran (Defo et al., 2011). Different herbicides such as triazophos,

bensulfuron-methyl and clobenthiazone showed significant inhibition in

dehydrogenase activity and this decrease in the activity of dehydrogenase due to

the toxic effect of these herbicides showed the order: bensulfuron <

chlobenthiazone < Triazophos (Xie et al., 2004).

In soil, the alkaline phosphatase plays essential role in phosphorus cycling

as it is confirmed that they are extremely correlated to phosphorus stress in soil

(Skujiņš and Burns, 1976). In case of any signal of phosphorus stress in soil, the

secretion of phosphatase from the roots of plants increased in order to increase

51

phosphate immobilization and solubilization therefore, helping the plants to

overcome the phosphorus stressed conditions (Karthikeyan et al., 2002; Mudge et

al., 2002; Versaw and Harrison 2002). In soil phosphatases have already been

widely studied (Speir and Ross, 1978; Malcom, 1983; Tabatabai, 1994) they act as

catalyst in phosphate bonds hydrolysis and help in phosphorus release that is used

by soil microbes and plants (Quiquampoix and Mousain, 2005). Phosphatase

converts complex organic phosphorus compounds into inorganic forms through

hydrolysis (Monkiedje et al., 2002). The activity of phosphatase enzyme depends

on several factors including soil texture, presence or absence of inhibitors, soil

microorganisms. Surface layer and rhizosphere soil exhibit more phosphatase

activity because of more organic matter (Tarafdar at al., 2001). Phosphatases

perform essential role in phosphorus availability to microbes and plants (Schneider

at al., 2001). Herbicides not only kill the weeds but also have harmful effects on

soil microorganisms eventually hampering various essential soil functions

including oxidation of methane, decomposition of organic matter and nitrogen

transformations (Hutsch, 2001). Herbicides also exert toxic effect on rhizobia and

affect nodule formation and nitrogen fixation (Singh and Wright, 2002). Higher

activities of soil enzymes indicate limitations of mineral elements in the ecosystem

(Makoi et al., 2010; Sinsabaugh, 1993). While investigating the effect of copper

oxichloride and miedzian using three concentrations of each fungicide on the

activity of dehydrogenase and ATP contents in clay soil, researchers (Klodka et

al., 2004) observed lower enzymes activity and ATP contents due to higher dose of

these fungicides. The effects of herbicides (aminopielik P and maloran) on soil

enzymes in sandy loam soil and herbicides (desmetrine and simazine) in loess soil

52

showed varied effect and ten times dose of these herbicides exhibited frequent

decrease in enzymes activity. Paddy and Singh (2005) reported 25% inhibition in

phosphatase activity due to quinalphos application as compared to control. Various

researches (Rani et al., 2008; Madhury and Rangaswamy, 2002) observed decline

in alkaline phosphatase activity due to chlorpyriphos application @ 5 kg ha -1. No

significant change in the population of phosphate solubilizing bacteria and rhizobia

by the application of phorate, carbofuron, carbosulfuron, thiomethaxan,

amidacloprid, chlorpyriphos and monocrotophos in comparison to control was

documented in some studies (Sarnaik et al., 2006). Fox and Comerford (1992)

noticed suppression in the activity of alkaline phosphatase due to phosphorus

addition in soil (Fox and Comerford, 1992).

2.4 EFFECT OF HERBICIDES ON NITRIFICATION AND NITRATE

NITROGEN

Nitrification is a two way process involving ammonium oxidizers

(Nitrosomonas sp.) and nitrite oxidizers (Nitrobacter sp.) in order to produce nitrate

(NO3) from ammonium (NH4). As most of the plants prefer nitrate form of nitrogen

for their growth. Nitrification being oxidation phenomena help in soil acidification

by releasing hydrogen ions (H+) in soil. The process of microbial oxidation lead to

the formation of nitric acid (HNO3) which aid in acidification of soil and when

nitric acid dissociate into NO3- and H+ ions this will increase acidification too (Van

Miegroet and Cole, 1984). Nitric acid (HNO3) formed during nitrification process

splits up into NO3- and H+ ions resulting decrease in soil pH and increase in

nutrients availability (Black et al., 1998). Due to lethal effect of sulfonyl urea

53

herbicides on autotrophic nitrifiers by hampering their amino acid assimilation

ability different studies reported decline in nitrification (Allievi and Giglioti, 2001).

Some researchers (Hernandez et al., 2001) reported suppression in ammonium

oxidizing bacteria (AOB) and ammonium oxidizing Archaea (AOA) due to

simazine herbicide (50 µg g-1soil) with concomitant inhibition in nitrification

process which in turn resulted decrease in nitrate nitrogen. Contrary to that, some

reports (Kanungo et al., 1995) showed increase in the population of Azotobactor

and Azospirillum due to repeated use of carbofuron while enhancement in

anaerobic nitrogen fixing bacteria by anilofos herbicide. Decrease in ammonium

oxidizers by combined mixture of herbicides (atrazine, dicamba-4, flumutoron,

metolachlor and sufentrazone) using different concentration (0, 10,100 and 1000

ppm) was experienced in some studies (Chang et al., 2011). Whereas, Li et al.

(2008) reported stimulation in ammonium oxidizers population due to acetachlor

herbicide and pronounced nitrification (Rangaswamay et al., 1992) by azospirillum

because of cypermethrin or fenvalerate treatment. Das and Mukherjee (1998)

reported increase in microbial activity and nutrient mineralization by the

application of phorate (1500 g a.i. ha-1) and carbofuron (1000 g a.i. ha-1). Scientists

(Ismail et al., 1995) noticed decline in bacteria and fungi population due to

glufosinate-ammonium (100 ppm) during initial days but later on they observed

increasing trend in their population.

2.5 EFFECT OF HERBICIDES ON OLSEN-P

The prime biological significance of phosphate is that it serve as power

house of energy in the form of adenosine triphosphate (ATP) inside the cell and is a

constituent of nucleotides which binds together to form DNA. The phosphate ester

http://en.wikipedia.org/wiki/Nucleotide

http://en.wikipedia.org/wiki/DNA

54

bridge is fundamental part of double helix of DNA. Phosphorus is an essential plant

nutrient which make up of about 0.2 % dry weight of plant (Schachtman, 1998).

Phosphorus is a fundamental part of phospholipids, nucleic acid and proteins. It

control different enzmymes activities and help in regulating different metabolic

processes (Theodorou and Plaxton, 1993). The uptake of phosphorus from the soil

is carried out as orthophosphate due to high affinity of transporters present in plant

roots which act in response to phosphorus deficiency (Bucher, 2007). Soil

microorganisms enhance the ability of plants to get phosphorus from soil through

different mechanisms such as changing sorption equilibria that can result in

enhanced transfer of orthophosphate ion in soil solution, by stimulating roots

growth, by producing hormones or through facilitating the mobility of organic

phosphorus by microbial decomposition (Seeling and Zasoski ,1993) or through

induction of different metabolic processes which help in solubilizing inorganic

phosphorus from soil (Richardson et al., 2011). Different studies (Khan et al.,

2005) reported 72 %, 91% and 94% decrease in phosphorus solubilizing activity of

Enterobacter asburiae due to different concentrations of quizalafop-p-ethyl viz. 40

µg L-1, 80 µg L-1 and 120 µg L-1, respectively as compared to control. This

decrease in Olsen-P might be due to the suppression in fungi population by the

herbicide residues. Since fungi are more efficient in solubilizing precipitated

calcium phosphate and rock phosphate than bacteria so due to their mortality

Olsen-P decreased significantly (Kucey, 1982). Contradictory to that, Das et al.

(2003) reported stimulation in the population of phosphate solubilizers and

increased phosphorus availability in soil. Whereas some studies (Defo et al., 2011)

noticed first increase in phosphorus availability by endosulfan application but after

55

day-60 decrease in phosphorus availability was found. While, Sarnaik et al. (2006)

reported no significant change in the population of phosphate solubilizing bacteria

and rhizobia in comparison to control by the application of phorate, carbofuron,

carbosulfuron, thiomethaxan, amidacloprid, chlorpyriphos and monocrotophos

application.

2.6 EFFECT OF HERBICIDES ON SOIL ORGANIC CARBON

Total organic carbon (TOC) is that portion of carbon which is stored in soil

organic matter. Decomposition of plant and animal residues, root exudates and

dead microbes results in organic carbon buildup in soil. Organic carbon fraction of

soil is the major source of microbes energy. Organic carbon is one of the most

essential components of the soil due to its ability to provide energy and enhance

nutrient availability to plants through mineralization. Total organic carbon (TOC) is

the major source of energy for soil microbes. Soil organic carbon helps in

improving the physical characteristics of soil. It has the ability of holding major

proportion of nutrients and made them available to plants. It act as buffering agent

in soil and resist changes in soil pH (Leu et al., 2007). Researchers (Sukul et al.,

2006) observed decrease in organic matter due to metalaxyl fungicide and reported

that this decrease in organic carbon was resulted due to co-metabolism phenomina.

Considerable drop of about 2.49% and 2.23% in soil organic carbon at day-7 and

day-28, respectively due to pyrazosulfuron herbicide (25g ha-1), while 1.90%,

2.47% and 2.32 % decline in soil organic carbon at day-7, day-21 and day-28,

respectively due to glyphosate herbicide (360g L-1), but increase in organic carbon

due to paraquot application up to day-14 (2.47%) followed by decrease at day-21

56

(2.15 %) was reported in some studies (Baboo et al., 2006). Herbicide caused lysis

of microbial cells resulting decline in their population and the remaining microbial

population increased the rate of decomposition of organic matter for obtaining

quick energy for their survival which in turn resulted loss of carbon dioxide leading

to decline in organic carbon. Other studies (Ayansina and Oso, 2006) found 13 %,

30 % and 11 % decrease in organic matter contents by combined mixture of two

herbicides (atrazine + metolachlor) during Ist, 4th and 6th weeks after herbicide

application, respectively as compared to control. Some reports highlighted 35 %,

76 %, 20.6 % and 22 % decrease in organic matter due to field application rates of

atrazine, glyphosate, paraquot and primeextra herbicides (Sebiomo et al., 2011).

Plant roots release auxin and gebrilin in soil that contribute towards increase in

organic matter, so death of weeds contributed towards decline in organic matter in

soil.

57

Chapter 3

MATERIALS AND METHODS

3.1 SURVEY STUDY

Survey of the areas where Buctril Super herbicide was being used for long

time was done and nine different sites of southern Punjab (Pakistan) which were

exposed to bromoxynil herbicide for the previous 10 years represented as soil ‘A’

were surveyed in September, 2011 and samples were taken to a depth of 10 cm.

The soil samples were equilibrated to room temperature for microbial and

biochemical analysis. The soil samples were sieved to remove stones, coarse roots

and all visible litter and anlyzed for soil microbial biomass carbon (MBC), soil

microbial biomass nitrogen (MBN), soil microbial biomass phosphorus (MBP) and

population of soil microbes (bacteria, fungi and actinomycetes), enzymes activity

(urease, alkaline phosphatase and dehydrogenase), total organic carbon (TOC),

nitrate nitrogen (NO3-N), and Olsen-P. Simultaneously, the samples from the same

sites which were not exposed to buctril super herbicide designated as soil B were

also collected for comparison. Descriptive statistics was applied and data

represented as mean ± standard deviation of three replications. The physico-

chemical properties of soil A and soil B are given in Table 1.

3.2 FIELD EXPERIMENTS

The impact of buctril super (bromoxynil) herbicide on the population of

soil microorganisms (bacteria, fungi and actinomycetes), microbial biomass (MBC,

MBN, MBP) soil enzymatic activity (urease, dehydrogenase and alkaline

phosphatase) was studied through field experiments conducted at two different sites

58

viz., PMAS-Arid Agriculture University Rawalpindi (Research Farm at Koont) and

D.G.Khan (Taunsa) farmer’s fields during Rabi season. The treatments were

Control, 375 mL ha-1 buctril super herbicide, 750 mL ha-1 buctril super herbicide,

1500 mL ha-1 buctril super herbicide and 2250 mL ha-1 buctril super herbicide.

Buctril super (bromoxynil) herbicide was purchased from local market. The

treatments were arranged in RCBD with four replications. Plot size was 5m x 5m.

Soil samples were collected before herbicide application and at 0-day, 7th day,15th

day, 30th day and 60th day of herbicidal treatment for the analyses of various

parameters including Soil Microbial Biomass Carbon (SMBC), Soil Microbial

Biomass Nitrogen (SMBN), Soil Microbial Biomass Phosphorus (SMBP) and

microbial population (bacteria, fungi and actinomycetes), enzymes activity (urease,

dehydrogenase and alkaline phosphatase), Total Organic Carbon (TOC), Nitrate

Nitrogen (NO3-N), Olsen-P and weed control efficiency. The detail of analytical

work is as under:

3.2.1 Soil Microbial Biomass Analysis

3.2.1.1 Soil microbial biomass carbon

Determination of soil microbial biomass carbon (SMBC) was done by

fumigating the soil samples with chloroform (CHCl3). Extraction of two soil

samples (10g each) was performed by 40 ml 0.5M K2SO4. Two other soil samples

fumigation was done with chloroform (alcohol free) for 24h at 25ºC and the

extraction of these samples were also done with 0.5M K2SO4 (Vance et al., 1987).

After filtration, MBC was computed as MBC = (Extracted-C fumigated soil –

Extracted-C unfumigated soil) ˣ 2.64 and carbon from the extracts was determined by

59

Nelson and Sommer (1982) method. Total nitrogen was assayed by Kjeldahl

protocol (Bremner, 1982).

3.2.1.2 Soil microbial biomass nitrogen

MBN was computed as MBN = (Extracted N fumigated soil - Extracted N unfumigated soil)

x 1.46 (Brookes et al., 1985).

3.2.1.3 Soil microbial biomass phosphorus (MBP)

MBP was estimated by extraction of soil samples with 0.5M NaHCO3 (pH

8.5). Determination of extracted phosphorus was done using ammonium molybdate

and ascorbic acid. KH2PO4 was used for phosphorus standards preparation and

reading was recorded through spectrophotometer at 880 nm. MBP was computed

as MBP = (Extracted Pfumigated soil - Extracted Punfumigated soil) x 2.5 (Brookes et al.,

1982).

3.2.2 Microbial Population Counting

3.2.2.1 Bacterial population count

The colony forming units of bacteria were counted by using dilution plate

technique. Fresh soil (1.0 g) was taken and serial dilutions were made. Tryptone

Soya Agar (TSA) modified by cyclohexamide (100 mg L -1) was used. The plates

were inoculated with soil suspension (0.1 ml) and stored at 28ºC for about 3-5 days

(William and Wellington, 1982).

3.2.2.2 Actinomycetes and fungi population count

Determination of total population of actinomycetes and fungi was done

through soil sample’s serial dilutions (10-4 to 10-10). The fungi count was made with

Rose Bengal Agar modified with 30 mg ml-1 streptomycin sulfate, while

60

actinomycete count was done on Glycerol Casein Agar adjusted with

cyclohexamide (0.05 mg ml-1). Incubation of plates was done using 100µl soil

suspension by keeping them for 10 days at 25 °C for fungi and actinomycetes

(William and Wellington, 1982).

3.2.3 Enzymes Activity Analysis

3.2.3.1 Urease activity assay

The activity of urease was assayed with urea solution being utilized as a

substrate by incubating the sample at 37 °C for 2 h. Ammonium librated was

determined at 690 nm on spectrophotometer and expressed as µg NH4-Ng-1dwt 2h-1

(Kandeler and Gerber, 1988).

3.2.3.2 Dehydrogenase activity

Activity of dehydrogenase was measured by using Triphenyl Tetrazolium

Chloride (TTC) as substrate by incubating the sample at 30° C for 24 h. The TPF

produced was estimated colorimetrically at 546 nm and expressed as µgTPF g-1 24

h-1 (Thalmann, 1968).

3.2.3.3 Alkaline phosphatase activity

The activity of alkaline phosphatase was determined by using p-nirophenyl

phosphate (PNP) as a substrate and incubation of sample was done for 1h at 37 °C.

The P-nitrophenol produced was estimated colorimetrically at 400 nm and

expressed as μg Phenol g-1 h-1 (Elivazi and Tabatabai, 1977).

3.2.4 Bromoxynil Residue Analysis

The residues of bromoxynil from the soil were determined with the help

61

of HPLC (Model SCL-10A VP). Soil (10g) was taken in centrifuge tube along

with acetonitrile (20 ml) followed by 5 ml distilled water having formic acid

(0.1%). Out of which, 10 ml acetonitrile supernatant was taken and concentrated to

less than 1 ml on evaporator at 50ºC. The solution was injected to the sample vial

of HPLC. The mobile phase used was of methanol, water and formic acid (60:

40:0.1 on v/v basis) with a flow rate of 800 µL min-1 and the wave length of

detection was 254 nm. The volume of injection was 20 μL. The retention time was

10.3 min for bromoxynil (Chen et al., 2011).

3.2.5 Nitrate Nitrogen

Extraction of fresh soil (10g) was done with 20 ml of 0.5M K2SO4 for 30

min at 600 rpm. Filtration was carried out using nitrate free Whatman No. 42 filter

paper. Stock solution (1000ppm) was prepared by dissolving 7.223g potassium

nitrate in 1000 ml of distilled. From stock solution working standards were

prepared (2, 4, 6, 8 and 10 ppm of nitrate nitrogen). Taken 0.5 ml of sample and

standards in test tubes, salicylic acid 1.0 ml was added and vortex. After that 10 ml

NaOH was added and for color development kept for 60min. Reading was recorded

at 410 nm absorbance. (Cataldo et al., 1975)

3.2.6 Olsen-P

Soil (2.5 g) was taken in polyethylene bottle and phosphorus extraction was

done with 50 ml extracting reagent (0.5 M NaHCO3, pH 8.5). Sample (1.0 ml) was

taken in test tube, 4 ml of ascorbic acid and 3ml of molybdate reagent was mixed in

it. Phosphorus stock solution (1000 µg ml-1 P) was prepared with potassium

dihydrogen phosphate (KH2PO4) and sub stock solution (20 µg ml-1 P) was

62

prepared from the stock solution. Working standards (0.5, 1.0, 1.5, 2.0, 2.5 µg ml-1

P) were prepared from sub stock. Readings of standards and samples were taken at

880 nm absorbance (Watanabe and Olsen, 1965).

3.2.7 Soil Total Nitrogen

In 10g of soil 30 ml of sulfuric acid and 10g digestion mixture (9:1 K2SO4:

CuSO4) was added and digestion was performed on automatic Kjeldahl digestion

block. After cooling the, digested material was added in 250 ml volumetric flask

and volume was made. About 10 ml of aliquot was transferred to distillation flask.

The ammonia librated was collected in receiver containing 4% boric acid and

titrated with 0.1N sulphuric acid (Buresh et al., 1982).

3.2.8 Soil Texture

Soil texture analysis was done according to Bouyoucus (1962). In 50g soil,

60 ml sodium hexametaphosphate (1%) was added in a beaker and 250ml distilled

water was added and stirred for 15 min through mechanical shaker. The suspension

was transferred in 1000ml graduated cylinder and volume was made to 1000 ml

with hydrometer inside. Hydrometer was removed. The stirring of soil suspension

was done through plunger. After 40-seconds, first hydrometer reading was recorded

which gave the percentage of silt+ clay. Second reading of hydrometer was

recorded after 2h which gave percent clay content. Using soil textural triangle, soil

textural class was determined (Bouyoucos, 1962).

3.2.9 Weed Control Efficiency

The weed control efficiency was calculated using formula proposed by

Gupta (1998):

63

Wc-Wt

WCE = -------------- X 100

Wc

Where:

Wc: Average dry weed biomass m-2 in the un-weeded plot.

Wt: Average dry weed biomass m-2 in the plot under treatment.

3.2.10 Bacterial DNA Isolation from Soil using PowerSoil DNA Isolation Kit

For incubation study the soil samples were collected from farms at the

University of Georgia Griffin Campus (USA), passed through 2-mm sieve and

thoroughly mixed. Herbicide was purchased from Sigma-Aldrich (St. Louis,

USA). The soil samples received the herbicide treatment at six levels which were

Control, 0.2µg g-1soil, 0.4µg g-1 soil, 0.6µg g-1 soil, 0.7µg g-1 soil and 0.8µg g-1

soil. Two hundred grams of the treated soils were transferred to 1 L mason jar for

incubation at 25 oC for 45 to 60 days. The herbicide was applied to the soil

samples to achieve a uniform distribution with final soil moisture content of 50%

of their water holding capacity. The treatments had three replications and were

arranged in the completely randomized design (CRD) during the incubation time.

The jars were weighted periodically and adjusted for any moisture loss

gravimetrically. Soil samples were collected before herbicide application and at 0,

15th, and 45th day of herbicide treatment for the analyses of ammonia oxidizing

bacteria - AOB and ammonia oxidizing archaea -AOA. Enumeration of phosphate

solubilizing bacteria (PSB) was done on soil samples that were collected at 0, 7th,

15th day, 30th and 60th day of herbicide application.

The isolation of microbial cell DNA from soil was performed by using by

64

using PowerSoil DNA Isolation kit. PowerSoil DNA isolation kit was purchased

from MO BIO Laboratories, San Diego biotech corridor (Carlsbad, CA USA). Soil

(0.25g) was taken in power bead tubes and vortexed. Then 60 µl solution C1 was

added and after gentle vortexing. The tubes were centrifuged at 10,000 xg for 30

seconds. About 400 to 450 µl of supernatant was transferred to a collection tube

(2ml). After adding a 250 µl of solution C-2. Again tubes were centrifuged at

10,000 xg for 60 seconds. In another collection tube 600 µl of supernatant was

transferred. Vortexed briefly after adding 200µl of solution C--3 and centrifuged at

10,000 x g. Supernatant 750 µl was then transferred to and other collection tube.

After adding 1200 µl of solution C-4 vortexed for 5 seconds. About 675 µl of

supernatant was loaded on to a spin filter and centrifuged at 10,000 x g. (Three

loads total). Then 500 µl of solution C-5 was added and centrifuged at 10,000 xg

for I minute. Carefully the spin filter was transferred to another collection tube and

100 µl of solution C-6 was added and centrifuged at 10,000 x g for 30 seconds.

Spin filter was discarded and the DNA in the tube was used kept at -20 ºC to -80

ºC) for downstream application.

3.2.11 Quantification of Ammonium Oxidizing Archaea through

qPCR

The quantification of ammonium oxidizing Archaea was carried out using

Applied Biosystem Step One Plus Real-time PCR. The primers used for

amplification of Archaea were Amo-19F (ATG GTC TGG CTW AGA CG) and

Amo643R (TCC CAC TTWGAC CAR GCG GCC ATC CA). SYBR Green Master

Mix was used for PCR amplification. The initial concentration of plasmid was 8.84

65

x10-8 and from this working standards were prepared. The PCR conditions used

were: 95 ºC, 10 min (ii) 95 ºC for 1 min (40 cycles), 55 ºC for 1min and 72 ºC for

7 min, 95 ºC for 15 sec, 55 ºC for 1min and 95 ºC for 15 sec.

3.2.12 Quantification of Ammonium Oxidizing Bacteria (Nitrosomonas

europea) ATCC 19718 through qPCR

The quantification of ammonium oxidizing Bacteria (Nitrosomonas

europea) was done with the help of Applied Biosystem Step One Plus Real-time

PCR. The primers used for amplification of Archaea were amoA-1F (GGG GTT

TCT ACT GGTGGT 18 bp) and amoA-2R (CCC CTC GGG AAA GCC TTC

TTC). SYBR Green Master Mix was used for PCR amplification. The initial

concentration of plasmid was 8.84 x10-8 and from this working standards were

prepared. The following PCR conditions were used. 94 ºC, 15 min (holding stage),

(ii) 94 ºC, 45 sec, 57 ºC, 30 sec and 72 ºC, 7 min Cycling stage (40 cycles) (iii) 95

ºC, 15 sec, 55 ºC, 1 min and 95 ºC, 15 sec (Melt curve stage).

3.2.13 Phosphate Solubilizing Bacteria (Pikovskaya’s medium)

Pikovskaya,s medium consists of: Ca3(PO4)2 = 5g, NaCl =0.2 g, (NH4)2

SO4= 0.5g, MgSO4. 7H2O= 100g, KCl =0.2g, MnSO4. H2O= 0.002g, FeSO4.7H2O

=0.002g, Yeast extract=0.5g and glucose=10g and the pH of the medium was 7.0.

To screen for PSB, one gram of each soil sample was suspended in 9 ml of

sterilized ddH2O and mixed vigorously. Serial dilutions were prepared and plated

100 µl soil suspension on Picovskaya’s media specific for phosphate solubilizing

bacteria and kept for 3 days at 25 °C and colony counting was done.

66

3.2.14 Detection and Identification of Bromoxynil Herbicide Metabolites

The soil samples were extracted with equal volume of dichloromethane

and water (1:1) then the extraction of residual aqueous phase was done with equal

volume of ethyl acetate and water (1:1); and finally, the residual aqueous phase was

acidified to pH 2.0 and extracted again with an equal volume of ethyl acetate and

water. After mixing the extracts, these samples were evaporated under reduced

pressure at room temperature using centrifugal evaporator. The detection of the

samples was done by HPLC. The samples were identified by using Mass

spectrometer (Cai et al., 2011).

3.2.15 Statistical Analyses

For field experiments, Rrandomized Completely Block Design (RCBD)

with two factors (Treatments and sampling days) was applied. The statistical

analysis of data was done through Statistix 8.1 software (2010). The technique of

analysis of variance (ANOVA) was used for testing the significance of the data.

Least Significant Difference (LSD) test at 5 % probability level was applied for

comparing the treatment means.

On incubation study data, completely randomized design (CRD) with two

factors (Treatments and sampling days) was applied. Analysis of variance

(ANOVA) and LSD was employed for means comparison using statistical software

Statistix 8.1. Descriptive statistics using maximum, minimum and mean ± standard

deviation of three replications was applied on survry study.

67

Chapter 4

RESULTS AND DISCUSSION

4.1 SURVEY STUDY

4.1.1 Microbial Biomass in Soils Exposed to Buctril Super Herbicide Versus

Unexposed Soils

Long term impact of buctril super (bromoxynil) herbicide in wheat fields on

soil microbial biomass, microbial population, enzymes activities, nitrate nitrogen,

Olsen-P and Total Organic Carbon (TOC) was evaluated in 18 sites in Pakistan.

Nine sites each were randomly selected from those places where bromoxynil

herbicide had been used for the last 10 years designated as soil A and other nine

where no herbicide was used for that period designated as soil B. Basic physico-

chemical analysis of soil A and soil B is given in (Table 4.1).

The microbial biomass carbon ranged from 131 to 457µg g-1, with an

average of 221±96 µg g-1 in soil A. In soil B, however, it ranged from 187 to 573

µg g-1, with an average value of 279±119 µg g-1 (Table 4.2). The highest biomass

carbon of 457 and 573 µg g-1 was recorded at Sher Shah in soil A and B,

respectively, which showed a 20% decline in the former soil (Figure 1). The lowest

biomass carbon of 131 and 187 µg g-1 was recorded at Daira Din Panah in soil A

and B, respectively, with a 30.3% decline in ‘A’. In the exposed soils, the microbial

biomass nitrogen ranged from 1.22 to 13.1µg g-1 with an average of 6.87±4.54µg g-

1, but in unexposed soils, it ranged from1.70 to 14.4µg g-1 with an average of

7.71±4.84 µg g-1. At site-8 (Qadirpur Raan), the MBN was 13.1µg g-1 in the soil

‘A’ and 14.4µg g-1 in the soil B, which showed 9% declinein the soil A. The

68

minimum MBN of 1.22µg g-1 was at Tibbi Qaisrani in the soil A and 1.70 µg g-1 in

the soil B, which showed 28.3% reduction in the MBN in soil A (Figure 2).

Microbial biomass phosphorus ranged 0.59 to 3.7 µg g-1 with an average of

2.01±0.94 µg g-1 in the contaminated soils, while in uncontaminated soils; it ranged

0.72 to 4.12 µg g-1 with an average of 2.01±0.94 µg g-1. The maximum MBP value

of 3.7µg g-1 at Sher Shah was in soil ‘A’ and 4.12 µg g-1 in soil ‘B’ from the same

site, which showed 10.2% decline in the MBP in soil A. Site-5 (Tibbi Qaisrani)

showed minimum MBP value of 0.59 µg g-1 in the soil ‘A’ while in the soil ‘B’, it

was 0.72 µg g-1 indicating 18% decrease in the MBP in soil ‘A’ (Figure 3).

Soil microbial biomass is considered as ecological marker of soil since it is

actively involved in nutrient release and because of key role in soil structure

development (Smith and Paul, 1990). Microbial biomass mediated organic matter

decompositions confirmed that it operate as a nutrient source in soils with low

nutrient level (Kang et al., 2012). In present study significant reduction in biomass

carbon was recorded at all experimental sites where soil was exposed to herbicide

as compared to unexposed soil. Highest decline in biomass carbon (35.17%) at

location-2 (Shah Saddar Din) in soil ‘A’ as compared to soil ‘B’ was due to high

pH at this location as some herbicides are more persistent at high pH due to their

restricted hydrolysis at high pH resulting more time of exposure to microbes

leading to their death which in turn result decrease in biomass carbon. Franzen and

Zolinger (1997) observed prologed persistence of herbicide (triazine) in high pH

soil. Omar (1994) observed similar inhibition in biomass carbon due to application

69

of bromoxynil herbicide. Nowak et al. (1999) noticed significant drop in bacterial

and fungal population with concomitant decrease in microbial biomass carbon due

to post emergence herbicide. Tenfolds decline in soil microbe population (Khalid et

al., 2001) by the use of tralkoxydim and fenoxyprop-p-ethyl herbicides. Vischetti et

al. (2002) noticed that imazamox and benfluralin herbicides caused 25% and 64.7%

suppression in biomass carbon, respectively.

Reduction in microbial biomass nitrogen (MBN) was similar to biomass

carbon at all experimental sites. Highest decline (21.52%) in MBN was recorded at

location-4 (Dona) in soil ‘A’ as compared to soil ’B’. which may be due to the

harmful effect of bromoxynil residues (0.24 mg kg-1) on soil microorganisms in soil

‘A’. Secondly this is because of high sensitivity of nitrogen fixing bacteria such as

Azotobacter to the herbicide. Milosevic et al. (2002) observed significant decline in

the population of Azotobacter in herbicide treated soil. High organic matter

contents also extended herbicide persistence at location-4 hence microbes died due

to which MBN declined. Yaron et al. (1985) reported high microbial activity in soil

containing high organic matter but such soils adsorb herbicide strongly and

decrease its concentration in soil solution and protect the herbicide from microbial

degradation. Inhibition in Rhizobia population and nodule formation due to

herbicide application was also observed by (Singh and Wright, 2002). High

electrical conductivity (4.20 dSm-1) at location-4 also suppressed microbial

population, consequently MBN decreased. Present results are in line with the

results of (Yuan et al., 2007). They reported

45

Table 4.1: Physico-chemical characteristics of soils under survey study.

Locations

Soil A Soil B

pH EC

Soil

Texture

TOC

BMX

residues

pH EC

Soil

Texture

TOC

BMX

residues

(dSm-1) (g Kg-1) (µg g-1) (dSm-1) (g Kg-1) (µg g-1)

Shadun Lund 8.0 0.37 Clay 4.00 0.09 8.1 0.38 Clay 5.11 ND

S. S. Din 8.0 0.38 Clay 2.00 0.21 8.0 0.36 Clay 2.80 ND

D. Din Pannah 8.2 0.39 Sandy

clay

1.90 0.18 8.1 0.39 Sandy

clay

3.01 ND

Dona 7.9 4.2 Clay 3.00 0.24 7.8 4.21 Clay 3.99 ND

Tibbi Qaisrani 7.7 0.41 Clay 2.20 0.09 7.7 0.4 Clay 2.61 ND

Sokar 7.4 0.35 Loam 2.60 0.14 7.2 0.35 Loam 2.99 ND

Vehova 8.2 0.43 Clay loam 2.80 0.19 8.0 0.43 Clay loam 3.10 ND

Qadirpur Raan 8.1 0.53 Clay loam 2.40 0.15 8.0 0.52 Clay loam 2.71 ND

Sher Shah 8.0 0.51 Sandy

clay loam

8.40 0.13 7.9 0.51 Sandy

clay loam

8.80 ND

ND, not detected; BMX, Bromoxynil

46

negative correlation between microbial biomass nitrogen and electrical

conductivity. Shah et al. (2011) observed similar decrease in MBN due to the

osmotic stress induced by elevated salinity. At all sites significant decrease in

microbial biomass phosphorus (MBP) was noticed in soil’ A’ as compared to soil

‘B’. Maximum reduction (28.87%) in MBP at location-3 (Kot Addu) and (32.38%)

at location-4 (Dona) was observed because of reduction in total microbial

population due to lethal effect of herbicide residues on soil microorganisms. Toxic

effect of herbicides (rimsulfuron and imazethapyr) on soil microorganisms and

various biochemical reactions taking place in soil has been reported by Perucci et

al. (2000). Moreover, decrease in MBP is due to the effect of herbicide on

membrane permeability of phosphorus solubilizers that release phosphatase

enzymes. Significant decrease in phosphate solubilizing bacteria (Enterobacter

asburiae) was reported by (Ahmad and Khan, 2010) due the application of

quizalafop-p-ethyl, clodinifop, metribuzin, glyphosate herbicides. They found that

quizalafop-p-ethyl herbicide alone when applied @ 40, 80 and 120 µg /L exerted

72%, 91% and 94% poisonous effect, respectively on phosphate solubilizing

activity of (Enterobacter asburiae) over control. The other reason for decline in

MBP was high organic matter and high clay contents at location-4 that result

increased persistence of herbicide in soil. Ingram and Pullin (1974) studied the

persistence of bromoxynil in three different soil types (sand, clay loam and peat).

By applying active ingredient @1.12 Kg ha-1, the residues of the herbicides

detected initially were 0.91 mgL-1 in clay, 0.53 mg L-1 in peat and 0.35mgL-1 in

sandy soil. But turn down below the level of detection after 28 days in clay, after

44 days in peat and after 14 days in sand. They observed inverse relationship

47

between decline rate and clay content. Same was the case with organic matter

content of the soil and rate of decline.

4.1.2 Microbial Population in Soils Exposed to Buctril Super Herbicide

Versus Unexposed Soils

Bacterial population ranged from 0.67x108 to 1.84x108 cfu g-1soil with an

average of 1.23x108±0.37 in soil ‘A’ while in soil ‘B’ it ranged from 0.87x108 to

2.37x108 cfu g-1 soil, with an average of 1.69x108±0.56 in all the sites under study

(Table 2). Highest bacterial population (1.84x108 cfu g-1soil) at site-4 (Dona) in soil

‘A’ and 2.37x108 cfu g-1soil from the same site in soil ‘B’ was observed which

showed 22.36% decrease in soil ‘A’.Site-8 (Qadir pur Raan) showed minimum

bacterial population (0.67x108 cfu g-1 soil) in soil ‘A’ and 0.87x108 cfu g-1 soil in

soil ‘B’ indicating 23% decrease in soil ‘A’ (Figure 4).

The population of actinomycetes in all sites ranged from 0.44x107 cfu g-

1soil to 1.75 x107 cfu g-1soil with mean value of 1.20 x107 ± 0.5 in soil A. Whereas,

it was 0.62x107 cfu g-1soil to 2.18 x107 cfu g-1soil with average value of 1.48 x107

± 0.6 in soil B (Table 2). The highest population observed was 1.75 x107 cfu g-1soil

and 2.18 x107 cfu g-1soil, respectively in soil A and in soil B at site-3 (D.D.Panah)

with 19.72 % less population in soil A. The lowest population was found at site-5

(Tibbi Qaisrani), which was 0.44 x107 cfu g-1soil and 0.62 x107 cfu g-1soil,

respectively in soil A and soil B indicating 29% decline in soil A (Figure 5).

Fungi population ranged between 3.1 x106 cfu g-1soil to 7.2 x106 cfu g-1soil

with mean values of 5.37 x106 ±1.46 in soil A. While, it ranged between 4.0 x106

48

cfu g-1soil to 8.4 x106 cfu g-1soil with an average values of 6.27 x106 ±1.46 in soil

B. In soil A, at site-8 (Qadir Pur Raan), the highest population was 7.2 x106 cfu g-1

soil. However, in soil B, it was 8.4 x106 cfu g-1soil indicating 14.28% decrease in

fungal population in soil A. Location-3 (D.D. Panah) showed minimum fungal

population of 3.1 x106 cfu g-1soil in soil A and 4.0 x106 cfu g-1soil in soil B,

indicating 22.5% decline in former soil (Figure 6).

Soil microorganism perform numerous essential functions in soil Viz. they are

involved in the transformation of nutrients, decompose animal and plant residues in

soil, microbial antagonistic role, soil structure improvement and aid in maintaining

soil biological equilibrium. Bacteria help in nitrogen fixation, phosphate

solubilization and sulpher oxidation. Actinomycetes have the ability to degrade

recalcitrant and fungi change dead organic matter into their biomass and carbob

dioxide (CO2) and help in breaking carbon ring structure of organic pollutants.

Significant inhibition in bacterial population in all the sites in soil ‘A’ was found.

Highest drop in bacterial population (42%) was found at location-2 (Shah Sadar

Din) in soil ‘A’ as compared to soil ‘B’. This might be because of elevated clay

contents and high soil pH which in turn result increased persistence and exposure

of herbicide to soil bacteria with concomitant decrease in bacterial population.

Different studies (Chau et al., 2011) experienced inhibition in bacterial population

due to herbicide application in heavy textured soil as compared to coarse textured

soil because of more persistence of herbicide in heavy textured soil. Drop in

bacterial population may be due to the injurious effect of herbicide on rhizobial

growth and development thus hampering nodule formation and nitrogen fixation.

49

Opposite to our results, Ratcliff et al. (2006) reported increase in bacterial

population by applying higher dose (100x field rate) of glyphosate herbicide. Singh

and Wright (2002) observed pronounced toxicity of the herbicides (chlorpyriphos,

fenomaiphos) on rhizobia in clay soil due to increased persistence of these

herbicides in this soil.

Substantial decrease in actinomycetes population at all locations in soil ‘A’

was noticed in comparison to soil without herbicide application (soil B). In soil ‘A’

at site-5 (Tibbi Qaisrani), 29% suppression in actinomycetes population was

observed as compared to soil B which could be due to high clay contents at

location-5. Because of adsorption of herbicides with caly its exposure to

actinomycetes increased ultimately their population decreased. Cupples et al.

