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DEVELOPMENT AND APPRAISAL OF ECONOMICAL AND SUSTAINABLE APPROACH FOR WEED MANAGEMENT IN DRILL SEEDED AEROBIC RICE (Oryza sativa L.) BY MUHAMMAD SAQIB M.Sc. (Hons.) Agriculture A thesis submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN AGRONOMY DEPARTMENT OF AGRONOMY FACULTY OF AGRICULTURE UNIVERSITY OF AGRICULTURE, FAISALABAD PAKISTAN 2013

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Page 1: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

DEVELOPMENT AND APPRAISAL OF ECONOMICAL AND SUSTAINABLE APPROACH FOR WEED MANAGEMENT IN DRILL SEEDED

AEROBIC RICE (Oryza sativa L.)

BY

MUHAMMAD SAQIB M.Sc. (Hons.) Agriculture

A thesis submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

IN

AGRONOMY

DEPARTMENT OF AGRONOMY

FACULTY OF AGRICULTURE

UNIVERSITY OF AGRICULTURE, FAISALABAD

PAKISTAN

2013

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To, The Controller of Examinations,

University of Agriculture,

Faisalabad.

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

submitted by Mr. Muhammad Saqib, Regd. No. 2001-ag-2563, have been found

satisfactory and recommend that it be processed for evaluation by External Examiner(s)

for the award of degree.”

SUPERVISORY COMMITTEE

1. Chairman: ___________________

Dr. Nadeem Akbar

2. Member: ___________________

Prof. Dr. Ehsanullah

3. Member: ___________________

Prof. Dr. Abdul Ghafoor

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Declaration

I hereby declare that contents of the thesis, “Development and appraisal

of economical and sustainable approach for weed management in drill

seeded aerobic rice (Oryza sativa L.)” are product of my own research

and no part has been copied from any published source (except the

references, standard mathematical or genetic models/equations/formulae

/protocols 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. (In case of any

default, the scholar will be proceeded against as per HEC plagiarism

policy).

MUHAMMAD SAQIB

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DEDICATED

TO

HOLY PROPHET MUHAMMAD

(Peace Be Upon Him)

The personality

for whom

world was created

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ACKNOWLEDGEMENTS

All acclamation, appreciation and praise for the ALMIGHTY ALLAH, the most

gracious and compassionate, whose blessing and exaltation flourished my thought and

thrived my ambition to have the cherished fruit of my modest efforts in the form of this

manuscript from the blooming spring of blossoming knowledge.

My special praises for the HOLY PROPHET MUHAMMAD (Peace Be Upon Him) who is

forever a torch of guidance for the entire humanity.

With a proud sense of gratitude, I acknowledge that this manuscript has found this shape

under the kind supervision, inspiring guidance and sympathetic attitude of Dr. Nadeem Akbar,

Asstt. Professor, Department of Agronomy, University of Agriculture, Faisalabad, who benevolently

extended all possible help for the smooth execution of this humble presentation.

I offer my great sense of gratitude to Dr. Ehsanullah, Professor, Department of Agronomy,

University of Agriculture, Faisalabad, for providing valuable suggestions, competent guidance and

boosting up my morale during the conduct of this study.

I am highly indebted to Dr. Abdul Ghafoor, Professor, Institute of Soil and Environmental

Sciences, University of Agriculture, Faisalabad, for his constructive criticism and valuable

suggestions to improve this manuscript.

I shall be missing something if I don’t extend my admiration and appreciation to Mr. Tariq

Masood Qurashi who helped me to increase my abilities of learning.

I am also thankful to my sincere friends Dr. Abdul Ghafar, Dr. Shahzad Ali Shahid

Chatta, Dr. Attiq-ur-Rehman, Adnan Shakir, Imran Ahmad Chishti, Sajja Anjum Sandhu and

Zafar Iqbal who supported me morally with sentiment throughout my research.

Last but not the least gratitude is to be expressed to my affectionate father Muhammad

Iqbal Goraya, my loving mother, my brother Muhammad Asif Iqbal Goraya, my beloved sister

and my wife for their love, patience, inspiration, good wishes and unceasing prayers for me to achieve

higher goals in life.

MUHAMMAD SAQIB

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TABLE OF CONTENTS

Chapter No. TITLE

ACKNOWLEDGEMENTS

TABLE OF CONTENTS

LIST OF TABLES

LIST OF FIGURES

LIST OF ABBREVIATIONS

ABSTRACT

Page No.

i

ii

vi

xi

xiv

xv

1 INTRODUCTION 1

2 REVIEW OF LITERATURE 5

2.1 Rice 5

2.1.1 History of domestication and cultivation 5

2.2 Crop establishment methods 6

2.2.1. Flooded rice 6

2.2.2 Aerobic rice 7

2.2.3 Global distribution of direct seeded rice 8

2.2.4 Crop establishment metods of direct seeded rice 9

2.2.4.1 Wet seedining 9

2.2.4.2 Water seeding 9

2.2.4.3 Zero tillage seeding 9

2.2.4.4 Dry seeding 10

2.3 Weeds 10

2.3.1 Effects of weeds on rice 10

2.3.2 Weeds in direct seeded rice 12

2.3.3 Weed control 12

2.3.4 Planning effective control 12

2.4 Weed control methods 13

2.4.1 Cultural control methods 13

2.4.2 Biological weed control methods 13

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2.4.3 Problems of biological weed control methods 13

2.4.4 Mannual weed control 14

2.4.5 Problems of Mannual weed control 14

2.4.6 Chemical weed control methods 15

2.4.7 Problems of chemical weed control methods 15

2.4.8 Mechanical weed control 16

3 MATERIALS AND METHODS

3.1 Location of studies 17

3.2 Characterization of Soil 17

3.2.1 Particle size analysis 17

3.2.2 pH of saturated soil paste 17

3.2.3 Soil saturated extract 18

3.2.4 Soil organic matter 18

3.2.5 Electrical conductivity of saturated soil extract 18

3.2.6 Total soluble salts 18

3.2.7 Available phosphorous 19

3.2.8 Extractable potassium 19

3.3 Treatment and layout of experiments 21

3.4 Planting of crop 25

3.4.1 Land preparation 25

3.4.2 Seeding method, planting geometry and fertilizer application 25

3.4.3 Water management 25

3.4.4 Harvesting and threshing 25

3.5 Weed management in experiment I 25

3.6 Weed management in experiment II 25

3.7 Observations 26

3.7.1 Yield related traits 26

3.7.2 Quality parameters 26

3.7.3 Growth parameters 26

3.7.4 Weed parameters 27

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3.8 Statistical analysis 31

4 REULTS AND DISCUSSION

STUDY-I : COMPARISON OF DIFFERENT WEED

MANAGEMENT STRATEGIES IN DRILL SEEDED

AEROBIC RICE

4.1 Weed biomass of sedges (15 DAS) 32

4.2 Weed biomass of broad leaf weeds (15 DAS) 32

4.3 Weed biomass of sedges (30 DAS) 34

4.3 Weed biomass of broad leaf weeds (30 DAS) 34

4.5 Weed biomass of sedges (45 DAS) 34

4.6 Weed biomass of broad leaf weeds (45 DAS) 37

4.7 Total weed biomass (15 DAS) 37

4.8 Total weed biomass (30 DAS) 37

4.9 Total weed biomass (45 DAS) 40

4.10 Plant Height 40

4.11 Total number of tillers 43

4.12 Number of fertile tillers 43

4.13 Number of unfertile tillers 47

4.14 Panicle length 47

4.15 Kernels per panicle 47

4.16 1000-kernel weight 51

4.17 Biological yield 51

4.18 Paddy yield 51

4.19 Straw yield 57

4.20 Harvest Index 57

4.21 Opaque kernels 57

4.22 Abortive kernels 60

4.23 Normal kernels 60

4.24 Sterile spikelets 60

4.25 Leaf area index 62

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4.26 Crop growth rate 62

4.27 Leaf area duration 62

4.28 Total dry matter 66

4.29 Net assimilation rate 66

4.30 Economic analysis 69

Discussion 73

STUDY-II: EVALUATION OF DIFFERENT INTER

CULTURAL IMPLEMENTS FOR WEED

MANAGEMENT IN DRILL SEEDED AEROBIC RICE

4.31 Weed biomass of broad leaf weeds (15 DAS) 80

4.32 Weed biomass of sedges (15 DAS) 80

4.33 Weed biomass of broad leaf weeds (30 DAS) 83

4.34 Weed biomass of sedges (30 DAS) 83

4.35 Weed biomass of broad leaf weeds (45 DAS) 86

4.36 Weed biomass of sedges (45 DAS) 88

4.37 Total weed biomass (15 DAS) 88

4.38 Total weed biomass (30 DAS) 91

4.39 Total weed biomass (45 DAS) 91

4.40 Plant height 94

4.41 Total number of tillers 97

4.42 Number of fertile tillers 99

4.43 Number of unfertile tillers 101

4.44 Panicle length 103

4.45 Kernels per panicle 103

4.46 1000-kernel weight 106

4.47 Biological yield 108

4.48 Paddy yield 110

4.49 Straw yield 112

4.50 Harvest Index 112

4.51 Opaque kernels 115

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4.52 Abortive kernels 117

4.53 Normal kernels 117

4.54 Sterile spikelets 120

4.55 Leaf area index 122

4.56 Crop growth rate 124

4.57 Leaf area duration 124

4.58 Total dry matter 127

4.59 Net assimilation rate 127

4.60 Economic analysis 130

Discussion 135

5 Summary 139

References 144

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LIST OF TABLES

Table Title Page

3.1 Physio-chemical analysis of experimental site 19

3.2 Meteorological data during the year 2008 at experimental site 20 3.3 Meteorological data during the year 2009 at experimental site 20 3.4 Weed flora 27 4.1 Effect of different weed management strategies on weed

biomass (45 DAS) 41

4.2 Effect of different weed management strategies on plant height

41

4.3 Effect of different weed management strategies on total number of tillers

44

4.4 Effect of different weed management strategies on number of fertile tillers

44

4.5 Effect of different weed management strategies on number of unfertile tillers

45

4.6 Effect of different weed management strategies on panicle Length

45

4.7 Effect of different weed management strategies on kernels per panicle

48

4.8 Effect of different weed management strategies on 1000 kernel weight

48

4.9 Effect of different weed management strategies on biological yield

52

4.10 Effect of different weed management strategies on paddy yield

52

4.11 Effect of different weed management strategies on straw yield

58

4.12 Effect of different weed management strategies on harvest index

58

4.13 Effect of different weed management strategies on opaque kernels

59

4.14 Effect of different Weed management strategies on abortive kernels

59

4.15 Effect of different weed management strategies on normal kernels

61

4.16 Effect of different weed management strategies on sterile spikelets

61

4.17 Economic analysis 2008 69 4.18 Economic analysis 2009 70 4.19 Dominance analysis 2008 71 4.20 Marginal analysis 2008 71

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4.21 Dominance analysis 2009 72 4.22 Marginal analysis 2009 72 4.23 Effect of different weed control implements on weed

biomass at 45 DAS 95

4.24 Effect of different weed control implements on plant height 96 4.25 Effect of different weed control implements on total number

of tillers 98

4.26 Effect of different weed control implements on number of fertile tillers

100

4.27 Effect of different weed control implements on number of unfertile tillers

102

4.28 Effect of different weed control implements on panicle length 104 4.29 Effect of different weed control implements on kernels per

panicle 105

4.30 Effect of different weed control implements on 1000 kernel weight

107

4.31 Effect of different weed control implements on biological yield

109

432 Effect of different weed control implements on paddy yield 111 4.33 Effect of different weed control implements on straw yield 113 4.34 Effect of different weed control implements on harvest index 114 4.35 Effect of different weed control implements opaque kernels 116 4.36 Effect of different weed control implements abortive kernels 118 4.37 Effect of different weed control implements normal kernels 119 4.38 Effect of different weed control implements on sterile

spikelets 121

4.39 Economic analysis 2008 131 4.40 Economic analysis 2009 132 4.41 Marginal analysis 2008 133 4.42 Marginal analysis 2009 134

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LIST OF FIGURES Figure Title Page

3.1 Layout plan for experiment-I 22

3.2 Layout plan for experiment-II 24

4.1 Effect of different weed management strategies on weed biomass of sedges and broad leaf weeds at 15 DAS

33

4.2 Effect of different weed management strategies on weed biomass of sedges and broad leaf weeds at 30 DAS

35

4.3 Effect of different weed management strategies on weed biomass of sedges and broad leaf weeds at 45 DAS

36

4.4 Effect of different weed management strategies on total weed biomass at 15 DAS

38

4.5 Effect of different weed management strategies on total weed biomass at 30 DAS

38

4.6 Effect of different weed management strategies on total weed biomass at 45 DAS

39

4.7 Relationship between total weed biomass (45 DAS) and plant height

42

4.8 Relationship between total weed biomass (45 DAS) and fertile tillers

46

4.9 Relationship between total weed biomass (45 DAS) and kernels per panicle

49

4.10 Relationship between total weed biomass (45 DAS) and 1000 kernels weight

50

4.11 Relationship between total weed biomass (45 DAS) and paddy yield

53

4.12 Relationship between number of fertile tillers and paddy yield 54 4.13 Relationship between kernels per panicle and paddy yield 55 4.14 Relationship between 1000 kernel weight and paddy yield 56 4.15 Effect of different weed management strategies on periodic

changes in leaf area index 63

4.16 Effect of different weed management strategies on periodic changes in crop growth rate

64

4.17 Effect of different weed management strategies on cumulative leaf area duration at 105 DAS

65

4.18 Effect of different weed management strategies on total dry matter at 105 DAS

67

4.19 Effect of different weed management strategies on NAR at 105 DAS

68

4.20 Effect of different weed control implements on weed biomass of broad Leaf weeds (15 DAS)

81

4.21 Effect of different weed control implements on weed biomass of sedges (15 DAS)

82

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4.22 Effect of different weed control implements on weed biomass of broad Leaf weeds (30 DAS)

84

4.23 Effect of different weed control implements on weed biomass of sedges (30 DAS)

85

4.24 Effect of different weed control implements on weed biomass of broad Leaf weeds (45 DAS)

87

4.25 Effect of different weed control implements on weed biomass of sedges (45 DAS)

89

4.26 Effect of different weed control implements on total weed biomass (15 DAS)

90

4.27 Effect of different weed control implements on total weed biomass (30 DAS)

92

4.28 Effect of different weed control implements on total weed biomass (45 DAS)

93

4.29 Effect of different weed control implements on periodic changes in leaf area index

123

4.30 Effect of different weed control implements on periodic changes in crop growth rate

125

4.31 Effect of different weed control implements on cumulative leaf area duration at 105 DAS

126

4.32 Effect of different weed control implements on total dry matter at 105 DAS

128

4.33 Effect of different weed control implements on NAR at 105 DAS

129

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LIST OF ABBEREVATIONS

ABBEREVATION DESCRIPTION DAS Days after sowing DSR Direct seeded rice LAI Leaf area index LAD Leaf area duration CGR Crop growth rate TDM Total dry matter NAR Net assimilation rate HI Harvest index LSD Least significant difference Zn Zinc t Ton ha-1 Per hectare cm Centimeter g Gram Fig Figure m-2 Per square meter % percentage @ At the rate of kg Kilogram ppm Parts per million N Nitrogen P Phosphorus K Potassium

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ABSTRACT

Traditional rice cultivation by puddling and manual transplanting is a labor intensive activity and

require significant quantities of water and power. The increasing scarcity of water threatens the

sustainability of transplanted rice. In many areas of Asia, transplanting of rice is being replaced

by direct seeding as farmers respond to increased labor cost and decreased water availability but

weed control is one of the major constraints to direct seeding. So, to control weeds in direct

seeded rice studies were designed. Experiments were conducted for two years to develop

sustainable and economical methods for managing weeds in aerobic rice grown by direct-seeding

at Student’s Farm, Department of Agronomy, University of Agriculture, Faisalabad during the

years 2008 and 2009. The first experiment was laid out in RCBD having five weed control

approaches; hand weeding, hoeing (with kasula), inter row cultivation with tine cultivator, inter

row cultivation with spike hoe and chemical control with Nominee 100 SC along with control

(no weeding). Weed dry weight was 300 g m-2, 257 g m-2, 225 g m-2 and 157 g m-2 less in hand

weeding, hoeing tine cultivator and Nominee 100 SC respectively than no weeding. Maximum

fertile tillers were recorded in hand weeding (369.73 m-2) and were followed by hoeing (356.94

m-2) and tine cultivator (346.78 m-2). Hand pulling, hoeing, tine cultivator, Nominee and spike

hoe gave 28, 25, 22, 12 and 6% more number of kernels per panicle respectively. Paddy yield

was 221, 203, 181 and 105% more in hand weeding, hoeing tine cultivator and Nominee 100 SC

respectively than no weeding. Highest net returns (Rs. 56905) were obtained by hand weeding

while highest BCR (1.75) was obtained in tine cultivator. A second experiment was laid out in

split plot design randomizing inter row cultivation implements in main plots and inter row

cultivation frequencies in sub plots. Weed dry weight was 199.16 g m-2 less when tine cultivator

was used at 15, 25, 35 and 45 DAS as compared to weed dry weight in inter row cultivation at15

days after seeding (DAS). More fertile tillers in tine cultivator and spike when used at 15, 25, 35

and 45 DAS were observed. Paddy yield was 159% more when tine cultivator was used at 15,

25, 35 and 45 as compared to paddy yield in inter row cultivation at15 DAS. Tine cultivator gave

maximum net return and BCR when used at 15, 25, 35 and 45 DAS. Tine cultivator gave

maximum net return and BCR when used at 15, 25, 35 and 45 DAS. Both experiments were

replicated thrice. Net plot size was 3.0 m x 6.0 m in both experiments. Weed control by tine

cultivator displayed excellent rice yields when repeated cultivation was done, and with the

reduced labor inputs compared to hand weeding and hoeing, is a viable and economical method.