(2005) also observed prolonged persistence of bromoxynil (3,5-dibromo-4-

Hydroxybenzonitrile) and ioxyinill (3,5-diiodo-4-hydroxy benzonitrile) herbicides

due to high clay contents in soil. This huge decrease in actinomycetes population in

soil ‘A’ might be due to the fatal effect of herbicide on actinomycetes. Negative

effects of different herbicides (paraquot, glyphosate, primeextra and atrazine) on

actinomycetes population has also been reported in many studies. Sebiomo et al.

(2011) observed substantial decrease in soil organic matter and actinomycetes

population due to paraquot, atrazine and glyphosate herbicides. Vischetti et al.

(2002) observed about 25 % and 64 % inhibition in actinomycetes due to

imazamox and benfluralin herbicides, respectively. Contrary to that, He et al.

(2006) observed no change in actinomycetes population due to metsulfuron-methyl

herbicide application.

50

Table 4.2. Average, maximum and minimum values of microbial parameters of soil exposed to buctril super

herbicide and unexposed soils of survey study

Microbial Biomass Carbon

Microbial Biomass Nitrogen

Microbial Biomass Phosphorus

-------------------------------------------------------(µg g-1 soil)----------------------------------------------

Average Max Min Average Max Min Average Max Min

Soil A 221±96 457 131 6.87±4.54 13.1 1.22 2.01±0.94 3.70 0.59

Soil B 279±119 573 187 7.71±4.84 14.4 1.70 2.59±1.06 4.12 0.72

Bacterial population Actinomycetes population Fungi population


(#x108 cfu g-1 soil) (#x107 cfu g-1 soil) (#x106 cfu g-1 soil)

Soil A 1.23±0.37 1.84 0.67 1.20±0.49 1.75 0.44 5.4±1.46 7.8 3.1

Soil B 1.69±0.56 2.37 0.87 1.46±0.58 2.18 0.62 6.3±1.46 8.4 4.0

Urease activity Dehydrogenase activity Alkaline phosphatase activity

(µgNH4-Ng-1 dwt 2h-1) (µg TPF g-1 24h-1) (μg Phenol g-1 h-1)


Soil A 204±62 301 112 46.0±8.5 54.6 29.1 51.8±15 69.3 29.2

Soil B 365±75 365 132 64.8±13.5 76.0 36.8 39.7±10.9 56.2 24.5

Nitrate nitrogen Olsen-P Total organic carbon

-----------------------(µg g-1 soil)-------------------------------- -------------(g kg-1)------------


Soil A 11.2±3.0 17.0 7.7 13.5±1.8 16.3 11.2 3.31±2.0 8.40 2.00

Soil B 18.6±4.7 25.0 12.4 15.1±1.6 18.4 12.6 3.92±2.0 8.80 2.66

51

100

200

300

400

500

600

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani

Sokar Vehova Qadirpur

Raan

Sher

Shah

Locations

MB

C (

µg g-1

)

Soil A Soil B

Figure 1: Microbial biomass carbon in soils exposed to buctril super herbicide for the last ten years versus

unexposed soils showing decline in MBC in exposed soils due to toxic effect of herbicide

52

0

3

6

9

12

15

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

MB

N (

µg g-1

)

Soil A Soil B

Figure 2: Microbial biomass nitrogen in soils exposed to buctril super herbicide for the last ten years versus

unexposed soils showing decline in MBN in exposed soil due to toxic effect of herbicide

53

0

1

2

3

4

5

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

M B

P (

µg g-1

)

Soil A Soil B

Figure 3: Microbial biomass phosphorus in soils exposed to buctril super herbicide for the last ten years versus

unexposed soils showing decline in MBP in exposed soil due to toxic effect of herbicide

54

Significant decline in fungi population in soil A was found in comparison to soil B.

At site-5 (Tibbi Qaisrani), in soil A considerable decrease (22.5%) in fungi

population was found as compared to soil B. This might be due to extreme

susceptibility of fungi to herbicide. Omar (1994) recorded significant decrease in

the population of osmophilic fungi due to different doses (0.3 µg g-1, 6.0 µg g-1) of

bromoxynil and profenofos herbicides. Sebiomo et al. (2011) observed

considerable inhibition in fungi population due to atrazine, paraquot, and

glyphosate herbicides. They also reported considerable decrease in soil organic

matter due to these herbicides. On the other hand, Araujo et al. (2003) observed

increase in the number of actinomycetes and fungi by the application of glyphosate

(2.16 mg glyphosate /kg soil).

4.1.3 Soil Enzymes Activity in Soils Exposed to Buctril Super Herbicide for

the Last Ten Years Versus Unexposed Soils

Enzymes carry out several important functions in soil and assist in nutrient

availability. Enzymes show typical characteristics and are resistant to different

factors causing their deactivation such as temperature, irradiation and substrate

presence. Therefore, no change in the activity of enzymes take place after their

exposure to those agents (Gainfreda et al., 2002: Gainfreda and Ruggiero, 2006).

Soil bound enzymes take part in transfer of different substrates due to their

immediate response and make them available to cells. Enzymes cause breakdown

of large substrate molecules by producing different intermediate metabolites

(Gianfreda et al., 2010). Soil enzyme are engaged in degradation of anthropogenic

chemicals (pesticides) thus help in decontamination of pesticides polluted soils

(Nannipieri and Bollag, 1991; Sutherland et al., 2002). In this study, the activity of

55

urease ranged from 112 µgNH4-N g-1 dwt 2h-1 to 301 µg NH4-N g-1 dwt 2h-1 with

mean value of 204 ±62 in soil A. Whereas, it ranged from 132 µgNH4-N g-1 dwt 2h-

1 to 365 µgNH4-N g-1 dwt 2h-1 with mean value of 234 ± 75 in soil B (Table 2). At

site-1 (Shadan Lund), the maximum urease activities were 301 µgNH4-N g-1 dwt

2h-1 and 365 µgNH4-N g-1 dwt 2h-1 in soil A and soils B, respectively, indicating

17.53% decrease in the activity of said enzyme in soil A. While at location-5 (Tibbi

Qaisrani), the minimum activities were 112 µgNH4-N g-1 dwt 2h-1 and 123 µgNH4-

N g-1 dwt 2h-1 in soil A and B, respectively showing 15.15% decline in urease

activity in former soil.

Dehydrogenase activity ranged from 29.1 µg TPF g-1 24h-1 to 54.6 µg TPF

g-1 24h-1 with mean value of 46.0± 8.5 at all locations in soil A. While, it ranged

from 36.8 µg TPF g-1 24h-1 to 76.0 TPF µg g-1 with mean value of 64 ± 13.5 in soil

B (Table 2). At site-9 (Sher Shah) maximum dehydrogenase activities were 54.6

µg TPF g-1 24h-1 and 76.0 µg TPF g-1 24h-1 in soil A and B, respectively showing

28.2 % decline in soil A. Minimum dehydrogenase activities were 29.1 µg TPF g-1

24h-1 and 36.8 µg TPF g-1 24h-1, respectively in soil A’ and B at location-2 (Shah

Sadar Din) which showed 20.92% decrease in dehydrogenase activity in soil A.

Alkaline phosphatase activity at all locations (1-9) ranged from 29.2 μg

Phenol g-1 h-1 to 69.3 μg Phenol g-1 h-1 with mean value of 51.8 ± 15.0 in soil A.

But in soil B, it was ranged from 24.5 μg Phenol g-1h-1 to 56.3 μg Phenol g-1h-1 with

an average of 39.7 ± 10.9 (Table 2). In soil A and soil B, maximum alkaline

phosphatase activities were 69.3 μg Phenol g-1h-1 and 56.2 μg Phenol g-1h-1,

56

respectively at location-9 (Sher Shah). Interestingly, indicating 23% high alkaline

phosphatae in soil A. The minimum alkaline phosphatase activity at site-5 (Tibbi

Qaisrani) in soil A was 29.2 μg phenol g-1h-1 and in soil B was 24.5 μg Phenol g-1h-1

indicating 19 % more activity in soil A.

The urease enzyme converts urea fertilizer in to ammonium. Different

herbicides exert different impacts on urease enzyme in soil. Cervelli et al. (1976)

reported considerable decline (10-30%) in hydrolysis of urea due to different

herbicides (linuron, diuron and monuron) through their competitive and non

competitive actions.

In this study significant decrease in enzymes activity was noticed in soil A

as compared to soil B. The results showed that applied herbicide had left injurious

effect on urease activity. Maximum reduction (17.6 %) was observed in location-1

in urease activity in soil A in contrast to soil B. This decrease was due to high

organic matter contents causing inadequate bioavailability of herbicide to soil

microbes that are involved in its biodegradation. Therefor, its persistence in soil

increased as a consequence urease activity declined. Cupples et al. (2005) also

reported prolonged persistence and limited bioavailability of herbicide

(bromoxynil) due to high organic matter in soil. This decrease in urease activity

might be due to herbicidal mortality of urease producing microbes. Ingram et al.

(2005) also reported death of urease synthesizing bacteria (Proteus vulgaris) due to

diazinon and imidacloprid. Similarly, Yu et al. (2011), observed significant

decrease (37.7%) in urease activity by chlorothalanil herbicide. On the contrary,

57

0

1

2

3

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

Bac

teri

al p

opul

atio

n (#

x108)

Soil A Soil B

Figure 4: Bacterial population in soils exposed to buctril super herbicide versus unexposed soils showing

decline in bacterial population in exposed soil due to toxic effect of herbicide

58

0

1

2

3

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

Act

ino

my

cete

s p

oup

latio

n (

#x

107)

Soil A Soil B

Figure 5: Actinomycetes population in soils exposed to buctril super herbicide for the last ten years

versus unexposed soils showing decline in population in exposed soil due to toxic effect of herbicide

59

0

3

6

9

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

Fun

gi p

opul

atio

n (#

x106)

Soil A Soil B

Figure 6: Fungi population in soils exposed to buctril super herbicide versus unexposed soils showing

decline in fungi population in exposed soil due to toxic effect of herbicide

60

Baboo et al. (2013) found increase in urease and dehydrogenase activity due to

various herbicides (butachlor 1kg/ha, pyrozosulfuron 25 g/ha, paraquot 200g /l and

glyphosate 360 g/l).

Dehydrogenase is a vital component of soil oxidation reduction processes

and is employed for measurement of electrons transfer during carbon substrate

utilization. It also acts as a sign of overall microbial activity in soil (Locke and

Zabolowicz, 2004). Anthropogenic chemicals interrupt dehydrogenase activity in

soil. In this study significant decrease in dehydrogenase activity in soil A as

compared to soil B was observed. Present results proved maxumum decline

(43.57%) in dehydrogenase activity at site-8 (Qadirpur Raan) in soil A as compared

to soil B. This might be due to heavy texture (36 % clay) of site-8 (Qadirpur Raan)

which prolonged the persistence of herbicide in soil. Therefore, microbes died due

to which dehydrogenase activity decreased. Cupples et al. (2005) experienced

increased bromoxynil persistence due to high clay contents in soil. Similarly,

Radiojevic et al. (2012) reported significant decrease (42.7%) in dehydrogenase

activity due to nicosulfuron herbicide (3.0 µg g-1 soil). Pampalha and Oliveria

(2006) found 80% reduction dehydrogenase activity by combined use of

prosulfuron and bromoxynil herbicides. Myanglambam et al. (2005) also

experienced significant decrease (35.5%) in dehydrogenase activity due to

quinalphos application. Decrease in weed roots due to herbicide might cused

inhibition in soil microbial community which in turn result reduced dehydrogenase

activity. Niemi et al. (2009) reported inhibition in dehydrogenase activity due to

decrease in the number of weed roots because of mortality of weeds by the

61

application of herbicide. On the other hand, Baboo et al. (2013) reported increase

in urease and dehydrogenase activity due to butachlor, pyrozosulfuron, paraquot

and glyphosate herbicide. However, Saha et al. (2012) reported 55 % increase in

dehydrogenase activity by field application rate of alachlor herbicide after 42 days.

Whereas, 5 FR and 10 FR of alachlor herbicide showed 58 % and 59 % increase,

respectively in dehydrogenase activity.

Alkaline phosphatase show active involvement in the mineralization of

organic phosphorus to inorganic form, thereby promoting availabity of phosphorus

to crop plants (Schneider at al., 2001). Alkaline phosphatase showed increased

activity in all locations in soil ‘A’ in contrast to soil ‘B’. At location-9 (Sher Shah)

highest incresae in alkaline phosphatase activity (23%) in soil A as compared to

soil B was observed. This may be because of negative correlation between

phosphorus contents and alkaline phosphatase activity. Because of decrease in

phosphorus due to herbicide in soil A, the activity of alkaline phosphatase

enhanced. This is because of high pH (8.0) at location-9 (Sher Shah) which has

enhanced the persisitence of herbicide residues and prolonged its exposure to

phosphate solubilizing microbes which in turn result decrease in phosphorus and

increase in alkaline phosphatase activity. Franzen and Zolinger (1997) also reported

prolonged persistence of bromoxynil in soil with high pH. This could be because of

inverse relationship between soil phosphorus and alkaline phosphatase activity.

Wright and Reddy (2001) exhibited negative correlation between alkaline

phosphatase activity (APA) and soil phosphorus as well as negative correlation of

APA with microbial biomass C and P. Similarly, Spiers and Gill (1979) observed

62

drop in phosphatase activity (APA) due to enhanced phosphorus contents in soil.

Tarafdar and Junk (1987) reported reduceion in alkaline phosphatase activity due to

phosphorus addition in soil. Fox and Comerford (1992) observed inverse

correlation between alkaline phosphatase activity and phosphorus contents in soil.

George et al. (2006) observed depletion in organic phosphorus due to increased

phosphatase activity. Opposite to our findings, Sarnaik et al. (2006) observed no

significant change in the population of phosphate solubilizing bacteria, soil

phosphorus contents and alkaline phosphatase activity by the application of

phorate, carbofuron, carbosulfuron, thiomethaxan, amidacloprid, chlorpyriphos and

monocrotophos application in comrarison to control.

4.1.4 Buctril Super Herbicide Impacts on Nitrate Nitrogen, Olsen-P and

Total Organic Carbon in Soils Exposed to Buctril Super Herbicide for

the Last Ten Years Versus Unexposed Soils

In all sites, nitrate nitrogen ranged from 7.7 to 17 µg g-1 soil with an average

of 11.2±3 in soil ‘A’ while in soil ‘B’ it ranged from 12.4 to 25.2 µg g-1 soil , with

an average of 18.6±4.7. The highest decline of about 55% in nitrate nitrogen at

location-9 (Sher Shah) in soil ‘A’ as compared to soil ‘B’ followed by 47.2%

decline in L8 (Qadirpur Raan) in soil ‘A’ as compared to soil ‘B’ was observed.

Olsen-P ranges from 11.2 to 16.3 µg g-1 soil with an average value of 13.5±1.8 in

soil A, while in soil B it rangrd from 12.6 to 16.5 µg g-1 soil with average value of

15.1±1.6. Highest decrease of about 17 % in Olsen-P was noticed in S-7 (Vehova)

followed by 16 % in S-6 (Sokar) in soil A in contrast to soil B.

63

Total organic carbon (TOC) was ranged from 2.0 to 8.40 g kg-1 with an

average value of 3.31±1.99 in soil A, while in soil B it rangrd from 2.69 to 8.80 g

kg-1 with average value of 3.91±1.99. Highest decrease of about 28.57 % in total

organic carbon was observed in S-2 (Shah Saddar Din) followed by 21.56% in S-1

(Shadan Lund) in soil A in contrast to soil B.

Nitrification being an essential component of nitrogen cycle, engage

ammonium oxidizing bacteria and ammonium oxidizing archaea for the production

of nitrate (NO3) from ammonium (NH4) as majority of the plants prefer nitrate form

of nitrogen. Nitric acid (HNO3) formed during nitrification process splits up into

NO3- and H+ ions resulting decrease in soil pH and increase in nutrients availability

(Black et al., 1998). Present results showed obvious drop of about 47.2 % and 55%

in nitrate nitrogen at S-8 (Qadirpur Raan) and S-9 (Sher Shah), respectively in soil

A as compared to soil B. This decrease in nitrate nitrogen in S-8 (Qadirpur Raan)

and S-9 (Sher Shah) was because of herbicide associated death of ammonium

oxidizing bacteria (AOB), since most of the autotrophic nitrifiers are sensitive to

herbicides.

Different studies reported decrease in anmmonium oxidizers population and

entire inhibition in nitrification process by simazine herbicide with concomitant

decrease in nitrate nitrogen (Hernandez et al., 20011). Allievi and Giglioti (2001)

observed lethal effect of sulfonyl urea herbicides on autotrophic nitrifiers by

hampering their amino acid assimilation ability. Other investigations revealed

about 90% and 33% decline in ammonium oxidizing bacteria by 100ppm and 1

64

ppm concentration of bromoxynil herbicide (Pampalha and Oliveria, 2006)

therefore, hindered nitrification with simultaneous decline in nitrate nitrogen.

Chang et al. (2011) observed substantial decrease in ammonium oxidizers due to

different herbicides (atrazine, dicamba-4, flumutoron, metolachlor and

sufentrazone) under different concentrations (0ppm, 10ppm, 100ppm and 1000

ppm). Opposite to our results, researchers reported stimulation in the activity of

ammonium oxidising bacteria by the application of acetachlor herbicide during

intial days of treatment (Li et al., 2008). Conversely to that boosted nitrification by

azospirillum isolated from soil treated with cypermethrin or fenvalerate pesticide

was reported by (Rangaswamay et al., 1992).

The principal importance of phosphorus is that it acts as energy store house

within the cell and is a fundanental component of DNA and proteins. Phosphorus

being neceaary nutrient element consist of approximately 0.2% of dry weight of

plant (Schachtman, 1998). It helps in mediating enzymes activities and regulating

various metabolic processes (Theodorou and Plaxton, 1993). Presence of huge

quantity of bromoxynil residues in Sokar (0.14 ppm) and Vehova (0.19 ppm) in soil

‘A’ suppressed fungi population as a consequece Olsen-P showed 16% and 17%

decrease in these sites, respectively. Similar decrease in fungi population has been

observed in our field studies due to different rates of bromoxynil herbicide. Kucey

(1983) reported that fungi are most efficient in solubilizing precipitated calcium

phosphate and rock phosphate and noted positive correlation between phosphate

solubilizing fungi and available phosphorus. Ahmad and Khan (2010) reported 72

%, 91% and 94% decrease in the population of phosphate solubilizing bacteria


65

(Enterobacter asburiae) due to different concentrations of quizalafop-p-ethyl (40,

80 and 120 µg/L) as compared to control. Contradictory to that, Das et al. (2003)

reported stimulation in phosphate solubilizer’s population and increased

phosphorus availability in soil. Whereas, Sarnaik et al. (2006) observed no change

in the population of phosphate solubilizing bacteria due to phorate, carbofuron,

carbosulfuron, thiomethaxan, amidacloprid, chlorpyriphos and monocrotophos

application.

Organic matter is considered as life blood of soil. It has remarkable impact

on soil physical, chemical and biological characteristics. Soil organic

constitutesabout 58% of soil organic matter (Bianchi et al., 2008). Soil organic

carbon is considered as fundamental indicator for the assessment of soil quality

(Adeboye et al., 2011). Organic carbon is the most necessary constituent of soil

because it provides energy and increase nutrient supply to plants through

mineralization. Apparent decline of about 28.57% and 21.56% in total organic

carbon in Site-2 (Shah Sadar Din) and Site-1 (Shadan Lund), respectively in soil A

was because of high clay contents in these sites prolonging herbicide persistence

with concomitant decrease in soil microorganisms.To overcome the injurious

impacts of herbicides microbes caused rapid decomposition of organic matter for

obtaining energy which in turn result loss of organic carbon in the form of CO2.

Diffrenet studies (Ayansina and Oso, 2006) observed 13%, 30% and 11% drop in

organic matter by combined mixture of two herbicides (atrazine + metolachlor)

during Ist, 4th and 6th weeks after herbicide application, respectively as compared to

control. This decrease in organic carbon in soil A might be due to co-metabolism of

66

50

150

250

350

450

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

(µ

gN

H4-N

g-1

2h-1

)

Soil A Soil B

Figure 7: Urease activity in soils exposed to buctril super herbicide for the last ten years versus unexposed

soils showing decline in urease activity in exposed soil due to toxic effect of herbicide

67

20

40

60

80

100

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

(µ

g T

PF

g-1

2

4 h

-1)

Soil A Soil B

Figure 8: Dehydrogenase activity in soils exposed to buctril super herbicide for the last ten years versus

unexposed soils showing decline in dehydrogenase activity in exposed soil due to toxic effect of herbicide

68

20

40

60

80

100

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

(µ

g T

PF

g-1 2

4 h-1

)

Soil A Soil B

Figure 9: Alkaline phosphatase activity in soils exposed to buctril super herbicide versus unexposed soils

showing increase in APA

in exposed soil due to toxic effect of herbicide on phosphate solubilizing bacteria and available-P

69

organic matter and herbicide. Researchers (Sukul et al., 2006) observed significant

decline in organic matter due to metalaxyl herbicide and reported that this dercease

in organic carbon was the result of co-metabolism phenomina. Weeds death due to

herbicide may be the second cause of organic matter inhibition because organic

matter comprises of both dead animal and plant residues. Plant roots liberate

different exudates and harmones (gebrilin and auxin) which increase organic matter

in soil, so death of weeds due to herbicide result decline in organic matter in soil.

Niemi at al. (2009) found decrease in enzymes activity and organic matter due to

herbicides application because of absence of stimulatory effect of weeds.

70

5

10

15

20

25

30

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

NO

3-N

(µ

g g-1

soil)

Soil A Soil B

Figure 10: Nitrate nitrogen in soils exposed to buctril super herbicide versus unexposed soils showing decline in

nitrate nitrogen in exposed soil due to toxic effect of herbicide

71

10

15

20

25

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

Ols

en-P

(µ

g g-1

)

Soil A Soil B

Figure 11: Olsen-P in soils exposed to buctril super herbicide for the last ten years versus unexposed soils

showing decline in Olsen-P in exposed soils due to toxic effect of herbicide

72

0

3

6

9

Shadun

Lund

Shah S.

Din

Daira D.

Pannah

Dona Tibbi

Qaisrani


Raan

Sher

Shah

Locations

Tota

l org

anic

car

bon (

gkg-1

)

Soil A Soil B

Figure 12: Total organic carbon in soils exposed to buctril super herbicide versus unexposed soils showing

increase in total organic carbon in exposed soils because the herbicide was used as a surce of energy

73

4.2 IMPACTS OF BUCTRIL SUPER HERBICIDE ON SOIL

MICROBIOLOGY

The physico-chemical and microbial properties of soil under the study are

given in (Table 4.3). The initial sand, silt and clay contents of soils were 48%,

24% and 28%, respectively and pH was 7.8. The electrical conductivity was

0.32dSm-1 whereas, total organic carbon and Olsen-P were 4.3 and 3.9 g kg-1 and

9.6 and 8.7 µg g-1 in 2011-12 and 2012-13, respectively. In 2011-12 and 2012-13,

the urease, dehydrogenase and alkaline phosphatase activities were 301 and 272

µgNH4-N g-1 dwt 2h-1, 31.3 and 36.6 µg TPF g-1 24h-1, 56.7 and 49.3 µg Phenol g-1

h-1, respectively. On the other hand bacterial population was 1.51 x 107 and 1.18 x

107, actinomycetes population 8.4 x 105 and 7.7 x 105, fungi population was 6.0 x

104 and 5.5 x 104 in 2011-12 and 2012-13, respectively. Microbial biomass carbon

was 473 µg g-1 and 435 µg g-1, microbial biomass nitrogen was 20.6 µg g-1 and 23.5

µg g-1, microbial biomass phosphorus was 10.3 µg g-1 and 8.6 µg g-1 and nitrate

nitrogen was 23.1 µg g-1 and 28.5 µg g-1 during both years, respectively.

4.2.1 Microbial Biomass Carbon under Different Treatments of Buctril

Super Herbicide in Light-Textured Soil

Soil microbial biomass carbon was significantly different in all herbicidal

treatments and was in the order of 375 mL ha-1 > 750 mL ha-1 > 1500 mL ha-1 >

2250 mL ha-1. Highest biomass carbon (471µg g-1 soil) was observed in control,

followed by 452 µg g-1soil in 375 mL ha-1 and lowest biomass carbon (308 µg g-

74

1soil) was observed in 2250 mL ha-1 during 2011-12. In 2012-13, highest biomass

carbon was found in control that was 414 µg g-1soil, followed by 380 µg g-1soil in

375 mL ha-1 and the minimum biomass carbon (269 µg g-1 soil) was observed in

2250 mL ha-1. Overall, 1500 mL ha-1 and 2250 mL ha-1 treatments caused 27 %

and 34.6 % reduction in biomass carbon as compared to control during 2011-12,

while 30% and 35.5 derease in biomass carbon was observed as compared to

control during 2012-13 in (light-textured soil) field experiment-1 (Table 4.4).

Sampling days resulted highly significant effect on biomass carbon (P ≤ 0.05).

Maximum biomass carbon was noticed at day-60 (474 µg g-1soil) and minimum

biomass carbon was found at day-7 (347µg g-1soil) indicating 26.8 % less biomass

carbon at day-7 as compared to day-60 during 2011-12. Similarly, during 2012-13

biomass carbon was maximum at day-60 (413 µg g-1soil) and minimum at day-7

(294 µg g-1soil), indicating 29 % decline in biomass carbon at day-7 as compared to

day-60. In general from day-0 to day-7 decrease in biomass carbon was observed

but after that biomass carbon showed inceasing trend up to day-60.

4.2.2 Microbial Biomass Nitrogen under Different Treatments of Buctril


Soil microbial biomass nitrogen was significantly different in all herbicidal

treatments. Maximum biomass nitrogen (18.4µg g-1soil) was observed in control,

followed by (16.3 µg g-1soil) in 375 mL ha-1 and minimum biomass nitrogen (12.6

µg g-1 soil) was observed in 2250 mL ha-1 in 2011-12. Whereas, in 2012-13, the

highest biomass nitrogen (22.8 µg g-1soil) was found in control followed by (20.1

75

Table 4.3. Physico-chemical characteristics of soils of field experiment-1 (light-

textured soil)

Parameters 2011-12 2012-13

Sand (%) 48 48

Silt (%) 24 24

Clay (%) 28 28

pH 7.8 7.8

EC (dSm-1) 0.32 0.32

TOC (g kg-1) 4.3 3.9

Olsen-P (µg g-1) 9.6 8.7

Urease activity (µgNH4-N g-1 dwt 2h-1) 301 272

Dehydrogenase activity (µg TPF g-1 24h-1) 31.3 36.3

Alkaline phosphatase activity

(µg Phenol g-1 h-1)

56.7 49.3

Bacterial population (#x107) 1.51 1.18

Actinomycetes population (#x105) 8.4 7.7

Fungi population (#x104) 6.0 5.5

Microbial biomass carbon (µg g-1) 473 435

Microbial biomass nitrogen (µg g-1) 20.6 23.5

Microbial biomass phosphorus (µg g-1) 10.3 8.6

Nitrate nitrogen (µg g-1soil) 23.1 28.5

76

µg g-1soil) in 375 mL ha-1 and minimum biomass nitrogen (14.7µg g-1soil) was

observed in 2250 mL ha-1. Overall, 1500 and 2250 mL ha-1 herbicide treatments

caused 25.5 % and 31.5 % reduction in biomass nitrogen as compared to control

during 2011-12, while, 29.8 % and 35.5 % decrease in biomass nitrogen as

compared to control in 2012-13 in Koont soil. Sampling days showed highly

significant effect on biomass nitrogen (P ≤ 0.05). Maximum biomass nitrogen was

noticed at day-60 (19.6 µg g-1soil) and minimum was found at day-15 (11.6 µg g-

1soil) indicating 41 % less biomass nitrogen at day-15 as compared to day-60

during 2011-12. Similarly, in 2012-13 biomass nitrogen was maximum at day-60

(23.7µg g-1soil) and minimum at day-7 (14.2 µg g-1soil) indicating 40 % decline in

biomass nitrogen at day-7 as compared to day-60. Biomass nitrogen showed

decreasing trend from day-0 to day-15 and then increasing trend was observed up

to day-60 (Table 4.4).

4.2.3 Microbial Biomass Phosphorus under Different Treatments of Buctril


Soil microbial biomass phosphorus was significantly different in all

herbicidal treatments and was found in the order of 375 mL ha-1 > 750 mL ha-1 >

1500 mL ha-1 > 2250 mL ha-1. Maximum biomass phosphorus (9.94 µg g-1soil) was

observed in control, followed by 8.43µg g-1 soil in 375 mL ha-1 and minimum

biomass phosphorus (6.54 µg g-1soil) was observed in 2250 mL ha-1 during 2011-

12. Highest biomass phosphorus was found in control (8.62 µg g-1soil) followed by

(6.77µg g-1soil) in 375 mL ha-1 and minimum biomass phosphorus (4.74 µg g-1soil)

was observed in 2250 mL ha-1 during 2012-13. Overall, 1500 mL ha-1 and 2250 mL

77

ha-1 herbicide treatments caused 29.5 % and 34.2 % reduction in biomass

phosphorus as compared to control during 2011-12, while, 39.2 % and 45 %

decrease in biomass phosphorus as compared to control during 2012-13 in field

experiment-1 (light-textured soil).

Sampling days illustrated highly significant effect on biomass phosphorus

(P ≤ 0.05). Maximum biomass phosphorus was noticed on day-0 (9.24 µg g-1soil)

and minimum was found at day-30 (6.41µg g-1soil) indicating 30.6 % less biomass

phosphorus at day-30 as compared to day-0 during 2011-12. Similarly, during

2012-13 biomass phosphorus was maximum (7.82µg g-1soil) at day-60 and

minimum (5.18µg g-1soil) at day-15 indicating 33.7 % decline in biomass

phosphorus at day-15 as compared to day-60. Biomass phosphorus showed

decreasing trend from day-0 to day-30 and afterward increasing trend was observed

up to day-60 (Table 4.4).

The interaction of sampling days and treatments revealed maximum

biomass carbon (485 μg g-1soil) at day-60 in control. Minumum biomass carbon

(243μg g-1soil) was recorded at day-7 in 2250 mL ha-1 treatment indicating 50%

decline in biomass carbon, followed by 255 μg g-1soil in 375 mL ha-1 at day-15

indicating 47.4 % drop in biomass carbon followed by 274μg g-1soil at day-0 by

375 mL ha-1 showing 43% drop in biomass carbon during 2011-12 as compared to

485μg g-1soil biomass carbon at day-60 in control. The treatment and sampling

days interaction showed maximum biomass carbon at day-15 in control (423 μg g-

1soil). Minimum biomass carbon was recorded at day-7 in 2250 mL ha-1 (206 μg g-

1soil) resulting 51% decline in biomass carbon, followed by 225 μg g-1soil at day-

78

0 in 2250 mL ha-1 indicating 47 % decline, followed by (227 μg g-1soil) at day-7 in

1500 mL ha-1 showing 46.3% decrease, followed by (234 μg g-1soil) at day-15 in

2250 mL ha-1 resulting 44.6% decline followed by (258 μg g-1soil) at day-30 in

2250 mL ha-1 resulting 39% decline in biomass carbon as compared to 234 μg g-1

soil that was found in control at day-15 during 2012-13 (Figure 13).

The interactive effects of sampling days and treatments revealed maximum

biomass nitrogen (19.7 μg g-1soil) at day-0 in control. Minumum biomass nitrogen

(6.9 μg g-1soil) was recorded at day-15 in 2250 mL ha-1 showing a 65% decline in

biomass nitrogen, followed by 2250 mL ha-1 at day-7 (7.5 μg g-1soil) indicating a

62 % drop in biomass nitrogen, followed by 8.6 μg g-1soil at day-15 by 1500 mL

ha-1 showing a 56% drop in biomass nitrogen, followed by day-7 in 1500 mL ha-1

(9.3 μg g-1soil) showing a 52% drop in biomass nitrogen as compared to 19.7 μg g-

1soil biomass nitrogen which was observed in contro at day-0 during 2011-12. The

interaction of treatment and sampling days showed maximum biomass nitrogen at

day-60 in 2250 mL ha-1 (24.8 μg g-1soil). Whereas, minimum biomass nitrogen

was recorded at day-7 in 2250 mL ha-1 (8.4 μg g-1soil) resulting a 66% decline in

biomass nitrogen, followed by 9.5 μg g-1soil at day-15 in 2250 mL ha-1 with 62 %

decrease, followed by 10.2 μg g-1soil at day-7 in 1500 mL ha-1 showing a 56%

decrease, followed by 11.7 μg g-1soil at day-15 in 1500 mL ha-1 treatment resulting

a 53% decline, followed by 12.6 μg g-1soil at day-7 in 750 mL ha-1 resulting a 49%

decline as compared to 2250 mL ha-1 at day-60 in 2012-13 (Figure 14). Sampling

days and treatments interactive effects revealed the highest biomass phosphorus at

day-0 in control (10.36μg g-1soil). Lowest biomass phosphorus was recorded at

79

day-30 in 2250 mL ha-1 (4.53 μg g-1soil) indicating 56% decline, followed by 5.15

μg g-1soil in 1500 mL ha-1 at day-30 indicating 50 % drop in biomass phosphorus,

followed by 5.43 μg g-1soil at day-7 by 2250 mL ha-1 showing 47.5% drop in

biomass phosphorus, followed by 5.81 μg g-1soil at day-15 in 2250 mL ha-1

showing 40% drop in biomass phosphorus as compared to 10.36 μg g-1soil which

was observed in control at day-60 during 2011-12. Similarly, the interaction of

treatment and sampling days showed maximum biomass phosphorus (8.92 μg g-

1soil) at day-7 in control. Minimum biomass phosphorus (3.33 μg g-1soil) was

recorded at day-7 in 2250 mL ha-1 resulting 63% decline in biomass phosphorus,

followed by 3.47 μg g-1soil at day-30 in 2250 mL ha-1 indicating 61 % decline,

followed by 3.72 μg g-1soil at day-15 in 2250 mL ha-1 showing 58% decrease,

followed by 4.11 μg g-1soil at day-15 in 1500 mL ha-1 resulting 54% decline,

followed by 4.32 μg g-1soil at day-30 in 1500 mL ha-1 resulting 52% decline in

biomass phosphorus as compared to 8.92 μg g-1soil biomass phosphorus at day-7 in

control during 2012-13 (Figure 15).

Soil microbial biomass comprises of substantial quantity of essential

elements that include calcium, carbon, nitrogen and phosphorus (Bardegu et al.,

1997) and act as ecological marker of soil because of its active contribution in

nutrients cycling and due to major role in soil structure formation (Smith and Paul,

1990). Soil microbial biomass constitutes about 2-6 % of soil organic matter

although being most mobile part of the soil organic matter, it execute major role in

nutrients cycling (Anderson and Domsch, 1980). Present study revealed highest

microbial biomass carbon in control follwed by 375 mL ha -1 and lowest biomass

80

carbon in 2250 mL ha-1 during both years in light-textured soil (field experiment-

1). The reason of more biomass carbon in control was because of no toxic effect of

herbicide on soil microbial community, while, relatively higher biomass carbon in

375 mL ha-1 might be because of lower concentration of herbicide that had not

affected soil microorganisms to a great extent. Highest reduction in biomass carbon

in 2250 mL ha-1 was due to high concentration of herbicide that had reduced the

population of soil microbes due to which microbe biomass carbon decreased. El-

Ghamary et al. (2001) decribed significant decrease in biomass carbon and nitrogen

due to bensulforon methyl and metsulfuron methyl herbicides. Many studies

highlighted adverse effects of different herbicides (ehion, carbofuron and

hexaconazole) on soil microbial community even upto 61% reduction in their

population with concomitant decrease in biomass carbon (Kalam and Mukhejee,

2001). Wang et al. (2006) reported appreciable decrease (41-83 %) in microbial

biomass carbon by the application of high and low dose of methamidophos and

urea. This could be because of the fact that the native soilmicrobial community that

was tolerant to the applied herbicide showed sensitivity (susceptiblity) to the

interaction product of soil and herbicide which exerted lethal effect on them

leading to decrease in biomass carbon. Researchers, (Baboo et al., 2013) reported

that some microorganisms that were tolerant to butachlor, paraquot and

pyrozosulfuron herbicides exhibited severe sensitivity to the interaction product of

soil and herbicides. Different researchers (Vischetti et al., 2002) while seeing the

effect of herbicides (benfluralin and imazamox) on microbial biomass in different

soil types noticed significant decrease (20 %) in microbial biomass carbon due to

the application of 50 % of the recommended dose of imazamox.

81

Table 4.4. Microbial biomass carbon, nitrogen and phosphorus as influenced by different treatments of buctril super

herbicide and sampling days in light-textured soil showing decline due to lethal effect of herbicide

Factors Microbial Biomass C

2011-12 2012-13

Microbial Biomass N

2011-12 2012-13

Microbial Biomass P

2011-12 2012-13

-----------------------------------------------(µg g-1 soil)------------------------------------------------

Treatments

Control

471 A

414 A

18.4 A

22.8 A

9.94 A

8.61 A

375 mL ha-1 452 B 380 B 16.3 B 20.1 B 8.43 B 6.77 B

750 mL ha-1 375 C 332 C 15.0 C 17.6 C 7.39 BC 5.82 C

1500 mL ha-1 343 D 289 D 13.7 D 16.0 C 7.0 C 5.24 D

2250 mL ha-1 308 E 269 E 12.6 D 14.7 D 6.54 C 4.74 E

LSD 8.32 7.77 1.14 2.08 0.49 0.194

Sampling days

0 389 B 321 C 17.3 B 20.5 B 9.24 A 7.20 B

7 347 E 294 D 12.3 D 14.2 D 7.31 B 5.48 C

15 358 D 319 C 11.6 D 15.1 D 7.27 B 5.18 C

30 381 C 338 B 15.3 C 17.7 C 6.41 B 5.51 C

60 474 A 413 A 19.6 A 23.7 A 9.07 A 7.82 A

LSD 8.32 7.77 1.14 2.08 0.49 0.194

Analysis of

variance

p-value p-value p-value p-value p-value p-value

Treatments (T) < 0.05 < 0.05 < 0.05 < 0.05 < 0.05 < 0.05

Sampling days (D) < 0.05 < 0.05 < 0.05 < 0.05 < 0.05 < 0.05

82

Results of present study showed highest MBC at day-60 and lowest was at

day-7. Highest MBC at day-60 was because of the reason that the microbes might

developed resistance against this herbicide and degrade it and used it as a source of

carbon consequently their population enhanced and MBC increased. The recovery

of biomass carbon with time was because of high sand contents (40 %) in light-

textured soil (field experiment-1) resulting decrease in persisitence and increase in

herbicide degradation ultimately biomass carbon increased. Das and Mukherjee

(2000) reported increase in the population of soil microorganisms by utilization of

herbicides (fenvelerate, carbofuron and phorate) as a source of carbon after

degradation of these herbicides. In this study, because of high concentration of

buctril super residues at day-7, the growth of microbial population ceased due to

which MBC decreased. Application of pre and post emergence herbicides including

pendimethalin{N- (1ethylpropyl)-3, 4-dimethyl-2, 6- dinitro benzenamine},

fenoxaprop-P- ethyl{(D+)-ethyl-2- (4-(6-chloro-2- benzoxazolyloxy)-phenoxy) -

propionate}. Metribuzin {4-amino-6-(1,1-dimethylethyl)-3-(methylthio)-1,2,4-

triazine-5(4H)-1}and tralkoxydim, showed 10-100 time decrease in soil

microorgamnisms population as a consequence microbial biomass decreased

(Khalid et al., 2001). While studying the impact of metalaxyl on soil microbial

biomass, researchers (Sukul and Spiteller, 2001) found inverse relationship

between metalaxyl persistence and microbial biomass carbon in soil. Vieri et al.

(2007) during evaluation of sulfentrazone herbicide (0.7 µg g-1soil) effect on soil

microbial community and microbial biomass observed substantial decrease in

biomass carbon. Microbial biomass of bacteria, fungi and actinomycetes can be

used for the measurement of the mass of the living part of soil organic matter. The

83

150

250

350

450

550

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

C (

µg g-1

soil)

Control 375 mL ha-1 750 mL ha-1

1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 13: Interactive effect of herbicide and sampling days on microbial biomass carbon in light-textured

soils showing decline in MBC upto day-30 which later on subsided due to herbicide degradation

84

5

10

15

20

25

30

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

N (

µg

g-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 14: Interactive effect of herbicide treatments and sampling days on microbial biomass nitrogen in

light-textured soils showing decline in MBN upto day-30 which later on subsided due to herbicide

degradation

85

2

5

8

11

14

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

P (

µg

g-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 15: Interactive effect of herbicide treatments and sampling days on Microbial biomass phosphorus

in light-textured soils first decline in MBP which later on susided due to degradation of herbicide

86

microbial biomass play a vital role in decomposing soil organic matter as well as

residues of different plants and animals which ultimately liberate carbon dioxide

(CO2) and nutrients and make them available for plant (Cookson et al., 2008). In

present study average highest decline (33.5 %) in biomass nitrogen in 2250 mL ha-1

and no decrease in control was recorded during both years in field experiment-1

(light-textured soil). This decline in MBN in 2250 mL ha-1 might be because of

lethal effect of high level of herbicide on the membrane permeability and

physiological functions of soil miorganisms leading to their death due to which

total microbial biomass including biomass nitrogen declined. The second reason for

inhibition in biomass nitrogen might be because of reduction in respiration and

metabolic and biochemical activities of soil microbial community leading to their

mortality, as our results highlighted significant decrease in actinomycetes, bacteria

and fungi population due to buctril super herbicide applicatin. Similar results were

reported by Nannipieri et al. (1990) they also found that essential cell function are

associated with respiration process so any hinderance in respiration activity can

hamper carbon mineralization leading to microbial mortality and as a result decline

in soil microbial biomass. Contrary to that, Weaver et al. (2007) reported no

significant decrease in microbial population due to glyphosate application even

when applied more than field application rates. As far as sampling days are

concerned, the microbial biomass nitrogen was highest at day-60 because of

degradation of the herbicide residues by some species of soil bacteria and fungi.

Allison (2005) reported debromination of buctril super (bromoxynil) herbicide by

Desulfitobacterium chlorospirans and its utilization by these bacteria as a source of

carbon and energy consequently the growth of susceptible microbe restored and

87

total bimass enhanced. Different studies (Yu et al., 2011) found significant

inhibition in bacteria, fungi and actinomycetes population (as well as enzymes

activities) in the beginning due to chlorothalanil application but later on they found

that microbes made adjustment against chlorothalanil and their population flourish,

consequently total microbial biomass boost up. This recovery of biomass nitrogen

at day-60 might be because of more sand contents and low persistence of herbicide

in Koont soil. Restoration of biomass nitrogen at day-60 might due to the release

of nitrilase enzyme by Klebsiella after its adjustment to the said herbicide which

converted 3,5-dibromo-4hydroxybenzinitrile to 3,5-dibromo-4-hydroxybenzoic

acid using ammonia (NH3) as a nitrogen source. Different studies (McBride et al.,

1986) reported similar conversion of 3,5-dibromo-4hydroxybenzinitrile to 3,5-

dibromo-4hydroxybenzoic acid by Klebsiella by using librated ammonia as a

carbon source. At day -7 maximum drop in biomass nitrogen was attributed

towards high concentration of herbicide residues leading mortality of most of the

soil mirooganisms.

Microbial biomass plays many important functions in soil including nutrient

cycling, breakdown of animals and plant resisues and biodegradation of different

agro-chemicals, therefore, reflect total biological activity in soil (Kaschuk et al.,

2010). Our results showed that microbial biomass phosphorus was statistically

different in all treated soils showing the order of 350 mL ha-1 > 750 mL ha-1 > 1500

mL ha-1 > 2250 mL ha-1 4. Maximum biomass phosphorus (9.94 µg g-1soil) was in

control, followed by 8.43µg g-1soil in 375 mL ha-1 and minimum biomass

phosphorus (6.54 µg g-1soil) was observed in 2250 mL ha-1 during first year,

similarly the highest MBP was in control (8.62 µg g-1soil), followed by (6.77µg g-

88

1soil) in 375 mL ha-1 and mimimum MBP (4.74 µg g-1soil) was recorded in 2250

mL ha-1 during second year. Overall, 1500 mL ha-1 and 2250 mL ha-1 herbicide

treatments caused 29.5 % and 34.2 % reduction in biomass phosphorus as

compared to control during first year, while 39.2 % and 45 % decrease in biomass

phosphorus as compared to control during second year in field experiment-1 (light

textured soil). This huge deline in biomass phosphorus was because of the reason

that the herbicide caused reduction of population and death of most of the soil

microbes (bacteria, actinomycetes and fungi) as it was evident from our results

indicating obvious reduction in bacterial, actinomycetes and fungi population in

light textured soil by high dose of buctril super herbicide application. Similarly,

Busse et al. (2001) reported toxicity of glyphosate to most of soil bacteria and fungi

with the concomitant decrease in their population. This reduction might be due to

the toxicity of high concentration of applied herbicide to soil enzymes

(dehydrogenase, alkaline phosphatse and urease) as it was proved in our present

study. Contrary to this, Digrak and Kazaniki (2001) observed increase in bacterial

population and no effect on other microbes in soil treated with organophosphorus

insecticide (isofenphos) in contrast to untreated soil. Sampling days exhibited

significant effect on MBP (P ≤ 0.05). During 2011-12, the highest biomass

phosphorus was noticed on day-0 and lowest was recorded at day-30 indicating

30.6 % less MBP at day-30 as compared to day-0. Similarly, during 2012-13, the

MBP was maximum at day-60 and minimum at day-15 indicating 33.7 % inhibition

in MBP at day-15 as compared to day-60. Biomass phosphorus showed decreasing

trend from day-0 to day-30 and after that increasing trend was observed up to day-

60 (Table 4.4). Hight decrese in biomass phosphorus at day-30 during first year and

89

at day-15 during second year in light textured soil was because of presence of

herbicide residues that caused death of soil microbes. As we noticed the

concentration of bromoxynil was 0.86 ppm at day-15 during first year and 0.27

ppm at day-30 during second year in light textured soil that inhibited microbial

population ultimately biomass phosphorus decreased. Highest biomass phosphorus

at day-0 in first year and at day-60 in second year was because of less time of

exposure of herbicide to soil microorganisms at day-0 and due to degradation of

bromoxynil by the micorobes at day-60. In present study we found almost complete

degradation of herbicide in all herbicidal treatment soil at day -60. Similar to our

results, Ingram and Pullin (1974) reported the persistence of herbicide

(bromoxynil) in three soil types (clay loam, sand and peat) with 1.12 Kg ha-

1application rate. Initially the residues of the herbicides found were 0.91mgL-1 in

clay, 0.53 mg L-1 in peat and 0.35mgl-1 in sandy soil. The residues of bromoxynil

turn down below the level of detection after 14th day in sand, after 28th days in clay

and after 44th days in peat.

4.2.4 Correlation of Microbial Biomass C, N and P with Buctril Super

Herbicide

Microbial biomass carbon (MBC) revealed strong negative correlation (-

0.74) with bromoxynil herbicide (Figure 16), similarly microbial biomass nitrogen

(MBN) showed negative correlation (-0.44) with bromoxynil herbicide (Figure 17).

Biomass phosphorus (MBP) also showed negative (-0.30) but weak correlation

with bromoxynil (Figure 18). Strong negative correlation was found in this study

between soil microbial biomass carbon and bromoxynil residues (r = - 0.74),

90

microbial biomass nitrogen and bromoxynil residues (r= -0.44), microbial biomass

phosphorus and bromoxynil residues (r= -0.30). Voos and Groffman (1997)

reported positive correlation of herbicides (dicambia and 2,4-D) dissipation with

soil organic matter, microbial biomass carbon and biomass nitrogen. These results

advocate association between soil microbial biomass and degradation of different

herbicides in the soil ecosystem and such relationships are helpful for the

development of different approaches for the evaluation and prediction of herbicides

fate in various soil ecologies.

4.2.5 Bacterial Population under Different Treatments of Buctril Super

Herbicide in Light-textured Soil

It is clearly depicted from the results that bacteria, actinomycetes and fungi

population were significantly different in all herbicidal treatments and were in the

order of 375 mL ha-1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL ha-1. In control, the

highest bacterial population was observed (i.e. 1.50 x107cfu g-1soil), followed by

1.38 x107cfu g-1soil in 375 mL ha-1, while the lowest population (1.05 x107cfu g-

1soil) was observed in 2250 mL ha-1 during 2011-12. On the other hand, the

highest bacterial population was found in control i.e 1.18 x107cfu g-1soil, followed

by1.04 x107 cfu g-1soil, in 375 mL ha-1 and the lowest bacterial population in 2250

mL ha-1 (0.76 x107cfu g-1 soil) during 2012-13. Overall, 1500 mL ha-1 and 2250 mL

ha-1 caused a 23.3% and 30.0 % reduction in bacterial population during 2011-12

and 25.4% and 36.0% decrease during 2012-13, respectively as compared to

control in the field experiment-1 (light-textured soil). Sampling days had a

significant effect on the bacterial population (P ≤ 0.005). The maximum value of

91

the bacterial population was noticed at day-60 (1.51x107cfu g-1 soil), while the

minimum bacterial population was found at day-7 (1.05x107cfu g-1 soil), indicating

a smaller population (by 30.4 %) than at day-60 during 2011-12. Similarly, in

2012-13 bacterial population was highest at 60th day of herbicide application

(1.21x107cfu g-1 soil) and lowest at 7th day (0.74 x107cfu g-1 soil) indicating 34 %

decline in bacterial population at 7th day as compared to 60th day. (Table 4.5).

4.2.6 Actinomycetes Population under Different Treatments of Buctril Super


Impact of herbicide on actinomycetes population during 2011- 12 and 2012-

13 is given in (Table 4.5). Highest population was found in control which was 8.1

x105 cfu g-1soil, followed by 7.1 x105 cfu g-1soil in 375 mL ha-1 and lowest was 6.2

x105 cfu g-1soil in 2250 mL ha-1. Similarly, during 2012-13 the highest population

(7.7 x105 cfu g-1soil) was found in control, followed by 6.6x105 cfu g-1soil in 375

mL ha-1 and minimum actinomycetes population (5.6 x105) was found in 2250 mL

ha-1. In general, 1500 mL ha-1 and 2250 mL ha-1 treatments showed 18.5 % and

23.4 % decline in actinomycetes in 2011-12, while 23.4 % and 27.2 % in 2012-13

in actinomycetes population as compared to control.

Sampling days showed the highly significant effect on actinomycetes

population (P ≤ 0.005). At day-60 maximum actinomycetes population (7.9 x105cfu

g-1 soil) while at day-15 minimum population (5.6x105cfu g-1 soil) was found

indicating 29 % less population at day-15 as compared to day-60 during 2011-12.

92

y = -421.75x + 667

R2 = 0.6576

200

400

600

800

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Herbicide concentration (ppm)

MB

C (

µg

g-1

)

MBC Linear (MBC )

Figure 16: Microbial biomass carbon and buctril super herbicide showing negative correlation in

light–textured soil

93

y = -19.643x + 18.305

R2 = 0.1938

5

10

15

20

25

30

0.00 0.10 0.20 0.30 0.40 0.50


MB

N (

µg

g-1

)

MBN Linear (MBN)

Figure 17: Microbial biomass nitrogen and buctril super herbicide showing negative correlation in


94

y = -4.9684x + 7.4469

R2 = 0.0925

3

5

7

9

11

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


MB

P (

µg

g-1)

MBP Linear (MBP)

Figure 18: Microbial biomass phosphorus and buctril super herbicide showing negative correlation in


95

Similarly, during 2012-13 the actinomycetes population was highest at day-60

which was 7.4 x105cfu g-1 soil and lowest at day-15 which was 5.4x105cfu g-1soil,

indicating 27 % decline at day-15 as compared to day-60 in actinomycetes

population. Decrease in actinomycetes population was found from day-7 to day-15

while increase was observed from day-30 to day-60 during both years in field

experiment-1 (light-textured soil).

4.2.7 Fungi Population under Different Treatments of Buctril Super


Highest fungi population (5.9 x104 cfu g-1soil) was observed in control,

followed by 5.7 x104 cfu g-1soil in 750 mL ha-11 and lowest (3.9 x104 cfu g-1soil)

was noticed where 2250 mL ha-1 was applied in 2011-12. However, in second year

maximum fungal population (5.7 x104 cfu g-1 soil) was found in control, followed

by 3750 mL ha-1 (5.4x104 cfu g-1soil) and minimum fungi population was found in

2250 mL ha-1 (3.5 x104 cfu g-1soil). As a whole, 1500 mL ha-1 and 2250 mL ha-1

treatments caused 29 % and 34 % reduction in fungal population than control in

2011-12, whereas 31.5 % and 38.6 % decrease in fungi population over control was

noticed in 2012-13. Sampling days also had significant effect on fungi population

(P ≤ 0.005). At day-60 maximum fungi population (6.1 x104cfu g-1soil) while at

day-15 minimum population (3.8 x104cfu g-1soil) was found indicating 38 % less

population at day-15 as compared to day-60 in 2011-12. Correspondingly, during

2012-13, the fungi population was maximum at day-60 which was 5.9 x104cfu g-

1soil and minimum at day-15 which was 3.6 x104 cfu g-1soil indicating 39 %

decline in population at day-15 as compared to day-60. During both the years

96

decline in fungi population was found from day-7 to day- 15 while increase was

observed from day-30 to day-60 in field experiment-1 (light-textured soil) (Table

4.5).

The interaction of treatments x sampling days was also statistically

significant. Maximum bacterial population (1.56 x107 cfu g-1soil) was recorded at

day-7 in control and at day-60 in 2250 mL ha-1 treatment. Whereas, minimum

bacterial population (0.63 x107 cfu g-1soil) was found at day-7 in 2250 mL ha-1

resulting a 60 % decline in bacterial population, followed by 2250 mL ha-1 (0.69

x107 cfu g-1soil) at day-15 indicating 56% inhibition in population, followed by

1500 mL ha-1 (0.82 x107 cfu g-1soil) at day-7 as compared to the population in

control (0.82 x107 cfu g-1soil) at day-7 in 2011-12. Similarly, the sampling days

and treatments interactive effect revealed highest population (1.24 x107 cfu g-1soil)

at day-60 in 2250 mL ha-1 treatment. Minimum bacterial population (0.39 x107 cfu

g-1soil) was noticed at day-7 in 2250 mL ha-1 resulting 68.5 % less population,

followed by (0.42 x107 cfu g-1soil) at day-15 by same dose of herbicide indicating

66% decline, followed by (0.58 x107 cfu g-1soil) at day-7 where 1500 mL ha-1 was

applied during 2012-13 as compared to 60th day of 2250 mL ha-1 (Figure 19).

The interaction impact of herbicidal treatments and sampling days exhibited

maximum actinomycetes number at day-7 in control (8.7 x105cfu g-1soil).

Minimum population was recorded at day-15 in 2250 mL ha-1 (4.2 x105 cfu g-1soil)

indicating 52 % decline as compared to control at day-7. These followed by (4.6

x105 cfu g-1soil) in 1500 mL ha-1 at day-15 indicating 47 % drop in actinomycetes

population, followed by (5.2 x105 cfu g-1soil) at same day by 375 mL ha-1 and 750

97

mL ha-1 showing 40% drop in population during 2011-12 as compared to control at

day-7. The interactive effect of treatment and sampling days showed maximum

actinomycetes population (7.8x105 cfu g-1soil) at day-15 in control. Minimum

actinomycetes population (3.9x105 cfu g-1soil) was recorded on same day in 2250

mL ha-1 treatment indicating 50 % less actinomycetes population followed by

(4.2x105 cfu g-1soil) at day-15 in 1500 mL ha-1 treatment indicating 45% decline

followed by (5.1x105 cfu g-1soil) at day-7 in 2250 mL ha-1 showing 34% decrease

in population in contrast to control at day-15 in 2012-13 (Figure 20).

The interaction effect of treatment and sampling days demonstrated highest

fungal population (6.6 x104cfu g-1soil) in 750 mL ha-1 at 60th day. The lowest

fungal population (2.0 x104 cfu g-1soil) was observed in 2250 mL ha-1 at day-15

representing 68 % decline, followed by (2.4 x104 cfu g-1soil) in 2250 mL ha-1 at

day-7 indicating 64% decline and (2.6 x104 cfu g-1soil) in 1500 mL ha-1 at day-15

showing 61% drop in comparison to 750 mL ha-1 (6.6 x104 cfu g-1soil) observed at

day-60 in first year. Likewise, in second year the interactive effect of treatment x

sampling days explained maximum fungi population (6.1 x104 cfu g-1soil) in 375

mL ha-1 at day-60. Minimum population (1.6 x104 cfu g-1soil) was found at day-15

in 2250 mL ha-1 and in same treatment at day-7 (2.1 x104 cfu g-1soil) followed by

1500 mL ha-1 (2.5 x104 cfu g-1soil) at day-15 (Figure 21).

Bacteria play a key role in nitrogen transformations, nutrient cycling and

organic matter decomposition. Different anthopogenic chemicals added to the soil

ecosystem directly or indirectly exert different impacts on soil microorganisms.

Few bacteria are resistant while most of them are susceptible to these synthetic

98

compounds. In present study highest bacterial population in control in both the

years in field experiment-1 (light-textured soil) was because there was no

interference of herbicide. In control, minimum decrease in bacterial population

might be due to low concentration of bromoxynil that has reduced the population

but not to a large extent. While, highest reduction (30 %) in bacterial population

was in 2250 mL ha-1 because of high concentration of bromoxynil that exerted

lethal effect on bacteria. Busse et al. (2001) reported toxic effect of glyphosate on

bacteria and this effect was found to be more severe with increased concentration

of glyphosate. On the contrary, other investigations (Ratcliff et al., 2006) revealed

increase in bacterial population by applying higher concentration (100 FR) of

glyphosate herbicide. A study regarding quantification of glyphosate herbicide

effect on soil microbial community (Waever et al., 2007) found no significant

change in microbial community even at higher than fied rate application (47 µg g -

1). Omer and Abdel Sattar (2001) observed promotion in bacterial population by

field rate application of brominal herbicide (0.6g a.i g-1 soil) and five times higher

dose of this herbicide. Ayansina and Oso (2005) while evaluating the impacts of

atrazine and combination of herbicides (atrazine + metolachlor) experienced

decrease in microbial population at field rate and 1½ of field rate. Some

heterotrophic bacteria showed severe sensitivity to metsulfurom-methyl (He et al.,

2006) and their population declined. Contrary to this, some studies (Dgrak and

Kazaniki, 2001) reported increased bacterial population in isofenophos insecticide

treated soil as compared to untreated soil. Das and Mukherjiee (2000) reported

99

Table 4.5. Microbial population (bacteria, actinomycetes and fungi) as influenced by different treatments of buctril super herbicide

and sampling days in light-textured soil showing decline in these parameters due to lethal effect of herbicide

Factors Bacterial population

2011-12 2012-13

Actinomycetes population

2011-12 2012-13

Fungi population

2011-12 2012-13

(#x107 cfu g-1 soil) (#x105 cfu g-1 soil) (#x104 cfu g-1 soil)

Treatments

Control

1.50 A

1.18 A

8.1 A

7.7 A

5.9 A

5.7 A

375 mL ha-1 1.38 B 1.04 B 7.1 B 6.6 B 5.7 A 5.4 B

750 mL ha-1 1.31 C 1.00 C 7.0 B 6.5 B 4.9 B 4.6 C

1500 mL ha-1 1.15 D 0.88 D 6.6 C 5.9 C 4.2 C 3.9 D

2250 mL ha-1 1.05 E 0.76 E 6.2 D 5.6 D 3.9 D 3.5 E

LSD 0.0377 0.0232 0.1086 0.2150 0.3169 0.2142

Sampling day

0 1.50 A 1.15 B 7.5 B 7.0 B 5.8 A 5.4 B

7 1.05 D 0.74 E 6.9 D 6.1 D 4.6 B 4.2 C

15 1.09 C 0.80 D 5.6 E 5.4 E 3.8 C 3.6 D

30 1.24 B 0.96 C 7.0 C 6.4 C 4.3 B 4.0 C

60 1.51 A 1.21 A 7.9 A 7.4 A 6.1 A 5.9 A

LSD 0.0377 0.0232 0.1086 0.2150 0.3169 0.2142

Analysis of

variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

T x D

C.V (± %)

<0.05

6.66

<0.05

5.78

<0.05

8.17

<0.05

8.29

<0.05

7.46

<0.05

7.35

100

0.3

0.9

1.5

2.1

0 7 15 30 60 0 7 15 30 60

Sampling days

Bac

teri

al p

opu

latio

n (

#x

107 c

fu g

-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 19: Interactive effect of herbicide treatments and sampling days on Bacterial population in light-textured

soils showing decline in bacterial population upto day-30 which later on subsided due to degradation of herbicide

101

3

6

9

12

0 7 15 30 60 0 7 15 30 60

Sampling days

Act

inom

ycet

es p

opul

atio

n (#

x105 c

fu g

-1 s

oil)

Control 375 mL ha-1 750 mL ha-11500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 20: Interactive effect of herbicide treatments and sampling days on actinomycetes population in light-

textured soils showing decline in population upto day-30 which later on subsided due to degradation of herbicide

102

0

3

6

9

0 7 15 30 60 0 7 15 30 60

Sampling days

Fun

gi p

opul

atio

n (#

x104 c

fu g

-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 21: Interactive effect of herbicide treatments and sampling days on Fungi population in light-textured

soils showing decline in biomass carbon upto day-30 which later on subsided due to degradation of herbicide

103

increase of N2-fixing and phosphate solublising bacteria by the application of

phorate, carbafuron and fenvalerate herbicides. By the application of 5.5 mg kg-1 to

22 mg kg-1 of butachlor (n- butoxymethyl-chloro-2’, 6’ diethylacetnilide) herbicide,

diffirent researchers (Min et al., 2001) reported stimulation in fermentative and

sulfate reducing bacteria, whereas, suppression in acetogenic bacterial population.

Allievi and Giglioti (2001) reported that sulfonylurea herbicide has suppressed the

population of nitrifying bacteria by disrupting their amino acid absorption ability.

Researchers (Ratnayak and Audus 1978) also reported inhibition in the growth of

nitrifying bacteria due to 3,5-dibro-4 hyroxybenznitrile herbicide.

Sampling days showed significant effect on bacterial population. Lowest

bacterial population was found at day-7, while highest at day-60 during both the

years in Koont soil. This was because of the fact that during early seven days the

herbicide exerted more toxic effect on bacteria and after that the microbes

overcomed the detrimental effect and degradaded the herbicide by using it as a

source of carbon so their population increased at day-60. About 14.4 % and 42.9 %

increase in bacterial number at 15th and 60th day was observed by Singh and Dileep

(2005) after application of diazinon to soil at 800 g a.i ha-1.

All species of actinomysce are facultative anaerobe except few one

(Actinomycetes meyeri) and show excellent growth under anaerobic environments.

They synthesise enzymes that can degrade diffent agrochemicals added to the soil

and protect the crop from insects and weeds. Actinomycetes also have the ability of

degrading lignin and cellulose. They are essential component of compost (Holt et

al., 1994). Our results showed highest actinomycetes population in control

followed by 3750 mL ha-1 and lowest population in 2250 mL ha-1 in field

104

experiment-1 (light-textured soil) during two years. Over all, 1500 mL ha-1 and

2250 mL ha-1 exhibited 21 % and 25 % inhibition in actinomycetes population. This

might be due to toxic effect of bromoxynil herbicide. As < 0.3% of the total applied

herbicide could reach the target organism and out of which 99.7% went to the soil

environment and cause toxicity to soil microbes (Pimental et al., 1995). Different

herbicides (paraquot, glyphosate, atrazine and primeextra) showed toxic effect on

actinomycetes and suppressed their population. Vischetti et al. (2002) reported

25% and 64 % inhibition in actinomycetes population due to imazamox and

benfluralin herbicides, respectively. Nevertheless, Araujo et al. (2003) observed

increase in actinomycetes and fungus population due to glyphosate application

(2.16 µg glyphosate g-1soil). He et al. (2006) found no change in actinomycetes

population due application of metsulfuron methyl herbicide. Some researchers

(Nowak et al., 2004) also reported suppression in actinomycetes and fungal

population due to degradation of isoproturon. Higher dose of brominal herbicide

resulted significant drop in actinomycetes (Omar and Abdel Sater, 2001).

In this study, the results showed statistically significant effect of sampling

days on the population of actinomycetes. Maximum population was at day-60 and

minimum at day-15 indicating 29% decline at day-15. This huge reduction in

actinomycetes population at day-15 might be because of poisonous residues of

herbicide during initial 15-days and after that actinomycetes have adopted

themselves against this herbicide and started its degradation. Yu et al. (2011)

observed the effect of chlorothalanil herbicide on soil microbial diversity and found

suppression in the population of bacteria, fungi and actinomycetes during intitial 2

weeks after herbicide application and after that the microorganisms have adopted

105

themselves against cholorothalanil and their population reached to their initial

level. Combined mixture of prosulfuron and bromoxynil herbicides (1ppm and

100pm), respectively exhibited 91% decrease in actinomycetes population as

compared to no application (Pampalha and Oliveria, 2006). Milosevic et al. (2002)

observed promotion in actinomycetes population under low concentrations of

different herbicides (imazrthapyr, clomasone, alachlor + linuron, flumetsulam) and

found that actinomycetes have used these herbicides as a source of carbon.

Recovery of actinomycetes population with the passage of time was due to

berbicide mineralization. Rosenbrock et al. (2004) while investigating the

formation of metabolites and non extractable residues after mineralization of

bromoxynil herbicides in soil observed 42% and 49% mineralization of bromoxynil

and bromoxynil octanoate, respectively within 60 days of herbicide application.

Fungi are present in soil in abundant quantity as high as one million fungi in

single gram of soil. Most of the fungi are chemo-heterotroph but some of them are

saprotrophic and depend on organic matter and convert it into plant available form.

Some fungi also have symbiotic relationship with plants and by virtue of it both of

them get benefits from each other which is called as mycorrhizae. In symbiosis,

fungi get carbohydrates from the roots and in return provide nitrogen and moisture

to the plants. Fungi bear thread like structure called as hyphae which release

enzymes in soil that promote nutrient transfortions in soil. Fungi contribute about

10-20 % of total soil microbial population in soil. The carbon use efficiency of

fungus is high so they have the ability of storing and recycling of carbon.

Asbuscular mycorhizal fungi produce amino polysaccharide (glomalin) which

http://en.wikipedia.org/wiki/Mycorrhiza

106

surrounds the soil particles and help in soil structure formation. Fungi can also

restore and reprocess nitrogen and phosphorus in soil and enhance N and P

extraction from soil (Hoorman, 2011). Our results indicated that fungi population

decreased with the increasing concentration of buctril super herbicide. The highest

fungal population was found in control and lowest was in 2250 mL ha-1. On an

average higher herbicide concentration in soil caused reduction in fungal

population by 36.3% in field experiment-1 (light-textured soil) during both the

years. Omer and Abdel Satter (2001) observed significant decrease in fungi

population due to increased concentration of bromoxynil herbicide. Maximum

population of fungi was found at day-60 and minimum population at day-15. This

recovery in fungi population after day-15 was due to the fact that fungi have

developed resistance against the herbicide with the passage of time. Ismail et al.

(1995) observed decrease in bacteria and fungi population due to glufosinate-

ammonium (100ppm) but their population recoverd after one week. Recommended

rate of application of different herbicides (atrazine, glyphosate and paraquot)

exhibited substantial decrease in fungi population (Sebiomo et al., 2011). Contrary

to our findings, Abdel-Mallek et al. (1994) reported stimulation in cellulolytic

fungi population due to glyphosate herbicide. Pampulha and Oliveira (2006) found

that all groups of fungi (except cellulolytic fungi) showed sensitivity to high dose

of bromoxynil leading their death. Omer (1994) noticed significant drop in fungi

population by the application of profenophos and bromoxynil herbicides (0.3ppm

and 6 ppm). Nowak et al. (1999) reported increase in the population of

actinomycetes but decrease in fungi population due to isoproturon application.

Bromoxynil and prosulfuron herbicides showed 43 % and 96 % decrease in fungi

107

population by 1ppm and 100ppm concentrations, respectively (Pampulha and

Oliveria, 2006). Ayansina and Oso (2006) reported 40 % decline in fungi

population due to 1.5 time field rate applications of atrazine and atrazine +

metolachlor herbicides.

4.2.8 Correlation of Microbial population with buctril super herbicide

Bacterial population revealed negative but weak correlation (-0.33) with

bromoxynil residues (Figure 22), actinomycetes population was negatively but

weakly correlated (-0.35) with bromoxynil residuse (Figure 23) Fungal population

also exhibited negative (-0.29) correlation with bromoxynil (Figure 24).

4.2.9 Urease Activity under Different Treatments of Buctril Super Herbicide

in Light-textured Soil

It was found that the soil enzymes activities were significantly differed in

all herbicidal treatments and were in the order of 375 mL ha-1 > 750 mL ha-1> 1500

mL ha-1> 2250 mL ha-1. In control highest urease activity was observed which was

299 µg NH4-N g-1dwt 2h-1, followed by 291 µgNH4-N g-1dwt 2h-1 in 375 mL ha-1

and urease activity of 210 µgNH4-N g-1dwt 2h-1 was observed in 2250 mL ha-1

during 2011-12. Highest urease activity was found in control that was 275 µg NH4-

N g-1dwt 2h-1, followed by 257µg NH4-N g-1dwt 2h-1 in 375 mL ha-1 and minimum

urease activity (190 µg NH4-N g-1dwt 2h-1) was observed in 2250 mL ha-1 during

2012-13. Overall, 1500 mL ha-1and 2250 mL ha-1 treatments caused 22 % and 30 %

reduction in urease activity, respectively as compared to control during 2011-12.

While, 25 % and 31% decrease in urease activity as compared to control during

2012-13 was observed in field experiment-1 (Table 4.12). Sampling days showed

108

highly significant effect on urease activity (P ≤ 0.005). Maximum urease activity

was noticed at initial day (299 µg NH4-N g-1dwt 2h-1) and minimum at day-7 (219

µg NH4-N g-1dwt 2h-1) indicating 27 % less activity at day-7 as compared to day-0

during 2011-12. But, during 2012-13 urease activity was maximum at day-60 (274

µg NH4-N g-1dwt 2h-1) and minimum at day-7 (197 µg NH4-N g-1dwt 2h-1)

indicating 28 % decrease in said enzyme activity at day-7 as compared to day-60.

4.2.10 Deydrogenase Activity under Different Treatments of Buctril Super


Response of dehydrogenase activity to applied herbicide during 2011-12

and 2012-13 is given in (Table 4.12). Results showed highest dehydrogenase

activity (31.3 µgTPF g-124h-1) in control, followed by 27.9 µg TPF g-124h-1 in 375

mL ha-1 and lowest (20.0 µg TPF g-124h-1) was noticed in 2250 mL ha-1 during

2011-12. While, highest dehydrogenase activity was found in control which was 36

µg TPF g-1 24h-1, followed by 30.5µg TPF g-1 24h-1 in 375 mL ha-1 and lowest

(23.1 µg TPF g-1 24h-1) was found in 2250 mL ha-1 during second year. On the

whole, 1500 mL ha-1 and 2250 mL ha-1treatments caused 31 % and 36 % reduction,

respectively during 2011-12. Whereas, 28 % and 35.8 % decrease in

dehydrogenase activity as compared to control during 2012-13. Sampling days

significantly affected the dehydrogenase activity (P ≤ 0.05). At day-0 maximum

dehydrogenase activity was recorded which was 30.3 µg TPF g-1 24h-1 while at

day-7 minimum dehydrogenase activity (18.6µg TPF g-1 24h-1) was found

indicating 39 % less activity at day-7 as compared to day-0 during 2011-12.

Similarly, during 2012-13 dehydrogenase activity was maximum at day-60 which

109

was 36.6µg TPF g-1 24h-1 and minimum at day-7 which was 21.7 µg TPF g-1 24h-1

indicating 40.7 % inhibition in dehydrogenase activity at day-7 as compared to day-

60 in field experiment-1 (light-textured soil).

4.2.11 Alkaline Phosphatase Activity under Different Treatments of Buctril

Super Herbicide in Light-textured Soil

Response of alkaline phosphatase activity to applied herbicide in 2011-12

and 2012-13 are presented in Table 4.6. Results indicated the highest alkaline

phosphatase activity (55.9 μg Phenol g-1h-1) in control, followed by 50.9 μg Phenol

g-1h-1 in 375 mL ha-1 and the lowest activity (36.9 μg Phenol g-1h-1) in 2250 mL ha-1

during 2011-12. Whereas, the highest alkaline phosphatase activity was observed in

control (47.1μg Phenol g-1h-1), followed by 41.2 μg Phenol g-1h-1 in 375 mL ha-1

and lowest activity (32.7 μg Phenol g-1 h-1) was found in 2250 mL ha-1 during

second year. As a whole, 1500 mL ha-1 and 2250 mL ha-1 treatments caused 28 %

and 34 % inhibition, respectively during 2011-12. While, 27.6 % and 31 %

decrease in alkaline phosphatase activity as compared to cntrol during 2012-13.

Sampling days showed highly significant effect on alkaline phosphatase activity (P

≤ 0.05). At day-60 maximum alkaline phosphatase activity was recorded which

was 54.6 μg Phenol g-1h-1, while at day-7 minimum alkaline phosphatase activity

(33.7μg Phenol g-1h-1) was observed indicating 38 % less activity at day-7 as

compared to day-60 in 2011-12. In 2012-13, the alkaline phosphatase activity was

maximum (46. 3 μg Phenol g-1h-1) at day-60 and minimum (29.8μg Phenol g-1h-1) at

day-7 indicating 39 % low alkaline phosphatase activity at day-7 as compared to

day-60 in field experiment-1 (light-textured soil).

110

y = -0.856x + 1.1952

R2 = 0.1113

0.4

0.8

1.2

1.6

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


Bac

teri

al c

fu (

#x10

7)

Bacterial population Linear (Bacterial population)

Figure 22: Correlation between bacterial population and buctril super herbicide in light–textured soil showing

negative correlation due to toxic effect of herbicide on soil microorganisms

111

y = -3.6388x + 7.022

R2 = 0.1236

2.0

4.0

6.0

8.0

10.0

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


Act

inom

ycet

es c

fu (

#105)

Actinomycetes Linear (Actinomycetes)

Figure 23: Correlation between actinomycetes population and buctril super herbicide in light–textured soil

showing negative correlation due to toxic effect of herbicide on soil microorganisms

112

y = -3.7439x + 5.0838

R2 = 0.0846

1

3

5

7

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


Fun

gal c

fu (

#104

)

Fungi Linear (Fungi )

Figure 24: Correlation between fungi population and buctril super herbicide in light–textured soil showing

Negative correlation due to toxic effect of herbicide on soil microorganisms

113

The interactive effect of treatment and sampling days showed statistically

significant difference. Maximum urease activity was recorded at day-7 in control

(303 µgNH4-Ng-1dwt 2h-1) and at day-0 in 375 mL ha-1 (302µg NH4-N g-1dwt 2h-1).

Minimum urease activity (134 µg NH4-N g-1dwt 2h-1) was found at day-7 in 2250

mL ha-1 indicating 56 % decline in urease activity, followed by (153 µg NH4-N g-

1dwt 2h-1) at day-15 in 2250 mL ha-1 indicating 49.5 % inhibition in urease activity,

followed by (171µg NH4-N g-1dwt 2h-1) at day-30 in 2250 mL ha-1 indicating 44%

decline in urease activity as compared to 303 µgNH4-Ng-1dwt 2h-1 that was found

in control at day-7 during 2011-12. Similarly, the interactive effect of treatment and

sampling days showed highest urease activity (285µg NH4-N g-1dwt 2h-1) at day-60

in 2250 mL ha-1. Lowest urease activity (122µg NH4-N g-1dwt 2h-1) was noticed at

day-7 in 2250 mL ha-1resulting 57 % decrease in urease activity followed by (139

µg NH4-N g-1dwt 2h-1) at day-7 in 1500 mL ha-1 indicating 51% decline, followed

by (159 µgNH4-Ng-1dwt2h-1) at day-30 in 2250 mL ha-1, resulting 44% inhibition

in urease activity during 2012-13 as compared to 2250 mL ha-1 (285 µgNH4-N g-

1dwt 2h-1) at day-60 (Figure 25).

The interaction between treatment and sampling days showed the highest

dehydrogenase activity (33.2 µgTPF g-1 24h-1) in control at day-30. The lowest

dehydrogenase activity (10.2 µgTPF g-1 24h-1) was observed in 2250 mL ha-1 at

day-7 indicating 69 % decline, followed by 12.3 µg TPF g-124h-1 in 1500 mL ha-1 at

day-7 indicating 63% decline, followed by 13.6 µgTPF g-1 24h-1 in 2250 mL ha-1 at

day-15 showing 59 % decline in dehydrogenase activity during 2011-12 as

compared to 33.2µg TPF g-1 24h-1 which was noticed in control at day-30.