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CHAPTER 1

INTRODUCTION

Rice (Oryza sativa L.) is a principal source of food for more than half of the world

population, especially in South and Southeast Asia and Latin America. Rice is the third largest

crop after wheat and cotton and second major grain crop of Pakistan. It accounts for 6.4 % of

value added in agriculture and 0.9 % in GDP of Pakistan. In Pakistan, it is grown on an area of

about 2.88 m ha and its total production is 4.82 million tons with an average paddy yield of 2.03

t ha-1. Rice is food as well as contributing 20 % in foreign exchange earnings of Pakistan (GOP,

2011).

Rice is cultivated in many parts of the world in different ways; transplanted flooded rice,

alternate wetting and drying, rice on raised beds and aerobic rice. The main cropping differences

are between aerobic and puddled rice. Seventy five percent of Asian rice is produced in irrigated

puddled fields with generally high irrigation requirements to sustain sub merged conditions for

most of the growing season (Bouman and Toung, 2003). In Pakistan rice is grown under diverse

climatic and edaphic conditions. Basmati cultivars (Super Basmati, Basmati Pak and Basmati

385) dominate in the traditional rice tract of the Punjab known as “Kalar” tract. At high altitudes

like Swat where temperature is low, temperate Japonica rice (IR-6, Shadab and Shua-92) is

grown. In the South of Khyber Pakhtoon Kha, Sindh and Baluchistan coarse rice (IR-6, IR-9,

DR-82 and DR-83) is grown. Rice is also grown on, ‘salt affected and water logged soils’ such

soils are generally unfit for the production of other agricultural crops (Funakawa et al., 2000).

Water is the major factor limiting crop production in many parts of the world. However,

concerns are increasing about its future availability even in areas where water for irrigation is

currently plentiful (Rijsberman, 2006). Bouman and Tuong (2003) reported that in 2025, 15 out

of 75 m ha of Asian transplanted rice crop will experience water shortage. Water shortage is a

great threat to Pakistan agriculture due to huge exploitation of available water. Agriculture

consumes 70 % of the world water use (IWMI, 2007). Owing to some irrigation water rice is

mostly grown by transplanting method. In this method field is puddled before rice transplantation

then water is impounded. This continuous flooding requires lot of water and high labor (Bhushan

et al., 2007). Pakistan is confronting severe canal water shortage due to lack of interest for the

construction of new surface reservoirs. Surface water availability in 2005-2006 was 100.9 MAF

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which decreased to 93.3 MAF in 2009-2010 (GOP, 2010). Due to constant decrease in

availability of irrigation water, it seems very difficult to grow rice with transplanting method in

future.

Paddy yield of Pakistan is either stagnant or declining, mostly due to late sowing, low

availability of water, nutrient imbalances, sub-optimum plant population, high infestation of

weeds and labor shortage in transplanted rice (Mann and Ashraf, 2001). Rapid economic

development has great influence on agricultural labor availability as it promotes rural labor

migration to urban areas for higher income from secondary industries resulting labor shortage in

rural area (Habito and Briones, 2005). Technological innovation is needed to allocate less labor

input for production of rice. Agricultural mechanization would be one possibility for labor-

saving. The alternative way is to partly shift from traditional transplanting to more labor and

water saving methods for rice production like alternate wetting and drying, rice on raised beds

and aerobic rice.

Aerobic rice is a good alternative of transplanting. Aerobic rice refers to the process of

establishing rice crop from seeds sown in the field rather than by transplanting seedlings (Rao et

al., 2007). This type of rice is also known as direct seeded rice (DSR). Direct seeded rice avoids

puddling and continuous wet soil conditions and thus decreases considerably the overall water

demand for rice culture while yield potential is equivalent to the transplanted rice (Awan et al.,

1989). In South Asia, direct seeded rice is being practiced in terraces on sloppy lands of

Bangladesh and along Western Himalayan region of India (Gupta et al., 2007). Direct seeding

with subsequent saturated conditions on flat land decreases the amount of water required during

land preparation (Bouman and Toung, 2003). Water saving of 35–57 % has been reported for

aerobic rice sown into non-puddled soil as compared with continuously flooded (up to 5 cm)

transplanted rice (Bhushan et al., 2007). Bouman and Toung (2003) also found that aerobic rice

can reduce water use by as much 50 % while maintaining a moderately high yield as compared

with transplanted rice. The DSR required 66 % less labor than transplanted rice (Ho and Romli,

2000).

Weeds pose a serious threat to the direct seeded rice crop by competing for nutrients,

light, space and moisture throughout the growing season. Ramzan (2004) reported up to 74 %

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yield reduction in direct seeded rice due to weeds. Aerobic soil conditions, dry-tillage practices

and alternate wetting and drying are favorable for germination and growth of highly competitive

weeds, causing grain yield losses up to 91 % (Elliot et al., 1984). Choubey et al. (2001) and

Bahar and Singh (2004) also reported that weeds can decrease yield of DSR from 75 to 100 %. If

weeding is delayed beyond 20 days after emergence, permanent damage may be done to rice

crop. During early establishment, weeds make 20-30 % of their growth while the crop makes 2-3

% of its growth (Moody, 1990). The optimum time at which crop must be free of the adverse

effect of weeds is referred to as the critical period of weed competition. Almost all the annual

crops are susceptible to weed competition during the early stage of development, particularly

within the first one-third to one-half of the crop life cycle (Mercado, 1979). Chauhan and

Johnson (2011) concluded that the critical period for controlling of rice weeds in DSR was

between 14 - 41 days after sowing (DAS). So, in critical period rice must be free from weeds for

better production.

In the light of above discussion it is concluded that an effective, economical and timely

weed control strategy must be developed for direct seeded rice. With the availability of proper

weed management technology, it is possible to raise the productivity of direct seeded rice. Weeds

in direct sown rice can be controlled by various methods. Weeds could be controlled by hand

weeding, chemical and mechanical methods. Weeds are manually removed or uprooted in hand

weeding. Hand weeding is commonly practiced against weeds on small-scale rice farms

(Adesina et al., 1994). Farmers in Africa use family labor to control weeds in DSR, weeding

starts at 15-30 DAS and continue for many days depending on the type of weeds (Oteng and

Sant’Anna, 1999). Similarly, in Cambodia hand weeding is done at least twice and commonly

thrice (Makara et al., 2001). Manual weeding can control weeds but it is laborious and time

consuming (Stessens, 2002). Herbicides provide effective weed management in DSR (Azmi et

al., 2005) using as pre emergence or post emergence (Rao et al., 2007). Although chemical

control provides a considerable weed control on DSR but availability of required weedicides is

limited in Pakistan. Secondly weed resistance to various chemicals is also a problem which may

be crested in future. Another way to control weeds in direct seeded rice is use of manually or

mechanically operated implements. In line sown DSR weeds can be controlled effectively by the

use of different inter row implements as reported by Islam et al. (2004). Remington and Posner

(2000) demonstrated effective weed control in DSR using a mechanical weeder. Fazlolallh et al.

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(2001) an Iranian scientist compared two mechanical weeders in rice; mechanical weeder with

engine power and mechanical weeder without engine power both provided effective and

economical weed control resulting in good yield.

The purpose of this study is to develop and test economical weed control methods that

would allow earlier and more rapid weeding in direct seeded rice. These options included: row

seeding rice with automatic drill to maintain row to row distance, mechanical inter row

cultivation with manual drawn equipment and weed control with herbicides. Keeping in view the

above facts this study was planned with the following objectives.

1. To assess the production potential of direct seeded rice.

2. Assessing the performance of different implements for inter-row weed control.

3. To identify the most suitable and economical weed control method.

4. Comparison of different weed management strategies and their impact on growth and

yield parameters of direct seeded rice.

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CHAPTER 2

REVIEW OF LITERATURE

On the basis of studies conducted on various aspects of aerobic rice cultivation system, this

chapter is divided into following sections.

1. Rice

2. Crop establishment methods of rice

3. Weeds

4. Methods of weed control

2.1 Rice

Rice is monocot plant Oryza sativa (Asian rice) or Oryza glaberrima (African rice). Rice

belongs to the genus Oryza of the sub tribe oryzineae in the family Gramineae. Its genus Oryza

comprises 25 accepted species, of which 23 are wild and two (Oryza sativa and Oryza

glaberrima) are cultivated. All the rice varieties of Europe, America and Asia belong to the

specie Oryza sativa, while many of the cultivated varieties of West Africa belong to the specie

Oryza glaberrima. Rice is used as staple food for more than half of the world (Chauhan and

Johnson, 2011). About 90 % of rice is produced in the South Asian countries on an area of

153.25 m ha with an average annual production of about 610 million tons, extending from the

Indo-Pak subcontinent to Japan (IRRI, 2004).

2.1.1 History of domestication and cultivation

The commonly accepted view is that rice was first domesticated in the region of the

Yangtze River valley in China (Vaughan et al., 2008). Morphological studies of rice phytoliths

from the Diaotonghuan archaeological site show the transition from cultivation of wild rice to

domesticated rice. Changes in the morphology of Diaotonghuan phytoliths dating from 10,000-

8,000 years before present show that rice had by this time been domesticated (Mac Neish and

Libby, 1995). Soon afterwards, the two major varieties of Indica and Japonica/Sinica rice were

grown in Central China (Harris, 1996). In the late 3rd millennium before Christ (BC), there was

a rapid expansion of rice cultivation into mainland of Southeast Asia and westwards across India

and Nepal (Harris, 1996).

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Korean archaeologists claimed to have discovered the world's oldest domesticated rice

(David, 2003). Although combined effort by the Stanford University, New York University,

Washington University in St. Louis, and Purdue University has provided the strongest evidence

yet there is only one origin of domesticated rice, in the Yangtze Valley of China (Molina et al.,

2011).

Thirty seven archeological sites have shown traces of rice cultivation in ancient time in

Indo-Pak subcontinent. These sites include Mohenjodaro in Pakistan, Gujrat, Lohal, Rangpur and

Uttar Pradesh in India (Chang, 1967). The earliest remains of rice in the Indian subcontinent

have been found in the Indo-Gangetic Plain and date from 7000-6000 BC though the earliest

widely accepted date for cultivated rice is placed at around 3000–2500 BC with findings in

regions belonging to the Indus Valley Civilization (Pokharia et al., 2009). It then spread to all the

fertile alluvial plains watered by rivers. Cultivation and cooking methods are thought to have

spread to the west rapidly and by medieval times, southern Europe saw the introduction of rice as

a hearty grain. According to Zohary and Maria (2000), Oryza sativa was recovered from a grave

at Susa in Iran (dated to the 1st century AD) at one end of the ancient world, another

domestication of rice in the South Asia.

2.2 Crop establishment methods

The production system of Asia is undergoing adjustments in response to rising scarcity of

land, water and labor. A major adjustment can be expected in the method of crop establishment.

Major determinants of farmer’s choice of crop establishment method are rainfall pattern,

sufficient water supply, weed incidence and field elevation. Availability of labor and power for

land preparation and wage rates were found to be among the major economic factors for the

choice of crop establishment method (Pandey and Velasco, 1999). Rice is grown by two methods

as discussed in the following sections.

2.2.1 Flooded rice

Commonly flooded rice is grown throughout the world. In this method first nursery plants

are grown which are then transplanted in the leveled and puddled field for establishment of crop.

This transplantation of rice seedling may be manual or by machines. Traditional method of

transplantation requires lot of labor and continuous water inputs. Shortage of labor at this critical

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stage often results in low production and increases labor costs. Rice has lower water productivity

than some other cereal crops (Bhuiyan, 1992). Puddling helps to decrease percolation losses and

control of weeds. However, the puddling process results in subsurface compaction (Kukal and

Aggarwal, 2003), which impedes the growth and yield of succeeding wheat crop. Puddling also

affects soil health due to mechanical dispersion of soil particles and making tillage operations

difficult, requiring more energy in succeeding crops such as wheat (Singh et al., 2003). Water in

conventional rice crop represents a major and necessary production cost for the growers.

Farmers in many rice growing areas have restricted availability of irrigation water and in

future it is predicted that in Asia, 17 m ha of irrigated rice areas may experience ‘‘physical water

scarcity’’ and 22 million ha may have ‘‘economic water scarcity’’ (Toung and Bouman, 2003).

Thus water scarcity threatens the sustainability of irrigated rice ecosystems since it may no

longer be feasible for farmers to undertake wet cultivation and flood fields to ensure good crop

growth and control weeds (Johnson and Mortimer, 2005). The increasing cost of labor threatens

the sustainability of transplanted rice within the rice wheat system of the Indo Gagnetic Plains.

2.2.2 Aerobic rice

One of the strategies to combat water shortage is the system of aerobic or direct seeded

rice. Aerobic rice production consists of sowing seeds in dry soils. Decreased water input, low

labor requirement and timely sowing can be listed as possible benefits of the DSR (Bhushan et

al., 2007). In aerobic or DSR, generally cultivars could have high yield, input-responsive and

could adapt to mild to medium water stress (Bouman et al., 2005). Especially on coarse textured

soils with high seepage and percolation rates, aerobic rice has an advantage over systems that

include saturated or partially flooded soil conditions (Wang et al., 2002). Aerobic rice systems

have been developed since the mid-eighties and aerobic rice is now grown commercially in many

countries of the world especially in Brazil and Northern China (Wang et al., 2002).