Similarly, during 2012-13 the interactive effect of treatment x sampling days

114

showed maximum dehydrogenase activity (37.9 µg TPF g-1 24h-1) in 2250 mL ha-1

at day-60. Minimum activity (10.8 µg TPF g-1 24h-1) was found at day-7 in 2250

mL ha-1, followed by 14.4µg TPF g-1 24h-1 at day-15 in 2250 mL ha-1, followed by

16.1 µg TPF g-1 24h-1 at day-7 in 1500 mL ha-1 (Figure 26).


alkaline phosphatase activity (57.1 μg Phenol g-1h-1) at day-60 in control. Minimum

alkaline phosphatase activity (17.0 μg Phenol g-1h-1) was recorded at day-7 in 2250

mL ha-1 indicating 70% decline, followed by 24.6μg Phenol g-1h-1 in 2250 mL ha-1

at day-15 indicating 57% drop in alkaline phosphatase activity, followed by 33.0 μg

Phenol g-1 h-1 at day-7 in 750 mL ha-1, showing 42% drop in activity as compared

to control at day-60 during 2011-12. The interaction of treatment and sampling

days showed the maximum alkaline phosphatase activity (49.2 μg Phenol g-1h-1) at

day-7 in control. Minimum alkaline phosphatase activity (18.3 μg Phenol g-1h-1)

was recorded on same day in 2250 mL ha-1 indicating 63% less alkaline

phosphatase activity, followed by 21.6 μg Phenol g-1h-1 at day-7 in 1500 mL ha-1

treatment indicating 56% decline, followed by 25.1 μg Phenol g-1h-1 at day-15 in

2250 mL ha-1 treatment showing 50% decrease in alkaline phosphatase activity,

followed by 28.4 μg Phenol g-1h-1 at day-15 in 1500 mL ha-1 resulting 42% decline

in alkaline phosphatase activity during 2012-13 as compared to control at day-7

(Figure 27).

Soil contains many enzymes including extracellular and intracellualar

enzymes (Mayanglambam et al., 2005). Soil enzymes act as marker of biological

activity and soil fertility (Antonius, 2003; Dick, 1994) and indicate alterations in

115

soil biological activity due to addition of anthropogenic chemicals (Nannipieri et

al., 1990). Nutreint cycling especially nitrogen transformations in soil are

performed by urease enzyme. Urease causes hydrolysis of urea to carbon dioxide

(CO2) and ammonium (NH3). Sarathchandra et al. (1984) observed urease activity

in many fungi and bacteria. In present study urease activity was highest in control

and lowest in 2250 mL ha-1 in field experiment-1 (light-textured soil) during both

years showing 30.5 % decrease in 2250 mL ha-1 as compared to control. This

decline in urease activity in 2250 mL ha-1 was because of toxicity of high dose of

buctril super herbicide to the microbes that produce urease enzyme in soil. Ingram

et al. (2005) found no effect of insecticides (imidacloprid and diazinon) on urease

enzyme produced by Bacillus pasteurii. However, they observed severe reduction

due to imidacloprid and diazinon insecticides in the population of Proteus vulgaris

that are involved in the production of urease enzyme with consequent decrease in

urease activity. Cervelli et al. (1976) noticed considerable reduction (10-30%) in

the hydrolysis of urea due to different herbicides (diuron, linuron and monuron).

Chlorothalanil and mancozeb herbicides (10 times higher than field application

rates) showed 37.7% decrease in urease activity. However chlorothalanil was less

toxic as compared to mancozeb (Yu et al., 2011). Application of chlorpyrifos (100

and 500 mg kg-1soil) revealed considerable decline in urease activity (Niu et al.,

2011). Contrary to our results, different studies (Baboo et al., 2013) highlighted

enhancement in the activities of urease and dehydrogenase enzymes by the

application of different herbicides (butachlor @1kg/ha, pyrozosulfuron @ 25 g/ha,

paraquot @ 200 g /l and glyphosate @360 g/l).

116

Sampling days showed significant effect on urease activity. Highest urease

activity was observed at day-0 and lowest at day-7 indicating 27% inhibition in the

said parameter at day-7. But, after that urease activity showed increasing trend and

reached to it initial level at day-60. This is because of the reason that at day-0 due

to less time of exposure of the herbicide to soil microbes (involved in urease

production) the activity of urease was high. The lowest activity of urease at day-7

might be due to more time of exposure of herbicide to microbial community

involved in production of urease enzyme. The recovery of urease activity with time

was because of adjustment of urease producing microbes to the herbicide so their

population increased as a consequence urease activity enhanced. Punitha et al.

(2012) reported 83%, 71% and 54% decline in urease activity at 10 th, 20th and 30th

day, respectively by the application of acetamiprid (0.4 a.i /column). They also

reported enhancement in the activity of said enzyme from 20 th day and it reached to

maximum at 60th day. Contrarily, Yang et al. (2006) while studying the impacts of

pesticides (furadan and chlorimuron-ethyl) on the activity of urease enzyme

observed significant stimulation of about 46.9% and 39.3% in the activity of

urease due to chlorimuron-ethyl and 21% to 12.7% due to furadan.

Dehydrogenase is found intercellularly in the clles of all living

microorganisms and is associated with respiration process of soil microbe (Bolton

et al., 1985). The activity of dehydrogenase reflects total microbiological activity

of soil. Dehydrogenase are concerned with the oxidation and reduction processes

taking place in soil and is used for the quantification of electrons transfer during

carbon substrate consumption, therefore, reflect total biological activity in soil

(Locke and Zabolowicz, 2004). Dehydrogenase play important role in soil organic


117

matter oxidation by transferring protons and electrons between substrate and

acceptor (Glinski and Stepniewski, 1985). In our study it was noticed that the

highest dehydrogenase activity was in control and lowest activity in 2250 mL ha-1

during both the years in field experiment-1 (light-textured soil). Highest

dehydrogenase activity in control was because of no interference of herbicide while

lowest dehydrogenase activity was due to 2250 mL ha-1 treatment was because of

lethal impact of applied herbicide on soil microbes leading to their death

consequently dehydrogenase activity declined. Allievi and Giglioti (2001) observed

that sulfonyl urea herbicides create hinderance in amino acid assimilation

capability of some microbes, ultimately decreasing their population with the

concomitant decrease in dehydrogenase activity. Contrary to that, He et al. (2006)

did not find any decrease in the activity of dehydrogenase enzyme due to

metsulfuron-methyl herbicide application. Other investigations (Baboo et al., 2013)

reported enhancement in the activities of urease and dehydrogenase enzyme by the

application of different doses of different herbicides (pyrozosulfuron 25 g/ha,

paraquot 200g/l, butachlor 1kg/ha and glyphosate 360 g/l). Min et al. (2001)

observed enhancement in dehydrogenase activity in butachlor treated soil. Different

hercicides (triazophos, bensulfuron-methyl, clobenthiazone) showed significant

inhibition in dehydrogenase activity (Xie et al., 1994) and this decrease in the

activity of dehydrogenase due to the toxic effect of these herbicides showed the

order: Bensulfuron < Chlobenthiazone <Triazophos. Significant increase (55%) in

the activity of dehydrogenase enzyme due to recommended rate, while 58 % and 59

% increase by 5x FR and 10x FR of alachlor herbicide, respectively was observed

in the activity of dehydrogenase enzyme after 42 of its application

118

Table 4.6. Soil enzymes activity as influenced by different treatments of buctril super herbicide and sampling days in ight-textured

soil showing decline in these parameters due to lethal effect of herbicide

Factors Urease activity

2011-12 2012-13

Dehydrogenase activity

2011-12 2012-13


2011-12 2012-13

(µg NH4-N g-1dwt 2 h-1) (µg TPF g-1 24 h-1) (μg Phenol g-1 h-1)

Treatments

Control 299 A 275 A 31.3 A 36.0 A 55.9 A 47.1 A

375 mL ha-1 291 B 257 B 27.9 B 30.5 B 50.9 B 41.2 B

750 mL ha-1 263 C 233 C 24.6 C 29.1 B 46.4 C 38.1 C

1500 mL ha-1 233 D 205 D 21.6 D 26.0 C 40.9 D 34.1 D

2250 mL ha-1 210 E 190 E 20.0 E 23.1 D 36.9 E 32.7 E

LSD 5.81 7.15 1.51 1.61 2.13 1.37

Sampling day

0 299 A 260 B 30.3 A 34.0 B 52.6 A 44.4 B

7 219 D 197 E 18.6 D 21.7 E 33.7 D 29.8 E

15 233 C 209 D 21.6 C 24.3 D 41.8 C 34.5 D

30 249 B 220 C 25.2 B 27.9 C 48.4 B 38.4 C

60 294 A 274 A 29.7 A 36.6 A 54.6 A 46.3 A

LSD 5.81 7.15 1.51 1.61 2.13 1.37

Analysis of

variance


Treatments (T) < 0.05 < 0.05 < 0.05 < 0.05 < 0.05 < 0.05

Sampling days (D) < 0.05 < 0.05 < 0.05 < 0.05 < 0.05 < 0.05

T x D

C.V (± %)

< 0.05

8.55

< 0.05

7.38

< 0.05

9.58

< 0.05

8.83

< 0.05

7.32

< 0.05

5.84

119

100

200

300

400

0 7 15 30 60 0 7 15 30 60

Sampling days

Ure

ase

Act

ivity

(µ

g N

H4-N

g-1

dw

t 2

h-1)


1500 mL ha-1 2250 mL ha-1

2011-122012-13

Figure 25: Interactive effect of herbicide treatments and sampling days on urease activity in light-textured soils

showing decline in urease activity upto day-30 which later on subsided due to degradation of herbicide

120

5

20

35

50

0 7 15 30 60 0 7 15 30 60

Sampling days

Deh

ydro

gena

se a

ctiv

ity (

µg

TP

F g-1

24

h-1)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 26: Interactive effect of herbicide treatments and sampling days on dehydrogenase activity in light-

textured soils showing decline in dehydrogenase activity upto day-30 which later on subsided due to

degradation of herbicide

121

10

30

50

70

0 7 15 30 60 0 7 15 30 60

Sampling days

(µg

phen

ol g-1

h-1

)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 27. Interactive effect of herbicide treatments and sampling days on alkaline phosphatase activity in

light-textured soils showing decline in alkaline phosphatase activity upto day-30 which later on subsided

due to degradation of herbicide

122

(Saha et al., 2012). Application of fonofos to see its impact on dehydrogenase

activity showed 25-21% decline when applied at 1µg g-1 while 10 times high dose

showd 17-44% decline in dehydrogenase activity (Stepniewska et al., 2007).

Radiojevic et al. (2012) reported substantial decrease (42.7%) in dehydrogenase

activity by applying 3.0 µg g-1soil of nicosulfuron herbicide. In an incubation study

to see the impact of insecticide (endosulfuron) on the activity of soil enzymes using

soil having different physico-chemical properties, Defo et al. (2011) noticed

considerable inhibition in phosphatase and dehydrogenase activity. Cycon et al.

(2010) found marked increase in the activity of dehydrogenase enzyme by

recommended and five times more of recommended rates of herbicides (diazinin

and linuron) in soils having loamy sand texture in contrast to sandy loam.

Sampling days showed statistically significant effect on dehydrogenase

activity. Maximum dehydrogenase activity was found at day-0 and minimum

activity at day-7 indicating 39% less activity at day-7. This might be because of

short contact period of herbicide to soil microbes at day-0 due to which their

population remain unaffected. But at day-7, because of more contatact time of

herbicide to soil microorganisms their population declined drastically. As

dehydrogenase enzyme occur intercellularly in all microbial cells so the death of

microbes ultimately resulted declined dehydrogenase activity. Recovery of

dehydrogenase activity with the passage of time was connected with the recovery

of microbial population because of their adaptability to herbicide. Vekova et al.

(1995) observed recovery of some bacterial species (Agrobacterium radiobacter) in

herbicides contaminated soils with the passage of time due to decrease in herbicide

concentration. Thus the recovery of microorganisms restored dehydrogenase

123

activity in soil. Mayanglambam et al. (2005) reported 30% decline in

dehydrogenase activity after 15 days of quinalphos application and the activity of

dehydrogenase restored after 90 days because of adoption of soil microorganisms

to counteract the impact of applied insecticide stress in hostile conditions.

Phosphatase activities in soils have already been widely studied (Speir and

Ross, 78; Malcom, 1983; Tabatabai, 1994) which act as catalyst in hydrolysis of

ester –phosphate bonds and help in the release of phosphorus that is subsequently

used by soil microbes and plants (Quiquampoix and Mousain, 2005). Phosphatases

help to convert organic phosphorus compounds into inorganic forms through

hydrolysis (Monkiedje et al., 2002). The activities of phosphatases depend on

several factors like soil texture, presence or absence of inhibitors and soil

microorganisms. Hydrolases are of prime importance because of their role in

carbon, nitrogen, sulfer and phosphorus cycling in soil (Megharaj et al., 1999). In

present study significant inhibition in alkaline phosphatase activity was observed

due to buctril super herbicide application. The highest alkaline phosphatase activity

was found in control, followed by 375 mL ha-1 and loweat activity in 2250 mL ha-1.

Highest activity of alkaline phosphatase in control was because of no inhibition

effect of buctril super herbicide. Highest drop in alkaline phosphatase activity in

2250 mL ha-1 was due to high concentration of applied herbicide that had retarded

the activities of organisms that are involed in the production of phosphatase

enzymes in soil. Tu et al. (1981) noticed suppression in phosphatase activity due to

application of 2, 4-D herbicide (10 mg kg-1soil). They found that this suppression in

alkaline phosphatase activity was due to interference of said herbicide in p-

nitrophenol release from p-nitrophenyl phosphate. The other reason of decrease in

124

alkaline phosphatase activity in HC-4 might be due to inactivation of said enzyme

by the herbicide because of attachment of herbicide on the active site of

phosphatase and preventing its binding to the substrate. Different researches (Locke

and Zablotowicz, 2004) observed inactivation of most of soil enzymes because of

herbicide attachment on the active site of enzyme and thus preventing substrate

attachment to the enzyme. Sannio and Gainfreda (2001) reported obvious decline

(98%) in alkaline phosphatase activity due to the glyphosate herbicide treatment.

On the other hand, some studies reorted increase in acid phosphatase activity but

decrease in alkaline phosphatase activity due to mefenoxam and metalaxyl

fungicides (Monkiedje et al., 2002). Contrary to our findings, Das et al. (2003)

reported increase in phosphate solubilizing microbes due to oxyfluorfen herbicide

(0.12 kg a.i ha-1) because this herbicide was used by soil microbes (that produce

phosphatase enzyme) as a source of nutrients and ultimately increased the activity

of alkaline phosphatase.

The activity of alkaline phosphatase was maximum at day-0 and day-60 and

minimum at day-7. Highest activity at day-0 was because of limited exposure time

of herbicide to microbes that produce phosphatses. Whereas, at day-60, high

activity of said enzymes was because of the fact that microbes have adapted

themselves against this herbicide with the passage of time. Similar trend was also

reported by Myanglambam and Singh (2005). They found decrease in the activities

of alkaline phosphatase and urease due to quinalphofos insecticide application

during first week, but later on they found restoration in the activities of these

enzymes. Qian et al. (2007) reported inhibition in the activities of urease, and

125

alkaline phosphatase enzymes during initial days of its application but the activities

of these enzymes showed recovery with time. Researchers (Punitha et al., 2010)

observed 90%, 81% and 74% decline in alkaline phosphatase at 10 th 20th and 30th

days, respectively due to acetamiprid application. Different studies reported diverse

effect of chlorpyriphos on alkaline phosphatase activity. Inhibition in alkaline

phosphatase activity due to chlorpyriphos was reported by (Rani et al., 2008) while

increase in the acivity of said enzyme due to 5kg ha -1 dose of chlorpyriphos was

supported by (Madhury and Rangaswamy, 2002).

4.2.12 Correlation Between Soil Enzymes Activity and Buctril Super

Herbicide

Negative but weak correlation (-0.35) was observed between

dehydrogenase activity and bromoxynil residues (Figure 28). Similarly, alkaline

phosphatase activity was weakly but negatively correlated (-0.44) with bromoxynil

herbicide (Figure 29). Urease activity showed negative (-0.30) correlation with

bromoxynil (Figure 30).

4.2.13 Nitrate Nitrogen under different treatments of buctril super herbicide

in light-textured soil

Nitrate nitrogen was significantly varied in all herbicidal treatments and

was in the order of 375 mL ha-1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL ha-1.

Highest nitrate nitrogen (26.9 µg g-1soil) was observed in control followed by 19.5

µg g-1soil in 375 mL ha-1, 15.8 µg g-1 soil in 70 mL ha-1,14.9 µg g-1soil in 1500 mL

ha-1 and lowest nitrate nitrogen (13.7µg g-1soil) was observed in 2250 mL ha-1

during 2011-12. On the other hand, the highest nitrate nitrogen (28.7 µg g-1soil)

126

was found in control followed by 25.3 µg g-1soil in 375 mL ha-1, 20.0 µg g-1soil in

750 mL ha-1 and 19.1 µg g-1soil in 1500 mL ha-1, while, minimum nitrate nitrogen

(17.2 µg g-1soil) was observed in 2250 mL ha-1 during 2012-13. Overall, 375 mL

ha-1, 750 mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 herbicide treatments caused 27.5

%, 41.2%, 44.6 % and 49% reduction in nitrate nitrogen, respectively, as compared

to control during 2011-12. In 2012-13 herbicide treatments viz. 375 mL ha-1, 750

mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 treatments caused a 11.8 %, 30.3%, 33.4%

and 40 % decrease in nitrate nitrogen respectively, as compared to conrol in field

experiment-1 (light-textured soil). Sampling days resulted high significant effect on

nitrate nitrogen (P ≤ 0.05). Maximum nitrate nitrogen (22.1 µg g-1 soil) was noticed

at day-0 and minimum (16.8 µg g-1soil) was found at day-7 and day-15 indicating

24 % inhibitions in nitrate nitrogen at day-7 and day-15 as compared to day-0

during 2011-12. Similarly, during 2012-13 nitrate nitrogen was maximum at day-0

(27.0µg g-1soil) and minimum at day-15 (20.3 µg g-1soil) indicating a 25 % decline

in nitrate nitrogen at day-15 as compared to day-0 (Table 4.7).

4.2.14 Olsen-P under different treatments of buctril super herbicide in light-

textured soil

Thae Olsen-P was significantly varied in all herbicidal treatments and was

in the order of 375 mL ha-1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL ha-1. In

control, the highest Olsen-P (9.5 µg g-1soil) was observed followed by 8.6 µg g-1

soil in 375 mL ha-1 treatment, 8.3 µg g-1soil in 750 mL ha-1 treatment, 7.9 µg g-1soil

in 1500 mL ha-1 treatment and lowest Olsen-P (7.4 µg g-1soil) was observed where

2250 mL ha-1 dose of herbicide was applied during 2011-12. During 2012-13, the

maximum Olsen-P (8.6 µg g-1soil) was found in control followed by

127

y = -23.403x + 28.779

R2 = 0.1239

5

15

25

35

45

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


(µ

g T

PF

g-1 2

4 h-1

)

Dehydrogenase Linear (Dehydrogenase)

Figure 28: Dehydrogenase activity and buctril super herbicide showing negative correlation due to toxic effect

of herbicide on soil microorganisms

128

y = -14.725x + 42.934

R2 = 0.0359

15

25

35

45

55

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


(µg

phen

ol g-1

h-1

)

Phosphatase Linear (Phosphatase)

Figure 29: Alkaline phosphatase activity and buctril super herbicide showing negative correlation due to

toxic effect of herbicide on soil microorganisms

129

y = -183.75x + 260.51

R2 = 0.1438

100

200

300

400

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


(µg

NH

4-N

g-1

dw

t 2

h-1

)

Urease Linear (Urease)

Figure 30: Urease activity and buctril super herbicide showing negative correlation due to toxic effect of

herbicide on soil microorganisms

130

7.8 µg g-1soil in 375 mL ha-1 herbicide treatment followed by 7.4 µg g-1soil in 750

mL ha-1, and 7.1 µg g-1soil in 1500 mL ha-1 treatment. Whereas, the lowest Olsen-P

(6.6 µg g-1soil) was observed in 2250 mL ha-1. In general, 375 mL ha-1, 750 mL ha-

1, 1500 mL ha-1 and 2250 mL ha-1 herbicide treatments caused 9.47 %, 12.63%,

16.84 % and 22.10% reduction in Olsen-P respectively, as compared to control

during 2011-12. During 2012-13 herbicide treatments viz. 375 mL ha-1, 750 mL ha-

1, 1500 mL ha-1 and 2250 mL ha-1 herbicide treatments caused a 9.30 %, 14.0%,

17.44% and 23.25 % decrease in Olsen-P respectively, as compared to control in

field experiment-1 (Table 7). Sampling days showed highly significant effect on

Olsen- P (P ≤ 0.05). Maximum Olsen-P (9.0 µg g-1soil) was noticed at day-0 and

minimum Olsen-P (8.0 µg g-1soil) was found at day-15 indicating a 11 % inhibition

in Olsen-P at day-15 as compared to day-0 during 2011-12. Similarly, Olsen-P was

maximum at day-0 (8.2 µg g-1soil) and minimum at day-15 (7.1 µg g-1soil)

indicating 13 % decline in Olsen-P at day-15 as compared to day-0 during 2012-13

(Table 4.7).

4.2.15 Total Organic Carbon under Different Treatments of Buctril Super

Herbicide in Light-Textured Soil

Highest TOC (4.22 g kg-1soil) was observed in control followed by (4.08 g

kg-1soil) in 375 mL ha-1, 3.99 g kg-1soil in 750 mL ha-1 and 4.01 g kg-1soil in 2250

mL ha-1 during 2011-12. In 2012-13, maximum TOC was found in control (3.91g

kg-1soil) followed by 375 mL ha-1 (3.76g kg-1soil) and in 750 mL ha-1 (3.63 g kg-

1soil), while, minimum TOC (3.53 g kg-1soil) was observed in 2250 mL ha-1. In

general 750 mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 herbicidal treatments caused

131

3.31%, 5.45% and 4.97% reduction in TOC respectively, as compared to control

during 2011-12. While, during 2012-13 herbicidal treatments viz. 375 mL ha-1, 750

mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 treatments caused 3.83 %, 7.16.0%, 9.71%

and 7.92 % decrease in TOC respectively, as compared to control in field

experiment-1 (Table 4.7). Maximum TOC (4.22 g kg-1soil) was noticed at day-60

and minimum TOC (3.81 g kg-1soil) was found at day-7 indicating 9.71 %

reduction in TOC at day-7 as compared to day-60 during 2011-12. Similarly,

during 2012-13 TOC was the maximum at day-30 (3.82 g kg-1soil) and minimum at

day-15 (3.47 g kg-1soil) indicating 9.16 % decline in TOC at day-15 as compared to

day-30.


nitrate nitrogen (28.1 μg g-1soil) at day-15 in control. Minumum nitrate nitrogen

(11.2 μg g-1soil) was recorded at day-15 in 2250 mL ha-1 indicating 60% decline in

nitrate nitrogen followed by (12.1 μg g-1soil) in HC-4 at day-30 indicating 57 %

drop followed by 1500 mL ha-1 (12.4 μg g-1soil) at day-15 showing 56.3% decline

followed by 1500 mL ha-1 (13.5 μg g-1soil) at day-30 showing 52% drop in nitrate

nitrogen followed by 750 mL ha-1 (14.2 5 μg g-1soil) at day-7 indicating 50.5%

decline in nitrate nitrogen as compared to control at day-15 in 2011-12. Similarly

during 2012-13, the interactive effect of treatment and sampling days showed

maximum nitrate nitrogen in control at day-60 (29.3 μg g-1soil). Minimum nitrate

nitrogen was recorded at day-15 in 2250 mL ha-1 (14.3 μg g-1soil) resulting 51%

decline in nitrate nitrogen followed by 2250 mL ha-1 at day-30 (15.1 μg g-1soil)

indicating 48.4 % decline, followed by 2250 mL ha-1 (15.7 μg g-1soil) at day-7

showing 46.4% decrease in nitrate nitrogen and in 1500 mL ha-1 (16.5μg g-1 soil) at

132

day-15 resulting 43.6% decline in nitrate nitrogen and 1500 mL ha-1 (17.1μg g-1

soil) at day-7 resulting 41.6% decline as compared to control at day-60 (Figure

31).


Olsen-P at day-60 in control (9.6μg g-1 soil). Minumum Olsen-P was recorded at

day-15 in 2250 mL ha-1 (7.1μg g-1 soil) indicating 26% decline in Olsen-P followed

by 2250 mL ha-1 at day-60 (7.3μg g-1 soil) indicating 24 % reduction followed by

2250 mL ha-1at day-30 (7.4μg g-1 soil) showing 22.9% drop followed by 1500 mL

ha-1at day-7 (7.8μg g-1 soil) showing 18.75% drop in Olsen-P and in 750 mL ha-12

at day-15 (8.0μg g-1 soil) indicating 16.6% decline in Olsen-P during 2011-12 as

compared to control at day-60 (9.6μg g-1 soil). In 2012-13, the interactive effect of

treatment and sampling days showed maximum Olsen-P in control at day-30 (8.7μg

g-1 soil). Minimum Olsen-P was recorded at day-15 in 2250 mL ha-1 (6.1μg g-1 soil)

resulting 30% decline in Olsen-P, followed by 2250 mL ha-1 at day-7 (6.2μg g-1

soil) indicating 28.7 % decline, and in 2250 mL ha-1 at day-30 (6.4μg g-1 soil),

showing 26.4% decrease, followed by 2250 mL ha-1 at day-60 (6.7μg g-1 soil)

resulting 22.9% decline in Olsen-P and in 1500 mL ha-1at day-30 (6.9μg g-1 soil)

resulting 20.6% decline in Olsen-P as compared to control (8.7μg g-1 soil) at day-0

(Figure 32).


total organic carbon at day-30 in 2250 mL ha-1 (4.50g kg-1 soil). Minumum TOC

was recorded at day-7 in 2250 mL ha-1 (3.40g kg-1 soil) indicating 24% decline in

TOC and it was 3.60g kg-1 soil in 2250 mL ha-1 at day-15 indicating 20 % drop in

133

TOC, followed by 1500 mL ha-1at day-15 (3.70g kg-1 soil) showing 17.7 drop in

TOC and at day-15 in 750 mL ha-1 (3.80g kg-1 soil) showing 15.5% decrease in

TOC, and 3.85 g kg-1 soil at day-7 in 750 mL ha-1 indicating 14.4% decline in TOC

during 2011-12 as compared to 4.50g kg-1 soil which was found in 2250 mL ha-1 at

day-30 (Figure 33). In 2012-13, the interactive effect of treatment and sampling

days showed maximum TOC in 2250 mL ha-1 at day-60(4.15g kg-1 soil). Minimum

TOC was recorded at day-15 in 2250 mL ha-1 (3.10g kg-1 soil) resulting 25.3%

decline in TOC, followed by 2250 mL ha-1 at day-7(3.15g kg-1 soil) indicating 24 %

decline, followed by 750 mL ha-1at day-15 (3.40g kg-1 soil) with 18% decrease in

TOC and in 1500 mL ha-1at day-7 (3.50g kg-1 soil) resulting 15.7% decline in TOC

followed by 750 mL ha-1 (3.60g kg-1 soil) at day-7 resulting 13.25% inhibition in

TOC as compared to 2250 mL ha-1 at day-60 (4.15g kg-1 soil).

Nitrification being vital process of worldwide nitrogen cycle, involve

ammonium oxidizing bacteria as well as ammonium oxidizing Archaea. In our

study, during 2011-12 the results demonstrated maximum nitrate nitrogen in

control followed by 375 mL ha-1and lowest nitrate nitrogen was found in 2250 mL

ha-1. Similarly, during 2012-13 the highest nitrate nitrogen was found in control

followed by 375 mL ha-1while minimum nitrate nitrogen was observed in 2250 mL

ha-1. Overall, 2250 mL ha-1 showed 49% reduction in nitrate nitrogen as compared

to control during first year and 40 % decrease in nitrate nitrogen as compared to

control during second year in field experiment-1 (light-textured soil).

This inhibition in nitrate nitrogen can be attributed towards the severe

sensitivity of most of autotrophic nitrifiers to the bromoxynil herbicide. Some

134

researchers (Allievi and Giglioti 2001) reported inhibitory effect of sulfonyl urea

herbicides on autotrophic nitrifiers by inhibiting their amino acid assimilation

ability. Similarly, Hernandez et al. (2001) reported inhibition in the activities of

ammonium oxidizing bacteria and ammonium oxidizing archaea through the

application of simazine herbicide (50 µg g-1soil) and found complete inhibition in

nitrification process which in turn resulted decrease in nitrate nitrogen. Different to

that some scientists (Kanungo et al., 1995) reported increase in the population of

Azotobactor and Azospirillum due to repeated use of carbofuron while increase in

the population of anaerobic nitrogen fixing bacteria due to anilofos herbicide.

Similarly, researchers(Chang et al., 2011) observed dcrease in the population of

ammonium oxidizing bacteria by combined mixture of herbicides (atrazine,

dicamba-4 emulsifiable concentrate, flumutoron 4L, metolachlor 7.8 E.C,

sufentrazone) using different concentration (0, 10,100 and 1000 ppm). Contrary to

that some researchers reported stimulation in the activity of ammonium oxidising

bacteria by the application of acetachlor herbicide during intial days of treatment

(Li X et al. 2008) and pronounced nitrification and ammonifiaction by

Azospirillum isolated from soil treated with 5 kgha-1 cypermethrin or fenvalerate

pesticide was reported by (Rangaswamay et al. 1992). Some studies (Das and

Mukherjee 1998) reported stimulation in microbial activity and nutrient

mineralization by the application of phorate (1.5 Kg a.i ha-1) and carbofuron (1.0

Kg a.i ha-1).

Sampling days resulted high significant effect on nitrate nitrogen (P ≤ 0.05).

Maximum nitrate nitrogen was noticed at day-0 and minimum was found day-15

135

but after day-15 it showed increasing trend during both years in Koont soil. High

contents of nitrate nitrogen at day-0 were because of less exposure time of

herbicide to nitrifying bacteria while obvious decline at day-15 was due to more

exposure time of herbicide to soil microbes. Recovery of nitrate nitrogen after day-

15 was because of recstoration of nitrifiers population by developing resistance

gainst the herbicide with the passage of time. Ismail et al. (1995) noticed decline in

bacteria and fungi population due to glufosinate-ammonium (100ppm) during

initial days but later on they found recovery in their population.

The prime biological significance of phosphates is that it serve as power

house of energy in the form of Adinosine triphosphate (ATP) inside the cell and is

a constituent of nucleotides which binds together to form DNA. The Phosphate

ester bridge is fundamental part of double helix of DNA. The results of present

study revealed maximum Olsen-P in control followed by 375 mL ha-1 and least

Olsen-P was observed in 2250 mL ha-1 during 2011-12 and 2012-13 in field

experiment-1. In general, 2250 mL ha-1 treatment resulted 22- 65 % reduction in

Olsen-P compared to control in both years. In 2250 mL ha-1, the highest decrease in

Olsen-P was because of high concentration of herbicide residues that caused

mortality of soil microbes especially phosphate solubilizing bacterial population.

The results of our present study showed significant drop in .in bacterial population.

This might be due to the the mortality of phosphatae solubilizing bacteria due to

which Olsen-P deciled. Ahmad and Khan (2010) reported that different

concentrations of quizalafop-p-ethyl viz. 40, 80 and 120 µg/L caused 72

http://en.wikipedia.org/wiki/Nucleotide


136

Table 4.7: Nitrate nitrogen, Olsen-P and total organic carbon as influenced by different treatments of buctril super herbicide

and sampling days in light-textured soil showing decline in these parameters due to lethal effect of herbicide

Factors Nitrate nitrogen

2011-12 2012-13

Olsen-P

2011-12 2012-13

Total Organic carbon

2011-12 2012-13

---------------------------(µg g-1 soil)------------------------- ------(g kg-1 soil)--------

Treatments

Control 26.9 A 28.7 A 9.5 A 8.6 A 4.22 A 3.91 A

375 mL ha-1 19.6 B 25.3 B 8.6 B 7.8 B 4.08 AB 3.76 AB

750 mL ha-1 15.8 C 20.0 C 8.3 B 7.4 B 3.99 B 3.63 BC

1500 mL ha-1 14.9 D 19.1 D 7.9 C 7.1 C 3.99 B 3.53 C

2250 mL ha-1 13.7 E 17.2 E 7.4 C 6.6 D 4.01 B 3.60 BC

LSD 07570 0.7226 0.3042 0.3248 0.1813 0.1996

Sampling days

0 22.1 A 27 A 9.0 A 8.2 A 4.16 A 3.78 A

7 16.8 C 20.7 BC 8.2 B 7.3 BC 3.81 B 3.56 B

15 16.8 C 20.3 C 8.0 B 7.1 C 3.88 B 3.47 B

30 17.5 BC 20.7 BC 8.2 B 7.4 BC 4.21 A 3.82 A

60 17.7 B 21.4 B 8.3 B 7.5 B 4.22 A 3.80 A

LSD 07570 0.7226 0.3042 0.3248 0.1813 0.1996

Analysis of

variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

T x D

C.V (± %)

<0.05

6.61

<0.05

5.20

<0.05

5.77

<0.05

6.88

<0.05

7.08

<0.05

8.59

137

5

15

25

35

0 7 15 30 60 0 7 15 30 60

Sampling days

Nitra

te n

itro

gen

(µ

g g-1

soil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 31: Interactive effect of herbicide treatments and sampling days on nitrate nitrogen in light-textured

soils showing decline in nitrate nitrogen due toxic effect of herbicide on nitrifiers

138

5

7

9

11

0 7 15 30 60 0 7 15 30 60

Sampling days

Ols

en-P

(µ

g

g-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-122012-13

Figure 32: Interactive effect of herbicide treatments and sampling days on Olsen-P in light-textured soils

showing decline in Olsen-P due toxic effect of herbicide on phosphate solubilizing bacteria

139

3.0

3.5

4.0

4.5

5.0

0 7 15 30 60 0 7 15 30 60

Sampling days

Tot

al o

rgai

c ca

rbon

( g

kg-1

soi

l)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 33: Interactive effect of herbicide treatments and sampling days on total organic carbon in light

-textured soils initially showing decline in TOC and then showed enhancement in TOC because

micobes used the herbicide metabolites as a source of carbon

140

%, 91% and 94% decrease, respectively on the phosphorus solublizing activity of

Enterobacter asburiae as compared to control. This reduction in Olsen-P might be

due to the suppression in fungi population by the herbicide residues as our results

showed significant suppression in fungal population due to different doses of

herbicides. Since fungi are more efficient in sloublising precipitated calcium

phosphate and rock phosphate than bacteria so due to their mortality Olsen-P

decreased significantly. Kucey (1983) reported more efficiency of fungi than

bacteria in solubilizing precipitated calcium phosphate as well as rock phosphatae

and observed highly significant correlation between the population of phosphate

solubilizing fungi and available phosphorus in soil. Contradictory to that Das et al.

2003 reported stimulation in the population of phosphate solubilizers and increased

phosphorus availability in soil. Defo et al. (2011) observed increased phosphorus

availability due to endosulfan (1.5 mL ha-1) during initial 30-days of its application.

Whereas, after days-60 decrease in phosphorus availability was noticed. While

some studies (Sarnaik et al. 2006) reported no significant change in the population

of phosphate solubilizing bacteria and rhizobia in comparison to control by the

application of phorate, carbofuron, carbosulfuron, thiomethaxan, amidacloprid,

chlorpyriphos and monocrotophos application. In this study, sampling days showed

maximum Olsen-P at day-0 and minimum at day-15 indicating 12 % inhibition in

Olsen-P at day-15 as compared to day-0 during 2011-12 and 2012-13 in field

experiment-1 (light-textured soil). Maximum Olsen-P at day-0 was due to less

esposure time of herbicides to phosphate solublizers. However, at day-15 the

Olsen-P was lowest because of toxic effect of herbicide residues so the population

of phosphate solubilizing microbes decreased. On the residues so the population of

141

phosphate solubilizing microbes decreased. On the other hand, some microbes used

the inorganic phosphorus as a source of energy to overcome the detrimental effect

of the herbicide which in turn result decline in Olsen-P.

Decomposition of plant and animal residues, root exudates and dead

microbes results in accumulation of organic carbon in soil. Soil organic carbon is

the main source of energy for soil microorganisms. Organic carbon is one of the

most essential components of the soil due to its ability to provide energy and

enhance nutrient availability to plants through mineralization. In present study

obvious decrease of 5.45 % and 4.97 % in total organic carbon was found due to

750 mL ha-1 in 2011-12 and 2012-13, respectively in light-textured soil. This

decrease in total organic carbon due to herbicide application may be attributed

towards co-metabolism phonominon in which degradation of one compound

depends on the presence of other compound. Sukul et al. (2006) observed decrease

in organic matter due to metalaxyl fungicide and reported that this dercease in

organic carbon was resulted due to co-metabolism phenomina. Similarly, Baboo et

al. (2006) reported 2.49% and 2.23% decline in soil organic carbon at day-7 and

day-28, respectively due to pyrazosulfuron herbicide (25g ha -1), while 1.90 %, 2.47

% and 2.32 % decline in soil organic carbon at day-7, day-21 and day-28,

respectively due to glyphosate herbicide (360g L-1). However, they observed

increase in organic carbon due to paraquot application up to day-14 (2.47%)

followed by decrease at day-21 (2.15 %). Herbicide caused lysis of microbial cells

resulting decline in their population and the remaining microbial population

increased the rate of decomposition of organic matter for obtaining quick energy

142

for their survival which in turn result loss of carbon dioxide with concomitent

deccrease in organic carbon. Ayansina and Oso (2006) reported 13 %, 30 % and 11

% decrease in organic matter contents by combined mixture of two herbicides

(atrazine + metolachlor) during 1st, 4th and 6th weeks after herbicide application,

respectively as compared to control. Defo et al. (2011) reported signifiacnt

decrease in organic carbon due to endosulfan application (100µg g-1 soil) after 60

days. The death of weeds due to herbicide application might be the other reason of

organic matter decrease because organic matter comprises of both dead animal and

plant residues. Plant roots release auxin and gebrilin in soil that contribute towards

increase in organic matter so death of weeds resulted concomitenet decline in

organic matter in soil. In our study, maximum TOC (4.22 g kg-1soil) was noticed at

day-60 and minimum TOC (3.81 g kg-1soil) was found at day-7 indicating 9.71 %

inhibition in TOC at day-7 as compared to day-60 during 2011-12. Similarly,

during 2012-13 TOC was the maximum at day-30 (3.82 g kg-1soil) and minimum at

day-15 (3.47 g kg-1soil) indicating 9.16 % decline in TOC at day-15 as compared to

day-30. Due to positive correlation between the population of soil microorganisms

and soil organic matter (Taiwo and Oso, 1997), the death of soil microbes due to

herbicide might resulted decrease in soil organic carbon at day-7 and day-15 during

2011 and 2012, respectively. Nevertheless, because of recovery of microbial

population after their adaption to herbicide, their population recovered hence soil

organic matter increased.

4.2.16 Correlation of nitrate nitrogen, Olsen-P and total organic carbon with

buctril super herbicide

143

Olsen-P revealed negative but weak correlation (-0. 25) with bromoxynil residues

(Figure 34) similarly nitrate nitrogen was negatively but weakly correlated (-0.16)

with bromoxynil residuse (Figure 35). Total Organic Carbon also indicated

negative (-0.28) correlation with bromoxynil (Figure 36).

4.2.17 Weed Control Efficiency of Buctril Super Herbicide in Light-

Textured Soil

The herbicide was applied using knapsack sprayer 3 weeks (21 days) after

sowing when crop reached 5-6 leaf stage. At that time weeds present in the field

were Chenopotium album (bathu), Vicia sativa (Revari), Fumaria officinalis

(Shahtra), Medicago polimorpha (Ma na), Rumex dentatus (Jangli palak),

Convolvulus arvensis (Lehli) and almost all the above mentioned weeds were in

seedling stage. The analysis of variance data showed statistically significant effect

of different concentrations of herbicide on weed control. Weed control efficiency

data is given in Table 4.8. Treatment means comparison revealed maximum weed

control efficiency by 2250 mL ha-1 (65%) followed by 1500 mL ha-1 (63%), 750

mL ha-1 (61%) and lowest by 375 mL ha-1 (22%) during 2011.

Similarly, in 2012 the analysis of variance data showed statistically

significant effect of different herbicidal treatments on weed control efficiency.

Comparison of treatment means showed maximum weed control efficiency by

2250 mL ha-1 (67%), followed by 1500 mL ha-1 (66%), 750 mL ha-1 (64%) and

lowest by 375 mL ha-1 (24%).

144

Among cereals after maize the wheat (Triticum aestivum) ranks second in the world

(FAO, 2005) and billions of peoples in the world use wheat as a staple food

(Fischer, 2007). By competing with wheat for nutrients, light, water and space,

weeds reduce crop yields (Grichar, 2006; Zand and Soufizadeh 2004). About 25%

loss in grain yield of wheat has been reported in many studies (Baghestani et al.,

2005). Broadleaved weeds are major issue in many wheat growing regions of the

world. The results indicated that 750 mL ha-1 dose of buctril super (bromoxynil)

herbicide have resulted effective control on weeds but increasing dose of herbicide

resulted very little increase in the weed control efficiency that was not cost

effective. Our results are in line to the results of Khan et al. (1999). Marwat et al.

(2008) while seeing the weed control efficiency of different herbicides (topic,

buctril super ,puma super, isoproturon, aid) observed 85.4% and 77.3% weed

control efficiency by isoproturon and buctril super herbicides, respectively.

Different researchers (Zand et al., 2007) using various herbicides viz: diflufenicon,

clopyralid, fluoroxypyr, tribenuron methyl and bromoxynil MCPA, observed better

weed control efficiency by bromoxynil as compared to other herbicides. Aslam et

al. (2007) observed 98% weed control efficiency by panter herbicides while seeing

the impact of different herbicides on weeds. Hussain et al. (2013) noticed

maximum weeds mortality (90.7%) and grain yield (3925 kg /ha) by the combined

mixtutre of bromoxynil and clodinofop-propargyl than weedy check. Baloch et al.

(2013) observed 73.9% suppression in weed density due to application of

combination of (buctril super + puma super) herbicides.

145

4.2.18 Recovery of Bromoxynil Residues after Buctril Super Herbicide

Application in Light- Textured Soil

The highest residues recovered in 2250 mL ha-1 treatment (1.79 mg kg-1)

followed by 1.28 mg kg-1 in 1500 mL ha-1, 0.70 mg kg-1 in 750 mL ha-1and least

residues in 375 mL ha-1 (0.44 mg kg-1) during 2011-12. Whereas, highest residues

recovered were 1.37 mg kg-1 from 2250 mL ha-1, followed by 0.94 mg kg-1 in 1500

mL ha-1, 0.60 mg kg-1 in 750 mL ha-1 and lowest residues (0.36 mg kg-1) in 375 mL

ha-1 during 2012-13.

Sampling days showed maximum residues at day-0 (1.60 mg kg-1) followed

by 1.37 mg kg-1 at day-7, 0.86 mg kg-1 at day-15, 0.27 mg kg-1 at day-30 and 0.11

mg kg-1 at day-60 during 2011-12. While sampling days showed maximum

residues at day-0 (1.34 mg kg-1) followed by 1.00 mg kg-1 at day-7, 0.57 mg kg-1 at

day-15, 0.27 mg kg-1 at day-30 and 0.09 mg kg-1at day-60 during second year

(Table 4.9)

Interactive effect of sampling days and treatments resulted 3.42 mg kg-1

bromoxynil residues in 2250 mL ha-1 at day-0 followed by 2.98 mg kg-1at day-7 in

2250 mL ha-1, 2.31 mg kg-1 at day-0 in 1500 mL ha-1, 2.11 mg kg-1 in 1500 mL ha-1

at day-7, 1.76 mg kg-1 at day-15 in 2250 mL ha-1, 1.44 mg kg-1 at day-0 in 2250 mL

ha-1 followed by 1.35 mg kg-1 at day-15 in 1500 mL ha-1and lowest residues were

detected in 1500 mL ha-1at day-60 (0.26 mg kg-1) during 2011-12. Interactive effect

of sampling days and treatments resulted 2.89 mg kg-1 residues in 2250 mL ha-1

146

y = -1.9336x + 8.0817

R2 = 0.0623

4

6

8

10

12

0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5 0.5


Ols

en-P

(ppm

)

Olsen P Linear (Olsen P)

Figure 34: Buctril super herbicide and Olsen-P showing negative correlation due to toxic effect of herbicide

on soil microorganisms

147

y = -7.6345x + 20.728

R2 = 0.0243

10

15

20

25

30

0.0 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 0.5


NO

3-N

( µ

g g

-1 so

il)

NO3-N Linear ( NO3-N )

Figure 35: Buctril super herbicide and nitrate nitrogen showing negative correlation due to toxic effect of


148

y = -0.8744x + 3.945

R2 = 0.0811

2

3

4

5

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


TO

C (g

kg-1

)

TOC (g kg-1 Linear (TOC (g kg-1)

Figure 36: Buctril super herbicide and total organic carbon showing negative correlation due to toxic effect


149

at day-0 followed by 0.287 mg kg-1at day-0 in 1500 mL ha-1 followed by 0.242 mg

kg-1 at day-7 in 2250 mL ha-1 followed by 2.14 mg kg-1 at day-7 in 2250 mL ha-1

followed by 1.86 mg kg-1 in 1500 mL ha-1 at day-0 followed by 1.33 mg kg-1 at

day-7 in 1500 mL ha-1 followed by 1.21 mg kg-1 at day-0 in 750 mL ha-1 followed

by 1.04 mg kg-1 at day-15 in 2250 mL ha-1 and least residues (0.18 mg kg-1) were

detected in 750 mL ha-1 at day-30 during second year in field experiment-1 (Figure

37). Cessna et al. (1994) reported recoveries of 5 µg g-1 and 14 µg g-1, respectively

for bromoxynil and MCPA during intial days of application to triticale. But after 21

days, the residues drop below the limit of quantification (0.025 µg g-1). Askar at al.

(2007) reported that the recovery of bromoxynil residues was ranged from 29.51%

to 71.94%, 18.89% to 43.88%, 9.82% to 35 and 1.80% to 19.2% at 3 rd, 7th, 14th, 21st

and 28th days, respectively from bacterial media enriched with bromoxynil.

However, recovery of residues ranged from 45% to 60%, 21% to 30%, 6.48 to 20

%, 1.25 to 10.49% and 0.63% to 1.56% at 3rd, 7th, 14th, 21st and 28th days,

respectively from fungal media enriched with bromoxynil. Chen et al. (2011)

observed average recovery of 100.90%, 86% and 83.7% from soil fortified with

0.05 mg kg-1, 0.5 mg kg-1 and 1mg kg-1 of bromoxybil, respectively. Other

investigations, (Golovleva et al., 1988) reported 70% decrease in the concentration

of bromoxynil from soil after 10 to 20th day of surface application of bromoxynil.

Whereas, from bromoxynil enriched culture, they reported 93% recovery of the

said herbicide after 21days of its application.

150

Table 4.8. Different doses of buctril super herbicide showing weeds control

efficiency by blocking electron transport in photosystem-II during

photosynthesis in weeds in field experiment-1 (light-textured soil)

Herbicide dose WCE

(2011)

WCE

(2012)

(%) (%)

Control 0.0 d 0.0 d

375 mL ha-1 22 c 24 c

750 mL ha-1 61 b 64 b

1500 mL ha-1 63 b 66 a

2250 mL ha-1 65 a 67 a

LSD value at 5% α level 1.95 1.30

Means having common letter are not significantly different at LSD test at 5%

probability level

151

Table 4.9 Bromoxynil residues concentration under different treatments of buctril super herbicide and sampling days in

light-textured and heavy-textured soil showing more residues in heavy-textured soil because of more persistence in this soil

Factor Bromoxynil residues Bromoxynil residues

2011-12 2012-13 2011-12 2012-13

(Light-textured soil) (Heavy-textured soil)

------------------------------------(mg kg-1)-----------------------------

Treatments

Control 0.00 0.00 0.0 0.0

375 mL ha-1 0.44 0.36 0.81 0.72

750 mL ha-1 0.70 0.60 1.34 1.41

1500 mL ha-1 1.28 0.94 2.23 2.22

2250 mL ha-1 1.79 1.37 3.31 3.29

Sampling days

0 1.60 1.34 1.66 1.62

7 1.37 1.00 1.58 1.58

15 0.86 0.57 1.55 1.53

30 0.27 0.27 1.48 1.48

60 0.11 0.09 1.43 1.43

152

0

1

2

3

4

0 7 15 30 60 0 7 15 30 60

Sampling days

Bro

mo

xyn

il r

esid

ues

co

nce

ntr

atio

n

(m

g k

g-1 )


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 37: Bromoxynil residues concentration versus time under different herbicide treatments in light-textured

soil showing decline in bromoxynil concentration due to low persistence of herbicide in light-textured soil

153

4.3 FIELD EXPERIMENT-2 (TO SEE THE IMPACTS OF BUCTRIL

SUPER HERBICIDE APPLICATION ON SOIL MICROBIAL

PARAMETERS IN HEAVY-TEXTURED SOIL)

The physico-chemical and microbial properties of soil under studty are given

in (Table 4.10). The sand, silt and clay contents of soils were 22%, 33% and 46%,

respectively and pH was 8.3. The electrical conductivity was 0.51 dSm-1 and 0.50

dSm-1, total organic carbon was 5.1 and 5.2 g kg-1 and Olsen-P was 16.3 and

16.1ppm in 2011-12 and 2012-13, respectively. The activity of urease was 459

µgNH4-N g-1 dwt 2h-1 and 387 µgNH4-N g-1 dwt 2h-1, the activity of dehydrogenase

was 117 µg TPF g-1 24h-1 and 98.1 µg TPF g-1 24h-1, and the activity of alkaline

phosphatase was 39.6 µg Phenol g-1 h-1 and 38.2 µg Phenol g-1 h-1 during 2011-12

and 2012-13, respectively. Bacterial population was 1.44 x 108 and 1.21 x 108,

actinomycetes population was 1.44 x 106 and 1.33 x 106 and fungal population was

4.8 x 105 and 3.9 x 105 during both years, respectively. Microbial biomass carbon

was 691 µg g-1 and 653 µg g-1, microbial biomass nitrogen was 29.2 µg g-1 and 32.1

µg g-1, microbial biomass phosphorus was 21.6 µg g-1 and 22.7 µg g-1, nitrate

nitrogen was 38.7 µg g-1 and 39.4 µg g-1 during 2011-12 and 2012-13, respectively.

4.3.1 Microbial Biomass Carbon under Different Treatments of Buctril

Super Herbicide in Heavy-textured Soil

Results demonstrated that soil microbial biomass carbon was significantly

different in all herbicidal treatments and was in the order of 375 mL ha-1 > 750 mL

ha-1> 1500 mL ha-1> 2250 mL ha-1. Maximum biomass carbon (685µg g-1 soil) was

154

observed in control followed by 643µg g-1soil in 375 mL ha-1 and minimum

biomass carbon (458 µg g-1soil) was observed in 2250 mL ha-1 followed by 587 µg

g-1soil in 1500 mL ha-1 in 2011-12. During 2012-13 the highest biomass carbon

(645 µg g-1soil) was found in control followed by 610 µg g-1soil in 375 mL ha-1 and

minimum biomass carbon (403 µg g-1 soil) was observed in 2250 mL ha-1 followed

by 574µg g-1soil in 1500 mL ha-1 in 2012-13. Overall, 1500 mL ha-1 and 2250 mL

ha-1 treatments caused 14.3 % and 33 % reduction in biomass carbon as compared

to control during 2011-12. While, 11 % and 37.5 % decrease in biomass carbon

was observed as compared to that of control in field experiment-2 (heavy-textured

soil) (Table 4.11). Sampling time had highly significant effect on biomass carbon

(P ≤ 0.05). Maximum biomass carbon was noticed at day-60 (636 µg g-1soil) and

minimum at day-7 (551µg g-1soil) indicating a 13 % less biomass carbon at day-7

as compared to day-60 during 2011-12. Similarly, during 2012-13 biomass carbon

was maximum at day-60 (595 µg g-1soil) and minimum at day-7 (503 µg g-1soil)

indicating a 15.4 % decline in biomass carbon at day-7 in contrast to day-60. In

general, from day-0 to day-60 biomass carbon remained suppressed and did not

recover to its initial level.

4.3.2 Microbial Biomass Nitrogen under Different Treatments of Buctril


Results depicted that soil microbial biomass nitrogen significantly differed

in all herbicidal treatments. The maximum biomass nitrogen (28.7 µg g-1soil) was

observed in control, followed by (20.3 µg g-1soil) in 375 mL ha-1 and least biomass

nitrogen (12.5 µg g-1 soil) was observed in 2250 mL ha-1 during 2011-12. During

155

Table 4.10. Physico-chemical and microbial characteristics of field experiment-2

(heavy-textured soil)

Parameters 2011-12 2012-13

Sand (%) 21 21

Silt (%) 33 33

Clay (%) 46 46

pH 8.3 8.3

EC (dSm-1) 0.51 0.50

TOC (g kg-1) 5.2 5.1

Olsen-P (µg g-1) 16.3 16.1

Urease activity (µgNH4-N g-1 dwt 2h-1) 459 387

Dehydrogenase activity (µg TPF g-1 24h-1) 117 98.1


(µg Phenol g-1 h-1)

39.6 38.2

Bacterial population (#x108) 1.44 1.21

Actinomycetes population (#x106) 1.44 1.33

Fungi population (#x105) 4.8 3.9

Microbial biomass carbon (µg g-1) 693 651

Microbial biomass nitrogen (µg g-1) 29.2 32.1

Microbial biomass phosphorus (µg g-1) 21.6 22.7

Nitrate nitrogen (µg g-1soil) 38.7 39.4

156

2012-13, the highest biomass nitrogen (31.3 µg g-1soil) was found in the control,

followed by (23.6 µg g-1soil) in 375 mL ha-1 and minimum biomass nitrogen

(15.7µg g-1soil) was observed in 2250 mL ha-1 followed by 19.4µg g-1soil in 1500

mL ha-1. Overall, 1500 mL ha-1 and 2250 mL ha-1 herbicidal doses caused a 45 %

and 56 % reduction in biomass nitrogen, respectively as compared to that of control

in 2011-12. Whereas, a 41.5 % and 50 % drop in biomass nitrogen as compared to

that of control during 2012-13 in field experiment-2. Sampling time (day) had a

highly significant impact on the biomass nitrogen (P ≤ 0.05). The maximum

biomass nitrogen was noticed on day-60 (20.3 µg g-1soil) and minimum at day-7

(16.6 µg g-1soil) indicating a 18.2 % decline in biomass nitrogen between the two

during 2011-12. Similarly, during 2012-13 biomass nitrogen was maximum at day-

0 (23.8µg g-1soil) and minimum at day-7 (19.9 µg g-1soil) indicating a 16.3 %

decline in biomass nitrogen at day-7 as compared to day-0. The microbial biomass

nitrogen remained suppressed and could not reach to its original level even upto

day-60 (Table 4.11).

4.3.3 Microbial Biomass Phosphorus under Different Treatments of Buctril


On the basis of present results, it is evident that the soil microbial biomass

phosphorus showed statistically significantly difference in all the herbicidal

treatments and was in the order of 375 mL ha-1 > 750 mL ha-1> 1500 mL ha-1>

2250 mL ha-1. The highest biomass phosphorus (21.1 µg g-1soil) was observed in

control, followed by 18.1 µg g-1soil in 375 mL ha-1. While, the lowest biomass

phosphorus (11.7 µg g-1soil) was recorded in 2250 mL ha-1 followed by 13.5 µg g-

157

1soil in 1500 mL ha-1 in 2011-12. Throughout 2012-13, the highest biomass

phosphorus was found in control (22.0 µg g-1soil) followed by (18.9µg g-1soil) in

375 mL ha-1 and minimum biomass phosphorus (12.3 µg g-1soil) was observed in

2250 mL ha-1 followed by 14.0 µg g-1soil in 1500 mL ha-1. Overall, the 1500 mL

ha-1 and 2250 mL ha-1 treatments showed a 36.0 % and 44.5 % decrease in biomass

phosphorus, respectively as compared to that of control during 2011-12. Similarly,

a 36 % and 39 % decrease in biomass phosphorus was seen in 1500 mL ha-1 and

2250 mL ha-1 treatments than that of control during 2012-13 in field experiment-2.

Sampling time exhibited statistically significant effect on biomass phosphorus (P ≤

0.05). Maximum biomass phosphorus was noticed on day-0 (18.9 µg g-1soil) and

minimum at day-30 (14.1µg g-1soil) indicating a 25.4 % difference between the two

during 2011-12. In the same way, during 2012-13 the biomass phosphorus was

maximum (18.5µg g-1soil) at day-0 and minimum (15.2µg g-1soil) at day-15,

indicating a 18 % decline in biomass phosphorus at day-15 as compared to day-60.

Biomass phosphorus showed a decreasing trend from day-7 to day-15 followed by

an increasing trend thereafter. Nevertheless, biomass phosphorus remined

suppreseed and could not approach to its first level even up to day-60 (Table 4.11).

The interactive effects of sampling days and herbicidal treatments revealed

a maximum biomass carbon (694 μg g-1soil) at day-30 in control and a minumum

biomass carbon (327 μg g-1soil) at day-7 in 2250 mL ha-1 treatment indicating a 53

% decline in biomass carbon followed by (467 μg g-1soil) in 2250 mL ha-1 at day-30

indicating a 32.7 % drop in biomass carbon followed by (537 μg g-1soil) at day-60

by 2250 mL ha-1 showing 22.6% decrease in it during 2011-12 as compared to that

of 694 μg g-1soil biomass carbon which was found at day-30 in control. The

158

treatment and sampling days interaction exhibited maximum biomass carbon (653

μg g-1soil) at day-7 in control and minimum biomass carbon (274 μg g-1soil) at

day-7 in 2250 mL ha-1 resulting a 58 % decline in biomass carbon followed by (384

μg g-1soil) at day-15 in 2250 mL ha-1, indicating a 41 % decline followed by (440

μg g-1soil) at day-60 in 2250 mL ha-1 showing 32.6 % decrease followed by (488 μg

g-1soil) at day-7 in 1500 mL ha-1 resulting a 25 % decline in biomass carbon than

that of control (653 μg g-1soil) which was found at day-7 during 2012-13 (Figure

38).

The sampling days and herbicidal treatments interactive effects revealed

maximum biomass nitrogen (29.2 μg g-1soil) at day-60 in control and minumum

biomass nitrogen (9.7 μg g-1soil) at day-7 in 2250 mL ha-1 showing a 68 % decline

in biomass nitrogen followed by (10.6 μg g-1soil) in 2250 mL ha-1 at day-15

indicating a 64.5 % drop followed by (12.6 μg g-1soil) at day-7 by 1500 mL ha-1

showing a 58 % decline in biomass nitrogen followed by (13.1 μg g-1soil) at day-15

by 1500 mL ha-1 showing a 54 % decrease in biomass nitrogen than that of control

(29.2 μg g-1soil) which was observed at day-60 during 2011-12. The interaction of

herbicidal treatments and sampling days showed maximum biomass nitrogen (32.1

μg g-1soil) at day-60 in control and least biomass nitrogen (11.7 μg g-1soil) at day-7

in 2250 mL ha-1 resulting a 63.5 % decline in biomass nitrogen, followed by (15.3

μg g-1soil) at day-15 in 2250 mL ha-1 indicating a 52 % decline followed by 1500

mL ha-1 (19.7 μg g-1soil) at day-7 with a 38.6% decrease in biomass nitrogen in

contrast to control at day-60 during 2012-13 (Figure 39)

159

Herbicidal treatements and sampling time (days) interactive effects showed

maximum biomass phosphorus (22.5 6μg g-1soil) at day-0 in control. Whereas,

lowest biomass phosphorus (9.2 μg g-1soil) was recorded at day-30 in 2250 mL ha-1

indicating a 59 % decline followed by (12.2 μg g-1soil) in 2250 mL ha-1 at day-7

indicating a 45.7 % drop in biomass phosphorus, followed by (13.2 μg g-1soil) at

day-60 in 1500 mL ha-1 showing a 41.3 % drop in biomass phosphorus, followed by

(15.9 μg g-1soil) at day-60 in 750 mL ha-1 with a 29 % less biomass phosphorus in

comparison to control (22.5 μg g-1soil) that was found at day-0 during 2011-12.

The interactive effects of herbicidal treatment and sampling days illustrated

maximum biomass phosphorus (23.1 μg g-1soil) at day-60 in control and lowest

biomass phosphorus (10.5 μg g-1soil) at day-30 in 2250 mL ha-1 resulting a 45.5 %

decline in biomass phosphorus, followed by (12.2 μg g-1soil) at day-7 in 2250 mL

ha-1 with a 47.1 % decline, followed by (13.8 μg g-1soil) at day-60 in 1500 mL ha-1

showing 40.2 % decrease, followed by (16.5 μg g-1soil) at day-7 in 750 mL ha-1

resulting a 28.5 % decline (Figure 40).

The soil microbial biomass act as a major driving force during soil organic

matter decomposition and is oftenly used as primary indicator of changes in soil

physico-chemical properties as a result of anthropogenic chemicals induced stress

in the soil environment (Baaru et al., 2007). Soil microorganisms comprise about

quarter of whole living biomass of the earth and carry out essential nutrients

transformations and influence accessibility of nutrients as well as soil quality and

health (Mungendi et al., 2007). Therefore, agro-ecosystem productivity is mainly

dependent on microbial biomass activity (Friedel et al., 1996). Present study

160

revealed highest Microbial biomass carbon in control, follwed by 375 mL ha-1 and

lowest biomass carbon in 2250 mL ha-1 during both years in field experiment-2.

The reason for more biomass carbon in control was because of absence of toxic

effect of herbicide on soil microbial community while high biomass carbon in 375

mL ha-1 might be because of lower concentration of herbicide that had not affected

soil microorganisms to a great extent due to which only little decrease was found in

375 mL ha-1. Highest reduction in biomass carbon in 2250 mL ha-1 might be

attributed towards high concentration of herbicide causing mortaility of soil

microbes which resulted decrease in biomass carbon. El-Ghamary et al. (2001)

described significant decrease in biomass carbon and nitrogen due to bensulforon

methyl and metsulfuron methyl herbicides. Many studies (Kalam and Mukhejee,

2001) reported pronounced decline (61%) in soil microbial groups with

concomitant decrease in biomass carbon due to different herbicides (ethion,

carbofuron and hexaconazole). Wang et al. (2006) observed appreciable drop (41-

83 %) in microbial biomass carbon with high and low rates of methamidophos and

urea. This could be because of the fact that the native soil microbial community

that was tolerant to the applied herbicide showed sensitivity to the interaction

product of soil and herbicide which exerted lethal effect on them leading to

decrease in biomass carbon. Baboo et al. (2013) reported that some

microorganisms that were tolerant to butachlor, paraquot and pyrozosulfuron

herbicides exhibited severe sensitivity to the interaction product of soil and

herbicides. Vischetti et al. (2002) while seeing the impacts of benfluralin and

imazamox herbicides on microbial biomass in different soil types found significant

decrease (20 %) in microbial biomass carbon due to 50 % recommended rate of

161

imazamox. Sampling days showed significant effect on soil microbial biomass

carbon. Results showed the highest MBC at day-60 and lowest at day-7. Highest

biomass carbon at day-60 was because of development of resistence in

microorganisms against herbicide and degradation of herbicide by them for

obtaining carbon as a source of energy consequently their population flourished.

Das and Mukherjee (2000) reported an increase in the population of soil

microorganisms by utilization of herbicides (fenvelerate, carbofuron and phorate)

as a source of carbon. Because of high concentration of buctril super residues at

day -7, the growth of microbial population ceased due to which MBC decreased.

Herbicides treatments viz. pendimethalin, fenoxaprop-P- ethyl, metribuzin and

tralkoxydim exhibited significant decline (10-100 times) in soil microbes

population, inturn microbial biomass decreased (Khalid et al., 2001). While

studying the impact of metalaxyl on soil microbial biomass different researchers

(Sukul and Spiteller, 2001) found negative correlation between persistence of

metalaxyl in soil and microbial biomass carbon. Vieri et al. (2007) recorded

substantial drop in soil microbial community and biomass carbon due to

sulfentrazone herbicide (0.7 µg g-1soil).

Microbial biomass being most labile in nature plays an important role in

nutrient transformations in soil. The microbial biomass play fundamental role in

organic matter decomposition and converstion of nutrients into plant available form

(Cookson et al., 2008). In present study average highest decline (53%) in biomass

nitrogen in 2250 mL ha-1 and no decrease in control was recorded during both years

in field experiment-2 (heavy-textured soil). This obvious decline in biomass

162

nitrogen due to 2250 mL ha-1 might be because of lethal effect of herbicide on

physiological functions and membrane permeability of soil microbial community

with concomitant decrease in microbial biomass biomass nitrogen. As our results

showed consider decline in bacteria, fungi and actinomycetes population due to

buctril super herbicide this could be the second reason of reduction in biomass

nitrogen. Present results showed significant drop in dehydrogenase activity due to

buctril super herbicide which is consisered as essential tool for estimation of

overall microbial metabolic activity, therefore, microbial population showed

obvious decline which inturn decreased biomass nitrogen. Different studies

(Nannipieri et al., 1990) reported that essential cell function are associated with

respiration process so any hinderance in respiration activity can hamper carbon

mineralization leading to microbial mortality and as a result decline in soil

micronial biomass. Contrarily, weaver et al. (2007) reported no significant change

in microbial community due to glyphosate application even when applied more

than field application rates. As for as sampling days are concerned the microbial

biomass nitrogen was highest at day-60 but not touched to its initial level. This

could be attributed towards partial degradation of herbicide residues by some

species of soil bacteria and fungi after day-60. Incomplete degradation of buctril

super (bromoxynil) by some bacteria (Desulfitobacterium chlorospirans) with

concomitant recovery of susceptible microbes due to herbicide degradation with

slight recovery in total biomass has been reported in different studies (Allison,

2005). Some researchers (Yu et al., 2011) reported significant inhibition in

bacteria, fungi and actinomycetes population (as well as enzymes activities) in the

beginning due to chlorothalanil application but later on they found soil

163

microorganism’s adjustment against chlorothalanil and their population showed

increasing trend. However, the microbial biomass could not recover to its original

levels because of presence of bromoxynil residues even after day-60. We detected

0.052, 0.082, 0.223 and 0.291 ppm herbicide residues during first year and 0.063,

0.098, 0.273 and 0.364 ppm residues during second year in 375 mL ha-1, 750 mL

ha-1, 1500 mL ha-1and 2250 mL ha-1 herbicidal treatments, respectively at 60th day

because of more organic matter and clay contents in field experiment-2 (heavy-

textured soil) supporting prolonged persistence of herbicide ultimately causing

death and even removal of some beneficial micobes. Yaron et al. (1985) reported

that soil with high organic matter adsorb herbicide more strongly, therefore,

decrease its concentration in soil solution, and thus protect herbicide against

biodegradation; eventually prolong its persistence in the soil.

Microbial biomass plays important functions in soil which include nutrient

supply to plants, control plant pathogens, animals and plant residues turnover,

biodegradation of heavy metals and pesticides. Therefore, reflect overall biological

activity in soil (Kaschuk et al., 2010). Microbial biomass P is extremely variable

but accounts for about 2% to 10% of total soil phosphorus, although it varies at

different soil development stages and in the upper surface layer and can be as high

as about 50% (Oberson and Joner, 2005). Soil microbes after decomposing the

organic matter mineralize organic phosphorus and quickly incorporate P into

microbial biomass with great recovery with in short time period. McLaughlin

(1988) reported around 28% incorporation of P from the residues of legumes into

microbial cells after 7th day of residues addition. Present study showed that

microbial biomass phosphorus was statistically different in all herbicide treated

164

soils showing the order of 375 mL ha-1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL

ha-1. Maximum biomass phosphorus was observed in control followed by 375 mL

ha-1 and minimum biomass phosphorus was observed in 2250 mL ha-1 during the

both experimental years. Overall, 1500 mL ha-1 and 2250 mL ha-1 herbicide

treatments caused a 36 % and 44.2 % reduction in biomass phosphorus as

compared to control during both years in field experiment-2 (heavy-textured soil).

This huge deline in biomass phosphorus was because of death of soil

microorganisms as it is evident from our results indicating obvious reduction in

bacterial, actinomycetes and fungi population due to higher rate of buctril super

herbicide application. Different researchers (Busse et al., 2001) reported toxicity of

glyphosate to most of soil bacteria and fungi causing their mortality ultimately

decreasing microbial biomass phosphorus. This inhibition in microbial biomass

phosphorus might be because of decreased activity of soil enzymes

(dehydrogenase, alkaline phosphatse and urease) due to herbicide as it is proved in

our present study. Contrary to this, Digrak and Kazaniki (2001) observed increase

in bacterial population and no effect on other microbes in soil treated with

organophosphorus insecticide (isofenphos) as compared to untreated soil. Sampling

days exhibited significant effect on microbial biomass phosphorus in experimental

site-2 (Taunsa) in both years. High biomass phosphorus was noticed on day-0 and

low day-30, indicating a 21% less MBP at day-30 as compared to day-0. Biomass

phosphorus could not reached to its original level and remain suppressed even up to

day-60. Hight decrese in biomass phosphorus at day-30 in field experiment-2 was

because of presence of herbicide residues that caused death of soil microbes. We

detected 0.61ppm, 1.34ppm, 3.23 ppm and 3.31 ppm bromoxynil residues during

165

first year whereas 0.72 ppm, 1.44 ppm, 2.22 ppm and 3.29 ppm, respectively in 375

mL ha-1, 750 mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 treatments applied soils,

respectively at day-30 in field experiment-2 that inhibited microbial population

ultimately biomass phosphorus decreased. Golovleva et al. (1988) reported around

80% recovery of initial quantity of applied herbicide even after 110 days in the

surface layer and 20% recovery in deeper layer.

4.3.4 Correlation Between Buctril Super Herbicide and Microbial Biomass

Present findings demonstrated strong negative correlation between

microbial biomass carbon bromoxynil residues (-0.81). Similarly, microbial

biomass nitrogen (MBN) showed negative correlation (-0.54) with bromoxynil

herbicide. Biomass phosphorus (MBP) also showed strong but negative (-0.73)

correlation with bromoxynil.

Our results showed strong negative correlation between bromoxynil

herbicide residues and microbial biomass. Similarly, Hart and Brookes (1996)

reported negative correlation between microbial biomass and benomyl herbicide

and observed 15% decrease in microbial biomass carbon (MBC) with benomyl

herbicide application. But they noticed positive correlation between microbial

biomass and aldicarb application and reporte 16% increase in MBC due to aldicarb

herbicide.

4.3.5 Bacterial Population under Different Treatments of Buctril Super

Herbicide in Heavy-textured Soil

166

The bacteria, actinomycetes and fungi populations showed statistically significant

difference in all herbicidal treatments and were consistently in the order of 375 mL

ha-1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL ha-1. In control, the highest bacterial

population was observed, which was 1.35 x108cfu g-1soil followed by 1.38 x108cfu

g-1soil in 375 mL ha-1 and the lowest population (0.76 x108cfu g-1soil) was

observed in 2250 mL ha-1 during 2011-12. Highest bacterial population was found

in control that was 1.21 x 108cfu g-1 soil followed by 0.89 x108 cfu g-1soil in 375

mL ha-1 and the least bacterial population (0.58 x108cfu g-1soil) in 2250 mL ha-1

during 2012-13. Overall, 1500 mL ha-1 and 2250 mL ha-1 herbicidal treatments

indicated a 31.0 % and 43.7 % reduction in bacterial population during 2011-12

and 39.0 % and 52.0 % decrease during 2012-13, respectively than that of control

in field experiment-2 (Table 4.12). Sampling time (days) had a highly significant

effect on the bacterial population (P ≤ 0.005). Maximum values of bacterial

population were recodred at day-0 (1.32 x108cfu g-1 soil) and minimum at day-30

(0.88x108cfu g-1 soil) indicating a 33.3 % decline between the two in 2011-12.

Similarly, during 2012-13 bacterial population was maximum at day-0

(1.10x108cfu g-1 soil) and minimum at day-30 (0.72 x108cfu g-1 soil) indicating a

34.5 % decline in bacterial population between them.

4.3.6 Actinomycetes Population under Different Treatments of Buctril Super


Effect of herbicide on actinomycetes population during 2011- 12 and 2012-

13 is given in (Table 4.12). Highest population was found in control which was

167

Table 4.11. Microbial biomass as influenced by different treatments of buctril super herbicide and sampling days in heavy-

textured soil showing decline in these parameters due to herbicidal toxicity

Factors Microbial Biomass C

2011-12 2012-13

Microbial Biomass N

2011-12 2012-13

Microbial Biomass P

2011-12 2012-13

-----------------------------------------------(µg g-1 soil)------------------------------------------------------

Treatments

Control

685 A

645 A

28.7 A

31.3 A

21.1 A

22.0 A

375 mL ha-1 643 B 610 B 20.3 B 23.6 B 18.1 B 18.9 B

750 mL ha 616 B 594 B 16.8 C 19.9 C 15.6 C 16.3 C

1500 mL ha 587 C 574 C 15.8 C 18.3 C 13.5 D 14.0 D

2250 mL ha 458 D 403 D 12.5 D 15.7 D 11.7 E 12.3 E

LSD 28.21 19.2 1.91 1.58 1.07 0.72

Sampling days

0 618 AB 567 B 20.5 A 23.8 A 18.9 A 18.5 A

7 551 C 503 C 16.6 B 19.9 B 16.8 B 16.7 B

15 576 C 575 B 17.4 B 20.6 B 14.2 C 15.2 C

30 608 B 586 AB 19.3 A 22.5 A 14.1 C 15.8 C

60 636 A 595 A 20.3 A 23.2 A 16.2 B 17.4 B

LSD 28.21 19.2 1.91 1.58 1.07 0.72

Analysis of

variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

T x D

C.V (± %)

<0.05

7.49

<0.05

5.40

<0.05

6.18

<0.05

7.11

<0.05

7.62

<0.05

6.88

168

250

400

550

700

850

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

C (

µg g-1

soil)


2011-12 2012-13

Figure 38: Interactive effect of herbicide treatments and sampling days on biomass carbon in heavy-textured

soil showing suppression in biomass carbon even upto day-60 due to high persistence of herbicide in this soils

169

5

15

25

35

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

N (

µg g-1

soil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 39: Interactive effect of herbicide treatments and sampling days on biomass nitrogen in heavy-

textured soil showing decline in MBN upto day-60 due to high persistence of herbicide in this soils.

170

5

15

25

35

0 7 15 30 60 0 7 15 30 60

Sampling days

MB

P (

µg

g-1 so

il)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 40: Interactive effect of herbicide treatments and sampling days on biomass phosphorus in heavy-textured

soils showing suppression in biomass phosphorus upto day-60 due to more persistence of herbicide in this soils

171

y = -421.75x + 667

R2 = 0.6576

200

400

600

800

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


MB

C (

µg

g-1)

MBC Linear (MBC )

Figure 41: Buctril super herbicide and microbial biomass carbon showing negative correlation dur to toxic

effect of herbicide on soil microorganisms

172

y = -29.168x + 22.696

R2 = 0.2879

5

15

25

35

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45


MB

N (

µg g-1

)

MBN Linear (MBN)

Figure 42: Buctril super herbicide and microbial biomass nitrogen showing negative correlation due to toxic


173

y = -15.913x + 19.627

R2 = 0.5307

5

10

15

20

25

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


MB

P (

µg

g-1)

MBP Linear (MBP)

Figure 43: Buctril super herbicide and microbial biomass phosphorus showing negative correlation due to toxic


174

1.49 x106 cfu g-1soil followed by 1.24 x106 cfu g-1soil in 375 mL ha-1 and lowest in

0.91 x106 cfu g-1soil in 2250 mL ha-1. In 2012-13, the highest population (1.34 x106

cfu g-1soil) was found in control, followed by 1.13 x106 cfug-1soil in 375 mL ha-1

and minimum actinomycetes population (0.81 x106) was found in 2250 mL ha-1. In

general 1500 mL ha-1 and 2250 mL ha-1 treatments showed 32 % and 39 % decline

in actinomycetes population during 2011-12, while 30.6 % and 39.5 % decrease

during 2012-13 in actinomycetes population as compared to control. Sampling days

had highly significant effect on actinomycetes population (P ≤ 0.005). At day-0

maximum actinomycetes population (1.26 x106cfu g-1 soil) was observed while, at

day-15 minimum population (1.0 x106cfu g-1 soil) was found indicating 20.6 % less

population at day-15 as compared to day-0 during 2011-12. Similarly, during 2012-

13 actinomycetes population was maximum at day-0 which was 1.16 x106cfu g-1

soil and minimum at day-15 which was 0.90 x106 cfu g-1soil indicating 22.4 %

decline at day-15 as compared to day-0 in actinomycetes population. The

actinomycetes population remain suppressed and could not recoverd to its itial

levevl even upto day-60 during both years in field experiment-2 (heavy-textured

soil).