According to Guimaraes and Stone (2000), aerobic rice yields similar to that from

transplanted. Direct seeding is cost effective, can save water through earlier rice crop

establishment and allows early sowing of wheat (Ladha et al., 2003; Singh et al., 2003). Aerobic

rice cultivation is a new technology that suits to high yielding varieties with a much lower water

input than that required for traditional rice cultivation. A commercial cropping system based on

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aerobic rice has spread widely in Brazil as a result of the development of improved high yielding

varieties (Pinhiero et al., 2006).

Paddy yield of 5-6 t ha-1 can be achieved in the aerobic rice system (George et al., 2002).

By limiting water losses through seepage, percolation and evaporation, aerobic rice limit total

water use by 27-51 % as compared with transplanted rice crop (Bouman et al., 2005). Similar

observations were reported by Wang et al. (2002) that aerobic rice system can decrease water

application by 44 % compared to the conventionally transplanted rice system, mostly through

decreasing percolation, seepage and evaporation losses, while maintaining yield at a satisfactory

level.

The water requirement of aerobic rice is potentially much less than that of flooded rice

because of: (1) the absence of water use for wet land preparation (puddling), (2) the absence of

continuous seepage and (3) the absence of evaporation losses from the pounded water layer

(Bouman et al., 2005). The potential water saving at field level when rice can be grown as an

upland crop are large, especially on soils with high seepage and percolation rates (Bouman

Toung, 2001). Properly managed aerobic rice results in reasonable yields as Tabbal et al. (2002)

reported that DSR yielded the same as transplanted rice while water inputs were decreased by 35

% and water productivity increased by 45 % compared with that under flooded conditions.

2.2.3 Global distribution of direct seeded rice

Growing of direct seeded rice varies broadly across countries and regions. DSR is planted

either in a dry seeded or wet seeded system in the United States (Gianessi et. al., 2002), Australia

and Europe (Ferrero and Nguyen, 2004). Pandey and Velasco (2002) reported that direct seeding

was rising rapidly in Asia, with 21-22 % of the total rice area being dry seeded or wet seeded.

Dry direct seeding in India is extensively practiced in rain fed lowlands, uplands and

flood prone areas, while wet seeding is a common practice in irrigated areas (Mishra et. al.,

2005). In Vietnam, especially in the Mekong Delta, rice is sown wet seeded and broadcasting is

common practice (Luat, 2000). Kim et al. (2001) reported that 11 % of the total rice was direct

seeded in Korea, dry seeding was 6.4% and wet seeding 4.7 %.

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In the northern provinces of Cambodia, in wet season, 80-90 % of rice fields are dry

direct seeded (CIAP, 1998). In Philippine both dry and wet seeding is commonly practiced (De

Dios et. al., 2005). In Thailand, the rain fed rice area is dry direct seeded, whereas irrigated area

in the Central Plain is mostly wet seeded (Azmi et al., 2005). In Malaysia, wet seeding is favored

but is encouraged only where efficient water management is possible (Azmi et al., 2005). In

Northern and North Eastern regions of China rice seeded directly into aerobic non puddled soils,

area under direct seeding in these regions is 80,000 and 60,000 ha, respectively (Xie et al.,

2005).

2.2.4 Crop establishment methods of direct seeded rice

Farmers usually adopt four types of crop establishment methods in relation to

hydrological conditions for direct seeding of rice.

2.2.4.1 Wet seeding

Rice seeds are soaked for 24 hrs and incubated from 24 to 36 hrs. Pre-germinated seeds

are then sown on to the soil surface. Typically water is reintroduced into fields for weed

suppression 7-10 days after sowing (DAS). Weed infestation is usually lower in wet seeded rice

than in dry-seeded and zero-tilled rice (Balasubramanian and Hill, 2002).

2.2.4.2 Water seeding

Pre-germinated seeds are sown directly into water. Water seeding enables farmers to

proceed without waiting for the flood water recession necessary for wet seeding and to minimize

the risk of late season drought in the crop. Fields are drained gradually as the crop develops. This

practice substantially reduces weed infestations during early crop establishment (Yamauchi

1996).

2.2.4.3 Zero-tillage seeding

In South Vietnam after the harvest of the wet seeded rice crop in January or February,

rice straw is scattered over the fields, dried for a few days and burned. Fields are then irrigated to

an average depth of 5 cm before sowing pre germinated seeds onto the wet ash layer. In this way,

zero tillage shortens the turnover time when cultivating three rice crops per year. However, zero

tillage results in high weed infestations, particularly of perennial weeds such as Paspalum

distichum (Hach et al., 1997) and insect pest predators have been recorded significantly lower in

fields where stubble is burned (Loc et al., 1998).

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2.2.4.4 Dry seeding

This method is practiced when water is in short supply. Land preparation involves

ploughing or rotovation. Non-germinated seeds are broadcasted or drill seeded in dry or moist

soil. Broadcasted seeds are covered by harrowing; more seeds are required for broadcast than for

drill seeding and stand establishment is poor with broadcasting. Dry seeded rice culture is

practiced in Africa, Australia, Europe, and USA (Kwesi and De Datta, 1991).

2.3 Weeds

Weeds are plants growing in an improper place in competition with a crop. Thus, a plant

species cannot be classified as a weed under all conditions. The major weeds associated with rice

include grasses Dactyloctenium aegyptium (L.) Echinochloa crus-galli (L.), Echinochloa colona

(L.) and Leptochloa chinensis (L.), Cyperus rotendusand and broadleaf weeds Commelina

benghalensis (L.), Caesulia axillaris, Eclipta prostrate (L.) Euphorbia hirta (L.), Portulaca

oleracea (L.), Trianthema portulacastrum (L.) and Lindernia spp. (Singh et al., 2006).

2.3.1 Effects of weeds on rice

Weeds have different effects on rice. Weed infestations primarily constrain rice

production by reducing grain yield. Yield reductions caused by uncontrolled weeds throughout a

crop season have been estimated to be from 44 to 96 %, depending on the rice culture.

Worldwide some 9 % loss of rice yield can be attributed just to weeds (Oerke and Dehne, 2004).

There is considerable variation in yield loss to weeds among countries.

The cost of rice weed control including herbicides, cultural and mechanical practices and

hand weeding, is estimated to be about 5 % of world rice production and amount to US $ 3.5

billion annually. When the 9 % loss of rough rice paddy yield is added to this cost, the world’s

total estimated cost for rice weeds and their control amounts to 15 % of total annual production

of rice valued at US $ 10.5 billion (Kwesi De Datta, 1991). Similar findings were observed by

Norton et al. 2010 who reported that herbicide sales for rice crops globally grew at an average

rate of more than 2 percent year-1 from US $ 741 million in 1980 to US $ 1.34 billion in 2007

and global sale of herbicides for application in rice farming systems could reach US $ 3 billion

per year by 2025 (Zhang et al., 2004).

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Weeds indirectly limit production by serving as hosts for organisms that adversely affect

rice. Weeds provide food, shelter and reproduction sites for insects, nematodes, pathogens and

rodents. Some weeds that serve as alternate hosts to rice pests are Cynodon dactylon, Cyperus

iria, Echinochloa colona, Echinochloa crus-galli and Cyperus rotundus. This indicates the

importance of recognizing weeds as secondary hosts for pests and of removing weeds from the

margins of rice fields to prevent continued infection of the rice crop.

Weeds hamper rice harvesting and increase harvest costs through direct interference with

the harvesting operation and by causing lodging. Weed seeds contaminate rough rice, thus

reducing grain quality and market value. For example, the weed red rice has a pigmented layer

that shatters easily and readily contaminates rough rice. Removing all traces of the pigmented

layer requires intense milling resulting in decreased grain quality and increased cost. The

drudgery of weeding and labor shortages has made rice farming unattractive. In most tropical

countries, farmers spend more time on weeding by hand or with simple tools, than on any other

farming task.

Nutrient availability and favorable temperatures throughout the year, especially in the

tropics, allow luxuriant aquatic weed growth in rice fields and weeds compete for nutrients with

rice (Phoung et al., 2005). Heavy aquatic weed infestation causes excessive water loss through

evaporation and impedes water flow in irrigation canals. In some cases, aquatic weeds may be a

health hazard to persons living near impounded water. Weeds interfere with rice growth by

competing for one or more growth limiting resources such as light, nutrients and water.

Allelopathy (chemical production by living or decaying weed plant tissues) may also adversely

affect the growth of a neighboring rice plant. Rice and rice weeds have similar requirements for

growth and development. Competition occurs when one of the limiting resources falls short of

the combined requirements of both. The degree of rice-weed competition depends on rainfall,

rice variety, soil factors, weed density, duration of rice and weed growth. Cultural practices

greatly alter the competitive relationship between rice and weeds. Thus, different cultures

(irrigated, rain fed lowland, upland, and deepwater) will be subjected to different kinds and

degrees of weed competition. To understand this competition, it is essential to know the growth

requirements of rice and helpful to know the growth requirements of weeds.

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2.3.2 Weeds in direct seeded rice

Weeds are the main problem in direct seeded rice which may cause 100 % failure of the

crop. Aerobic soil, dry tillage and alternate wetting and drying conditions are favorable to the

germination and growth of weeds causing grain yield losses up to 90 % (Rao et al., 2007). Crop

loss due to weed competition varies with the duration of weed infestation of the crop. The crop is

likely to experience yield reduction, unless weeds are kept free during a part of its growing

period (Azmi et al., 2007). Johnson et al. (2004) noted that in direct seeded rice weeds can

emerge at the same time or before the rice plants, causing serious competition.

The labor requirement for weeding is a major impediment to the adoption of water saving

aerobic rice and increasing the productivity of aerobic rice based cropping systems (Singh et al.,

2006). After broadcast or drill seeding rice into dry soil field is irrigated just enough to provide

the soil moisture that allows the seeds to germinate. Thus, aerobic conditions remain ideal for the

germination of upland and aquatic weeds and weed problems are much worse in dry seeded

irrigated than in wet seeded rice (Kwesi and De Detta, 1991). Weeds are a major hurdle to broad

adoption of aerobic rice and greatest yield limiting constraint to aerobic rice, contributing about

50 % to yield losses (WARDA, 1996). Aerobic rice is subjected to more severe weed infestation

than transplanted lowland rice, because direct seeded aerobic rice germinates simultaneously

with weeds, in this way weeds dominates the crop due to the lack of water layer that suppress the

weed germination (Moody, 1983).

2.3.3 Weed control

Weeds have always reduced rice yields. As a result different weed control methods have

evolved. Farmers consider financial resources and availability of labor in deciding what weed

control method to use. Problems of input availability, availability of new technologies, specific

weed problems, farm size and availability of family labor are basic management factors in

making weed control decisions.

2.3.4 Planning effective control

Planning is important in making appropriate decisions on weed control. Unfortunately,

weed control usually is not planned. The decision to control is not made until the problem has

become serious, when control may be uneconomical, ineffective. Advance knowledge of weed

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problems can be obtained by surveying and recording the weed species in a rice field after rice

emergence. This record is useful in planning weed control and crop rotation programs.

2.4 Weed control methods

Weed control can be grouped into cultural, manual, mechanical, chemical, and biological

control methods. Each control method has advantages and disadvantages.

2.4.1 Cultural control methods

A basic principle of cultural control is to increase the competitive ability of rice and

enable it to suppress weed growth. Vigorous rice crop competes more effectively with weeds.

Cultural control methods includes; use of weed free and certified seed land preparation, cultivar

selection, time of seeding, planting method, crop rotation, plant population, fertilization and

water management (Rao et al., 2007).

2.4.2 Biological weed control methods

Several biological agents such as insects, mites, and fungi have been used successfully to

control rice weeds. The possibility of using tadpole shrimp (Triopus longicaudatus, T. granaris,

and T. cancriformis) for weed control in transplanted rice has been demonstrated in Japan. The

small crustaceans feed on weed seedlings and disturb their roots by mechanical agitation of the

soil. Labor for hand weeding in farmers’ fields was reduced 70-80 % in initial field trials with

tadpole shrimp (Matsunaka, 1975).

2.4.3 Problems of biological weed control methods

Tadpole shrimp (Triopus longicaudatus, T. granaris, and T. cancriformis) decreases

weed infestation but later on becomes a pest cause serious problems to rice crop (Matsunaka,

1975). Biological agents are selective in their control action and their activity may be restricted

to a single weed. Biological control programs may be applicable to an introduced perennial weed

growing in areas that are seldom disturbed, such as pastures, forests and water bodies. In a rice

cropping situation with a mixed weed flora, the selective control of a single weed will not solve

the weed problem and biological agents also work slowly.

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2.4.4 Manual weed control

Manual weed control includes removing and hand pulling. This method is the oldest and

in many cases, the farmer’s only way of controlling weeds in rice. Manual weeding is very

effective weed control method (Singh, 2005). Ekleme et al. (2009) conducted two field

experiments in Nigeria, results showed that lowest weed biomass (48 g m-2) was produced by

weeding twice with highest plant height (116 cm), tillers (203 m-2) and grain yield (3.62 t h-1) in

direct seeded rice. Singh et al. (2008) noted that hand weeding twice resulted in significantly

lower weed biomass (61.6 g) as compared to no weeding (329.5 g). Singh et al. (2007)

concluded that hand weeding six times in dry seeded rice resulted in lowest weed biomass (0 g

m-2) with highest panicle length (24.5 cm), panicles (160 m-2), grains panicle-1 (96), 1000 grain

weight (25.9 g), grain yield (5.58 t h-1) and straw yield (7.28 t h-1). Mann et al. (2007) conducted

an experiment and results revealed that in hand weeding with lowest weed biomass highest plant

height (92 cm), panicles (215 m-2), panicle length (27.3 cm), grains panicle-1 (120) and grain

yield (3.70 t h-1) were produced as compared to no weeding

Manual weeding is practiced in Cambodia at least twice and commonly three times

(Makara et al., 2001). In Vietnam, Chin et al. (2000a) found that hand weeding twice was the

most effective treatment in terms of both controlling weeds and crop safety in DSR. African

farmers normally rely on family labor for weeding in direct seeded rice, which usually starts at

15-30 DAS (Oteng and Sant’Anna, 1999). Chandra et al. (1998) concluded that hand weeding

resulted in lowest weed density, weed dry weight and highest grain yield over control. Bhaghat

et al. (1991) conducted a field experiment and results showed that hand weeding (15, 30 and 45

days after seedling emergence) produced highest paddy yield of 4.14 t ha-1.

2.4.5 Problems of manual weed control

Hand weeding is a very effective way to control weeds in DSR but it requires high labor

due to which cost of production also increases. Manual weeding can be done only when weeds

have adequate size to be pulled (Singh et al., 2005). Hand weeding in wet-seeded rice requires

more time (Moody, 1983). This labor demanding method requires 250–780 man h ha-1 (Stessens,

2002). Hand weeding is the most widely practiced intervention against weeds on small-scale rice

farms in Africa (Adesina et al., 1994) but shortage of labor, high labor cost, poor weather

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conditions and the presence of perennial weeds that fragment on pulling are problems of hand

weeding

2.4.6 Chemical weed control methods

Herbicide use is one of the most labor-saving innovations that have been introduced in

rice farming. Hussain et al. (2008) used Nominee 100 SC to control weeds in direct seeded rice

resulting in grain yield (3.61 t ha-1) and giving 90 % weed control as compared to no weeding.

Effective weed management practices are an important requirement in DSR culture, with

herbicide application it is very easy to control weeds (Azmi et al., 2007). Islam et al. (2004)

compared hand weeding with different herbicides and found Pretilachlor as a most successful

weedicide with higher yield and cost benefit ratio. In America, Australia, Europe and East

Asia, over 90 % of DSR areas are treated with herbicides for weed control (Baltazar and De

Datta, 1992). Herbicide options for weed control in DSR differ according to method of crop

establishment because the performance of herbicides varies in relation to water regimes.

Extensive research has been conducted over the years by many researchers to find out the

optimum rate, time, type and method of herbicide application. Labor unavailability, high labor

costs and the urgent need to raise yields and maintain profit on a progressively limited land have

been major drivers for farmers to seek alternatives to manual weeding and herbicides are one

such alternative.

2.4.7 Problems of chemical weed control methods

Labor shortages have led to an increase in direct seeding and a rapid increase in the use

of herbicides. This reliance has resulted in an unwanted shift in weed species and concerns about

environmental pollution. Phenoxy and sulfonylurea compounds are extensively used herbicides

in Malaysia, Vietnam and Thailand to control broadleaf weeds and sedges in DSR. Weeds

resistant to these herbicides have developed and there is confirmation that weed species such as

S. zeylanica, Marsilea minuta, and F. miliacea have developed resistance to phenoxy herbicides

(Watanabe et al., 1997). Chemical weed control through the commonly used pre-emergence

herbicides (such as butachlor and thiobencarb) has been broadly investigated but their efficiency

depends on the water regime, soil tilth, composition of the weed and environmental conditions

(Baltazar and De Datta, 1992). Weedicide used for weed control in transplanted rice in Pakistan

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are not suitable for weeds in DSR and required weedicide for effective weed control in DSR are

not available.

2.4.8 Mechanical weed control

Mechanical weed control with the use of implements is a practical and economic method

for farmers. Mechanical weeding is almost generally practiced on row seeded rice since inter row

cultivation with either animal or tractor drawn implements reduces time in weed control and

minimizes crop damages. A weeder (with a straight line peg arrangement) showed outstanding

results on a range of soil types with unstable soil moisture levels and weed intensity and saving

57 % labor as compared with hand weeding (Subudhi, 2004). In Bangladesh a rake type weeder

had shown good results and it works in light and heavy soils with same efficacy (Islam et al.,

2004). Victor and Verma (2003) reported that Power operated rotary weeders have improved

weeding efficiency. In Thailand, a mechanized direct seeded rice management system has been

adopted, which includes weed control with a soil cultivator involving tillage between rows of

rice twice; 15 and 28 DAS (Kabaki et al., 2003). Mechanical weed control is similar to the weed

free control in terms of grain yield due to its bigger weed control efficiency (Morthy, 2003). In

Gambia effective weed management has been established with donkey drawn equipment using

twice (Remington and Posner, 2000). Beushening in which dry seeded rice is compressed by

‘‘planking’’ (drawing of a heavy flat wooden object over the crop) is also practiced to control

weeds. This process kills weed species with single main stems, whereas rice is able to retiller

from basal nodes. Sharma (1997) conducted a series of experiments on weed management in

rice, results showed that beushening is a very good technique to control weeds in rice, producing

paddy yield 3.5 t ha-1.

Comparisons of traditional and mechanically modernized weeding equipment suggest the

value of these technologies in resource limited farming communities. With labor shortage

mechanical weed control methods may be more efficient and suitable in DSR. Hence, efforts to

improve the effectiveness of existing weeding tools and implements are desirable, especially for

developing countries.

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CHAPTER 2

REVIEW OF LITERATURE

On the basis of studies conducted on various aspects of aerobic rice cultivation system, this

chapter is divided into following sections.

1. Rice

2. Crop establishment methods of rice

3. Weeds

4. Methods of weed control

2.1 Rice

Rice is monocot plant Oryza sativa (Asian rice) or Oryza glaberrima (African rice). Rice

belongs to the genus Oryza of the sub tribe oryzineae in the family Gramineae. Its genus Oryza

comprises 25 accepted species, of which 23 are wild and two (Oryza sativa and Oryza

glaberrima) are cultivated. All the rice varieties of Europe, America and Asia belong to the

specie Oryza sativa, while many of the cultivated varieties of West Africa belong to the specie

Oryza glaberrima. Rice is used as staple food for more than half of the world (Chauhan and

Johnson, 2011). About 90 % of rice is produced in the South Asian countries on an area of

153.25 m ha with an average annual production of about 610 million tons, extending from the

Indo-Pak subcontinent to Japan (IRRI, 2004).

2.1.1 History of domestication and cultivation

The commonly accepted view is that rice was first domesticated in the region of the

Yangtze River valley in China (Vaughan et al., 2008). Morphological studies of rice phytoliths

from the Diaotonghuan archaeological site show the transition from cultivation of wild rice to

domesticated rice. Changes in the morphology of Diaotonghuan phytoliths dating from 10,000-

8,000 years before present show that rice had by this time been domesticated (Mac Neish and

Libby, 1995). Soon afterwards, the two major varieties of Indica and Japonica/Sinica rice were

grown in Central China (Harris, 1996). In the late 3rd millennium before Christ (BC), there was

a rapid expansion of rice cultivation into mainland of Southeast Asia and westwards across India

and Nepal (Harris, 1996).

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Korean archaeologists claimed to have discovered the world's oldest domesticated rice

(David, 2003). Although combined effort by the Stanford University, New York University,

Washington University in St. Louis, and Purdue University has provided the strongest evidence

yet there is only one origin of domesticated rice, in the Yangtze Valley of China (Molina et al.,

2011).

Thirty seven archeological sites have shown traces of rice cultivation in ancient time in

Indo-Pak subcontinent. These sites include Mohenjodaro in Pakistan, Gujrat, Lohal, Rangpur and

Uttar Pradesh in India (Chang, 1967). The earliest remains of rice in the Indian subcontinent

have been found in the Indo-Gangetic Plain and date from 7000-6000 BC though the earliest

widely accepted date for cultivated rice is placed at around 3000–2500 BC with findings in

regions belonging to the Indus Valley Civilization (Pokharia et al., 2009). It then spread to all the

fertile alluvial plains watered by rivers. Cultivation and cooking methods are thought to have

spread to the west rapidly and by medieval times, southern Europe saw the introduction of rice as

a hearty grain. According to Zohary and Maria (2000), Oryza sativa was recovered from a grave

at Susa in Iran (dated to the 1st century AD) at one end of the ancient world, another

domestication of rice in the South Asia.

2.2 Crop establishment methods

The production system of Asia is undergoing adjustments in response to rising scarcity of

land, water and labor. A major adjustment can be expected in the method of crop establishment.

Major determinants of farmer’s choice of crop establishment method are rainfall pattern,

sufficient water supply, weed incidence and field elevation. Availability of labor and power for

land preparation and wage rates were found to be among the major economic factors for the

choice of crop establishment method (Pandey and Velasco, 1999). Rice is grown by two methods

as discussed in the following sections.

2.2.1 Flooded rice

Commonly flooded rice is grown throughout the world. In this method first nursery plants

are grown which are then transplanted in the leveled and puddled field for establishment of crop.

This transplantation of rice seedling may be manual or by machines. Traditional method of

transplantation requires lot of labor and continuous water inputs. Shortage of labor at this critical

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stage often results in low production and increases labor costs. Rice has lower water productivity

than some other cereal crops (Bhuiyan, 1992). Puddling helps to decrease percolation losses and

control of weeds. However, the puddling process results in subsurface compaction (Kukal and

Aggarwal, 2003), which impedes the growth and yield of succeeding wheat crop. Puddling also

affects soil health due to mechanical dispersion of soil particles and making tillage operations

difficult, requiring more energy in succeeding crops such as wheat (Singh et al., 2003). Water in

conventional rice crop represents a major and necessary production cost for the growers.

Farmers in many rice growing areas have restricted availability of irrigation water and in

future it is predicted that in Asia, 17 m ha of irrigated rice areas may experience ‘‘physical water

scarcity’’ and 22 million ha may have ‘‘economic water scarcity’’ (Toung and Bouman, 2003).

Thus water scarcity threatens the sustainability of irrigated rice ecosystems since it may no

longer be feasible for farmers to undertake wet cultivation and flood fields to ensure good crop

growth and control weeds (Johnson and Mortimer, 2005). The increasing cost of labor threatens

the sustainability of transplanted rice within the rice wheat system of the Indo Gagnetic Plains.

2.2.2 Aerobic rice

One of the strategies to combat water shortage is the system of aerobic or direct seeded

rice. Aerobic rice production consists of sowing seeds in dry soils. Decreased water input, low

labor requirement and timely sowing can be listed as possible benefits of the DSR (Bhushan et

al., 2007). In aerobic or DSR, generally cultivars could have high yield, input-responsive and

could adapt to mild to medium water stress (Bouman et al., 2005). Especially on coarse textured

soils with high seepage and percolation rates, aerobic rice has an advantage over systems that

include saturated or partially flooded soil conditions (Wang et al., 2002). Aerobic rice systems

have been developed since the mid-eighties and aerobic rice is now grown commercially in many

countries of the world especially in Brazil and Northern China (Wang et al., 2002).

According to Guimaraes and Stone (2000), aerobic rice yields similar to that from

transplanted. Direct seeding is cost effective, can save water through earlier rice crop

establishment and allows early sowing of wheat (Ladha et al., 2003; Singh et al., 2003). Aerobic

rice cultivation is a new technology that suits to high yielding varieties with a much lower water

input than that required for traditional rice cultivation. A commercial cropping system based on

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aerobic rice has spread widely in Brazil as a result of the development of improved high yielding

varieties (Pinhiero et al., 2006).

Paddy yield of 5-6 t ha-1 can be achieved in the aerobic rice system (George et al., 2002).

By limiting water losses through seepage, percolation and evaporation, aerobic rice limit total

water use by 27-51 % as compared with transplanted rice crop (Bouman et al., 2005). Similar

observations were reported by Wang et al. (2002) that aerobic rice system can decrease water

application by 44 % compared to the conventionally transplanted rice system, mostly through

decreasing percolation, seepage and evaporation losses, while maintaining yield at a satisfactory

level.

The water requirement of aerobic rice is potentially much less than that of flooded rice

because of: (1) the absence of water use for wet land preparation (puddling), (2) the absence of

continuous seepage and (3) the absence of evaporation losses from the pounded water layer

(Bouman et al., 2005). The potential water saving at field level when rice can be grown as an

upland crop are large, especially on soils with high seepage and percolation rates (Bouman

Toung, 2001). Properly managed aerobic rice results in reasonable yields as Tabbal et al. (2002)

reported that DSR yielded the same as transplanted rice while water inputs were decreased by 35

% and water productivity increased by 45 % compared with that under flooded conditions.

2.2.3 Global distribution of direct seeded rice

Growing of direct seeded rice varies broadly across countries and regions. DSR is planted

either in a dry seeded or wet seeded system in the United States (Gianessi et. al., 2002), Australia

and Europe (Ferrero and Nguyen, 2004). Pandey and Velasco (2002) reported that direct seeding

was rising rapidly in Asia, with 21-22 % of the total rice area being dry seeded or wet seeded.

Dry direct seeding in India is extensively practiced in rain fed lowlands, uplands and

flood prone areas, while wet seeding is a common practice in irrigated areas (Mishra et. al.,

2005). In Vietnam, especially in the Mekong Delta, rice is sown wet seeded and broadcasting is

common practice (Luat, 2000). Kim et al. (2001) reported that 11 % of the total rice was direct

seeded in Korea, dry seeding was 6.4% and wet seeding 4.7 %.

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In the northern provinces of Cambodia, in wet season, 80-90 % of rice fields are dry

direct seeded (CIAP, 1998). In Philippine both dry and wet seeding is commonly practiced (De

Dios et. al., 2005). In Thailand, the rain fed rice area is dry direct seeded, whereas irrigated area

in the Central Plain is mostly wet seeded (Azmi et al., 2005). In Malaysia, wet seeding is favored

but is encouraged only where efficient water management is possible (Azmi et al., 2005). In

Northern and North Eastern regions of China rice seeded directly into aerobic non puddled soils,

area under direct seeding in these regions is 80,000 and 60,000 ha, respectively (Xie et al.,

2005).

2.2.4 Crop establishment methods of direct seeded rice

Farmers usually adopt four types of crop establishment methods in relation to

hydrological conditions for direct seeding of rice.

2.2.4.1 Wet seeding

Rice seeds are soaked for 24 hrs and incubated from 24 to 36 hrs. Pre-germinated seeds

are then sown on to the soil surface. Typically water is reintroduced into fields for weed

suppression 7-10 days after sowing (DAS). Weed infestation is usually lower in wet seeded rice

than in dry-seeded and zero-tilled rice (Balasubramanian and Hill, 2002).

2.2.4.2 Water seeding

Pre-germinated seeds are sown directly into water. Water seeding enables farmers to

proceed without waiting for the flood water recession necessary for wet seeding and to minimize

the risk of late season drought in the crop. Fields are drained gradually as the crop develops. This

practice substantially reduces weed infestations during early crop establishment (Yamauchi

1996).

2.2.4.3 Zero-tillage seeding

In South Vietnam after the harvest of the wet seeded rice crop in January or February,

rice straw is scattered over the fields, dried for a few days and burned. Fields are then irrigated to

an average depth of 5 cm before sowing pre germinated seeds onto the wet ash layer. In this way,

zero tillage shortens the turnover time when cultivating three rice crops per year. However, zero

tillage results in high weed infestations, particularly of perennial weeds such as Paspalum

distichum (Hach et al., 1997) and insect pest predators have been recorded significantly lower in

fields where stubble is burned (Loc et al., 1998).

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2.2.4.4 Dry seeding

This method is practiced when water is in short supply. Land preparation involves

ploughing or rotovation. Non-germinated seeds are broadcasted or drill seeded in dry or moist

soil. Broadcasted seeds are covered by harrowing; more seeds are required for broadcast than for

drill seeding and stand establishment is poor with broadcasting. Dry seeded rice culture is

practiced in Africa, Australia, Europe, and USA (Kwesi and De Datta, 1991).

2.3 Weeds

Weeds are plants growing in an improper place in competition with a crop. Thus, a plant

species cannot be classified as a weed under all conditions. The major weeds associated with rice

include grasses Dactyloctenium aegyptium (L.) Echinochloa crus-galli (L.), Echinochloa colona

(L.) and Leptochloa chinensis (L.), Cyperus rotendusand and broadleaf weeds Commelina

benghalensis (L.), Caesulia axillaris, Eclipta prostrate (L.) Euphorbia hirta (L.), Portulaca

oleracea (L.), Trianthema portulacastrum (L.) and Lindernia spp. (Singh et al., 2006).

2.3.1 Effects of weeds on rice

Weeds have different effects on rice. Weed infestations primarily constrain rice

production by reducing grain yield. Yield reductions caused by uncontrolled weeds throughout a

crop season have been estimated to be from 44 to 96 %, depending on the rice culture.

Worldwide some 9 % loss of rice yield can be attributed just to weeds (Oerke and Dehne, 2004).

There is considerable variation in yield loss to weeds among countries.

The cost of rice weed control including herbicides, cultural and mechanical practices and

hand weeding, is estimated to be about 5 % of world rice production and amount to US $ 3.5

billion annually. When the 9 % loss of rough rice paddy yield is added to this cost, the world’s

total estimated cost for rice weeds and their control amounts to 15 % of total annual production

of rice valued at US $ 10.5 billion (Kwesi De Datta, 1991). Similar findings were observed by

Norton et al. 2010 who reported that herbicide sales for rice crops globally grew at an average

rate of more than 2 percent year-1 from US $ 741 million in 1980 to US $ 1.34 billion in 2007

and global sale of herbicides for application in rice farming systems could reach US $ 3 billion

per year by 2025 (Zhang et al., 2004).

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Weeds indirectly limit production by serving as hosts for organisms that adversely affect

rice. Weeds provide food, shelter and reproduction sites for insects, nematodes, pathogens and

rodents. Some weeds that serve as alternate hosts to rice pests are Cynodon dactylon, Cyperus

iria, Echinochloa colona, Echinochloa crus-galli and Cyperus rotundus. This indicates the

importance of recognizing weeds as secondary hosts for pests and of removing weeds from the

margins of rice fields to prevent continued infection of the rice crop.