4.3.7 Fungi Population under Different Treatments of Buctril Super

Herbicide in Heavy-Textured Soil

Fungal population response to applied herbicide during 2011-12 and 2012-

13 is presented in (Table 4.12). Results showed highest fungi population (4.7 x105

cfu g-1soil) in control followed by 375 mL ha-1 (4.2 x105 cfu g-1soil) and lowest

population was noticed in 2250 mL ha-1 (3.2 x104 cfu g-1soil) during 2011-12.

175

However, in second year maximum fungal population was found in control (3.8

x105 cfu g-1 soil), followed by 375 mL ha-1 (3.3 x105 cfu g-1soil) and lowest

population was found in 2250 mL ha-1 (2.3 x105 cfu g-1 soil). As a whole, 1500 mL

ha-1 and 2250 mL ha-1 herbicidal treatments indicted a 28.2 % and 30.4 % reduction

during 2011-12. Whereas, a 36.0 % and 39.0 % decrease in fungi population was

experienced during 2012-13, respectively over control. Sampling days had

significant effect on fungi population (P ≤ 0.005). At day-0 maximum fungi

population (4.2 x105cfu g-1soil) while at day-15 minimum population (3.6 x105cfu

g-1soil) was found indicating a 14 % less population between thm during 2011-12.

Similarly, in 2012-13, the fungi population was highest at day-0 (3.3 x105cfu g-

1soil) and lowest at day-15 which was 2.7 x105 cfu g-1soil indicating a 18 % decline

in fungi population at day-15 in contrast to day-0. During both years decline in

fungi population was found from day-0 to day- 60 and the population could not

reached to its original stage even up to 60th day.

The interactive effect of treatments and sampling days showed statistically

significant difference. Maximum bacterial population (1.48 x108 cfu g-1soil) was

recorded at day-0 in control. Minimum bacterial population (0.56 x108 cfu g-1soil)

was found at day-30 in 2250 mL ha-1 showing a 62 % inhibition in bacterial

population, followed by (0.63 x108 cfu g-1soil) at day-15 in 2250 mL ha-1 indicating

a 57.4% inhibition in population followed by (0.73 x108 cfu g-1soil) at day-30 in

1500 mL ha-1 as compared to control (1.48 x108 cfu g-1soil) at day-0 during 2011-

12. Similarly, in 2012-13, the interaction of herbicidal treatment and sampling days

showed maximum population (1.24 x108 cfu g-1soil) at day-60 where no herbicide

176

was applied. Least bacterial population (0.39 x108 cfu g-1soil) was recorde at day-

30 in 2250 mL ha-1 resulting a 68.0 % less population followed by 2250 mL ha-1 at

day-15 (0.46 x108 cfu g-1soil) indicating a 63 % decline, followed by 2250 mL ha-1

at day-60 (0.48 x108 cfu g-1soil) exhibiting a 61.3 % as compared to day-60 at

control (Figure 44).

The interaction of sampling days and treatments demonstrated maximum

actinomycetes population at day-0 in control (1.50 x106 cfu g-1soil) and lowest

population at day-15 in 2250 mL ha-1 (0.73 x106 cfu g-1soil) indicating a 51 %

decline followed by 2250 mL ha-1 at day-7 (0.76 x106 cfu g-1soil) indicating a 49 %

drop in actinomycetes population, followed by 0.81 x106 cfu g-1soil at day-15 in

1500 mL ha-1 showing a 46 % drop in population during 2011-12 as compared to

that of control at day-0.

In 2012-13, the interactive effect of treatment and sampling days showed a

maximum actinomycetes population at day-0 (1.36x106 cfu g-1soil) in control and

minimum population was observed at day-15 (0.66 x106 cfu g-1soil) in 2250 mL ha-

1 indicating a 51.4 % less population, followed by 1500 mL ha-1 at day-15 (0.71

x106 cfu g-1soil) indicating a 48 % decline, followed by 1500 mL ha -1 at day-7 (0.79

x106 cfu g-1soil) showing a 42 % decrease in actinomycetes population as

compared to that of control at day-0 (Figure 45)

The interaction between treatment and sampling days showed highest population of

fungi in control at day-7 (4.9 x105 cfu g-1soil). The lowest fungal population (2.8

177

x105 cfu g-1soil) was observed in 225 mL ha-1 at day-15 indicating a 43 % decline,

followed by in 1500 mL ha-1at day-30 (3.0 x105 cfu g-1soil) indicating a 39%

deccrease, followed by 1500 mL ha -1 at day-15 (3.1 x105 cfu g-1soil) showing a

36.7% decline as compared to control at day-7 (4.9 x105 cfu g-1soil) in 2011-12.

Similarly, in 2012-13 the interactive effect of treatment x sampling days showed

maximum fungi population in 375 mL ha-1 at day-60 (4.0 x105 cfu g-1soil) and

minimum population at day-7 in 2250 mL ha-1 (1.9 x105 cfu g-1soil) with a 52%

decline, followed by 2250 mL ha-1 (2.0 x105 cfu g-1soil) at day-15 exhibiting a 50%

drop, followed by 1500 mL ha-1 at day-60 (2.2 x105 cfu g-1soil) indicating a 45%

decline as compared to that of control at day-60 (4.0 x105 cfu g-1soil) (Figure 46).

Bacteria play an essential role in the soil ecosystem including the

decomposition of organic matter, degradation of organic pollutants and nutrients

transformations. Nitrification, denitrification, phosphorus solubilization and many

other important processes are carried out by the bacteria in soil. They are present in

the soil in great abundance. A single gram of soil may contain upto 3 billion

bacteria. They reproduce rapidly up to 16 million times in 24 hours. Introduction of

pesticides to the soil environment exert toxic impacts on soil microbial diversity.

Some microbes are resistant to various anthropogenic chemicals, while others are

highly susceptible to them. Results of the present study exhibited the highest

incidence of bacterial population in conrol followed by 1.38 x108cfu g- 1soil in 375

mL ha-1and the least in 2250 mL ha-1 during 2011-12. In 2012-13 the highest

bacterial population was found in control, followed by 0.89 x108 cfu g-1soil in 375

mL ha-1 and the least in 2250 mL ha-1. Overall, 1500 mL ha-1 and 2250 mL ha-1

178

Table 4.12: Microbial population showing extended decline in heavy-textured soil due to buctril super herbicide treatments and

sampling days because of more persistence of herbicide in this soil


2011-12 2012-13

Actinomycetes population

2011-12 2012-13

Fungi population

2011-12 2012-13

--(#x107 cfu g-1 soil)-- ---(#x105 cfu g-1 soil)--- ---(#x104 cfu g-1 soil)---

Treatments

Control

1.35 A

1.21 A

1.49 A

1.34 A

4.7 A

3.8 A

375 mL ha-1 1.11 B 0.89 B 1.24 B 1.13 B 4.2 A 3.3 B

750 mL ha-1 1.03 B 0.82 C 1.15 B 1.05 C 3.8 B 2.8 C

1500 mL ha-1 0.93 C 0.74 D 1.01 C 0.93 D 3.3 BC 2.4 D

2250 mL ha-1 0.76 D 0.58 E 0.91 D 0.81 E 3.2 C 2.3 D

LSD 0.0848 0.0341 0.0942 0.0404 0.458 0.171

Sampling days

0 1.32 A 1.10 A 1.26 A 1.16 A 4.2 A 3.3 A

7 1.05 B 0.86 B 1.05 B 0.97 C 3.8 AB 2.8 CD

15 0.97 BC 0.80 C 1.00 B 0.90 D 3.6 B 2.7 D

30 0.88 D 0.72 E 1.18 A 1.09 B 3.7 B 2.8 BC

60 0.94 CD 0.76 D 1.25 A 1.13 AB 3.8 AB 2.9 B

LSD 0.0848 0.0340 0.0942 0.0404 0.458 0.171

Analysis of

variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

179

herbicidal treatments resulted in 31.0 % and 43.7 % decline in bacterial population

during the first year and 39.0 % and 52.0 % decrease during the second year,

respectively as compared to control in field experiment-2 (Table 4.12). Maximum

incidence of bacterial population during both years in control was because of the

absence of herbicidal residues. Low decline in the bacterial population in 375 mL

ha-1 could be due to the low concentration of bromoxynil toxicity to bacterial

population but not to a great degree. Relatively sharp decrease of 43.7% and 52%

in bacterial population in 2250 mL ha-1 during the 1st and 2nd year may be attributed

to the high concentration and toxicity of bromoxynil. Perhaps the herbicide

adsorption by soil organic matter has increased its detrimental effects on bacteria

leading to their cell lysis. Numerous studies (Perruci and Scarponi, 1994:

Jayamadhuri and Rangaswamy, 2005) reported microbial cells lysis due to

prolonged exposure to herbicide and its adsorption by the soil organic matter.

Busse et al. (2001) reported lethal effects of glyphosate on bacteria and increased

in severity with higher concentration of glyphosate. However, Ratcliff et al. (2006)

observed increase in bacterial population with higher dose (100xFR) of glyphosate

herbicide. Another study (Waever et al., 2007) reprted no any significant change in

bacterial population due to higher concentration of glyphosate. Allievi and Giglioti

(2001) found suppression in the growth of nitrifying bacteria with sulfonylurea

herbicide due to disruption in their amino acid absorption ability. A similar study

(Ratnayak and Audus, 1978) noted inhibition in nitrifying bacteria due to the

application of 3,5-dibro-4 Hyroxybenznitrile herbicide. Sampling days have

resulted highly significant effect on the bacterial population (P ≤ 0.005). Highest

population count was at day-0 and least at day-30 which was 33.3 % less as

180

compared to that of day-0 during 2011-12. Similarly, during 2012-13 the bacterial

population was maximum at day-0 and minimum at day-30 (0.72 x108 cfu g-1soil)

which highlighted a 34.5 % decline in bacterial population at day-30 as compared

to day-0. This may be attributed to the concentration sustained up to 7th day. The

subsequent recovery of bacterial population may be the result of their adaption to

herbicide and ultimate herbicide degradation. Singh and Dileep (2005) reported an

initial decline in bacterial population due to exposure to diazini herbicide and then

their subsequent recovery as reflected by their increased population of 14.4 % and

42.9 % at 15th and 60th day, respectively.

Actinomycetes exhibit some common characteristics of both fungi and bacteria.

However, because of their unique features they are classified into a separate

category. Actinomycetes are found in such abundant quantities in soil as they are

rated next to bacteria in numbers. Actinomycetes have the unique ability of

degrading various kinds of substrates such as cellulose and nondecomposable

larger protein molecules. Actinomycetes are considered as on of the most essential

components of compost (Holt et al., 1994). Results of the present study exhibited

highest actinomycetes population in control, followed by 375 mL ha-1 and lowest in

2250 mL ha-1 during both years of testing in Taunsa soils. In general, 1500 mL ha-1

and 2250 mL ha-1 herbicidal treatments showed 32 % and 39 % decline in

actinomycetes population during both years as compared to that of control. This

might be because of the herbicidal residues constituting only a minute quantity of

the applied chemical (< 0.3%) to the target organism, while the remainder (99.7%)

directly goes to the soil ecosystem inflicting irreversible injury to soil microbial

181

community (Pimental et al., 1995). Different studies (Omar and Abdel Sater, 2001)

reported significant decline in actinomycetes population due to high dose of

herbicide (brominal). Application of 1ppm and 100pm dose of prosulfuron and

bromoxynil herbicides showed 91% suppression in actinomycetes population in

contrast to that of control (Pampalha and Oliveria 2006). Actinomycetes showed

severe sensitivity to imazamox and benfluralin herbicides (Vischetti et al., 2002)

that caused about 25% and 64 % drop in their populations, respectively. Contrary

to that, He et al. (2006) observed no alteration in the actinomycetes population

under metsulfuron methyl herbicide. Interestingly other researchers (Araujo et al.,

2003) reported enhancement in population of actinomycetes due to the addition of

glyphosate herbicide. Our results revealed statistically significant effect of

sampling days on actinomycetes population. Actinomycetes showed maximum

population count at day-0 and minimum at day-15 indicating 20.6 % less

population at day-15 as compared to day-0 during both years. The population of

actinomycetes remained suppressed and did not reach to its initial level even upto

60th day during both years in Taunsa soil. This significant drop in actinomycetes

population at day-15 was due to the severe toxicity of herbicide during the initial

period of first 15-days and then the detrimental effect of herbicide dissipated.

Similarly, Yu et al. (2011) found suppression in actinomycetes population up to

two weeks under chlorothanil herbicide application, but thereafter they gradually

increased in population because of acclamatization to the herbicide. The population

of actinomycetes remained below its original level upto day-60 because of the

adsorption of herbicide to clay and lesser degradation. Different scientists

(Rosenbrock et al., 2004) observed 42% and 49% mineralization of bromoxynil

182

0.3

0.6

0.9

1.2

1.5

1.8

0 7 15 30 60 0 7 15 30 60

Sampling days

Bac

teri

a (

#x10

8 cf

u g-

1soi

l)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 44: Interactive effect of herbicide treatments and sampling days on bacterial population in heavy-textured

soils showing suppression in bacterial population and their population could not recover to its initial level even

upto day-60 due to high persistence and low degradation of herbicide in these soils

183

0.5

0.8

1.1

1.4

1.7

0 7 15 30 60 0 7 15 30 60

Sampling days

Act

inom

ycet

ed p

opul

atio

n

(#x1

06 c

fu g

-1 s

oil)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 45: Interactive effect of herbicide treatments and sampling days on actinomycetes population in heavy-

textured soils showing suppression in actinomycetes population and their population could not recovered to its

initial level even upto day-60 due to high persistence and low degradation of herbicide in these soils

184

1.5

3.0

4.5

6.0

0 7 15 30 60 0 7 15 30 60

Sampling days

Fun

gi p

opul

atio

n (#

x105 c

fu g

-1 so

il)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 46: Interactive effect of herbicide treatments and sampling days on fungi population in heavy-textured

soil showing suppression in fungi population and their population could not recovered to its initial level even


185

and bromoxynil octanoate, respectively with in 60 days of herbicide application

and the residual portion of both the herbicides remained unchanged.

Fungi perform numerous functions in soil. Mycorrhizal fungi develop a

symbiotic relationship with plants and obtain carbohydrates from plant roots and in

turn supply nitrogen phosphorus and moisture to them. The hyphae of fungi release

some enzymes in soil that help in nutrient cycling. Some fungi (Asbuscular

mycorhizal fungi) manufacture glomalin that binds to the soil particles and assist in

soil structure development (Hoorman, 2011). Present results showed a decrease in

fungal growth with increased concentration of herbicide. The population of fungi

was maximum in control and minimum in 2250 mL ha-1 followed by 1500 mL ha-1

during both years in field experiment-2 (heavy-textured soil). On an average 1500

mL ha-1 and 2250 mL ha-1 showed 32% and 34.5% decline in fungi population

during both years. This marked decline in fungi population in 2250 mL ha-1 and

1500 mL ha-1 was because of the toxicity of high concentration of herbicide causing

damage to their membrane and ultimately leading their cell lysis. Sebiomo et al.

(2011) reported 52%, 74%, 80% and 53% decline during the 2nd week while 37.5%,

21%, 58% and 8.1% decline during 6th week in fungi population due to

manufacturer recommended rates of atrazin, glyphosate, paraqout and primeextra

herbicides, respectively. Contrary to our findings, (Abdel-Mallek et al., 1994)

reported stimulation in cellulolytic fungi population due to glyphosate herbicide. At

day-0 maximum fungi population was observed while minimum at day-15

indicating a 16 % less population at day-15 as compared to day-0 during both

years. The population of fungi was maximum at day-0 because of limited exposure

http://en.wikipedia.org/wiki/Mycorrhiza

186

time of fungi population to herbicide and its decline at day-15 was more exposure

of fungi population to herbicide. Opposite to our findings in field experiment-1 in

which the population of fungi reached its initial level after 60 days, the population

of fungi could not reach to its intial level even after sixty days in field experiment-2

because of the high clay contents in later soil which resulted in adsorption of

herbicide to caly. Therefore, herbicide persistence increased with concomitant

decrease in fungi population.

4.3.8 Correlation Between Buctril Super Herbicide and Microbial

Population

Bacterial population and bromoxynil residues were negatively correlated

(-0.59) with each other. Similarly, actinomycetes population was strongly but

negatively correlated with bromoxynil residuses (-0.77). Fungal population also

exhibited strong negative correlation (-0.67) with bromoxynil residues. Current

results illustrated strong negative correlation between microbial population and

bromoxynil residues. This might be because of toxic effects of herbicide on soil

microbes causing alteration in their metabolic activity leding to mortaility. The

herbicide induced reaction in complex microbial enzymes hampers their

physiological functions and ATP formation. Contrary to that Araujo et al. (2003)

observed positive correlation between glyphosate herbicide and populations of

fungi and actinomycetes but negative correlation between bacterial population and

glyphosate herbicide application. Other investigations (Haney et al., 2009) reported

strong positive correlation (r = 0.995) between glyphosate herbicide and microbial

187

population. Incresae in microbial population might result when glyphosate is being

used as a sole carbon source by soil microorganisms.

4.3.9 Urease Activity under Different Treatments of Buctril Super Herbicide

in Heavy-textured Soil

It is evident from the results of present study that soil enzymes activities

varied significantly in all herbicidal treatments and were in the order of 375 mL ha-

1 > 750 mL ha-1 > 1500 mL ha-1 > 2250 mL ha-1. Highest urease activity was

observed in control which was 456 µg NH4-N g-1 dwt 2h-1, followed by 429

µgNH4-N g-1dwt 2h-1 in 375 mL ha-1 and least activity was 293 µgNH4-N g-1dwt 2h-

1 in 2250 mL ha-1 in 2011-12. While, highest urease activity (383 µg NH4-N g-1dwt

2h-1) was found in control, followed by 356 µg NH4-N g-1dwt 2h-1 in 375 mL ha-1

and lowest urease activity was in 2250 mL ha-1 (231 µg NH4-N g-1dwt 2h-1) during

2012-13. Overall, 1500 mL ha-1 and 2250 mL ha-1 caused a 26 % and 35.7 %

reduction in urease activity as compared to that of control during 2011-12, while 27

% and 40 % decrease in urease activity as compared to control during 2012-13 in

field experiment-2 (Table 4.13). Sampling days showed highly significant effect on

urease activity (P ≤ 0.05). Maximum urease activity was observed at day-60 (410

µg NH4-N g-1dwt 2h-1) and minimum activity was at day-7(348 µg NH4-N g-1dwt

2h-1) indicating a 15.2 % less activity at day-7 as compared to day-60 during 2011-

12. Similarly, during 2012-13 the activity of urease was maximum at day-60 (334

µg NH4-N g-1dwt 2h-1) and minimum at day-7 (293 µg NH4-N g-1dwt 2h-1)

indicating a 12 % decrease in said enzyme activity at day-7 as compared to day-60.

188

4.3.10 Dehydrogenase Activity under Different Treatments of Buctril Super


Response of dehydrogenase activity to herbicide application during 2011-12

and 2012-13 is given in (Table 4.13). The highest dehydrogenase activity was

observed in control (114 µgTPF g-124h-1), followed by 375 mL ha-1 (103 µg TPF g-

124h-1) and least activity in 2250 mL ha -1 (82 µg TPF g-124h-1) during 2011-12,

while maximum dehydrogenase activity was found in control which was 97.9 µg

TPF g-1 24h-1, followed by 85.3 µg TPF g-1 24h-1 in 375 mL ha-1 and lowest activity

was found in 2250 mL ha-1 (64.0 µg TPF g-1 24h-1) during second year. On the

whole, 1500 mL ha-1 and 2250 mL ha-1 herbicidal treatments indicated a 20.0 % and

28.0 % decline in dehydrogenase activity during 2011-12. Whereas, 27.2 % and

34.6 % decrease in dehydrogenase activity was found as compared to that of

control during 2012-13. Sampling days had high significant effect on

dehydrogenase activity (P ≤ 0.05). At day-60, maximum dehydrogenase activity

was recorded which was 110 µg TPF g-1 24h-1, while at day-15 minimum

dehydrogenase activity (84.0 µg TPF g-1 24h-1) was found indicating a 23.6 %

decrease between the two during 2011-12. Similarly, during 2012-13

dehydrogenase activity was maximum at day-60 (90.7 µg TPF g-1 24h-1) and

minimum at day-15 (64.0 µg TPF g-1 24h-1) indicating a 29 % inhibition in

dehydrogenase activity at day-7 in contrast to day-60 in field experiment-2 (heavy-

textured soil).

189

y = -9.1524x + 13.138

R2 = 0.3483

4

8

12

16

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


Bac

teri

al c

fu (

#x108

)

Bacterial population Linear (Bacterial population)

Figure 47: Buctril super herbicide and bacterial population showing negative correlation due to toxic


190

y = -9.5519x + 12.955

R2 = 0.5938

3

6

9

12

15

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


Act

inom

ycet

es c

fu (

#106)

Actinomycetes Linear (Actinomycetes)

Figure 48: Buctril super herbicide and actinomycetes population showing negative correlation due to toxic


191

y = -25.995x + 39.013

R2 = 0.4488

10

20

30

40

50

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


Fun

gal p

opul

atio

n (#

x10 5

)

Fungi Linear (Fungi )

Figure 49: Buctril super herbicide and fungi population showing negative correlation due to toxic


192

4.3.11 Alkaline Phosphatase Activity under Different Treatments of Buctril


The impacts of buctril super herbicide on alkaline phosphatase activity

during 2011-12 and 2012-13 is given in (Table 4.13). Results showed the highest

alkaline phosphatase activity in control (40.0 μg Phenol g-1h-1), followed by 375

mL ha-1 (27.5 μg Phenol g-1h-1) and the lowest activity in 2250 mL ha-1 (17.2 μg

Phenol g-1h-1) during 2011-12. The highest alkaline phosphatase activity was found

in control (38.3 μg Phenol g-1h-1), followed by 375 mL ha-1 (26.0 μg Phenol g-1h-1)

and minimum activity in 2250 mL ha-1 (15.5 μg Phenol g-1 h-1) during second year.

As a whole, 1500 mL ha-1 and 2250 mL ha-1 treatments caused a 49 % and 57 %

decrease during 2011-12, whereas 50 % and 61 % decrease in alkaline phosphatase

activity as compared to control during 2012-13. Sampling days also showed highly

significant effect on alkaline phosphatase activity (P ≤ 0.05). Maximum alkaline

phosphatase activity (30.8 μg Phenol g-1h-1) was recorded at day-60, while at day-7

minimum alkaline phosphatase activity (20.6 μg Phenol g-1h-1) was noticed

indicating a 33 % less activity at day-7 as compared to day-60 in 2011-12.

Similarly, in 2012-13 alkaline phosphatase activity was maximum (28.9 μg Phenol

g-1h-1) at day-60 and minimum (19.8μg Phenol g-1h-1) at day-7 indicating a 31 %

inhibition in alkaline phosphatase activity at day-7 as compared to day-60 in field

experiment-2.

The interactive effect of herbicide treatments and sampling days showed

statistically significant difference. Maximum urease activity (458 µgNH4-Ng-1dwt

2h-1) was recorded at day-0 in control. Minimum urease activity (250 µg NH4-N g-

1dwt 2h-1) was found at day-7 in 2250 mL ha-1 with a 45 % decline in urease

193

activity followed by (271 µg NH4-N g-1dwt 2h-1) at day-15 in 2250 mL ha-1

showing a 41 % inhibition in urease activity followed by (315 µg NH4-N g-1dwt 2h-

1) at day-15 in 1500 mL ha-1 with a 31 % decline in urease activity as compared to

458 µgNH4-Ng-1dwt 2h-1 that was found in control at day-0 during 2011-12.

Similarly, the interactive effect of treatments and sampling days showed maximum

urease activity (387 µg NH4-N g-1dwt 2h-1) at day-7 in control and the minimum

urease activity (193 µg NH4-N g-1dwt 2h-1) was noticed at day-7 in 2250 mL ha-1

resulting a 50 % decrease in urease activity, followed by 209 µg NH4-N g-1dwt 2h-1

which was found at day-15 in 2250 mL ha-1 indicating a 46 % decline, followed by

(225 µgNH4-Ng-1dwt2h-1) at day-0 in 2250 mL ha-1 resulting a 42% inhibition in

urease activity during 2012-13 as compared to 387 µgNH4-N g-1dwt 2h-1 at day-7

in control (Figure 50).

The interaction between herbicidal treatments and sampling days showed

the highest dehydrogenase activity in control at day-15 (118 µgTPF g-1 24h-1) and

the lowest dehydrogenase activity was observed in 2250 mL ha-1 at day-15 (61.0

µgTPF g-1 24h-1) indicating a 48 % decline followed by 2250 mL ha-1 at day-7 (67

µg TPF g-1 24h-1) indicating a 34 % decline in dehydrogenase activity followed by

(72.0 µgTPF g-1 24h-1) in 1500 mL ha-1 at day-15 showing a 33 % decrease in

dehydrogenase activity during 2011-12 as compared to (118 µg TPF g-1 24h-1)

which was noticed in control at day-30. Similarly, during 2012-13, the interactive

effect of treatments x sampling days showed maximum dehydrogenase activity

(99.2 µg TPF g-1 24h-1) in control at day-7. Minimum activity (42.2 µg TPF g-1

24h-1) was at day-15 in 2250 mL ha-1, followed by 49.8 µg TPF g-1 24h-1 at day-15

194

in 1500 mL ha-1, followed by 51.1 µg TPF g-1 24h-1 at day-7 in 2250 mL ha-1

(Figure 51).


alkaline phosphatase activity (40.3 μg Phenol g-1h-1) at ady-60 in control and least

activity (9.21 μg Phenol g-1h-1) at day-7 in 2250 mL ha-1 indicating a 77 % decline

followed by (13.2 μg Phenol g-1h-1) in 1500 mL ha-1 at day-7 indicating a 67% drop

in alkaline phosphatase activity, followed by (13.7 μg Phenol g-1 h-1) at day-15 in

2250 mL ha-1 showing a 66 % drop in alkaline phosphatase activity as compared to

control at day-60 during 2011-12. The sampling time (days) and treatments

interactive effects showed the maximum alkaline phosphatase activity (38.7 μg

Phenol g-1h-1) at day-15 in control and lowest alkaline phosphatase activity (7.8 μg

Phenol g-1h-1) at day-7 in 2250 mL ha-1 indicating a 80 % less alkaline phosphatase

activity, followed by (11.8 μg Phenol g-1h-1) at day-15 in 2250 mL ha-1 indicating a

69 % decline followed by (17.2 μg Phenol g-1h-1) at day-30 in 2250 mL ha-1

showing a 55% decrease in alkaline phosphatase activity, followed by (19.8 μg

Phenol g-1h-1) at day-30 in 1500 mL ha-1 resulting a 48.8 % decline in alkaline

phosphatase activity during 2012-13 as compared to control at day-15 (Figure 52).

Urease was reported for the first time by Rotini (1935). Urease is engaged

in urea hydrolysis which is added in soil and causes its convertion to ammonium

(NH3) and carbon dioxide (CO2) with concomitant raise in soil pH (Andrews et al.,

1989; Byrens and Amberger, 1989). Generally, the soil urease originate from

microbes (Pollaco, 1977) and plants and exist as intra and extracellular enzyme

(Mobley and Hausinger, 1989). However, urease of microbes or plant origin is

195

rapidly degraded by proteolytic enzyme in soil (Zantua and Bremner, 1977). This

indicates that a considerable part of ureolytic activity in the soil is conceded by

extracellular urease that becomes stable by immobilization with soil organic matter.

Our results demonstrated maximum urease activity in control followed by 375 mL

ha-1 and lowest urease activity in 2250 mL ha-1 during both the years of experiment.

On an average, the 1500 mL ha-1 and 2250 mL ha-1 herbicide doses exhibited a 26

% and 38 % reduction in urease activity as compared to control during both years

in field experiment-2 (heavy-testured soils). This inhibition in urease activity due to

2250 mL ha-1 was due to the lethal impact of high concentration of herbicide

residues on soil microbes that are involved in the production of urease enzyme in

soil. Ingram et al. (2005) observed pronounced decline in Proteus vulgaris

population that librate urease in soil with concomitant decrease in urease activity

due to diazinon and imidacloprid application. Different herbicides (chlorothalanil

and mancozeb) when applied at 10 times higher than recommended rates exhibited

a 37.7% suppression in the activity of urease enzyme, but mancozeb imparted more

toxicity than chlorothalanil (Yu et al., 2011). Chlorpyrifos induced a significant

drop in the urease activity at 100 mg kg-1soil and 500 mg kg-1soil application rates

(Niu et al., 2011). Different studies (Cervelli et al., 1976) detected a 10-30% drop

in urea hydrolysis due to the application of diuron, linuron and monuron herbicides

Contrary to that, Baboo et al. (2013) observed an increase in the activities of

different enzymes (urease and dehydrogenase) due to butachlor, pyrozosulfuron,

paraquot and glyphosate herbicides application. Sampling days resulted in highly

significant effects on urease activity. Highest activity was seen at 60th day and

lowest at 7th day indicating on an average about a 15.2 % drop in the activity of

196

said enzyme at day-7 as compared to day-60 during both years in site-2 (Taunsa)

soil. This might be because of minimum exposure time of herbicide residues to

typical soil microorganisms (producing urease) at day-0 so the activity of urease

was highest at day-0. The lowest activity of urease at day-7 might be because of

extended exposure of herbicide to soil microbial population that release urease

enzyme. With pssage of time the resumption of high activity of urease was due to

the adaption of microbes to the herbicide so their population also recovered. Earlier

studies (Punitha et al., 2012) reported obvious decrease (83%, 71% and 54%) at

10th, 20th and 30th day, respectively in the urease activity due to acetamiprid

treatment. But after day-20, they reported gradual increase in its activity which

reached to its maximum at 60th day. Contrarily, Yang et al. (2006) observed

stimulation of about 47% and 39.3% in urease activity with furadan+ chlorimuron-

ethyl combination, while 21% and 12.7% increase with furadan alone.

Dehydrogenase plays a vital role in the oxidation of organic matter by the

transfer of both electrons and protons from substrates to acceptors. This phnomina

is a part of soil microorganism respiration (Schinner et al., 1995). As these

processes are integral parts of respiration pathway of soil microbial community.

Therefore, studies about the activity of dehydrogenase in soil is inevitable because

it provide indication about soil capability to support different biochemical

processes which are necessary for maintaining soil health and fertility.

Dehydrogenase also acts as marker of microbial redox system and can be used for

the measurement of soil microorganism oxidative activity (Trevors, 1984).

Furthermore, dehydrogenase is often used for the measurement of any interruption


197

caused due the addition of anthopogenic chemicals and heavy metals in soil (Wilke,

1991; Frank and Malkoms, 1993). Dehydrogenase also indicates kind and

importance of pollution in soil e.g the dehydrogenase activity is high in paper and

pulp industry effluents polluted soils (Siddaramappa et al., 1994) but its activity is

low in fly ash polluted soils (Pitchel and Hayes, 1990). Results illustrated

maximum dehydrogenase activity in control, followed by 375 mL ha-1 and lowest

activity in 2250 mL ha-1 during both years in field experiment-2. On the whole,

1500 mL ha-1 and 2250 mL ha-1 herbicidal treatments caused 20.0 % and 28.0 %

reduction during 2011-12 and 27.2 % and 34.6 % decrease in dehydrogenase

activity during 2012-13 as compared to control.

Highest dehydrogenase activity in control was because of no herbicide

interference, while, lowest activity at 2250 mL ha-1 was due negative effect of

herbicide on soil microbial growth causing their mortality with concomitant

decrease in dehydrogenase activity. Allievi and Giglioti (2001) noticed suppression

in amino acid absorption potential of soil microbes due to sulfonyl urea herbicide

with simultaneous decrease in dehydrogenase activity. Contrary to that, He et al.

(2006) did not find any decline in dehydrogenase enzyme activity with

metsulfuron-methyl herbicide treatment. Different studies (Baboo et al., 2013)

found augmentation in dehydrogenase and urease activities due to different rates of

herbicides (pyrozosulfuron 25 g/ha, paraquot 200g/l, butachlor 1kg/ha and

glyphosate 360 g/l). Min et al. (2001) experienced increase in dehydrogenase

activity in soil treated with butachlor. Some reports (Xie et al., 1994) confirmed

obvious decrease in dehydrogenase activity due to bensulfuron-methyl,

198

clobenthiazone and triazophos herbicides. Saha et al. (2012) reported a 55%, 58%

and 59% increase in dehydrogenase activity due to recommended rate, 5FR and

10FR of alachlor herbicide, respectively after 42 days of its application. Various

studies (Radiojevic et al., 2012) reported substantial decrease (42.7%) in

dehydrogenase activity with 3.0 µg g-1soil of nicosulfuron herbicide. Cycon et al.

(2010) found marked increase in dehydrogenase activity by recommended and five

times of recommended rates of applications of diazinin and linuronherbicides in

loamy sand in contrast to sandy loam soil.

Sampling days had statistically significant effect on dehydrogenase activity.

Maximumde hydrogenase activity was at day-60 and minimum activity at day-15

indicating a 23.6% less activity at day-7. This might be because of less contact

duration of herbicide to soil microorganisms at day-0 due to which their population

remain unaffected. But at day-15, because of extended exposure of herbicide to soil

microbes their population declined severely. As dehydrogenase enzyme occur

intercellularly in all microbial cells so the death of microbes ultimately resulted

decreased dehydrogenase activity. Revival of dehydrogenase activity with time was

attributed towards the recovery of microbial population due to their adaption to

herbicide. Vekova et al. (1995) observed recovery of Agrobacterium radiobacter in

herbicides contaminated soils with time due to decrease in herbicide persistence.

Mayanglambam et al. (2005) reported a 30% decline in dehydrogenase activity

after 15 days of quinalphos application and the activity of dehydrogenase restored

after 90 days because of adoption of soil microorganisms to counteract the impact

of applied chemical.

199

The alkaline phosphatase play an essential role in phosphorus cycling as it

is confirmed that they are extremely correlated to phosphorus sress in soil (Skujiņš

and Burns, 1976). In case of any signal of phosphorus stress in soil, the secretion

of phosphatase from the roots of plants increased in order to increase phosphate

immobilization and solubilization, therefore, helping the plants to overcome the

phosphorus stressed conditions ( Karthikeyan et al., 2002; Versaw and Harrison,

2002; Mudge et a.,l 2002). Phosphatases convert organic forms of phosphorus into

inorganic form by hydrolysis (Monkiedje et al., 2002). Phosphatase activity is

influenced by many factors e.g soil texture, inhibitors presence and soil microbial

diversity. In present study significant inhibition in alkaline phosphatase activity

was observed due to buctril super herbicide application. Highest alkaline

phosphatase activity was found in control, followed by 375 mL ha-1 and loweat

activity in 2250 mL ha-1 Maximum alkaline phosphatase activity in control was

attributed towards the freedom of soil mroorganisms from herbicide residues.

Highest drop in alkaline phosphatase activity in 2250 mL ha-1 was due to high

concentration of herbicide residues hampering the growth of those soil microbes

which release phosphatase enzymes. Tu et al. (1981) noticed decrease in

phosphatase activity due to 2, 4-D herbicide (10 mg /kg soil) and found that this

decline was attributed toward intervention of herbicide in release of p-nitrophenol

from p-nitrophenyl phosphate. The other reason might be due to herbicide binding

on the active sites of alkaline phosphatase, therefore, preventing its attachment to

substrate. Weaver et al. (2004) reported inactivation of most of soil enzymes

because of herbicide attachment on the active site of enzyme and thus preventing

substrate attachment to the enzyme. Sannio and Gainfreda (2001) reported obvious

200

decline (98%) in alkaline phosphatase activity with the glyphosate herbicide. Some

studies reorted increase in acid phosphatase activity but decrease in alkaline

phosphatase activity due to mefenoxam and metalaxyl fungicides (Monkiedje et al.,

2002). Opposite to our results, Das et al. (2003) observed increase in phosphate

solubling microbes due to oxyfluorfen herbicide (0.12 kg a.i ha-1). These microbes

(that produce phosphatase enzyme) used it as a source of carbon with concomitant

increase in alkaline phosphatase activity. Sampling days exhibited statistically

significant effect on alkaline phosphatase activity. The activity of alkaline

phosphatase was highest at day-0 and day-60 and lowest at day-7. Highest activity

at day-0 was because of limited exposure of phosphatse producing

microoorganisms to herbicide and at day-60 high activity was because of

adaptability of microbes to the herbicide. Similar tendency was reported in

different studies. Myanglambam and Singh (2005) found decrease in alkaline

phosphatase and urease activities with quinalphofos treatment during first week,

but after that they found recovery in the activity of these enzymes. Qian et al.

(2007) reported inhibition in the activities of urease and alkaline phosphatase

enzymes during initial period of application but the activities of these enzymes

showed recovery with time. Researchers, Punitha et al. (2010) observed a 90%,

81% and 74% decline in alkaline phosphatase at 10th 20th and 30th days,

respectively due to acetamiprid application. Different studies reported diverse

effect of chlorpyriphos on alkaline phosphatase activity. Rani et al. (2008)

observed inhibition in alkaline phosphatase activity due to chlorpyriphos, but

Madhury and Rangaswamy (2002) noticed increase in the acivity of said enzyme

due to 5kg/ha rate of chlorpyriphos.

201

4.3.12 Correlation Between Soil Enzymes Activity and Buctril Super

Herbicide

On the basis of results a strong negative correlation (-0.71) was observed

between urease activity and bromoxynil residues, dehydrogenase activity and

bromoxynil residues (-0.71). As well as the activity of alkaline phosphatase and

bromoxynil herbicide were negatively correlated with each other (-0.73).