Weeds hamper rice harvesting and increase harvest costs through direct interference with

the harvesting operation and by causing lodging. Weed seeds contaminate rough rice, thus

reducing grain quality and market value. For example, the weed red rice has a pigmented layer

that shatters easily and readily contaminates rough rice. Removing all traces of the pigmented

layer requires intense milling resulting in decreased grain quality and increased cost. The

drudgery of weeding and labor shortages has made rice farming unattractive. In most tropical

countries, farmers spend more time on weeding by hand or with simple tools, than on any other

farming task.

Nutrient availability and favorable temperatures throughout the year, especially in the

tropics, allow luxuriant aquatic weed growth in rice fields and weeds compete for nutrients with

rice (Phoung et al., 2005). Heavy aquatic weed infestation causes excessive water loss through

evaporation and impedes water flow in irrigation canals. In some cases, aquatic weeds may be a

health hazard to persons living near impounded water. Weeds interfere with rice growth by

competing for one or more growth limiting resources such as light, nutrients and water.

Allelopathy (chemical production by living or decaying weed plant tissues) may also adversely

affect the growth of a neighboring rice plant. Rice and rice weeds have similar requirements for

growth and development. Competition occurs when one of the limiting resources falls short of

the combined requirements of both. The degree of rice-weed competition depends on rainfall,

rice variety, soil factors, weed density, duration of rice and weed growth. Cultural practices

greatly alter the competitive relationship between rice and weeds. Thus, different cultures

(irrigated, rain fed lowland, upland, and deepwater) will be subjected to different kinds and

degrees of weed competition. To understand this competition, it is essential to know the growth

requirements of rice and helpful to know the growth requirements of weeds.

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2.3.2 Weeds in direct seeded rice

Weeds are the main problem in direct seeded rice which may cause 100 % failure of the

crop. Aerobic soil, dry tillage and alternate wetting and drying conditions are favorable to the

germination and growth of weeds causing grain yield losses up to 90 % (Rao et al., 2007). Crop

loss due to weed competition varies with the duration of weed infestation of the crop. The crop is

likely to experience yield reduction, unless weeds are kept free during a part of its growing

period (Azmi et al., 2007). Johnson et al. (2004) noted that in direct seeded rice weeds can

emerge at the same time or before the rice plants, causing serious competition.

The labor requirement for weeding is a major impediment to the adoption of water saving

aerobic rice and increasing the productivity of aerobic rice based cropping systems (Singh et al.,

2006). After broadcast or drill seeding rice into dry soil field is irrigated just enough to provide

the soil moisture that allows the seeds to germinate. Thus, aerobic conditions remain ideal for the

germination of upland and aquatic weeds and weed problems are much worse in dry seeded

irrigated than in wet seeded rice (Kwesi and De Detta, 1991). Weeds are a major hurdle to broad

adoption of aerobic rice and greatest yield limiting constraint to aerobic rice, contributing about

50 % to yield losses (WARDA, 1996). Aerobic rice is subjected to more severe weed infestation

than transplanted lowland rice, because direct seeded aerobic rice germinates simultaneously

with weeds, in this way weeds dominates the crop due to the lack of water layer that suppress the

weed germination (Moody, 1983).

2.3.3 Weed control

Weeds have always reduced rice yields. As a result different weed control methods have

evolved. Farmers consider financial resources and availability of labor in deciding what weed

control method to use. Problems of input availability, availability of new technologies, specific

weed problems, farm size and availability of family labor are basic management factors in

making weed control decisions.

2.3.4 Planning effective control

Planning is important in making appropriate decisions on weed control. Unfortunately,

weed control usually is not planned. The decision to control is not made until the problem has

become serious, when control may be uneconomical, ineffective. Advance knowledge of weed

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problems can be obtained by surveying and recording the weed species in a rice field after rice

emergence. This record is useful in planning weed control and crop rotation programs.

2.4 Weed control methods

Weed control can be grouped into cultural, manual, mechanical, chemical, and biological

control methods. Each control method has advantages and disadvantages.

2.4.1 Cultural control methods

A basic principle of cultural control is to increase the competitive ability of rice and

enable it to suppress weed growth. Vigorous rice crop competes more effectively with weeds.

Cultural control methods includes; use of weed free and certified seed land preparation, cultivar

selection, time of seeding, planting method, crop rotation, plant population, fertilization and

water management (Rao et al., 2007).

2.4.2 Biological weed control methods

Several biological agents such as insects, mites, and fungi have been used successfully to

control rice weeds. The possibility of using tadpole shrimp (Triopus longicaudatus, T. granaris,

and T. cancriformis) for weed control in transplanted rice has been demonstrated in Japan. The

small crustaceans feed on weed seedlings and disturb their roots by mechanical agitation of the

soil. Labor for hand weeding in farmers’ fields was reduced 70-80 % in initial field trials with

tadpole shrimp (Matsunaka, 1975).

2.4.3 Problems of biological weed control methods

Tadpole shrimp (Triopus longicaudatus, T. granaris, and T. cancriformis) decreases

weed infestation but later on becomes a pest cause serious problems to rice crop (Matsunaka,

1975). Biological agents are selective in their control action and their activity may be restricted

to a single weed. Biological control programs may be applicable to an introduced perennial weed

growing in areas that are seldom disturbed, such as pastures, forests and water bodies. In a rice

cropping situation with a mixed weed flora, the selective control of a single weed will not solve

the weed problem and biological agents also work slowly.

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2.4.4 Manual weed control

Manual weed control includes removing and hand pulling. This method is the oldest and

in many cases, the farmer’s only way of controlling weeds in rice. Manual weeding is very

effective weed control method (Singh, 2005). Ekleme et al. (2009) conducted two field

experiments in Nigeria, results showed that lowest weed biomass (48 g m-2) was produced by

weeding twice with highest plant height (116 cm), tillers (203 m-2) and grain yield (3.62 t h-1) in

direct seeded rice. Singh et al. (2008) noted that hand weeding twice resulted in significantly

lower weed biomass (61.6 g) as compared to no weeding (329.5 g). Singh et al. (2007)

concluded that hand weeding six times in dry seeded rice resulted in lowest weed biomass (0 g

m-2) with highest panicle length (24.5 cm), panicles (160 m-2), grains panicle-1 (96), 1000 grain

weight (25.9 g), grain yield (5.58 t h-1) and straw yield (7.28 t h-1). Mann et al. (2007) conducted

an experiment and results revealed that in hand weeding with lowest weed biomass highest plant

height (92 cm), panicles (215 m-2), panicle length (27.3 cm), grains panicle-1 (120) and grain

yield (3.70 t h-1) were produced as compared to no weeding

Manual weeding is practiced in Cambodia at least twice and commonly three times

(Makara et al., 2001). In Vietnam, Chin et al. (2000a) found that hand weeding twice was the

most effective treatment in terms of both controlling weeds and crop safety in DSR. African

farmers normally rely on family labor for weeding in direct seeded rice, which usually starts at

15-30 DAS (Oteng and Sant’Anna, 1999). Chandra et al. (1998) concluded that hand weeding

resulted in lowest weed density, weed dry weight and highest grain yield over control. Bhaghat

et al. (1991) conducted a field experiment and results showed that hand weeding (15, 30 and 45

days after seedling emergence) produced highest paddy yield of 4.14 t ha-1.

2.4.5 Problems of manual weed control

Hand weeding is a very effective way to control weeds in DSR but it requires high labor

due to which cost of production also increases. Manual weeding can be done only when weeds

have adequate size to be pulled (Singh et al., 2005). Hand weeding in wet-seeded rice requires

more time (Moody, 1983). This labor demanding method requires 250–780 man h ha-1 (Stessens,

2002). Hand weeding is the most widely practiced intervention against weeds on small-scale rice

farms in Africa (Adesina et al., 1994) but shortage of labor, high labor cost, poor weather

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conditions and the presence of perennial weeds that fragment on pulling are problems of hand

weeding

2.4.6 Chemical weed control methods

Herbicide use is one of the most labor-saving innovations that have been introduced in

rice farming. Hussain et al. (2008) used Nominee 100 SC to control weeds in direct seeded rice

resulting in grain yield (3.61 t ha-1) and giving 90 % weed control as compared to no weeding.

Effective weed management practices are an important requirement in DSR culture, with

herbicide application it is very easy to control weeds (Azmi et al., 2007). Islam et al. (2004)

compared hand weeding with different herbicides and found Pretilachlor as a most successful

weedicide with higher yield and cost benefit ratio. In America, Australia, Europe and East

Asia, over 90 % of DSR areas are treated with herbicides for weed control (Baltazar and De

Datta, 1992). Herbicide options for weed control in DSR differ according to method of crop

establishment because the performance of herbicides varies in relation to water regimes.

Extensive research has been conducted over the years by many researchers to find out the

optimum rate, time, type and method of herbicide application. Labor unavailability, high labor

costs and the urgent need to raise yields and maintain profit on a progressively limited land have

been major drivers for farmers to seek alternatives to manual weeding and herbicides are one

such alternative.

2.4.7 Problems of chemical weed control methods

Labor shortages have led to an increase in direct seeding and a rapid increase in the use

of herbicides. This reliance has resulted in an unwanted shift in weed species and concerns about

environmental pollution. Phenoxy and sulfonylurea compounds are extensively used herbicides

in Malaysia, Vietnam and Thailand to control broadleaf weeds and sedges in DSR. Weeds

resistant to these herbicides have developed and there is confirmation that weed species such as

S. zeylanica, Marsilea minuta, and F. miliacea have developed resistance to phenoxy herbicides

(Watanabe et al., 1997). Chemical weed control through the commonly used pre-emergence

herbicides (such as butachlor and thiobencarb) has been broadly investigated but their efficiency

depends on the water regime, soil tilth, composition of the weed and environmental conditions

(Baltazar and De Datta, 1992). Weedicide used for weed control in transplanted rice in Pakistan

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are not suitable for weeds in DSR and required weedicide for effective weed control in DSR are

not available.

2.4.8 Mechanical weed control

Mechanical weed control with the use of implements is a practical and economic method

for farmers. Mechanical weeding is almost generally practiced on row seeded rice since inter row

cultivation with either animal or tractor drawn implements reduces time in weed control and

minimizes crop damages. A weeder (with a straight line peg arrangement) showed outstanding

results on a range of soil types with unstable soil moisture levels and weed intensity and saving

57 % labor as compared with hand weeding (Subudhi, 2004). In Bangladesh a rake type weeder

had shown good results and it works in light and heavy soils with same efficacy (Islam et al.,

2004). Victor and Verma (2003) reported that Power operated rotary weeders have improved

weeding efficiency. In Thailand, a mechanized direct seeded rice management system has been

adopted, which includes weed control with a soil cultivator involving tillage between rows of

rice twice; 15 and 28 DAS (Kabaki et al., 2003). Mechanical weed control is similar to the weed

free control in terms of grain yield due to its bigger weed control efficiency (Morthy, 2003). In

Gambia effective weed management has been established with donkey drawn equipment using

twice (Remington and Posner, 2000). Beushening in which dry seeded rice is compressed by

‘‘planking’’ (drawing of a heavy flat wooden object over the crop) is also practiced to control

weeds. This process kills weed species with single main stems, whereas rice is able to retiller

from basal nodes. Sharma (1997) conducted a series of experiments on weed management in

rice, results showed that beushening is a very good technique to control weeds in rice, producing

paddy yield 3.5 t ha-1.

Comparisons of traditional and mechanically modernized weeding equipment suggest the

value of these technologies in resource limited farming communities. With labor shortage

mechanical weed control methods may be more efficient and suitable in DSR. Hence, efforts to

improve the effectiveness of existing weeding tools and implements are desirable, especially for

developing countries.

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CHAPTER 3

MATERIALS AND METHODS

3.1 Location of studies

The proposed field studies were conducted at the Agronomic Research Farm,

Department of Agronomy, University of Agriculture, Faisalabad (31o-25‘N, 73o-09‘E),

Pakistan during rice growing seasons of 2008 and 2009. District Faisalabad is situated in

Punjab province (Pakistan), 150 m above sea level with flat plain developed by River Ravi

and Chenab. Faisalabad has extreme climate and area of this district is highly favorable for

canal irrigation. Summer season begins in April, ends in October while winter season starts

from November and continues till March. May, June and July are the hottest months while

December, January and February are the coldest months.

3.2 Characterization of soil

Composite soil samples were collected with auger up to a depth of 30 cm before rice

sowing and were analyzed for physical and chemical properties during both the cropping

seasons (Table 3.1).

3.2.1 Particle size analysis

Hydrometer method (Bouyoucos, 1962) was used for determining the percentage of

sand, silt and clay. Dispersion solution was made by dissolving 10 g of sodium

hexametaphosphate and 2.5 g of sodium carbonate in 250 ml of distilled water. Soil (50 g)

was taken in a 600 ml beaker and 60 ml of dispersing solution was added. Mixture was

covered with watch glass and kept overnight. Next day, it was transferred to stirring cup and

stirred at high speed for 3 minutes. Then material was transferred into I L graduate cylinder.

Required volume was made by adding deionized water. Contents of cylinder were shaken

manually using a metal plunger. After obtaining homogeneous suspension, plunger was taken

out and silt and clay (%) was determined using Bouyoucos hydrometer. Percent sand was

determined by subtracting percent silt and clay from 100. Texture class was determined by

following the International Society of Soil Science Triangle (Moodie et al., 1959).

3.2.2 pH of saturated soil paste

A pH meter (WTW pH 315 i) was used for determination of soil pH. Instrument first

was calibrated with standard buffer solution of pH 4.00, 7.00 and 9.00. Then it was inserted

in soil saturated paste. Stable meter reading was noted as pH.

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3.2.3 Soil saturated extract

Extract from the soil saturated paste was obtained by applying positive pressure with

the help of air pump. It was preserved in air tight plastic bottles for further analysis. Sodium

hexametaphposphate (0.1%) solution was added @ one drop per 25 mL extract to prevent

precipitation of salts during storage.

3.2.4 Soil organic matter

Soil organic matter (OM) was determined fallowing Walkly-Black method (Nelson

and Sommers, 1982). For this purpose two gram soil was swirled in 10 mL of 1.0 N K2Cr2O7

solution. After adding 20 mL of concentrated H2SO4, the suspension was well mixed and

allowed to stand for 30 minutes. Then it was diluted to 200 mL with distilled water.

Diphenylamine (30 drops) was used as indicator in the presence of 0.5 g sodium fluoride

(NaF). Finally mixture was titrated against ferrous sulphate 7-hydrate (FeSO4.7H2O) to dull

green end point.

Organic matter was calculated by the formula:

OM (%) =[ (Vblank – Vsample) × M × 0.69] / [ Wt. of soil (g)]

Where

Vblank = Volume (mL) of FeSO4.7H2O used in blank

Vsample = Volume (mL) of FeSO4.7H2O used to titrate the sample

M = Molarity of FeSO4.7H2O solution

0.69 =0.003 × 100 × (100/72) × (100/58)

Where

0.003 = Mean weight of carbon

100 = To convert OM in %

100/58 = Factor to convert organic carbon to OM

100/72 = Recovery factor for carbon

3.2.5 Electrical conductivity of saturated soil extract

Clear extract of saturated soil paste was obtained by a vacuum pump. The EC was

measured by using Jenway electrical conductivity meter, Model-4070 (Method 4b. p.89)

3.2.6 Total soluble salts

EC was converted in TSS (m molc L-1) fallowing the graph given in the handbook 60

(US Salinity Lab. Staff, 1954).

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3.2.7 Available phosphorous

10 g of soil sample was extracted with AB-DTPA solution while shaking on

mechanical shaker. 1 ml of the aliquot was taken and diluted with the 10 ml each of color

developing reagents (ascorbic acid, ammonium molybdate, antimony potassium titrate and

sulphuric acid). After 30 minutes reading was recorded on ANA-730 spectrophotometer at a

wavelength of 880 nm (method 16, p. 134).

3.2.8 Extractable potassium

Extraction was made with ammonium acetate solution and extractable K was

determined by Corning Flame Photometer-410 after calibrating with standard solutions of

potassium (Method 58, a: p. 132).

Table 3.1: Analysis of the experimental site

characteristics Unit 2008 2009

Sand % 52.0 52.2

Silt % 22.2 21.8

Clay % 26.9 26.8

Texture Class - Sandy clay loam Sandy clay loam

pH - 8.0 7.9

TSS % 0.21 0.22

Organic matter % 0.73 0.74

Total Nitrogen % 0.052 0.053

Available P ppm 6.5 6.2

Available K ppm 186 185

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Table 3.2 Meteorological data during the rice season of 2008 at experimental site Months Rainfall Relative humidity Temperature (C) (mm) (%) Daily

maximum Daily

minimum Daily

average June 41.7 48.00 38.4 27.4 32.9 July 81.6 52.97 37.5 28.3 32.9 August 204.5 65.00 35.1 26.8 30.9 September 28.8 59.33 34.4 23.7 29.0 October 0 57.65 33.1 20.2 26.6 November 0 58.87 27.3 12.2 19.7

Source: Agricultural Meteorology Cell, Department of Crop Physiology, University of Agriculture, Faisalabad, Pakistan.

Table 3.3 Meteorological data during the rice season of 2009 at experimental site Months Rainfall Relative humidity Temperature (C) (mm) (%) Daily

maximum Daily

minimum Daily

average June 9.6 33.6 40.7 27.0 33.8 July 43.5 59.0 38.0 27.9 32.9 August 116.0 65.8 36.6 27.6 32.1 September 20.6 61.0 36.3 24.4 30.3 October 17.5 57.9 32.7 17.1 24.9 November 0.7 64.7 25.7 10.8 18.2 Source: Agricultural Meteorology Cell, Department of Crop Physiology, University of Agriculture, Faisalabad, Pakistan.

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3.3 Treatments and lay out of experiments

The experiments were conducted during the years 2008 and 2009.

EXPERIMENT-I: COMPARISON OF DIFFERENT WEED

MANAGEMENT STRATEGIES IN DRILL SEEDED AEROBIC RICE

TREATMENTS: WEED MANAGEMENT STRATEGIE

S1: No weeding (weedy check)

S2: Hand pulling 15, 25, 35 and 45 DAS

S3: Hoeing with kasulla 15, 25, 35 and 45 DAS

S4: Inter row cultivation with Tine cultivator 15, 25, 35 and 45 DAS

S5: Inter row cultivation with Spike hoe 15, 25, 35 and 45 DAS

S6: Chemical control (Nominee 100 SC (bispyribac-sodium100 g a.i per L) @ 250 ml ha-1)

Layout

Experiment was laid out in randomized complete block design with 3 replications. Net plot

size was 2.7 m x 6.0 m.

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Fig 3.1 Layout plan for experiment-I

Sub water channel M

ain

wat

er c

han

nel

R1

S1

S2

S3

S4

S5

S6

Pat

h

Path

R2

S6

S5

S4

S3

S2

S1

Sub water channel

R3

S4

S3

S6

S2

S1

S5

Non experimental area

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EXPERIMENT-II: EVALUATION OF DIFFERENT INTER CULTURAL

IMPLEMENTS FOR WEED MANAGEMENT IN DRILL SEEDED

AEROBIC RICE

TREATMENTS

A. INTER ROW CULTIVATION IMPLEMENTS (main plots)

S1: Tine Cultivator

S2: Spike Hoe

S3: Plug Weeder

B. INTER ROW CULTIVATION FREQUENCIES (sub plots)

F1: Inter row cultivation at 15 DAS

F2: Inter c row cultivation at 15 and 25 DAS

F3: Inter row cultivation at 15, 25 and 35 DAS

F4: Inter row cultivation at 15, 25, 35 and 45 DAS

Layout

Experiment was laid out in randomized complete block design in split arrangement with 3

replications. Net plot size was 2.7 m x 6.0 m.

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Fig 3.2 Layout plan for experiment-II

Sub water channel

Mai

n w

ater

ch

ann

el

R1

S1 S2 S3

Pat

h

F1 F2 F3 F4 F2 F3

F4 F1 F4 F1

F2 F3

Path

R2

S2 S3 S1 F2 F3

F4 F1 F4 F2

F1 F3 F2 F3

F4 F1

Sub water channel

R3

S3 S1 S2 F3 F4

F1 F2 F3 F1

F2 F4 F1 F2

F3

F4

Non experimental area

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3.4 Planting of crop

3.4.1 Land preparation

After the harvesting of wheat, land was ploughed twice followed by planking with

tractor drawn implements to achieve the required soil tilth for direct seeded rice.

3.4.2 Seeding method, planting geometry and fertilizer application

Rice cultivar Super Basmati was sown on 20th June during 2008 and 28th June during

2009 using seed rate of 75 kg ha-1. Direct seeding was done by automatic Rabi drill

maintaining 22.5 cm line to line distance. The crop was provided with 150 kg N, 85 kg P and

67 kg K in the form of urea, DAP and potassium sulphate respectively. Half of N and whole

of the P and k were applied at sowing, while remaining nitrogen was given in two equal

splits, at tillering and panicle initiation stage of the crop.

3.4.3 Water management

First irrigation was of 4 acre inch for seed bed preparation. Then crop was irrigated to

keep the soil moisture at field capacity level; each irrigation was of 3 acre inch. Total 16

irrigations were applied.

3.4.4 Harvesting and threshing

During the year 2008 crop was harvested on 15th November and during the year 2009

on 21st November. Threshing of each plot was done separately.

3.5 Weed management in experiment I

Weeds were left unchecked in all the plots of no weeding treatment. Weeds in hand

pulling treatment were completely removed manually by uprooting and cutting. Weeds in

hoeing treatment were removed manually with the help of kasula, only inter row weeds were

removed by this implement and within row weeds remain unchecked. Tine cultivator was

operated manually and it removed and uprooted inter row weeds only; crop was laid down

after the implementation of tine cultivator just like beushaning. Spike hoe was also operated

manually and its spikes removed minor amount of weeds; crop was laid down after its

implementation as in tine cultivator. The weedicide Nominee 100 SC was dissolved in water

and sprayed after 20 days of sowing with the help of knap sack sprayer @ 250 ml ha-1.

3.6 Weed management in experiment II

All three implements were operated manually at different frequencies. Tine cultivator

removed and uprooted inter row weeds, within row weeds remained unchecked; crop was laid

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down after its operation just like beushaning. Spike hoe was also operated at different

frequencies but it removed a minor quantity of weed; within row weeds remain unchecked,

crop was laid down after its implementation. Plug weeder was operated manually at different

frequencies and it removed no weeds.

3.7 Observations

Following observations were recorded during both the years.

3.7.1 Weed parameters

1. Weed biomass (g).

3.7.2 Yield related traits

1. Plant height at maturity (cm).

2. Number of total tillers m-2 at maturity.

3. Number of fertile tillers m-2 at maturity.

4. Number of unfertile tillers m-2 at maturity.

5. Panicle length (cm).

6. Number of kernels per panicle.

7. 1000-kernel weight (g).

8. Paddy yield (kg ha-1).

9. Biological yield (kg ha-1).

10. Harvest index (%).

3.7.4 Quality parameters

1. Sterile spikelets (%).

2. Opaque kernels (%).

3. Abortive kernels (%).

4. Normal kernels (%).

3.7.3 Growth parameters

1. Leaf area index (LAI).

2. Lea area duration (days).

3. Total dry matter production (kg ha-1).

4. Crop growth rate (g m-2 day-1).

5. Net assimilation rate (g m-2 day-1).

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Weed parameters

i. Weed biomass (g)

Weeds from an area of 100 x 100 cm from each plot were collected manually at 15, 30 and 45

DAS and washed. After sun drying these samples were oven dried at 80 oC and then weighed

to record weed dry weight. Weed flora observed in current studies is given in Table 3.4

Table 3.4 Weed flora observed in studies

English name Local name Botanical name

Nut sedge Deela Cyperus rotundas

Jungle rice Swanki Echonocola colona

Barnyardgrass Dhiden Echonocola crusgalli

Egyptian crowfoot grass Madana Dactyloctenium aegyptium

Desert horse purslane Itsit Trianthum portulacastrum

False Daisy Daryae booti Eclipt alba

Spurge Hazardani Euphorbia granulata

Yield related traits

i. Plant height at maturity (cm)

Plant height at maturity was measured from base to leaf tip with the help of a meter rod. The

height of 15 tillers selected randomly in each plot was measured at maturity and then averaged.

ii. Number of total tillers m-2

Number of tillers was counted from four rows of 100 cm length and then converted into 100 x

100 cm area in each plot at maturity.

iii. Number of fertile tillers m-2 at maturity

The number of tillers bearing panicles was counted from four rows of 100 cm length and then

converted into 100 x 100 cm area in each plot at maturity.

iv. Number of unfertile tillers m-2 at maturity

The number of tillers bearing no panicles was counted from four rows of 100 cm length and

then converted into 100 x 100 cm area in each plot at maturity.

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v. Panicle length (cm)

Fifteen panicles were selected randomly from each plot. Panicle length was measured and then

averaged.

vi. Number of kernels per panicle

Ten panicles of tillers were randomly collected from each plot at harvest and saved in paper bags.

Grains were separated from each panicle and separated on working board. Afterward number of

grains per panicle was counted separately and then average.d

vii. 1000-kernel weight (g)

Out of each treatment random sample of one thousand kernels was taken and weighed with an

electric balance.

viii. Biological yield (t ha-1)

Biological yield per plot was determined after sun drying for one week and expressed in t ha-1.

ix. Paddy yield (t ha-1)

After harvesting and threshing each plot the clean rough rice was sun dried up to 14 % moisture,

bulked and weighed to record the paddy yield. The paddy weight was expressed in t ha-1.

x. Straw yield (t ha-1)

Straw yield per plot was determined after sun-drying for one week and expressed in t ha-1.

xi. Harvest index (%)

Harvest index was calculated as the ratio of grain yield to total (above ground) biological yield

using the formula:

Growth parameters

A randomly selected area of 30 x 30 cm was harvested at 15 days interval from each plot and was

analyzed for leaf area and dry matter accumulation. First reading was taken at 60 DAS.

i. Leaf area index (LAI)

For determining the leaf area index, plant samples were collected from each plot at intervals

of 15 days throughout the growing season of the crop. The green leaves were separated from

the plants and characterized into three categories according to their size. The area of 5 leaves

100yeild Biological

yeild KernelHI

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was measured using leaf area meter. LAI was computed by using the area–weight

relationship (Watson, 1947).

ii. Crop growth rate (g m-2 d-1)

Crop growth rate was measured using the formula given by Hunt (1978).

CGR = (W2 – W1) / (t2-t1)

Where

W1 = Total dry matter at the first harvest

W2 = Total dry matter at the second harvest

t1 = Date of observation of first dry matter recorded

t2 = Date of observation of second dry matter recorded

iii. Cumulative leaf area duration (LAD)

Leaf area duration (LAD) for entire growing season was estimated using the formula of Hunt

(1978).

LAD = (LAI1+LAI2) (t2-t1)/2

Where

LAI1 = Leaf area index at the first harvest

LAI2 = Leaf area index at the second harvest

t1 = Data of observation of the first harvest

t2 = Data of observation of the second harvest

iv. Net assimilation rate (g m-2 d-1)

Net assimilation rate was estimated by using formula proposed by Hunt (1978).

NAR = TDM/LAD

Where,

TDM = Final total dry matter at harvest.

LAD = Final leaf area duration at harvest.

Kernel quality

To record the occurrence of sterile, abortive, opaqueness and percentage of normal kernels, 10

panicles were randomly selected from each plot and information was recorded after having the

panicles carefully sketched for differentiation of different categories of kernels. A lamp having a

flexible stand was used as a source of light. A panicle was positioned in front of the lamp so that

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light may pass through it in order to differentiate between different forms of kernel development.

Abortive and opaque kernels were separated.

i. Sterile kernels

Sterile kernels are unfilled and unfertilized spikelets and these are easily distinguished from other

categories.

ii. Opaque kernels

Opaque kernels are those that attain full size but do not become translucent due to lack of

carbohydrates and also do not allow light to pass through them because of overall dull chalky

structure. However, these were bigger than abortive kernels as their development stopped at later

stage. These did not acquired normal size because of retarded development.

iii. Abortive kernels

Abortive kernels are those in which fertilization does take place but kernels do not attain full size

as these stop growing during early stages of kernel development. These look dull and do not

permit light to pass through them.

iv. Normal kernels

Normal kernels are those that attain full size, translucent, show normal starch filling and allow

light to pass through them. Normal, the clear translucent and without any chalky spots kernels,

were computed by deducting all the abnormal kernels from total number of spikelets.

3.8 Economic analysis

Economic analysis was made by calculating the gross income by summing up the total value of

adjusted paddy and straw yields.

Adjusted yield= 10 % less than actual

Cost of production= Fixed cost + Harvesting and threshing charges+ cost of intervention

Net income was calculated by

Net income = Gross income – Cost of production

Benefit cost ratio (BCR) was calculated by the following formula

BCR = Gross income / Cost of production

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3.9 Marginal rate of return

To calculate marginal rate of return net field benefits were calculated by following formula

Net field benefits= Gross income – Variable cost

Then dominance analysis was carried out

The marginal net benefit (MNB) divided by the marginal cost (MC), expressed in percentage;

is called marginal rate of return (MRR). MRR was calculated with the formula

MRR (%) = 100 MC

MNB

(CIMMYT 1988)

3.10 Statistical analysis

The collected data were analyzed using the Fisher’s analysis of variance technique. Then

treatment means were compared using Least Significant Difference (LSD) test at 5%

probability level (Steel et al., 1997).

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CHAPTER 4

RESULTS AND DISCUSSION

Results pertaining to different agro-qualitative traits of direct sown rice as affected by

different weed management strategies and weed control implements along with statistical

interpretation are presented and discussed in this chapter.

STUDY-I: COMPARISON OF DIFFERENT WEED MANAGEMENT

STRATEGIES IN DRILL SEEDED AEROBIC RICE

4.1 Weed biomass of sedges (15 DAS)

The Fig. 4.1 showed that different weed management strategies significantly affected

weed biomass of sedges during both the years at 15 DAS. During the year 2008 minimum

weed dry weight (0.31 g m-2) was recorded in hand pulling followed by hoeing (0.65 g m-2)

and tine cultivator (0.93 g m-2). Maximum weed dry weight of sedges was found in spike hoe

(1.28 g m-2) that was statistically similar to no weeding (1.29 g m-2) and Nominee 100 SC

(1.32 g m-2).

During the year 2009 minimum weed dry weight (0.47 g m-2) of sedges was recorded

in hand pulling followed by hoeing (0.90 g m-2) and tine cultivator (1.03 g m-2). Weed dry

weight in spike hoe (1.38 g m-2), no weeding (1.1.40 g m-2) and Nominee 100 SC (1.41 g m-2)

was statistically similar.

4.2 Weed biomass of broad leaf weeds (15 DAS)

The Fig. 4.1 showed that different weed management strategies significantly affected

weed biomass of broad leaf weeds during both the years at 15 DAS. During the year 2008

minimum weed dry weight (0.44 g m-2) was recorded in hand pulling that was similar to

hoeing (0.56 g m-2) followed by tine cultivator (0.74 g m-2). Maximum weed dry weight was

found in Nominee 100 SC (1.54 g m-2) that was statistically similar to weed dry weight in no

weeding (1.53 g m-2) and spike hoe (1.52 g m-2).