4.3.13 Nitrate Nitrogen under Different Treatments of Buctril Super


The data pertaining to the buctril super herbicide impacts on nitrate nitrogen

revealed that nitrate nitrogen was statistically significantly different in all

herbicidal treatments. Highest nitrate nitrogen was observed in control (41.5 µg g-

1soil), followed by 375 mL ha-1 (35.5 µg g-1soil), 750 mL ha-1 (31.3 µg g-1soil),

1500 mL ha-1 (29.7 µg g-1soil) and lowest nitrate nitrogen (28.4 µg g-1soil) was

observed in 2250 mL ha-1 during 2011-12. Whereas, maximum nitrate nitrogen

(39.8 µg g-1soil) was found in control, followed by 375 mL ha-1 (36.1 µg g-1soil),

followed by 750 mL ha-1 2 (33.4 µg g-1soil), followed by 1500 mL ha-1 (30.1 µg g-

1soil) and minimum nitrate nitrogen (28.6 µg g-1soil) was observed in 2250 mL ha-1

during 2012-13. Overall, the 375 mL ha-1, 750 mL ha-1, 1500 mL ha-1 and 2250 mL

ha-1 herbicide treatments caused a 14.4 %, 24.5 %, 28.4 % and 32 % reduction in

nitrate nitrogen, respectively, as compared to that of control during 2011-12. In

2012-13, the herbicide treatments viz. 375 mL ha-1, 750 mL ha-1, 1500 mL ha-1 and

2250 mL ha-1 exhibited a 9.2 %, 16 %, 24.3 % and 28 % decrease in nitrate

nitrogen respectively, as compared to that of control in field experiment-2

202

Table 4.13: Soil enzymes activity showing extended decline in heavy-textured soil due to different treatments of buctril super

herbicide and sampling day because of more persistence of herbicide in this soil

Factors Urease activity

2011-12 2012-13

Dehydrogenase activity

2011-12 2012-13


2011-12 2012-13

(µg NH4-N g-1dwt 2h-1) (µg TPF g-1 24h-1) (μg Phenol g-1 h-1)

Treatments

Control

456 A

383 A

114 A

97.9 A 40.0 A 38.3 A

375 mL ha-1 429 B 356 B 103 B 85.3 B 27.5 B 26.0 B

750 mL ha-1 385 C 322 C 98 C 77.5 C 23.8 C 22.9 C

1500 mL ha-1 336 D 279 D 91 D 71.2 D 20.5 D 19.0 D

2250 mL ha-1 293 E 231 E 82 E 64.0 E 17.2 E 15.5 E

LSD 4.77 6.46 1.79 2.26 0.62 0.52

Sampling days

0 380 C 316 C 102 B 85.8 B 26.7 B 25.3 B

7 348 E 293 E 89 C 74.2 D 20.6 D 19.8 D

15 367 D 305 D 84 D 64.0 E 24.4 C 22.9 C

30 395 B 323 B 103 B 81.2 C 26.4 B 24.8 B

60 410 A 334 A 110 A 90.7 A 30.8 A 28.9 A

LSD 4.77 6.46 1.79 2.26 0.62 0.52

Analysis of variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

203

150

250

350

450

550

0 7 15 30 60 0 7 15 30 60

Sampling days

Ure

ase

activ

ity

(µg

NH4

-N g

-1 d

wt 2

h-1

)


2011-122012-13

Figure 50: Interactive effect of herbicide treatments and sampling days on urease activity in heavy-textured

soils showing suppression in urease activity and even it could not recovered to its intial level upto day-60 due

to high persistence and low degradation of herbicide in these soils

204

30

60

90

120

150

0 7 15 30 60 0 7 15 30 60

Sampling days

Deh

ydro

gena

se a

ctiv

ity

(µg

TP

F g-1

24

h-1)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 51: Interactive effect of herbicide treatments and sampling days on dehydrogenase activity in

heavy-textured soils showing suppression in its activity and even it could not recovered to its intial level


205

5

15

25

35

45

0 7 15 30 60 0 7 15 30 60

Sampling days

Alk

alin

e ph

osph

atas

e ac

tivity

(µ

g ph

enol

g-1 h

-1)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 52: Interaction of herbicide treatments and sampling days on alkaline phosphatase activity in heavy-

Textured soils showing suppression in its activity and even it could not recovered to its intial level upto

day-60 due to high persistence of herbicide in these soils

206

(heavy-textured soil). Maximum nitrate nitrogen was noticed at day-0 (36.9 µg g-1

soil) and minimum was at day-60 (32 µg g-1soil) indicating a 13.27 % inhibition in

nitrate nitrogen between the two during 2011-12. Similarly, during 2012-13, the

nitrate nitrogen was maximum at day-0 (37.9 µg g-1soil) and minimum at day-7

(31.7 µg g-1soil) indicating a16 % decline in nitrate nitrogen at day-7 as compared

to day-0 (Table 4.14).

4.3.14 Olsen-P under Different Treatments of Buctril Super Herbicide in

Heavy-textured Soil

The data regarding the impacts of herbicide (buctril super) on Olsen-P

showed the highest Olsen-P in control (16.4 µg g-1soil), followed by 375 mL ha-1

(15.1 µg g-1soil), 750 mL ha-1 treatment (14.5 µg g-1soil), 1500 mL ha-1 (14.6 µg g-

1soil) and least Olsen-P (13.9 µg g-1soil) was observed where 2250 mL ha-1 dose of

herbicide was applied during 2011-12. Whereas in 2012-13, the maximum Olsen-P

(18.2µg g-1soil) was found in control, followed by 375 mL ha -1 (17.4 µg g-1soil),

750 mL ha-1 (16.2 µg g-1soil), followed by 1500 mL ha-1 (15.8 µg g-1soil) and

minimum Olsen-P (14.2 µg g-1soil) in 2250 mL ha-1. In general, 375 mL ha-1, 750

mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 herbicidal treatments exhibited a 7.9 %,

11.6 %, 11.0 % and 15 % decrease in Olsen-P respectively, as compared to that of

control during 2011-12. During 2012-13 herbicide treatments viz. 375 mL ha-1, 750

mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 caused a 4.4 %, 11.0%, 13.2 % and 22.0

% decline in Olsen-P respectively, as compared to that of contrl in field

experiment-2 (Table 4.14). Sampling days showed statistically significant impact

on Olsen- P (P ≤ 0.05). Maximum Olsen-P was at day-0 (15.3 µg g-1soil) and

207

y = -327.33x + 413.98

R2 = 0.9243

150

200

250

300

350

400

450

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70


(µg

NH4

-N g

-1 d

wt 2

h-1

)

Urease Linear (Urease)

Figure 53: Buctril super herbicide and urease activity showing negative correlation due to toxic effect of


208

y = -64.904x + 101.74

R2 = 0.5374

40

60

80

100

120

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70


(µg

TP

F g-1

24h-1

)

DHA Linear (DHA)

Figure 54: Buctril super herbicide and dehydrogenase activity showing negative correlation due to toxic


209

y = -82.484x + 78.236

R2 = 0.5281

20

40

60

80

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


(µg

phen

ol g-1

24

h-1)

Phosphatase Linear (Phosphatase)

Figure 55: Buctril super herbicide and alkaline phosphatase activity showing negative correlation due to toxic effect of


210

minimum at day-7 (14.2 µg g-1soil), indicating a 7.2 % inhibition in Olsen-P at day-

7 as compared to day-0 during 2011-12. Similarly, Olsen-P was highest at day-0

(17.2 µg g-1soil) and lowest at day-7 (15.8 µg g-1soil), indicating a 8.1 % decline in

Olsen-P at day-7 as compared to day-0 during second year (2012-13).

4.3.15 Total Organic Carbon under Different Treatments of Buctril Super


The investigations in respect of the impacts of buctril super herbicide on

total organic carbon revealed the highest TOC in control ( 5.72g kg-1soil), followed

by 5.57 g kg-1soil which was found in 375 mL ha-1, followed by 750 mL ha-1 (5.52

g kg-1soil) and 5.45 g kg-1soil TOC was observed in 2250 mL ha-1 during 2011-12.

In the same way, during 2012-13, the maximum TOC was found in control (5.08 g

kg-1soil) followed by (5.06g kg-1soil) in 3750 mL ha-1, followed by 4.98 g kg-1soil

in 750 mL ha-1 while 4.95 g kg-1soil TOC was observed in 2250 mL ha-1. As a

whole, the 750 mL ha-1, 1500 mL ha-1 and 2250 mL ha-1 caused a 2.62%, 3.49%

and 4.7% reduction in TOC respectively, as compared to that of control during

2011-12. While, during 2012-13 herbicide doses viz. 375 mL ha-1, 750 mL ha-1 and

1500 mL ha-1 caused a 0.39 %, 1.96% and 2.6% decrease in TOC respectively, in

contrast to control in field experiment-2 (Table 4.14). Maximum TOC (5.71 g kg-

1soil) was noticed at day-0 and day-60 while minimum TOC (5.24 g kg-1soil) at

day-7, indicating a 8.23 % inhibition in TOC at day-7 as compared to day-0 and

day-60 during 2011-12. Likewise, in 2012-13, the TOC was maximum at day-30

(5.11g kg-1soil) and minimum at day-7 (4.84 g kg-1soil), indicating a 5.28 % decline

in TOC at day-7 as compared to that of day-30.

211

The interaction ofsampling days and herbicide treatments revealed

maximum nitrate nitrogen at day-30 and day-60 in control which was 42.0μg g-

1soil. Minumum nitrate nitrogen (26.2 μg g-1soil) at day-60 in 2250 mL ha-1,

indicating a 38% decline in nitrate nitrogen, followed by 1500 mL ha-1 (28.2 μg g-

1soil) at day-30 indicating a 32.8% decline, followed by 750 mL ha-1 (29.3 μg g-

1soil) at day-15, indicating a 30.2 % drop, followed by 375 mL ha-1 (34.7 μg g-1soil)

at day-7 showing a 17.38% decline, followed by 1500 mL ha-1 (35.8 μg g-1soil) at

day-0 with a 14.76% drop in nitrate nitrogen as compared to control at day-30 and

day-60 in 2011-12. In second year (2012-13), the interactive effect of treatment

and sampling time (days) showed maximum nitrate nitrogen in control at day-60

(43.5 μg g-1soil) and minimum nitrate nitrogen was recorded on day-7 in 2250 mL

ha-1 (25.0 μg g-1soil), indicating a 42.5% decline, followed by 28.1 μg g-1soil at

day-15 in 2250 mL ha-1, indicating a 35.4 % decline, followed by 31.5 μg g-1soil

which was observed at day-7 in 750 mL ha-1 showing a 27.5% decrease, followed

by (35.8 μg g-1 soil) at day-7 in 375 mL ha-1 resulting a 17.7% decline in nitrate

nitrogen as compared to control at day-60 (Figure 56).

The sampling days and herbicide treatments interactive effects revealed

highest Olsen-P (16.5 μg g-1 soil) at day-30 and day-60 in control and the lowest

Olsen-P (12.6μg g-1 soil) at day-7 in 2250 mL ha-1, indicating a 23.6% decline in

Olsen-P and it was 13.5 μg g-1 soil in 1500 mL ha-1 at day-7, indicating a 18.2 %

drop, followed by (15.1μg g-1 soil) at day-60 in 375 mL ha-1 showing a 8.48% drop

in Olsen-P during 2011-12 as compared to (16.4μg g-1 soil) which was found in

control at day-30 and day-60. The interaction of treatment of herbicides and

sampling time showed the maximum Olsen-P in control at day-7(18.3μg g-1 soil),

212

whereas, minimum Olsen-P at day-7 in 2250 mL ha-1 (13.3μg g-1 soil) resulting a

27.32% decline in Olsen-P, followed by 17.2μg g-1soil at day-0 in 750 mL ha-1

indicating a 19.67 % decline, followed by 16.1μg g-1soil at day-30 in 1500 mL ha-1

showing a 12.2% decrease in Olsen-P as compared to 8.7μg g-1 soil which was

found in control at day-0, 30 and 60 during 2012-13 in field experiment-2 (Figure

57).

The sampling time and treatments interaction described maximum total

organic carbon at ady-30 in 2250 mL ha-1 (6.05g kg-1 soil) and minumum TOC

(4.75g kg-1 soil) at day-7 in 2250 mL ha-1 indicating a 21.48% decline in TOC. It

was 5.0g kg-1 soil in 2250 mL ha-1 at day-15 indicating a 17.35 % drop in TOC,

followed by 5.05 g kg-1 soil at day-15 in 2250 mL ha-1 showing a 16.52 drop in

TOC, followed by 5.20 g kg-1 soil at day-15 in 1500 mL ha-1 showing a 14.0% drop

in TOC, followed by 5.35 g kg-1 soil at day-15 in 750 mL ha-1 with 9.91 % decline

in TOC during 2011-12 as compared to 6.05 g kg-1 soil which was found in 2250

mL ha-1 at day-30. The interactive effect of treatment and sampling days showed

maximum TOC (5.35g kg-1 soil) in 2250 mL ha-1 at day-30. Whereas, least TOC

(4.55g kg-1 soil) was recorded on day-7 in 2250 mL ha-1 resulting a 14.95% decline

in TOC, followed by (4.75 g kg-1 soil) at day-15 in 1500 mL ha-1 indicating a 11.21

% decline, followed by (4.80 g kg-1 soil) at day-7 in 1500 mL ha-1 showing a

10.28% decrease in TOC, followed by 4.85 g kg-1 soil at day-7 in 750 mL ha-1

resulting a 9.34 % decline in TOC followed by 4.95 g kg-1 soil at day-30 in 750 mL

ha-1, resulting a 7.47 % decline in TOC during 2012-13 as compared to that of

5.35g kg-1 soil which was recorded in 2250 mL ha-1 at day-30 (Figure 58)

213

Nitrification is a two way process involving ammonium oxidizers

(Nitrosomonas sp.) and nitrite oxidizers (Nitrobacter sp.) in order to produce nitrate

(NO3) from ammonium (NH4) because most of the plants use nitrate rorm of

nitrogen for their growth. Nitrification helps in soil acidification by releasing

hydrogen ions (H+). The process of microbial oxidation lead to the formation of

nitric acid (HNO3) which aid in acidification of soil and when nitric acid dissociate

into NO3- and H+ ions this will increase acidification too (Van Miegroet and Cole,

1984). Our results confirmed maximum nitrate nitrogen in control followed by 375

mL ha-1 and least nitrate nitrogen in 2250 mL ha-1 during both years in field

experiment-2. About 36% and 44% decline in NO3-N due to 1500 mL ha-1 and

2250 mL ha-1, respectively was observed during both years. This enormous decline

in NO3-N was because of high susceptibility of autotrophic nitrifiers to elevated

dosage of herbicide. Scientists (Allievi and Giglioti, 2001) reported negative effect

of sulfonyl urea herbicide on amino acid assimilation ability of autotrophic

nitrifiers. Hernandez et al. (2001) reported suppression in ammonium oxidizing

bacteria (AOB) and ammonium oxidizing archaea (AOA) due to simazine

herbicide (50 µg g-1soil) with concomitant inhibition in nitrification process which

in turn resulted decrease in nitrate nitrogen. Contrary to that, Kanungo et al., (1995)

reported increase in the population of Azotobactor and Azospirillum due to repeated

use of carbofuron while increase in the population of anaerobic nitrogen fixing

bacteria due to anilofos herbicide. Chang et al. (2011) observed decrease in the

population of ammonium oxidizing bacteria by combined mixture of herbicides

(atrazine, dicamba-4, flumutoron, metolachlor and sufentrazone) using different

concentration (0, 10,100 and 1000 ppm). Whereas, sme studies (Li X et al. 2008)

214

reported stimulation in ammonium oxidisizers population due to acetachlor

herbicide and pronounced nitrification (Rangaswamay et al. 1992) by azospirillum

because of cypermethrin or fenvalerate treatment. Das and Mukherjee (1998)

reported increase in microbial activity and nutrient mineralization by the

application of phorate (1.5 Kg a.i ha-1) and carbofuron (1.0 Kg a.i ha-1).

Sampling days showed statistically significant effect on nitrate nitrogen.

Maximum NO3-N was noticed at day-0 and minimum was found day-15 but after

day-15 it showed increasing trend during both years in field experiment-2 (heavy-

textured soil) but even at 60th day NO3-N could not reached to its original level.

High contents of nitrate nitrogen at day-0 were because of less exposure of

herbicide to nitrifying bacteria while obvious decline at day-15 was due to more

exposure time of herbicide to soil microbes. Increasing trend in NO3-N after day-15

was because of reinstatement of nitrifiers by developing resistance gainst herbicide.

Ismail et al. (1995) noticed decline in bacteria and fungi population due to

glufosinate-ammonium (100ppm) during initial days but later on they observed

increasing trend in their population. The reason for non recovery of NO3-N to its

original level upto day-60 was because of presence of significant quantity of

herbicide residues at day-60 in field experiment-2.

Phosphorus is an essential plant nutrient which make up of about 0.2% dry weight

of plant (Schachtman, 1998). It is a fundamental part of phospholipids, nucleic acid

and proteins. It control different enzmymes activities and help in regulating

different metabolic processes (Theodorou and Plaxton, 1993). The uptake of

phosphorus from the soil is carried out as orthophosphate due high affinity of

215

trnasporters present in plant roots which act in response to phosphorus deficiency

(Bucher, 2007). Soil microorganisms enhance the ability of plants to get

phosphorus from soil through different mechanisms e.g changing sorption

equilibria that can result in enhanced transfer of orthophosphste ion in soil solution,

by stimulating roots growth, by producing harmones or through facilitating the

mobility of organic phosphorus by microbial decomposition (Seeling and Zasoski,

1993) or through induction of different metabolic processes which help in

solubilizing inorganic phosphorusfrom soil (Ricardson et al., 2011). Present study

showed maximum Olsen-P in control, followed by 375 mL ha-1 and least Olsen-P in

2250 mL ha-1 during both experimental periods in field experiment-2. In general,

2250 mL ha-1 caused a 15% and 22.6 % reduction in Olsen-P during first and

second year, respectively as compared to control. Because of high sensitivity of

phosphate solublizers to herbicide residues their population severely decreased in

control consequently Olse-P drop down. Significant drop in overall microbial

population has already been confirmed in our present study. Ahmad and Khan

(2010) reported a 72 %, 91% and 94% suppression in phosphorus solublizing

activity of Enterobacter asburiae as compared to control due to 40 µg/L, 80 µg/L

and 120 µg/L concentration of quizalafop-p-ethyl, respectively. This reduction in

Olsen-P might be due to the suppression in fungi population by the herbicide

residues which is confirmed from our field experiment results. Since fungi are more

efficient in sloublising precipitated calcium phosphate and rock phosphate than

bacteria so due to their mortality Olsen-P decreased significantly. Kucey (1983)

reported more efficiency of fungi than bacteria in solubilizing precipitated calcium

phosphate as well as rock phosphatae and observed positive correlation between the

216

population of phosphate solubilizing fungi and available phosphorus in soil.

Contradictory to that, Das et al. (2003) observed stimulation in the population of

phosphate solubilizers and increased phosphorus availability in soil. Defo et al.

(2011) observed increase in phosphorus availability with endosulfan (1.5 mL ha -1)

during initial 30- days but afterwards decrease in phosphorus availability was

found. While some studies (Sarnaik et al., 2006) reported no significant change in

the population of phosphate solubilizing bacteria and rhizobia in comparison to

control by the application of phorate, carbofuron, carbosulfuron, thiomethaxan,

amidacloprid, chlorpyriphos and monocrotophos application. Sampling days

showed maximum Olsen-P at day-0 and minimum at day-7, indicating a 7.5 %

inhibition in Olsen-P at day-7 as compared to day-0 during both years in site-2

(heavy-textured soil). Maximum Olsen-P at day-0 was due to short duration

esposure of herbicides to phosphate solublizers. But at day-15 the Olsen-P was

lowest because of toxicity of herbicide residues to phosphate solubilizing microbes

with concomitant decrease in Olsen-P.

Organic Carbon (TOC) is the major source of energy for soil microbes. Soil

organic carbon helps in improving the physical characteristics of soil. It enhances

the water holding capacity and cation exchange capacity of light textured soils and

aids in binding the particles into aggregates and contributes towards structural

stability of clay. It has the ability of holding major proportion of nutrients and made

them available to plants. It also act as buffering agent in soil and resist changes in

soil pH (Leu, 2007). In present study about 2.62% drop in total organic carbon due

to 375 mL ha-11, 3.49% due to 750 mL ha-1 and 4.71% drop due to 1500 mL ha-1

http://en.wikipedia.org/wiki/Cation_exchange_capacity

217

Table 4.14: Decrease in Nitrate nitrogen, Olsen-P and total organic carbon in heavy-textured soil due to different

treatments of buctril super herbicide and sampling days because of more persistence of herbicide in this soil

Factors Nitrate nitrogen Olsen-P Total Organic carbon

2011-12 2012-13 2011-12 2012-13 2011-12 2012-13

------------------------(µg g-1 soil)---------------------------- --------(g kg-1 soil)--------

Treatments

Control

41.5 A

39.8 A

16.4 A

18.2 A

5.72 A

5.08 A

375 mL ha-1 35.5 B 36.1 B 15.1 B 17.4 B 5.57 AB 5.06 A

750 mL ha-1 31.3 C 33.4 C 14.5 C 16.2 C 5.52 AB 4.98 A

1500 mL ha-1 29.7 D 30.1 D 14.6 BC 15.8 C 5.45 B 4.95 A

2250 mL ha-1 28.4 E 28.6 E 13.9 D 14.2 D 5.45 B 4.98 A

LSD 1.28 0.489 0.022 0.023

Sampling days

0 36.9 A 37.9 A 15.3 A 17.2 A 5.71 A 5.07 AB

07 32.3 B 31.8 C 14.2 C 15.8 D 5.24 B 4.85 B

15 32.4 B 32.5 BC 14.7 B 16.0 CD 5.40 B 4.94 AB

30 32.7 B 32.9 B 15.0 AB 16.2 BC 5.65 A 5.11 A

60 32.0 B 32.8 BC 15.2 AB 16.5 B 5.71 A 5.08 AB

LSD 1.28 0.489 0.022 0.023

Analysis of variance


Treatments (T) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

Sampling days (D) <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

218

20

30

40

50

0 7 15 30 60 0 7 15 30 60

Sampling days

Nitr

ate

nitr

ogen

(µ

g g-1

soi

l)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 56: Interactive effect of herbicide treatments and sampling days showing suppression in nitrate nitrogen

even upto day-60 due to prolonged persistence of herbicide in heavy-textured soils

219

12

14

16

18

20

0 7 15 30 60 0 7 15 30 60

Sampling days

Ols

en-P

(µ

g g-1

soil)


1500 mL ha-1 2250 mL ha-1

2011-122012-13

Figure 57: Interactive effect of herbicide treatments and sampling days showing suppression in Olsen-P

even upto day-60 due to prolonged persistence and toxicity of herbicide in heavy-textured soils

220

4

5

6

7

0 7 15 30 60 0 7 15 30 60

Sampling days

Tot

al o

rgan

ic c

arbo

n (g

kg-1

soi

l)


1500 mL ha-1 2250 mL ha-1

2011-122012-13

Figure 58: Interactive effect of herbicide treatments and sampling days showing suppression in total organic

carbon upto day-60 due to prolonged persistence and toxicity of herbicide in heavy-textured soils

221

and 2250 mL ha-1 was found during 1st year and no significant change in total

organic carbon due to herbicide application during 2nd year in field experiment-2

(heavy-textured soi) was observed. This inhibition in total organic carbon due to

herbicide application was because of phonomina of co-metabolism in which one

compound’s degradation depends on the existence of other compound. Sukul et al.

(2006) experienced reduction in organic matter due metalaxyl herbicide and

reported that this dercease in organic carbon was the result of co-metabolism

phenomina. Similarly, Baboo et al. (2006) observed 2.49% and 2.23% decrease in

soil organic carbon at 7th and 28th day, respectively with pyrazosulfuron herbicide,

whereas 1.90%, 2.47% and 2.32 % drop in soil organic carbon at 7th, 21st and 28th

day, respectively with glyphosate herbicide, but they observed enhancement in

organic carbon due to paraquot treatment up to 14th day (2.47%), followed by

decrease of about 2.15% at 21st day. Herbicide caused lysis of microbial cells with

concmitant decrease in their population and the remaining microbial population

increased the rate of decomposition of organic matter for obtaining quick energy

for their survival which in turn result loss of carbon dioxide leading to decline in

organic carbon. Ayansina and Oso (2006) reported a 13 %, 30 % and 11 %

decrease in organic matter contents by combined mixture of two herbicides

(atrazine + metolachlor) during 1st, 4th and 6th weeks of herbicide application,

respectively as compared to control. Defo et al. (2011) reported signifiacnt

decrease in organic carbon due to endosulfan application (100 µg g -1 soil) after 60

days. The death of weeds due to herbicide application might be the other reason of

organic matter decrease because organic matter comprises of both dead animal and

plant residues. Sebiomo et al. (2011) reported a 35 %, 76 %, 20.6 % and 22 %

222

decrease in organic matter due to field application rates of atrazine, glyphosate,

paraquot and primeextra herbicides. Plant roots release auxin and gebrilin in soil

that contribute towards increase in organic matter so death of weeds resulted

decline in organic matterl. Maximum TOC was noticed at day-0 and day-60 and

minimum TOC at day-7 indicating a 8.23 % inhibition in TOC at day-7 as

compared to day-60 during 2011-12.

Whereas, TOC was maximum at day-30 and minimum at day-15 indicating

a 3.32 % decline in TOC at day-15 as compared to day-30 in site-2 (Taunsa) during

2nd year. This decrease in TOC at day-7 in first year and at day-15 during 2nd year

was due to herbicidal mortaility of soil microbes. As our results showed severe

decrease in microbial population due to bromoxynil herbicide treatment. Due to

positive correlation (Taiwo and Oso, 1997) between the population of soil

microorganisms and soil organic matter the death of soil microbes resulted decrease

in soil organic carbon at day-7 and day-15 during 2011 and 2012, respectively. But

due to the recovery of microbial population after their adaption to herbicide their

population recovered hence soil organic matter increased.

4.3.16 Correlation of Buctril Super Herbicide with Nitrate Nitrogen, Olsen-P

and Total Organic Carbon in Heavy-textured Soil

Above results depicted that the nitrate nitrogen was negatively but strongly

correlated (-0.66) with bromoxynil residues. Olsen-P revealed negative but strong

correlation with bromoxynil residues (-0.76). Similarly, Total organic carbon also

indicated negative but weak correlation (-0.30) with bromoxynil.

223

4.3.17 Recovery of Bromoxynil Residues after Buctril Super Herbicide

Application in Heavy- textured Soil

The highest residues recovered were 3.31 mg kg-1 from 2250 mL ha-1,

followed by 3.23 mg kg-1 in 1500 mL ha-1, followed by 1.34 mg kg-1 in 750 mL ha-

1 and lowest residues found were 0.81 mg kg kg-1 in 375 mL ha-1during 2011-12.

Whereas, highest residues recovered were 3.29 mg kg-1 from 2250 mL ha-1,

followed by 2.22 mg kg-1 in 1500 mL ha-1, followed by 1.44 mg kg-1 in 750 mL ha-

1 and lowest residues found were 0.72 mg kg-1 in 375 mL ha-1in 2012-13.

Sampling days showed maximum recovery of residues at day-0 (1.66 mg

kg-1), followed by day-7 (1.58 mg kg-1), day-15 (1.55 mg kg-1), followed by day-30

(1.48 mg kg-1), followed by day-60 (1.43 mg kg-1) at day-60 during 2011-12.

Whereas, in 2012-13, sampling days showed maximum recovery of residues at day-

0 (1.62 mg kg-1) followed by 1.58 mg kg-1 at day-7 followed by 1.53 mg kg-1 at

day-15 followed by 1.48 mg kg-1 at day-30 and 1.43 mg kg-1 at day-60 (Table 4.9).

The interactive effect of sampling days and treatments showed the highest

recovery of residues at day-0 in 2250 mL ha-1 (3.55 mg kg-1), followed by 3.36 mg

kg-1at day-7 in 2250 mL ha-1, followed by 3.31 mg kg-1 at day-15 in 2250 mL ha-1,

followed by 3.22 mg kg-1 in 2250 mL ha-1 at day-30, followed by 3.13 mg kg-1 at

day-60 in 2250 mL ha-1, followed by 2.39 mg kg-1 at day-0 in 1500 mL ha-1,

followed by 2.28 mg kg-1 at day-7 in 1500 mL ha-1, followed by 2.26 mg kg-1 in

1500 mL ha-1 at day-15, followed by 2.11 mg kg-1 at day-30 in 1500 mL ha-1,

followed by 2.10 mg kg-1 day-60 in 500 mL ha-1, followed by 1.49 mg kg-1 in 750

224

mL ha-1day-0, followed by 1.41 mg kg-1 in 750 mL ha-1 at day-7 and lowest

residues recovered were (0.75 mg kg-1) at day-60 in 375 mL ha-1 in 2011-12. In

2012-13, the interactive effect of sampling days and treatments showed maximum

recovery of bromoxynil residues in 2250 mL ha-1 (3.48 mg kg-1) at day-0, followed

by 3.36mg kg-1 at day-7 in 2250 mL ha-1, followed by 3.29 mg kg-1 at day-15 in

2250 mL ha-1, followed by 3.21 mg kg-1 in 2250 mL ha-1 at day-30, followed by

3.13 mg kg-1 at day-60 in 2250 mL ha-1, followed by 2.33 mg kg-1 at day-0 in 1500

mL ha-1, followed by 2.28 mg kg-1 at day-7 in 1500 mL ha-1followed by 2.21mg kg-

1 in 1500 mL ha-1at day-15, followed by 2.17 mg kg-1 at day-30 in 1500 mL ha-1,

followed by 2.10 mg kg-1 at day-60 in 1500 mL ha-1 followed by 1.53 mg kg-1 in

750 mL ha-1day-0 followed 1.50 mg kg-1 in 750 mL ha-1 at day-7 and lowest

residues recovered were (0.65 mg kg-1) at day-60 in 375 mL ha-1 in field

experiment-2 (heavy-textured soil) (Figure 62).

4.3.18 Weeds Control Efficiency of Buctril Super Herbicide in Heavy-

Textured Soil

The herbicide was applied using knapsack sprayer 3 weeks (21 days) after

sowing when the crop reached to 5-6 leaf stage. At that time the weeds present in

the field were: Chronopus didymus (Jangli haloon), Rumex dentatus (Jangli

palak), Chenopotium album (bathu), Vicia sativa (Revari), Fumaria officinalis

(Shahtra), Lycopsis arvensis L. (Dhodak), Medicago polimorpha (Mana),

Convolvulus arvensis (Lehli) and almost all the above mentioned weeds were in

seedling stage.

The analysis of variance data showed statistically significant effect of

225

y = -18.963x + 37.311

R2 = 0.4339

10

20

30

40

50

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


NO

3-N

( µ

g g

-1 s

oil)

NO3-N Linear ( NO3-N )

Figure 59: Buctril super herbicide and nitrate nitrogen showing negative correlation due to toxic


226

y = -5.3832x + 16.731

R2 = 0.5793

10

12

14

16

18

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


Ols

en-P

(p

pm

)

Olsen "P" Linear (Olsen "P" )

Figure 60: Buctril super herbicide and Olsen-P showing negative correlation due to toxic effect


227

y = -0.5238x + 5.3857

R2 = 0.0891

4

5

6

7

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7


TO

C (

g k

g-1)

TOC Linear (TOC )

Figure 61: Buctril super herbicide and total organic carbon showing negative correlation due to toxic


228

0.0

1.5

3.0

4.5

0 7 15 30 60 0 7 15 30 60

Sampling days

Bro

mox

ynil

redi

dues

con

cent

ratio

n

(m

g kg

-1)


1500 mL ha-1 2250 mL ha-1

2011-12 2012-13

Figure 62: Bromoxynil residues concentration in soil versus time under different herbicide treatments in

heavy-textured soil showing residues even upto day-60 due to prolonged persistence of herbicide

229

different herbicidal treatments on weed control. Weed control efficiency data is

given in (Table 4.15) .Treatment means comparison revealed the maximum weed

control efficiency by 2250 mL ha-1 (76%), followed by 74% by 1500 mL ha-1, and

followed by 71% by 750 mL ha-1and lowest 22% by 375 mL ha-1 in 2011-12.

Similarly, in second year (2012-13), the analysis of variance data showed

statistically significant effect of different herbicide doses on weed control

efficiency. Comparison of treatment means reveal maximum weed control

efficiency (74%) by 2250 mL ha-1, followed by (72%) by 1500 mL ha-1, followed

by 69% by 750 mL ha-1 and lowest weed control efficiency (21%) by 375 mL ha-1,

while, in control it was 0. On the basis of above results it is evident that 750 mL

ha-1 treatment had effectively controlled the weeds. However, higher rate of this

herbicide showed minute increase in weed control efficiency. But that increase

was not cost effective.

Billions of peoples in the world are using wheat as a staple food (Fischer,

2007). After maize, the wheat ranks second in the world (FAO, 2005). The weeds

reduce wheat yield by depriving it from essential nutrients, water space, and light

(Grichar, 2006; Zand and Soufizadeh, 2004). Baghestani et al. (2005) observed

25% decrease in wheat yield due to weeds infestittion in wheat fields. Out of

different weeds, the broadleaved weeds are more injurious because they occupy

more space and need more nutrients and water for their growth. Our results are in

agreement with Khan et al. (1999). Different researchers, Marwat et al. (2008)

during comparison of weed control efficiency of various herbicides (aid, buctril

super, topic, puma super, isoproturon) found 85 % weed control efficiency through

230

isoproturon and 77.3% through buctril super. Zand et al. (2007) noticed highest

weed control by bromoxynil herbicide in contrast to clopyralid, diflufenicon,

fluoroxypyr, tribenuron methyl. However, Aslam et al. (2007) reported 98% weed

control by panter herbicide. Hussain et al. (2013) observed maximum weeds

control (90.7%) and highest grain yield (3925 kg ha-1) due to bromoxynil and

clodinofop-propargyl mixture as compared to weedy check. Baloch et al. (2013)

also reported significanr suppression (73.9%) in weeds population due to combined

mixture of buctril super and puma super herbicides.

4.3.19 Correlation Among Microbial Parameters in Field Experiment-2

(Heavy-Textured Soil)

The Pearson’s correlation coefficients between actinomycetes, bacteria, fungi

population, microbial biomass carbon, microbial biomass nitrogen, microbial

biomass phosphorus, dehydrogenase, alkaline phosphatase and urease activity, nitrate

nitrogen, Olsen-P and total organic carbon in presented in (Table 4.16). Highest

positive correlation was found between actinomycetes and bacteria population (r

=0.78), actinomycetes and fungi population (r =0.70), actinomycetes and microbial

biomass carbon (r =0.73), actinomycetes and microbial biomass nitrogen (r =0.82),

actinomycetes and microbial biomass phosphorus (r=0.78), actinomycetes and urease

activity (r =0.53), actinomycetes and dehydrogenase activity (r=0.86), actinomycetes

and alkaline phosphatase activity (r = -0.079), actinomycetes and nitrate nitrogen (r

=0.77), actinomycetes and Olsen-P (r=0.81), actinomycetes and Olsen-P (r=0.81),

actinomycetes and total organic carbon (r= 0.41). Similarly, positive correlation was

found between bacteria and fungi population (r=0.58), bacteria and MBC (r=0.70),

231

bacteria and MBN (r=0.65), bacterial population and MBP (r=0.64), bacterial

population and activity of urease (r=0.56), bacterial population and dehydrogenase

activity (r=0.83), bacterial population and alkaline phophatase activity (r=0.025),

bacterial population and nitrate nitrogen (r=0.63), bacterial population and Olsen-P

(r=0.72), bacterial population and TOC (r=0.46). Also positive correlation were

found between fungi and MBC (r= 0.57), fungi and MBN (r= 0.69), fungi and MBP

(r= 0.78), fungi and urease activity (r= 0.42), fungi and dehydrogenase activity (r=

0.65), fungi and alkaline phosphatse activity (r= 0.0.86), fungi nitrate nitrogen (r=

0.76), fungi and Olsen-P (r= 0.68), fungi and TOC (r= 0.35). Microbial biomass

carbon also positively correlated with MBN (r = 0.71), with MBP (r= 0.64),

dehydrogenase activity (r=0.70), but negatively correlated with alkaline phosphatase

(r= -.045) urease activity (r2= - 0.70), MBN was positively correlated with nitrate

nitrogen (r= 0.64), Olsen-P (r= 0.80), TOC (r=0.13), MBP (r2=0.81), with urease

activity (r2=0.38), with dehydrogenase activity (r=0.79), with nitrate nitrogen

(r=0.79), with Olsen-P (r=0.85) with TOC (r=0.38), but negatively correlated with

alkaline phosphatase activity (r2= -0.07). Microbial biomass phosphorus (MBP)

showed positive correlation with urease activity (r=0.41), with dehydrogenase

activity (r=0.73), with nitrate nitrogen (r=0.78),with Olsen-P (r=0.79), with TOC

(r=0.23), but negatively correlated with alkaline phosphatase activity (r= -0.17).

The activity of urease also exhibited positive correlation with with

dehydrogenase activity (r=0.54), with nitrate nitrogen (r=0.36), with Olsen-P

(r=0.50) with TOC (r=0.29), but negatively correlated with alkaline phosphatase

232

Table 4.15: Different doses of buctril super herbicide showing weeds control

efficiency by blocking electron transport in photosystem-II in weeds in field

experiment-2 (heavy-textured soil)

Herbicide dose WCE

(2011)

WCE

(2012)

(%) (%)

Control 0.0 e 0.0 e

375 mL ha-1 22 d 21 d

750 mL ha-1 71 c 69 c

1500 mL ha-1 74 b 72 b

2250 mL ha-1 76 a 74 a

Means having common letter are not significantly different at LSD Test at 5%

probability level

233

(r= -0.39). The activity of dehydrogenase also exhibited positive correlation with

nitrate nitrogen (r=0.64), with Olsen-P (r=0.76) with TOC (r=0.39), but negatively

correlated with alkaline phosphatase activity (r= -0.19). The activity of alkaline

phosphatase showed negative correlation with nitrate nitrogen (r=0.080), Olsen-P

(r=0.66) but weak positive correlation with TOC (r=0.12). Positive correlation was

observed between nitrate nitrogen and Olsen-P (r=0.83) and TOC (r=0.28). Weak

positive correlation was experienced between Olse-P and TOC (r=0.31).

Kucey (1983) reported highly significant correlation between phosphorus

level and population of fungi in soil. Sharma and Mishra (1992) observed positive

correlation of dehydrogenase activity with fungi and bacterial population. They also

reported positively correlation of urease activity with bacteria and fungi population.

Speir and Gill (1979) found negative correlation between phosphatase activity and

soil phosphorus. Similarly, George et al. (2006) reported that alkaline phosphatase

negatively correlated with soil P contents. Trafdar and Junk (1979) noticed positive

correlation between phosphatase activity and organic phosphorus depletion in soil.