During the year 2009 minimum weed dry weight was recorded in hand pulling (0.47 g

m-2) followed by hoeing (0.66 g m-2), tine cultivator (0.81 g m-2). Maximum weed dry weight

was found in Nominee 100 SC (1.62 g m-2) that was statistically similar to weed dry weight

in no weeding (1.58 g m-2) and spike hoe (1.57 g m-2).

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Fig. 4.1 Effect of different weed management strategies on weed biomass of sedges

and broad leaf weeds at 15 DAS

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

B.Leaves Sedges

g m

-2

(a) 2008

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

B.Leaves Sedges

g m

-2

(b) 2009

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

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4.3 Weed biomass of sedges (30 DAS)

The Fig. 4.2 showed that different weed management strategies significantly affected

weed biomass of sedges during both the years at 30 DAS. During the year 2008 minimum

weed dry weight (2.98 g m-2) of sedges was recorded in hand pulling followed by hoeing

(10.88 g m-2), tine cultivator (18.01 g m-2), Nominee 100 SC (43.5 g m-2) and spike hoe

(55.43 g m-2). Weed dry weight of sedges in no weeding (61.77 g m-2) was found maximum.

During the year 2009 minimum weed dry weight of sedges was recorded in hand

pulling (3.93 g m-2) followed by hoeing (11.24 g m-2), tine cultivator (18.53 g m-2), Nominee

100 SC (45.56 g m-2) and spike hoe (54.82 g m-2). The maximum weed dry weight of sedges

was recorded in no weeding (64.33 g m-2).

4.4 Weed biomass of broad leaf weeds (30 DAS)

The Fig. 4.2 showed that different weed management strategies significantly affected

weed biomass of broad leaf weeds during both the years at 30 DAS. During the year 2008

minimum weed dry weight (3.27 g m-2) was recorded in hand pulling that was similar to

hoeing (10.69 g m-2). Weed biomass in tine cultivator (23.34 g m-2) was similar to Nominee

100 SC (26.91 g m-2). Maximum weed dry weight was found in no weeding (92.92 g m-2) that

was statistically similar to weed dry weight in spike hoe (88.73 g m-2).

During the year 2009 minimum weed dry weight was recorded in hand pulling (6.31 g

m-2) followed by hoeing (14.93 g m-2). Weed biomass in tine cultivator (27.64 g m-2) was

similar to Nominee 100 SC (32.72 g m-2) followed by spike hoe (80.65 g m-2). Maximum

weed dry weight was found in no weeding (95.02 g m-2).

4.5 Weed biomass of sedges (45 DAS)

The fig 4.3 showed that different weed management strategies significantly affected

weed biomass of sedges during both the years at 45 DAS. During the year 2008 minimum

weed dry weight (7.28 g m-2) of sedges was recorded in hand pulling followed by hoeing

(31.39 g m-2), tine cultivator (45.82 g m-2), Nominee 100 SC (98.84 g m-2) and spike hoe

(117.45 g m-2). Weed dry weight (159.46 g m-2) of sedges in no weeding was found

maximum.

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Fig. 4.2 Effect of different weed management strategies on weed biomass of sedges

and broad leaf weeds at 30 DAS

0

20

40

60

80

100

120

B.Leaves Sedges

g m

-2

(a) 2008

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

0

20

40

60

80

100

120

B.Leaves Sedges

g m

-2

(b) 2009

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

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Fig. 4.3 Effect of different weed management strategies on weed biomass of sedges

and broad leaf weeds at 45 DAS

0

20

40

60

80

100

120

140

160

180

B.Leaves Sedges

g m

-2

(a) 2008

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

0

20

40

60

80

100

120

140

160

180

200

B.Leaves Sedges

g m

-2

(b) 2009

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

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During the year 2009 minimum weed dry weight of sedges was recorded in hand

pulling (8.35 g m-2) followed by hoeing (27.56 g m-2), tine cultivator (46.65 g m-2), Nominee

100 SC (108.53 g m-2) and spike hoe (123.56 g m-2). The maximum weed dry weight of

sedges was recorded in no weeding (167.56 g m-2).

4.6 Weed biomass of broad leaf weeds (45 DAS)

The Fig. 4.3 showed that different weed management strategies significantly affected

weed biomass of broad leaf weeds during both the years at 45 DAS. During the year 2008

minimum weed dry weight was recorded in hand pulling (5.19 g m-2) followed by hoeing

(22.27 g m-2), tine cultivator (39.35 g m-2) and Nominee 100 SC (51.80 g m-2). Maximum

weed dry weight was found in no weeding (148.66 g m-2) that was statistically similar to

weed dry weight in spike hoe (148.13 g m-2).

During the year 2009 minimum weed dry weight was recorded in hand pulling (10.97

g m-2) followed by hoeing (36.54 g m-2), tine cultivator (49.87 g m-2) and Nominee 100 SC

(58.91 g m-2). Maximum weed dry weight was found in no weeding (156.92 g m-2) that was

statistically similar to weed dry weight in spike hoe (153.53 g m-2).

4.7 Total weed biomass (15 DAS)

The fig 4.4 showed that different weed management strategies significantly affected

total weed biomass during both the years at 15 DAS. During the year 2008 minimum weed

dry weight was recorded in hand pulling (0.75 g m-2) followed by hoeing (1.21 g m-2) and

tine cultivator (1.68 g m-2). Maximum weed dry weight was found in no weeding (2.85 g m-2)

that was statistically similar spike hoe (2.68 g m-2) and Nominee 100 SC (2.67 g m-2).

During the year 2009 minimum weed dry weight was recorded in hand pulling (1.13 g

m-2) followed by hoeing (1.36 g m-2) and tine cultivator (1.84 g m-2). Maximum weed dry

weight was found in Nominee 100 SC (3.04 g m-2) that was statistically similar spike hoe

(2.99 g m-2) and no weeding (2.98 g m-2).

4.8 Total weed biomass (30 DAS)

The Fig 4.5 showed that different weed management strategies significantly affected

total weed biomass during both the years at 30 DAS. During the year 2008 minimum weed

dry weight was recorded in hand pulling (6.27 g m-2) followed by hoeing (21.52 g m-2), tine

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Fig. 4.4 Effect of different weed management strategies on total weed biomass at

15 DAS

Fig. 4.5 Effect of different weed management strategies on total weed biomass at

30 DAS

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2008 2009

g m

-2

(a) 2008

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

0

20

40

60

80

100

120

140

160

180

2008 2009

g m

-2

(b) 2009

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

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39

Fig. 4.6 Effect of different weed management strategies on total weed biomass at

45 DAS

0

50

100

150

200

250

300

350

2008 2009

g m

-2

Hand pulling

Hoeing

Tine cultivator

Nominee

Spike hoe

No weeding

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cultivator (41.36 g m-2), Nominee 100 SC (70.48 g m-2) and spike hoe (144.17 g m-2).

Maximum weed dry weight was found in no weeding (154.77 g m-2).

During the year 2009 minimum weed dry weight was recorded in hand pulling (10.24

g m-2) followed by hoeing (26.15 g m-2), tine cultivator (45.98 g m-2), Nominee 100 SC

(78.28 g m-2) and spike hoe (135.48 g m-2). Maximum weed dry weight was found in no

weeding (159.40 g m-2).

4.9 Total weed biomass (45 DAS)

There was a non significant year effect on total weed biomass at 45 DAS, however

two years average data are discussed. The data presented in table 4.1 indicated the significant

effect of different weed management strategies on weed biomass. Highest weed biomass

(316.61 g m-2) was recorded in no weeding followed by spike hoe (271.30 g m-2), Nominee

(159.04 g m-2), tine cultivator (90.86 g m-2) and hoeing (58.84 g m-2). The lowest weed

biomass (15.89 g m-2) was observed in hand pulling.

4.10 Plant height

Analysis of the data revealed that both the years affected plant height of rice

significantly. Therefore results of both the years are discussed separately. The data regarding

plant height (Table 4.2) showed that different weed management strategies significantly

effected plant height at maturity.

During the year 2008, maximum plant height (95.97 cm) was recorded for the hand

pulling treatment followed by tine cultivator (90.83 cm), Nominee (89.77 cm) and spike hoe

(83.07 cm). Minimum plant height was observed in no weeding (73.97 cm).

During the year 2009, maximum plant height was recorded in hand pulling (94.44 cm)

followed by tine cultivator (89.32 cm) and spike hoe (81.28 cm). Plant height in Nominee

100 SC (87.97 cm) was similar to tine cultivator. Minimum plant height was found in no

weeding (72.02 cm).

Total weed biomass (45 DAS) and plant height were linearly related and the

regression accounted for 91% of the variation during 2008 and 2009 (Fig. 4.7).

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Table 4.1 Effect of different weed management strategies on weed Biomass at 45 DAS (g m-2) Treatment

2008

2009

Mean

No weeding

308.79

324.43

316.61 a

Hand pulling

12.46

19.31

15.89 f

Hoeing

53.63

64.05

58.84 e Tine cultivator

85.16

96.51

90.86 d

Spike hoe

265.55

277.06

271.30 b

Nominee 100 SC

150.66

167.43

159.04 c

LSD

9.15

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.2 Effect of different weed management strategies on plant height (cm)

Treatment

2008

2009

Mean

No weeding

73.97 d

72.02 d

72.99

Hand pulling

95.97 a

94.44 a

95.20

Hoeing

92.5 ab

90.57 ab

91.53 Tine cultivator

90.83 b

89.32 b

90.07

Spike hoe

83.07 c

81.28 c

82.17

Nominee 100 SC

89.77 b

87.97 b

88.86

LSD

4.57

4.83

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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Fig. 4.7 Relationship between total weed biomass (45 DAS) and plant height

y = -0.0637x + 96.993R² = 0.9126

50

55

60

65

70

75

80

85

90

95

100

0 50 100 150 200 250 300 350

Pla

nt h

eigh

t (c

m)

Weed biomass (g m-2)

(a) 2008

y = -0.0633x + 95.948R² = 0.9116

50

55

60

65

70

75

80

85

90

95

100

0 50 100 150 200 250 300 350

Pla

nt h

eigh

t (c

m)

Weed biomass (g m-2)

(b) 2009

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4.11 Total number of tillers

There was a significant year effect on total number of tillers of rice at maturity

therefore results of both the years are discussed separately.

The data (Table 4.3) revealed that different weed management strategies had

significant effect on total number of tillers m-2. During the year 2008, maximum total number

of tillers was recorded in hand pulling (401.44 m-2) followed by tine cultivator (379.10 m-2)

and Nominee 100 SC (333.59 m-2). Total number of tillers in spike hoe was 293.67 m-2

followed by no weeding (260.91 m-2).

During the year 2009, maximum total number of tillers (389.27 m-2) was noted in

hand pulling (389.27 m-2) followed by tine cultivator (373.46 m-2), Nominee 100 SC (316.71

m-2) and spike hoe (282.52 m-2). Minimum total number of tillers was recorded in no weeding

(227.89 m-2).

4.12 Number of fertile tillers

Significant year effect on number of fertile tillers of rice was found at maturity

therefore results of both the years are discussed separately.

The data presented in table 4.4 indicated that different weed management strategies

had significant effect on number of fertile tillers m-2. During the year 2008, maximum

number of fertile tillers was recorded in hand pulling (375.11 m-2) followed by hoeing

(364.63 m-2), tine cultivator (350.44 m-2), Nominee 100 SC (302.92 m-2) and spike hoe

(255.00 m-2). Minimum number of fertile tillers was recorded in no weeding (215.58 m-2).

Similar trend was observed during the year 2009. Significantly maximum number of

fertile tillers was observed in hand pulling (363.60 m-2) followed by tine cultivator (343.12 m-

2), Nominee 100 SC (283.38 m-2) and spike hoe (243.19 m-2). In no weeding (181.89 m-2)

significantly minimum number of fertile tillers was recorded.

Total weed biomass (45 DAS) and fertile tillers were linearly related and the

regression accounted for 98 and 96% of the variation during 2008 and 2009, respectively

(Fig. 4.8).

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Table 4.3 Effect of different weed management strategies on total number of tillers (m-2)

Treatment

2008

2009

Mean

No weeding

260.91 e

227.89 e

244.40

Hand pulling

401.44 a

389.27 a

395.35

Hoeing (with kasula)

392.96 ab

377.27 b

385.11 Tine cultivator

379.10 b

373.46 b

376.28

Spike hoe

293.67 d

282.52 d

288.09

Nominee 100 SC

333.59 c

316.71 c

325.15

LSD

14.22

8.85

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.4 Effect of different weed management strategies on number of fertile tillers (m-2) Treatment

2008

2009

Mean

No weeding

215.58 e

181.89 e

198.73

Hand pulling

375.11 a

363.60 a

369.35

Hoeing (with kasula)

364.63 a

349.27 b

356.94 Tine cultivator

350.44 b

343.12 b

346.78

Spike hoe

255.00 d

243.19 d

249.09

Nominee 100 SC

302.92 c

283.38 c

293.15

LSD

13.80

5.69

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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Table 4.5 Effect of different weed management strategies on number of unfertile tillers (m-2)

Treatment

2008

2009

Mean

No weeding

45.33

46.00

45.66 a

Hand pulling

26.33

25.67

26.00 d

Hoeing

28.33

28.00

28.16 cd Tine cultivator

28.67

30.33

29.5 cd

Spike hoe

38.67

39.33

39.00 b

Nominee 100 SC

30.67

33.33

32.00 c

LSD

4.12

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.6 Effect of different weed management strategies on panicle length (cm)

Treatment

2008

2009

Mean

No weeding

16.13 c

16.01 d

16.07

Hand pulling

23.90 a

23.8 a

23.85

Hoeing

22.93 a

22.79 b

22.86 Tine cultivator

22.77 a

22.62 b

22.69

Spike hoe

20.13 b

19.93 c

20.03

Nominee 100 SC

22.87 a

22.22 b

22.54

LSD

1.09

0.77

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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Fig. 4.8 Relationship between fertile tillers and total weed biomass (45 DAS)

y = -0.5387x + 389.28R² = 0.9865

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350

Fer

tile

til

lers

(m

-2)

Weed biomass (g m-2)

(a) 2008

y = -0.5782x + 385.51R² = 0.9648

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350

Fer

tile

til

lers

(m

-2)

Weed biomass (g m-2)

(b) 2009

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4.13 Number of unfertile tillers

Year effect was non significant on number of unfertile tillers, however two years

average data are discussed.

The data presented in table 4.7 revealed that there was a significant effect of different

weed management strategies on number of unfertile tillers. Significantly maximum number

of unfertile tillers was recorded in no weeding (45.66 m-2) followed by spike hoe (39.00 m-2)

and Nominee 100 SC (32.00 m-2). Number of unfertile tillers in tine cultivator (29.50 m-2)

and hoeing (28.16 m-2) was similar. Whereas, minimum number of unfertile tillers was

observed in hand pulling (26.00 m-2).

4.14 Panicle length

A significant year effect was found on panicle length at maturity therefore results of

both the years are discussed separately.

The data regarding panicle length (Table 4.6) showed that different weed management

strategies had significant effect on panicle length. During the year 2008, statistically similar

panicle length was observed in hoeing (22.93 cm), hand pulling (23.90 cm), tine cultivator

(22.77 cm) and Nominee 100 SC (22.87 cm) followed by spike hoe (20.13 cm). Minimum

panicle length was recorded in no weeding (16.13 cm).