Wright and Reddy (2001) found that the activity of alkaline phosphatase was

influenced by phosphorus contents and showed negative correlation to the

concentration of soil phosphorus. Liu et al. (2008) reported positive correlation

between total carbon and microbial biomass carbon, total carbon and microbial

biomass nitrogen. They also noticed positive correlation between MBC/MBN ratio

and TOC, They observed positive correlation of pH with urease and dehydrogenase

activity. TOC showed positive correlation with dehydrogenase (r= 0.102), with

urease (r= 0.69), with microbial biomass carbon (r= 0.0.74), with microbial biomass

234

nitrogen (r= 0.37), with MBC/MBN ratio (r= 0.50). They also reported positive

correalation between total phosphorus and urease activity (r= 0.086), total

phosphorus and dehydrogenase activity (r= 0.291), total phosphorus and MBC (r=

0.77), total phosphorus and MBN (r= 0.62), total phosphorus and MBC/MBN ratio

(r= 0.091). However, they reported negative correlation between MBC and urease (r=

- 0.122), MBC and dehydrogenase (r= - 0.297). Positive correlation between urease,

degydrogenase, soil pH and electrical conductivity was reported in some

investigations (Kheyrodin and Khosro, 2012). They also found that available

phosphorus and MBN were positively correlated with TOC. MBC/MBN ratio was

positively correlated with TOC and C/N. Hoorman and Islam (2010) observed that

low content of nitrogen and high C/N ratio slow down the process of decoposition of

soil organic matter. They advocated that for proper decomposition of soil organic

matter low C/N ratio (< 20) is better one.

235

Table 4.16. Correlation (r) among microbial parameters in field experiment-2 (heavy-textured soil)

ACT BAC FUN MBC MBN MBP UA DHA APA NN OP

ACT -

BAC 0.78 -

FUN 0.70 0.58 -

MBC 0.73 0.70 0.57 -

MBN 0.82 0.65 0.69 0.71 -

MBP 0.78 0.64 0.78 0.64 0.81 -

UA 0.53 0.56 0.42 0.70 0.38 0.41 -

DHA 0.86 0.83 0.65 0.70 0.79 0.73 0.54 -

APA -0.08 0.025 -0.08 -0.45 -0.07 0.17 -0.39 -0.02 -

NN 0.77 0.63 0.76 0.64 0.79 0.78 0.36 0.64 -0.08 -

OP 0.81 0.72 0.68 0.80 0.85 0.79 0.50 0.76 -0.66 0.8 -

TOC 0.41 0.46 0.35 0.13 0.38 0.23 0.29 0.47 0.12 0.8 0.31

ACT, actinomycetes; BAC, bacteria; FUN, fungi; MBC, microbial biomass carbon; MBN,

microbial biomass nitrogen; MBP, microbial biomass phosphorus;UA, urease activity; DHA,

dehydrogenase activity; APA, alkaline phosphatase activity; NN, nitrate nitrogen; OP,Olsen-P

236

4.4. INCUBATION STUDY

4.4.1 Effect of Buctril Super Herbicide and its Metabolites on Beneficial

Microorganisms Responsible for N and P-transformations

Intensive agriculture is dependent on extensive use of anthropogenic

chemicals like herbicides, insecticides and fungicides commonly known as

pesticides. However, these chemicals can cause damage to soil health because of

their toxicity to the soil microbial community. Pimentel (1995) reported that less

than 0.3 % of the applied chemicals had reached the target organisms and the rest

(99.7 %) directly affected the whole soil environment, disrupting the balance

among different groups of microorganisms and causing harm to susceptible

microbial population. Organic matter turnover, nutrients mineralization and

degradation of different agrochemicals in soil are performed by soil

microorganisms (El-Ghamry et al. 2000; Pampulha and Oliveira, 2006). The use of

these chemicals can potentially hamper these processes. Soil microorganisms also

mediate enzyme activity which is adversely affected by herbicides addition to soil

and indicates stresses (Domsch et al., 1983). Hutsh (2001) reported a considerable

decrease in soil microbial population and organic matter decomposition due to

different herbicides. Ammonia oxidizing archaea (AOA) and ammonia oxidizing

bacteria (AOB) mediate the first and rate limiting step of nitrification, which is the

conversion of ammonia to nitrate (Norton, 2008; Leininger et al., 2006).

Nitrification is a key process as it affects N mobility and availability in soils.

Nitrate can easily be lost from soils via leaching or denitrification (Norton and

Stark, 2011). The impact of bromoxynil on the populations of ammonia oxidizers is

not known. A study by Edward et al. (1993) observed extreme sensitivity of

237

nitrifying bacteria to bromoxynil herbicide. This study was limited in scope and did

not look at the impact of the herbicide on AOA whose role in mediating

nitrification was discovered recently (Treusch et al., 2005). A better understanding

of the impact of bromoxynil on ammonia oxidizers is needed to improve N

management in soils.

Cultivated soils have plenty of total phosphorus (400-1200 µg g-1).

However, the bioavailable phosphorus is very low (1.0 µg g-1). Furthermore, the

efficiency of phosphatic fertilizers in alkaline calcareous soils is about 15%. The

deficiency of phosphorus is commonly found in tropical and weathered soils all

over the world which has raised the costs of phosphatic fertilizers. Although most

soils contain large quantity of total phosphorus, most of it is scarcely available to

plants (Richardson and Simpson, 2011). Microorganisms can efficiently solubilize

the precipitated phosphorus in soil and made it available to plants for subsequent

use (Kucey, 1983). In order to understand the contribution of soil microorganisms

regarding availability of phosphorus to plants and to manipulate typical microbes

that could enhance the phosphorus availability in soils is a matter of great concern

(Richardson and Simpson, 2011). The idea of microbial enhancement of

phosphorus availability to plants is not a new one. Gerresten (1948) demonstrated

that some soil bacteria have the ability to enhance the phosphorus availability to

plants by solubilizing the precipitated calcium phosphate. But these microbes are

very sensitive to different anthropogenic chemicals such as herbicides insecticides

and pesticides. Ahmad and Khan (2010) found an obvious decline of 72 %, 91%

238

and 94% in phosphate solubilizers (Enterobacter asburiae) population due to 40

µg/L, 80 µg/L and 120 µg/L, dose of quizalafop-p-ethyl, respectively.

Wheat is the major staple food of many countries of the world. But its

production is low because of weed infestation in wheat fields. Weeds deprive the

wheat crop from essential nutrients, water, space and light due to their rapid

growth. Shah et al. (2005) observed a significant decline (20 to 45 %) in wheat

yield due to weeds. Mechanical (hand weeding and tillage) and chemical

(application of herbicides) methods are commonly employed for controlling weeds.

However, implementation of no till practice to conserve soil moisture made the use

of herbicides inevitable (Trigo and Cap, 2003). Because of ban on atrazine

herbicide usage, bromoxynil herbicide is being used as an alternate all over the

world, promoting it extensive use in future. About 18000 to 22000 tons of

bromoxynil herbicide was being applied annually in the United States of America

(Gianessi and Cressida, 2000).

Bromoxynil pesticide is also used heavily and frequently in Pakistan under

the name buctril super for controlling weeds in wheat fields (Aslam et al., 2007;

Cheema et al., 2006). In spite of the benefits of this herbicide in controlling weeds

it also has negative effect on beneficial soil microorganisms which are integral

components of soil ecosystems. Follak et al. (2005) reported that the use of

bromoxynil herbicide exerted potential toxic effect in soil environment, but how

such effect is dependent on soil property is unknown. This study was designed to

examine the impacts of bromoxynil and its metabolites on beneficial

239

microorganisms (AOA, AOB and phosphate solubilizing bacteria) responsible for

N and P transformations in two contrasting soil textures.

240

Table 4.17: Physical and chemical characteristics of soils used in incubation

study

Parameters Heavy-textured soil Light-textured soil

Sand (%) 41.8 56

Silt (%) 13.4 25

Clay (%) 44.8 19

Soil texture Clay Sandy loam

pH 6.4 7.2

EC (µScm-1) 259 234

Organic matter (%) 1.38 0.92

241

Table 4.18: Decline in bacterial amoA abundance in two different textured

soils that received buctril super herbicide at different concentrations due to

poisonous effect of herbicide on them

Heavy textured soil Light textured soil

Factors ------------ cfu g-1 soil x106 -----------

Treatments

Control 4.39 A 4.21 A

0.2 µg g-1 soil 4.12 B 3.97 B

0.4 µg g-1 soil 3.77 C 3.69 C

0.6 µg g-1 soil 3.59 D 3.52 D

0.7 µg g-1 soil 3.27 E 3.31 E

0.8 µg g-1 soil 2.99 F 3.01 F

Sampling day

Day-0 3.93 A 3.71 A

Day-15 3.71 B 3.43 B

Day-45 3.43 C 3.74 A

C.V (%) 4.55 3.79

Means with same letter suffix are not significantly different at p ≤ 0.05.

Comparison is valid with in a column

242

The results of the study showed the highest number of bacterial amoA abundance

in control which were 4.39 copies/g soil x106, followed by 4.12 copies/g soil x106

in 0.2 µg g-1 soil and lowest in 0.8 µg g-1 soil. Overall, 0.6 µg g-1 soil, 0.7 µg g-1

soil and 0.8 µg g-1 soil caused 18.2 %, 25.5% and 32.0 % decrease in AOB

population size as compared to control in heavy textured soil. Similarly, AOB

population was highest in control (4.21 copies/g soil x 106) followed by 0.2 µg g-

1soil (3.97 copies/g soil x106), 0.4 µg g-1 soil (3.69 copies/g soil x106) and lowest

population (3.05 copies/g soil x106) was found in 0.8 µg g-1 soil in light textured

soil. As a whole, 0.6 µg g-1 soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil treatments

showed a decrease of about 16.38 %, 21.37% and 28.50% in AOB population in

light textured soil (Table 4.18). Sampling days had a significant effect on the

bacterial population (P ≤ 0.005). The maximum AOB population was observed at

day-0 (3.93 copies/g x106) and minimum at day-45 (3.43 copies/g x106),

indicating a 12.7 % less population at day-45 as compared to day-0 in heavy

textured soil. Similarly, in light textured soil, AOB population was highest at day-

0 of herbicide application (3.71 copies/g x106), while lowest at day 15 (3.43

copies/g soil x106) indicating a 7.5% decline. Overall, the AOB population

showed decrease from day-0 today-15, but at day-45 the population reached to its

initial level, showing no statistically difference in AOB population at day-0 and

day-45 (Table 4.18).

Sampling days and treatments, interactive effects revealed the highest

population at day-0 in control (4.46 copies/g x106). However, the lowest AOB

population was noticed at day-45 in 0.8 µg g-1 soil (2.45 copies/g x106) resulting a

243

45 % less population, followed by 0.7 µg g-1 soil (2.96 x106 cfu g-1soil) at day-45

showing a 34.1 % decline, followed by 0.6 µg g-1 soil (3.33 copies/g x106) at day-

45 indicating a 25.7 % inhibition as compared to control (4.46 copies/g x106) at

day 0 in heavy textured soil (Figure 63). Whereas, in light textured soil highest

AOB population was found at day-15 in control ( 4.41 copies/g x106) and lowest

population was recorded at same day in 0.8 µg g-1soil (2.45 copies/g x106)

indicating a 44 % decrease in AOB population, followed by 0.7 µg g-1 soil (2.96

copies/g x106) at day 15 indicating 32.87% inhibition, followed by 0.8 µg g-1 soil

(3.31 copies/g x106) at day-0 in light textured soil indicating 24.94% decline in

AOB population (Figure 64).

Results of the present study revealed highest number of AOA in control

(5.99 copies/g x106) followed by 0.2 µg g-1 soil (5.00 copies/g x106) and lowest in

0.8 µg g-1 soil (2.66 x106cfu g-1soil). In general, 0.6 µg g-1 soil, 0.7 µg g-1 soil and

0.8 µg g-1 soil caused a 39.5 %, 51% and 57.0 % decrease in AOA population in

heavy textured soil. On the other hand the highest AOA population was found in

control (4.59 copies/g x106), followed 0.2 µg g-1 soil (4.09 copies/g x106), HC-2

(3.56 copies/g x106) and lowest population in 0.8 µg g-1 soil (2.69 copies/g x106) in

light textured soil. Generally, 0.6 µg g-1 soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil

showed 30.5 %, 34.2% and 41.0% decrease in AOA population in light textured

soil (Table 4.19).

Sampling days had a significant effect on AOA (P ≤ 0.005). The maximum

AOA population was observed at day-0 (4.53 copies/g soil x106) and minimum at

244

day-45 (3.65 copies/g x106) indicating a 19.4 % less population at day-45 as

compared to day-0 in heavy textured soil. In the same way, in light textured soil,

AOA population was highest at day-0 (3.72 copies/g x106) and lowest at day 45

(3.39 copies/g x106) indicating 8.8% decline followed by day-15 (3.46 copies/g

x106) indicating a 7.0 % decrease. However, no statistically significant difference

was found in AOA population at day-15 and day-45 (Table 4.19).

The interactive effect of treatments and sampling days revealed highest

population at day-15 in control (6.17 copies/g x106) and the lowest AOA

population was noticed at day-45 in 0.8 µg g-1 soil (1.89 copies/g x106) with a

huge decrease of 69 %, followed, by the same dose (0.8 µg g-1 soil) at day-15 (2.65

copies/g x106) indicating 57% decline followed by 0.8 µg g-1 soil (3.25 copies/g

x106) at day-0 indicating a 47 % inhibition as compared to control (6.17 x106 cfu g-

1soil) at day 15 heavy textured soil (Figure 65). Similarly, in light textured soil, the

highest AOA population was at day-45 in control (4.85 copies/g x106) and lowest

population was at the same day in 0.8 µg g-1 soil (2.34 copies/g x106) indicating a

52 % decrease in AOA population, followed by 0.7 µg g-1 soil (2.94 copies/g x106)

at day15 indicating a 39.3 % decrease as compared to control (4.85 copies/g x106)

at day-45 (Figure 66).

The population of phosphate solubilizing bacteria (PSB) significantly varied

in all herbicidal treatments and was in the order of 0.2 µg g-1 soil > 0.4 µg g-1 soil >

0.6 µg g-1 soil > 0.7 µg g-1 soil > 0.8 µg g-1 soil. The highest PSB population was

found in control (7.03 x105 cfu g-1soil) followed by 0.2 µg g-1 soil (5.80 x105 cfu g-

245

1soil), 0.4 µg g-1 soil (5.18 x105 cfu g-1soil), 0.6 µg g-1 soil (4.52 x105 cfu g-1soil)

and lowest population in 0.8 µg g-1 soil (3.10 x105 cfu g-1soil) in heavy textured

soil. In light textured soil the highest PSB population was in control (5.68 x105 cfu

g-1soil) followed by 0.2 µg g-1 soil (4.99 x105 cfu g-1soil) followed by 0.4 µg g-1

soil (4.64 x105 cfu g-1soil) followed by 0.6 µg g-1 soil (3.84 x105 cfu g-1soil) and

lowest population in 0.8 µg g-1 soil (3.25 x105 cfu g-1soil). In general, 0.6 µg g-1

soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil showed 35.7 %, 47.9% and 60% decrease in

PSB population in heavy textured soil in comparison to control. Whereas, a

18.30%, 38.7%, 39.61% and 42.7% decrease in PSB was recorded in light textured

soil due to 0.4 µg g-1 soil, 0.6 µg g-1 soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil,

respectively as compared to control (Table 4.20). Sampling days had a significant

effect on PSB population (P ≤ 0.005). The maximum PSB population was observed

at day-0 (6.13 x105 cfu g-1soil) and minimum at day-60 (4.30 x105 cfu g-1soil)

indicating a 29.85 % less population at day-60 as compared to day-0 in heavy

textured soil. Likewise, in light textured soil, the PSB population was highest at

day-0 (5.07 x105 cfu g-1soil) and lowest at day 15 (3.57 x105cfu g-1 soil) indicating

a 29.6 % decline followed by a day-30 (3.85 x105 cfu g-1soil) with a 24 % decrease.

However, no statistically significant difference was found in a PSB population at

day-0 and day-60 (Table 4.20). The interactive effect of treatments and sampling

days revealed highest PSB at day-60 in control (7.70 x105 cfu g-1soil) and lowest

PSB population was at day-60 in 0.8 µg g-1 soil (1.93 x105 cfu g-1soil) with a huge

decrease of 74.9 %, followed by 0.8 µg g-1 soil (2.47 x106 cfu g-1soil) at day-15

indicating 68.0% decline followed by 0.8 µg g-1 soil (3.03 x105 cfu g-1soil) at day-7

indicating 60.6 % inhibition as compared to control (7.70 x106 cfu g-

246

1.5

2.5

3.5

4.5

5.5

D-0 D-15 D-45

Sampling day

(Bac

teri

al a

moA

copie

s * 106

g-1 s

oil)

Control 0.2 µg g-1 soil 0.4 µg g-1 soil

0.6 µg g-1 soil 0.7 µg g-1 soil 0.8 µg g-1 soil

Figure 63: Ammonium oxidizing bacteria showing decline up to day-45 in heavy-textured soil under different

doses of buctril super herbicide because of prolonged persistence of herbicide in this soil

247

1.5

2.5

3.5

4.5

5.5

D-0 D-15 D-45

Sampling day

(Bac

teri

al a

mo

A c

op

ies

*

106

g-1

so

il)



Figure 64: Different doses of buctril super herbicide causing suppression in ammonium oxidizing bacteria up to day-15 and

afterward showing recovery in AOB in light-textured soil because of low persistence of herbicide in this soil

248

Table 4.19. Decline in archaeal amoA abundance in two different

textured soils that received buctril super herbicide at different

concentrations due to poisonous effect of herbicide on them

Factors Heavy Textured soil

Light Textured soil

Treatments ------- cfu g-1 soil x106 ---------


0.2 µg g-1 soil 5.00 B 4.09 B

0.4 µg g-1 soil 4.26 C 3.56 C

0.6 µg g-1 soil 3.62 D 3.19 D

0.7 µg g-1 soil 2.93 E 3.02 E

0.8 µg g-1 soil 2.60 F 2.69 E

Sampling days

Day-0 4.53 A 3.72 A

Day-15 4.01 B 3.46 B

Day-45 3.65 C 3.39 B

C.V (%) 6.35 7.91

Means with same letter are not significantly different at p = 0.05.


249

1.5

3

4.5

6

7.5

D-0 D-15 D-45

Sampling day

(Arc

hae

al am

oA

copie

s * 1

06 g

-1 s

oil)

Control 0.2 µg g-1 soil 0.4 µg g-1 soil0.6 µg g-1 soil 0.7 µg g-1 soil 0.8 µg g-1 soil

Figure 65: Ammonium oxidizing archaea showing decline up to day-45 in heavy-textured soil under

different doses of buctril super herbicide because of prolonged persistence of herbicide in this soil

250

1.5

2.5

3.5

4.5

5.5

D-0 D-15 D-45

Sampling day

(Arc

haea

l am

oA c

opie

s *

106 g

-1 s

oil)



Figure 66: Decline in ammonium oxidizing archaea in light-textured soil under different doses of

buctril super herbicide because of poisonous effect of herbicide

251

Table 4.20. Decline in phosphate solubilizing bacteria in two different

textured soils that received buctril super herbicide at different concentrations

due to poisonous effect of herbicide on them

Factors Heavy Textured soil

Light Textured soil

Treatments ------- cfu g-1 soil x105 ----------


0.2 µg g-1 soil 5.80 B 4.99 B

0.4 µg g-1 soil 5.18 C 4.64 C

0.6 µg g-1 soil 4.52 D 3.84 D

0.7 µg g-1 soil 3.66 E 3.25 E

0.8 µg g-1 soil 3.10 F 3.43 E

Sampling days

Day-0 6.13 A 5.07 A

Day-7 4.84 B 4.13 B

Day-15 4.76 B 3.57 D

Day-30 4.39 C 3.85 C

Day-60 4.30 C 4.91 A

C.V (%) 5.17 6.13

Means with same letter suffix are not significantly different at p = 0.05.


252

1soil) at day 60 in heavy textured soil (Figure 67). Similarly, in light textured soil

the highest PSB population was at day-60 in control (5.93 x105 cfu g-1soil) and

lowest population was in 0.7 µg g-1 soil (1.33 x105 cfu g-1soil) indicating a 77.6 %

decrease followed by 0.7 µg g-1 soil (1.87 x105 cfu g-1soil) at day15 showing a 68.5

% decrease as compared to control (7.70 x105 cfu g-1soil) at day-60 (Figure 68).

The metabolite analyzed from bromoxynil contaminated soil showed

characteristic fragment ion peak of MS at m/z 172.7, 216.7 and 80.1 as shown in

(Figure 69). Therefore, on the basis of MS analysis the product was identified as 3-

bromo-4-hydroxybenzoic acid. Cai et al. (2011) also reported the same metabolites

from the soil after application of bromoxynil herbicide. The effect of this

metabolite (3-bromo-4-hydroxybenzoic acid) on overall bacterial population and on

phosphate solubilizing bacteria was determined and described below.

The impact of bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) on

phosphate solubilizing bacteria is presented in (Table 4.21). The statistical analysis

showed the highest PSB population in 0.8 µg g-1 soil (6.31 x105 cfu g-1 soil), while

the lowest population was found in control (6.12 x105 cfu g-1 soil), indicating a

3.10% more population in 0.8 µg g-1 soil than control. However, the control, 0.2 µg

g-1 soil and 0.4 µg g-1 soil were not statistically different from one another.

Sampling days showed the highest PSB population at day-15 (6.31 x105 cfu g-1

soil), followed by day-30 (6.31 x105 cfu g-1 soil) while, the lowest population was

at day-7 (6.11 x105 cfu g-1 soil), indicating 3.27% and 3.11% more PSB at day-15

and day-30, respectively. The interactive effect of sampling days and metabolite

253

1.0

3.5

6.0

8.5

D-0 D-7 D-15 D-30 D-60

Sampling day

(PS

B a

bu

nd

ance

* 1

0 5 g

-1 s

oil)



Figure 67: Phosphate solubilizing bacteria showing severe decrease under different doses of buctril super

herbicide in heavy-textured soil because of more persistence of herbicide in this soil

254

1.0

3.5

6.0

8.5

D-0 D-7 D-15 D-30 D-60

Sampling day

(PS

B a

bundan

ce *

10 5 g

-1 s

oil)



Figure 68: Phosphate solubilizing bacteria showing slight decrease due to buctril super herbicide upto day-30

and after that increase in population because of low persistence of herbicide in light-textured soil

255

15:00:0622-May-20143

60 80 100 120 140 160 180 200 220 240m/z2

100

%

216.713056

171.810240

80.17168

80.92976

172.79088

Figure 69: Bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) analyzed

from bromoxynil contaminated soil showing characteristic fragment ion peak of

MS at m/z 172.7, 216.7 and 80.1

256

Table 4.21: Phosphate solubilizing bacteria in soil that received

bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) at different

concentrations showing increase in PSB population because they used the

metabolite as a source of carbon

Factors PSB

Treatments (cfu g-1 soil x105)

Control 6.12 B

0.2 µg g-1 soil 6.15 B

0.4 µg g-1 soil 6.18 B

0.6 µg g-1 soil 6.27 AB

0.7 µg g-1 soil 6.27 AB

0.8 µg g-1 soil 6.31 A

Sampling day

Day-0 6.17 B

Day-7 6.11 B

Day-15 6.31 A

Day-30 6.30 A

C.V (%) 2.95

Means with same letter are not significantly different at p = 0.05

comparison is valid with in a column

257

treatments revealed a highest PSB population at day-30 in 0.8 µg g-1 soil (6.50 x105

cfu g-1 soil) and lowest at day-0 and day-7 in control (6.03 x105 cfu g-1 soil), which

showed a 7.79 % increase in PSB population at day-30 in 0.8 µg g-1 soil (Figure

70).

The effect of bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) on

total bacterial abundance is presented in (Table 4.21). In 0.8 µg g-1 soil, the highest

bacterial population was found (i.e 1.45 x108 cfu g-1 soil), followed by 1.44 x108

cfu g-1 soil in 0.7 µg g-1 soil, while the lowest population (1.32 x108 cfu g-1 soil)

was observed in 0.2 µg g-1 soil. Overall, 0.7 µg g-1 soil and 0.8 µg g-1 soil caused a

9.09% and 9.84% enhancement in bacterial population over 0.2 µg g-1 soil during

entire period of incubation. No any statistically significant difference was found in

bacterial population at day-7, day-15 and day-30. However, 5.22%, 6.71% and

5.97% increase in bacterial population was observed at day-7, day-15 and day-30,

respectively than day-0.

The interactive effect of treatments and sampling days showed the highest

bacterial population (i.e. 1.48 x108 cfu g-1 soil) in 0.8 µg g-1 soil at day-7, 15 and

30, while the lowest population (1.31 x108 cfu g-1 soil) was observed at day-7 in 0.2

µg g-1 soil, indicating a 11.48 % less population, followed by (1.32 x108 cfu g-1

soil) at day-0 in 0.2 µg g-1 soil at day-0, indicating a smaller population (by 10.8%)

than 0.8 µg g-1 soil (1.48 x108 cfu g-1 soil) at day-7, 15 and 30 (Figure 71).

Ammonia oxidizing bacteria and Achaea play a key role in nitrification.

258

Generally, in nitrification the rate limiting step is the conversion of ammonia to

nitrite. It is important because the majority of plants use nitrate form of nitrogen for

their growth and that nitrate can easily be lost from the soil system via leaching or

denitrification. Nitrification causes soil acidification by producing hydrogen ions in

soil (Van and Cole, 1984). Present results showed the highest AOB population in

control and lowest in 0.8 µg g-1 soil with a 32 % decrease in heavy textured soil and

28.5% in light textured soil in 0.8 µg g-1 soil as compared to control. Highest

population in control was because of the absence of herbicide. However, this large

decrease of 32% and 28.50 % in AOB population size, respectively in heavy

textured soil and light textured soil in 0.8 µg g-1 soil was due to toxic effect of high

dose of herbicide to autotrophic nitrifiers. Similarly, Allievi and Giglioti (2001)

observed inactivation and inhibition in amino acid assimilation of some autotrophic

nitrifying bacteria by the sulfonyl urea herbicide. Hernandez et al. (2011) reported

a decrease in the population of AOB and AOA due 50 mg kg-1soil dose of simazine

herbicide. They also observed inhibition in nitrification. Chang et al. (2001)

observed significant suppression in AOB due to10 ppm and 100 ppm mixture of

herbicides (atrazine, dicamba-4, flumutoron, metolachlor and sufentrazone).

Further, they reported that no amoA gene was detected in soil treated with 1000

ppm of these herbicides. In soil-2, the suppressive effect of buctril super remained

only up to day-15 and afterward AOB population show decline but this decline was

not statistically significant. Contrary to that, Li et al. (2008) reported enhancement

the population of AOB by acetachlor herbicide. Rangaswamay et al. (1993)

observed stimulation in the nitrification process as a result of azospirillum due to

fenvalerate application. Sampling days had statistically significant effect on AOB

259

5.5

6.0

6.5

7.0

0 7 15 30

Sampling day

PS

B (

#1

05 c

fu/g

so

il)



Figure 70. Phosphate solubilizing bacteria showing increase in population in heavy-textured soil by different

doses of bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) as it is used as a source of carbon by PSB

260

1.1

1.2

1.3

1.4

1.5

1.6

0 7 15 30Sampling day

(#10

8 c

fu/g

soil)



Figure 71. Total bacterial population showing increase in heavy-textured soil by different doses of

bromoxynil metabolite (3-bromo-4-hydroxybenzoic acid) as it is used as a source of carbon by them

261

Table 4.22: Total bacterial population in soil that received bromoxynil

metabolite (3-bromo-4-hydroxybenzoic acid) at different concentrations

showing increase in bacterial population because they used the metabolite

as a source of carbon


Treatments (cfu g-1 soil x108)

Control 1.34 C

0.2 µg g-1 soil 1.32 C

0.4 µg g-1 soil 1.41 AB

0.6 µg g-1 soil 1.42 AB

0.7 µg g-1 soil 1.44 A

0.8 µg g-1 soil 1.45 A

Sampling day

Day-0 1.34 B

Day-7 1.41 A

Day-15 1.43 A

Day-30 1.42 A

C.V (%) 5.64

Means with same letter suffix are not significantly different at

p = 0.05, Comparison is valid with in a column

262

population. In soil-1, the AOB population was lowest at day-45 and highest at day-

0. Actually, at day-0 the population was highest because of limited exposure of

herbicide to AOB. Whereas, the population was lowest at day-45 because of

extended exposure of herbicide due to its increased persistence in soil-1 due to high

organic matter. Yaron et al. (1985) reported high microbial activity in soil

containing high organic matter, but such soils can adsorb herbicide strongly and

decreases its concentration in soil solution and protect the herbicide from microbial

degradation.

In the present study, AOA were observed to be more abundant as compared

to AOB in all herbicidal treatments in both soils. Further, archaeal amoA gene

numbers exhibited a slight increase in control throughout the study (Table 4.52).

However, a 39.5 %, 51 % and 57 % inhibition in AOA number, respectively, due to

0.6 µg g-1 soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil in heavy textures soil. While,

30.5%, 34.2 % and 41 % decline was observed in AOA population by 0.6 µg g-1

soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil, respectively in light textures soil as

compared to control. The bromoxynil herbicide demonstrated more persistent

detrimental impacts on AOA population in heavy textures soil as compared to light

textures soil. This might be because of more organic matter in heavy textures soil.

Some researchers (Yaron et al., 1985) found that soil with high organic matter can

strongly adsorb the herbicide and protect it from microbial degradation. Therefore,

increase its persistence in high organic matter soil. No sign of recovery of AOA

was observed in 0.8 µg g-1 soil throughout the study period. These results

illustrated that both AOA and AOB were inhibited significantly by the higher dose

263

(0.8 µg g-1 soil) of bromoxynil herbicide. Higher concentration of buctril super

corresponded to less AOA and AOB copy numbers in both soils. Tan et al. (2013)

while seeing the effect of chlorimuron-ethyl on the abundance of AOB and AOA

observed significant suppression in their population as well as in nitrification due to

this herbicide. Our results are in agreement with the previous findings of Saeki and

Toyota (2004) who reported significant and longer lasting suppression in

nitrification due to ten times higher application rate of benselfuron-methyl

herbicide. In soil-2, similar to AOB, the AOA population also showed a statistically

significant decrease up to day-15 and afterward decline was not statistically

significant.

The phosphorus is the most important nutrient element being a fundamental

constituent of protein and DNA. It plays a vital role in storing energy within the

cell. Phosphorus comprises of around 0.2 % of plant weight of (Schachtman, 1998).

It mediates various soil enzyme activities and regulates different metabolic

processes (Theodorou and Plaxton, 1993). Most of the soils contain sufficient

phosphorus (400-1200 µg g-1) but that is not available to plants because of its

precipitation to [Ca3 (PO4)2]. Gerresten (1948) observed that some soil bacteria are

capable of enhancing phosphorus availability to plants by solubilizing the

precipitated calcium phosphate. However, these microbes are highly sensitive to

different agrochemicals added in the soil. Consequently, they lose their potential to

solubilize the precipitated calcium phosphate.

264

In our study, the population of PSB was found to be more in heavy textures soil as

compared to light textures soil. However, the PSB population showed a slight

increasing trend in control during the study period. On the other hand, around

35.7%, 47.9 % and 60 % decrease in PSB number was observed due to 0.6 µg g-1

soil, 0.7 µg g-1 soil and 0.8 µg g-1 soil, respectively as compared to control, in

heavy textures soil. Whereas, 18.30%, 38.7 %, 39.6 % and 42.7 % inhibition in

PSB population was found in 0.4 µg g-1 soil, 0.6 µg g-1 soil, 0.7 µg g-1 soil and 0.8

µg g-1 soil, respectively in contrast to control in light textures soil (Table 4.20).

This large decrease in PSB’s population might be due to lethal effects of buctril

super herbicide on them. Previously research has reported a 72 %, 91% and 94%

suppression in the PSB (Enterobacter asburiae) due to 40 µg/L, 80 µg/L and 120

µg/L application rate of quizalafop-p-ethyl, respectively as compared to control

(Ahemad and Khan, 2010). However, some studies reported no significant change

in PSB abundance due thiomethaxan, phorate, carbosulfuron and carbofuron

application (Sarnaik et al., 2006). Results demonstrated that the negative effect of

the buctril super herbicide on PSB population persisted up to 60 th day of incubation

in heavy-textured soil due to high clay and organic matter in this soil. Unlike

heavy-textured soil, the negative effect of herbicide on PSB persisted up to day-15

in light-textured soil and later on population increased gradually and reached near

to initial level at day-60 because of low organic matter and clay contents in the

former soil. This might be due to degradation of herbicide in light textured soil.

Similarly, Rosenbrock et al. (2004) observed 42% and 49% mineralization of

bromoxynil and bromoxynil octanoate, respectively, within 60 days of herbicide

application in light textured soils.

265

Present results depicted a 3.10% higher PSB population in 0.8 µg g-1 soil

than control. This increase in PSB population with increase in metabolite

concentration in soil indicated that the particular group of bacteria that are involved

in phosphorus solubilization has used the metabolites as a source of carbon and

energy due to which their population was more in 0.8 µg g-1 soil than control.

Similar to our results, Ratcliff et al. (2006) observed increase in bacterial

population due to 100xFR of glyphosate herbicide. Contrary to that, Waever et al.

(2007) observed no significant change in bacterial population due to higher

concentration of glyphosate. At day-7 low population was because of less time for

the microbes to use the metabolites, while at day-15 and day-15 because of more

time for the PSB’s to use the metabolites as a source of energy, so their population

was higher. Singh and Dileep (2005) noticed a 14.4 % and 42.9 % increase in

bacterial popultion at 15th and 60th day, respectively due to diazinon herbicide (800

g kg-1).

In the present study, total bacterial population was more in 0.7 µg g-1 soil

and 0.8 µg g-1 soil as compared 0.2 µg g-1 soil. This indicated that the increased

concentration of the metabolite had increased the bacterial population. It might be

due to the fact that the some of the bacterial species have used this metabolite as a

sole source of carbon due to which their growth increased. Similarly, Dgrak and

Kazaniki (2001) observed substantial increase in bacterial population in the soil

treated with isofenophos than untreated soil. Das and Mukherjiee (2000), observed

increase in phosphate solubilizing and nitrogen fixing bacteria in soil by phorate,

carbafuron and fenvalerate herbicides at day-7, 15 and 30.

266

About, 5.22%, 6.71% and 5.97% increase in bacterial population was

observed at day-7, day-15 and day-30, respectively than day-0. This might be

because of limited time for the bacteria to use the metabolites as a source of carbon

at day-0, while at day-7, 15 and 30 population was more because bacteria used the

herbicide metabolite and showed rapid growth.

267

SUMMARY

Long term impact of buctril super (bromoxynil) herbicide in wheat fields on

soil microbial population, nitrate nitrogen and Olsen-P, Total Organic Carbon

(TOC) and enzymes activities were evaluated in 18 sites in Pakistan. Nine sites

each were randomly selected from those places where bromoxynil herbicide had

been used for the last 10 years designated as Soil ‘A’ and other nine where no

herbicide was used for that period designated as Soil ‘B’. Very importantly it was

found that long term application of this herbicide in wheat fields reduced the

actinomycetes and fungi population up to 19.72 % and 14.28 %, respectively,

urease and dehydrogenase activity to 17.53% and 28.15 %, respectively, and

inhibited nitrate nitrogen, Olsen-P and TOC to 55%, 17 % and 28.57%,

respectively. Presence of high clay and organic matter contents enhanced the

detrimental effect of herbicides by prolonging its persistence as compared to light

textured soils.

Two years field experiments were conducted at University research Farm at

Koont and farmers fields Taunsa during 2011-12 and 2012-13 to see the effect of

buctril super herbicide on microbial parameters in soil .About 30 % and 56%

decrease in bacterial population, 23% and 47.5% decrease in actinomycetes

population 23 % and 34.5% decrease in fungi population ,30 % and 38% decrease

in urease activity, 36 % and 31 % decrease in dehydrogenase, 34 % and 50%

decrease in alkaline phosphatase ,35 % and 36% decrease in MBC, 34 % and 53%

decrease in MBN, 39.5 % and 44.5% decrease in MBP, 44.5 % and 30 % decrease

in NO3-N, 22.5 % and 18.5% decrease in Olsen-P and 6.34% and 3.5 % decrease in

TOC in light and heavy-textured soils in 2011-12 and 2012-13, respectively

268

was observed. But the detrimental effects of this herbicide on above parameters

were transitional and all parameters recovered to their initial level after day-30 in

Koont soil (light textured soil). On the other hand, the harmful effects were longer

lasting in Taunsa soil (heavy textured soil) and these parameters could not recover

to their initial levels even after sixty days.

Incubation study was conducted at Department of Crop and Soil Sciences,

University of Georgia (USA) to see the effect of buctril super herbicide on

beneficial soil microorganisms responsible for N and P-mineralization using two

different soil types. About 32% and 35.2% decrease in ammonium oxidizing

bacteria population was observed in soil-1 and soil-2, respectively. Ammonium

oxidizing Archaea showed 57.5 and 41% decline in soil-1 and soil-2, respectively.

Suppression of about 60% and 42.7% was observed in phosphate solubilizing

bacterial population.

In soil-1, the high clay contents prolonged the persistence and exposure of

herbicide to AOA, AOB and PSB populations as compared to soil-2 (light textured

soils). Therefore, alternate herbicide (with low persistence in heavy textured soil)

other than buctril super (bromoxynil) which could also significantly suppress the

weeds in wheat should be used in heavy textured soils containing high organic

matter.

Significant decline in ammonium oxidizing bacteria and ammonium

oxidizing archaea population was observed due to buctril super herbicide up to day-

269

15 in soil-2 (light textured soils) But after day-15 no detrimental effect of this

herbicide was found because of degradation of herbicide. Therefore, this herbicide

is safe to use in light textured soils. However, in such type of soils the urea

fertilizer should be applied 15 days after this herbicide application to protect AOB

and AOA population for smooth nitrification.

CONCLUSION

The harmful effects of buctril super (bromoxynil) herbicide were transitional at

location -1 (light-textured soil) and persisted longer time at location-2 (heavy-

textured soil) and the above parameters could not recover to their initial level even

after 60-days at location-2 because of relatively:

high clay contents

Which lengthened its persistence in soil resulting more time of exposure of this

herbicide to soil microbes and enzymes consequently declined their activity for

long time.

RECOMMENDATIONS

1. On the basis of above results, recommended dose of this herbicide is safe to

use in light textured soils. However, in such type of soils the urea fertilizer

should be applied 15 days after this herbicide application to protect

ammonium oxidizing bacteria and ammonium oxidizing archea population

for smooth nitrification.

270

2. These findings also suggested the use of alternate herbicide in wheat fields

particularly in heavy textured (clay) and high organic matter soils for

maintaining soil health.

271

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