During the year 2009 maximum panicle length was recorded in hand pulling (23.80

cm). Panicle length in hoeing (22.79 cm) was similar to tine cultivator (22.62 cm) followed

by Nominee 100 SC (22.22 cm), spike hoe (19.93 cm) and no weeding (16.01 cm).

4.15 Kernels per panicle

There was a non significant year effect on kernels per panicle, however two years

average data are discussed.

The data presented in table 4.7 revealed that different weed management strategies

affected kernels per panicle significantly. Maximum kernels per panicle were recorded in

hand pulling (77.19) and hoeing (75.70) followed by tine cultivator (73.73), Nominee 100 SC

(67.70), spike hoe (64.19 ) and no weeding (60.16).

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Table 4.7 Effect of different weed management strategies on kernels per Panicle Treatment

2008

2009

Mean

No weeding

60.43

59.89

60.16 e

Hand pulling

78.15

76.25

77.19 a

Hoeing (with kasula)

75.92

75.49

75.70 a Tine cultivator

74.31

73.16

73.73 b

Spike hoe

65.5

62.89

64.19 d

Nominee 100 SC

69.43

65.97

67.70 c

LSD

1.92

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.8 Effect of different weed management strategies on 1000 kernel weight (g)

Treatment

2008

2009

Mean

No weeding

14.5

15.17

14.83 e

Hand pulling

20.87

20.4

20.63 a

Hoeing (with kasula)

20.6

20.17

20.38 a Tine cultivator

19.47

19.2

19.33 b

Spike hoe

17.17

16.52

16.84 d

Nominee 100 SC

18.07

17.6

17.83 c

LSD

0.63

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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Fig. 4.9 Relationship between weed biomass (45 DAS) and kernels per panicle

y = -0.0564x + 78.857R² = 0.9801

40

45

50

55

60

65

70

75

80

85

0 50 100 150 200 250 300 350

Ker

nel

s p

er p

anic

le

Weed biomass (g m-2)

(a) 2008

y = -0.0561x + 77.819R² = 0.9632

40

45

50

55

60

65

70

75

80

0 50 100 150 200 250 300 350

Ker

nel

s pe

r pa

nic

le

Weed biomass (g m-2)

(b) 2009

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50

Fig. 4.10 Relationship between 1000 kernels weight and weed biomass (45 DAS)

y = -0.0195x + 21.294R² = 0.9317

5

7

9

11

13

15

17

19

21

23

0 50 100 150 200 250 300 350

1000

ker

nel

wei

ght

(g)

Weed biomass (g m-2)

(a) 2008

y = -0.0171x + 20.88R² = 0.9767

5

7

9

11

13

15

17

19

21

23

0 50 100 150 200 250 300 350

1000

ker

nel

wei

ght

(g)

Weed biomass (g m-2)

(b) 2009

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51

Total weed biomass (45 DAS) and kernels per panicle were linearly related and the

regression accounted for 98 and 96% of the variation during 2008 and 2009, respectively

(Fig. 4.9).

4.16 1000 kernel weight

Year effect was non significant however two years average data are discussed.

The data (Table 4.8) indicated that there was a significant effect of different weed

management strategies on 1000 kernel weight. Significantly heavier 1000 kernel weight was

recorded in hand pulling (20.63 g) followed by hoeing (20.38 g), tine cultivator (19.33 g),

Nominee 100 SC (17.83 g), spike hoe (16.84 g) and no weeding (14.83 g).

Total weed biomass (45 DAS) and 1000 kernel weight were linearly related and the

regression accounted for 93 and 97% of the variation during 2008 and 2009, respectively

(Fig. 4.10).

4.17 Biological yield

The year effect was found significant on biological yield at maturity therefore results

of both the years are discussed separately.

The data (Table 4.9) revealed that different weed management strategies had

significant effect on biological yield. During the year 2008, maximum biological yield was

recorded in hand pulling (13.18 t ha-1) followed by tine cultivator (12.09 t ha-1), Nominee 100

SC (9.90 t ha-1) and spike hoe (8.65 t ha-1). Biological yield in no weeding (6.03 t ha-1) was

observed minimum.

During the year 2009, higher biological yield was observed in hand pulling (12.62 t

ha-1) and hoeing (12.45 t ha-1) followed by tine cultivator (11.89 t ha-1), Nominee 100 SC

(9.20 t ha-1) and spike hoe (8.13 t ha-1). Lowest biological yield was observed in no weeding

(5.67 t ha-1).

4.18 Paddy yield

There was a significant year effect on paddy yield at maturity therefore results of both

the years are discussed separately.

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Table 4.9 Effect of different weed management strategies on biological yield (t ha-1) Treatment

2008

2009

Mean

No weeding

6.03 e

5.67 e

5.85

Hand pulling

13.18 a

12.62 a

12.89

Hoeing (with kasula)

12.95 ab

12.45 a

12.69 Tine cultivator

12.09 b

11.89 b

11.99

Spike hoe

8.65 d

8.13 d

8.39

Nominee 100 SC

9.90 c

9.20 c

9.54

LSD

0.95

0.40

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.10 Effect of different weed management strategies on paddy yield (t ha-1)

Treatment

2008

2009

Mean

No weeding

1.47 e

1.27 e

1.37

Hand pulling

4.45 a 4.35 a

4.44

Hoeing (with kasula)

4.21 a

4.11 a

4.16 Tine cultivator

3.91 b

3.81 b

3.86

Spike hoe

2.44 d

2.05 d

2.25

Nominee 100 SC

3.02 c

2.59 c

2.81

LSD

0.29

0.26

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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53

Fig. 4.11 Relationship between paddy yield and total weed biomass (45 DAS)

y = -0.0095x + 4.6445R² = 0.9681

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0 50 100 150 200 250 300 350

Pad

dy y

ield

(t

ha-1

)

Weed biomass (g m-2)

(a) 2008

y = -0.0101x + 4.6289R² = 0.9712

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0 50 100 150 200 250 300 350

Pad

dy

yiel

d (

t h

a-1)

Weed biomass (g m-2)

(b) 2009

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Fig. 4.12 Relationship between paddy yield and number of fertile tillers

y = 0.0182x - 2.3506R² = 0.9945

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

160 210 260 310 360 410

Pad

dy

yiel

d(t

ha-1

)

Fertile tillers (m-2)

(a) 2008

y = 0.0172x - 2.0156R² = 0.9929

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

160 210 260 310 360 410

Pad

dy

yiel

d(t

ha-1

)

Fertile tillers (m-2)

(b) 2009

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Fig. 4.13 Relationship between paddy yield and kernels per panicle

y = 0.1571x - 7.8718R² = 0.9775

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

55 60 65 70 75 80 85

Pad

dy

yiel

d(t

ha-1

)

kernels per panicle

(a) 2008

y = 0.1588x - 8.0522R² = 0.9733

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

55 60 65 70 75 80 85

Pad

dy

yiel

d(t

ha-1

)

kernels per panicle

(b) 2009

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Fig. 4.14 Relationship between paddy yield and 1000 kernel weight

y = 0.5816x - 7.5592R² = 0.98

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

14 15 16 17 18 19 20 21 22

Pad

dy

yiel

d(t

ha-1

)

1000 kernel weight (g)

(a) 2008

y = 0.6142x - 8.2054R² = 0.9703

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

14 15 16 17 18 19 20 21

Pad

dy

yiel

d(t

ha-1

)

1000 kernel weight (g)

(b) 2009

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The data pertaining paddy yield presented in table 4.10 indicated that all weed

management strategies had significant effect on paddy yield. During the year 2008,

significantly maximum paddy yield (4.45 t ha-1) was recorded in hand pulling similar to

hoeing (4.21 t ha-1) followed by tine cultivator (3.91 t ha-1), Nominee 100 SC (3.02 t ha-1) and

spike hoe (2.44 t ha-1). Minimum paddy yield was recorded in no weeding (1.47 t ha-1).

Similar trend was observed during the year 2009. Significantly maximum paddy yield

(4.35 t ha-1) was recorded in hand pulling and hoeing (4.11 t ha-1) followed by tine cultivator

(3.81 t ha-1), Nominee 100 SC (2.59 t ha-1) and spike hoe (2.05). Lowest paddy yield was

found in no weeding (1.27 t ha-1).

Total weed biomass (45 DAS) and paddy yield were linearly related and the

regression accounted for 96 and 97% of the variation during 2008 and 2009, respectively

(Fig. 4.11). Relationship of paddy yield with number of fertile tillers, kernels per panicle and

1000 kernel weight was linear during 2008 and 2009 (Fig. 4.12-14).

4.19 Straw yield

The year effect was found to be non significant on straw yield however two years

average data are discussed. The data presented in table 4.11 revealed that there was a

significant effect of different weed management strategies on straw yield. Significantly

maximum straw yield was recorded in hand pulling (8.53 t ha-1) followed by tine cultivator

(8.12 t ha-1), Nominee 100 SC (6.73 t ha-1) and spike hoe (6.14 t ha-1). In no weeding (4.47 t

ha-1) minimum straw yield was recorded.

4.20 Harvest index

The year effect was non significant on harvest index however two years average data

are discussed. The data (Table 4.12) showed that there was a significant effect of different

weed management strategies on harvest index. Significantly maximum harvest index was

recorded in hand pulling (34.17) followed by tine cultivator (32.24), Nominee 100 SC

(29.38), spike hoe (26.77) and no weeding (23.40).

4.21 Opaque kernels

There was a non significant year effect on opaque kernels (%), however two years

average data are discussed.

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Table 4.11 Effect of different weed management strategies on straw yield (t ha-1) Treatment

2008

2009

Mean

No weeding

4.55

4.39

4.47 e

Hand pulling

8.72

8.26

8.53 a

Hoeing

8.73

8.34

8.49 ab Tine cultivator

8.18

8.07

8.12 b

Spike hoe

6.21

6.07

6.14 d

Nominee 100 SC

6.87

6.60

6.73 c

LSD

0.38

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.12 Effect of different weed management strategies on harvest Index Treatment

2008

2009

Mean

No weeding

24.4

22.48

23.4 e

Hand pulling

33.83

34.51

34.17 a

Hoeing

32.55

32.03

32.79 b Tine cultivator

32.36

32.12

32.24 b

Spike hoe

28.2

25.27

26.77 d

Nominee 100 SC

30.55

28.21

29.38 c

LSD

0.05

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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Table 4.13 Effect of different weed management strategies on opaque kernels

Treatment

2008

2009

Mean

No weeding

8.88 a

8.63

8.75 a

Hand pulling

7.32 e

7.42

7.37 e

Hoeing

7.43 e

7.52

7.47 e Tine cultivator

7.72 d

7.75

7.73 d

Spike hoe

8.42 b

8.50

8.46 b

Nominee 100 SC

8.02 c

8.07

8.04 c

LSD

0.19

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.14 Effect of different Weed management strategies on abortive kernels

Treatment

2008

2009

Mean

No weeding

3.86

3.88

3.87 a

Hand pulling

3.31

3.32

3.31 f

Hoeing

3.41

3.04

3.40 e Tine cultivator

3.50

3.52

3.51 d

Spike hoe

3.72

3.78

3.75 b

Nominee 100 SC

3.58

3.63

3.61 c

LSD

0.04

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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The opaque kernels (%) were significantly affected by different weed management

strategies (Table 4.13). Significantly maximum opaque kernels (%) were recorded in no

weeding (8.75 %) followed by spike hoe (8.46 %), Nominee 100 SC (8.04 %) and tine

cultivator (7.73 %) hoeing (7.47 %) and hand pulling (7.37 %).

4.22 Abortive kernels

A non significant year effect was recorded on abortive kernels (%), however two

years average data are discussed. The data presented in table 4.14 indicated that there was a

significant effect of different weed management strategies on abortive kernels (%).

Significantly maximum abortive kernels (%) were recorded in no weeding (3.87 %) followed

by spike hoe (3.75 %), Nominee 100 SC (3.61 %), tine cultivator (3.51 %), hoeing (3.40 %)

and hand pulling (3.31 %).

4.23 Normal kernels

There was a significant year effect on normal kernels (%) at maturity therefore results

of both years are discussed separately.

The data (Table 4.17) revealed that normal kernels (%) were significantly affected by

different weed management strategies. During the year 2008, significantly maximum normal

kernels (%) was recorded in hand pulling (63.21 %) followed by hoeing (62.15 %), tine

cultivator (60.04 %), Nominee 100 SC (58.15 %), spike hoe (55.93 %) and no weeding

(53.74 %).

During the year 2009, significantly maximum normal kernels (%) were recorded for

hand pulling (62.37 %) followed by hoeing (61.21 %), tine cultivator (59.32 %), Nominee

100 SC (58.03 %), spike hoe (56.06 %) and no weeding (53.63 %).

4.24 Sterile spikelets

A significant year effect on sterile spikeleets (%) was observed therefore results of

both the years are discussed separately.

The data presented in Table 4.18 indicated that there was a significant effect of

different weed management strategies on sterile spikeleets (%). During the year 2008,

significantly maximum sterile spikeleets (%) were recorded in no weeding (11.80 %)

followed by spike hoe (10.15 %), Nominee 100 SC (9.46 %) and hand pulling (8.25 %).

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Table 4.15 Effect of different weed management strategies on normal kernels

Treatment

2008

2009

Mean

No weeding

53.74 f

53.63 f

53.68

Hand pulling

63.21 a

62.37 a

62.79

Hoeing

62.15 b

61.21 b

61.68 Tine cultivator

60.04 c

59.32 c

59.68

Spike hoe

55.93 e

56.06 e

55.99

Nominee 100 SC

58.15 d

58.03 d

58.09

LSD

0.84

0.71

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

Table 4.16 Effect of different weed management strategies on sterile spikelets

Treatment

2008

2009

Mean

No weeding

11.8 a

12.49 a

12.14

Hand pulling

8.25 e

8.51 e

8.38

Hoeing

8.65 de

9.00 de

8.82 Tine cultivator

8.94 cd

9.27 d

9.11

Spike hoe

10.15 b

11.15 b

10.65

Nominee 100 SC

9.46 c

10.17 c

9.81

LSD

0.58

0.49

Any two means not sharing a letter in common differ significantly (p ≤ 0.05)

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During the year 2009, significantly maximum sterile spikeleets (%) were recorded in

no weeding (12.49 %) followed by spike hoe (11.15 %), Nominee 100 SC (10.17 %), tine

cultivator (9.27 %) and hand pulling (8.51 %).

4.25 Leaf area index

The Fig. 4.15 showed that during the year 2008 there was a gradual increase in leaf

area index (LAI) of rice under different weed management strategies. Maximum LAI at 90

DAS was noted in hand pulling (4.07) followed by hoeing (3.96), tine cultivator (3.85),

Nominee 100 SC (3.68) and spike hoe (3.31) at 90 DAS. Minimum LAI at 90 DAS was

recorded in no weeding (3.28).

During the year 2009 maximum LAI at 90 DAS was noted in hand pulling (3.96)

followed by hoeing (3.91), tine cultivator (3.79), Nominee 100 SC (3.59) and spike hoe

(3.26) at 90 DAS. Minimum LAI at 90 DAS was recorded in no weeding (3.21).

4.26 Crop growth rate

The Fig. 4.16 showed that during the year 2008 there was a gradual increase in crop

growth rate (CGR) of different weed management strategies. Maximum CGR was noted in

hand pulling (25.14 g m-2 d-1) followed by hoeing (24.68 g m-2 d-1), tine cultivator (24.71 g m-

2 d-1), Nominee 100 SC (24.38 g m-2 d-1) and spike hoe (20.14 g m-2 d-15 ) at 90 DAS.

Minimum CGR at 90 DAS was recorded in no weeding (17.95 g m-2 d-1).

During the year 2009 maximum CGR was noted in hand pulling (25.30 g m-2 d-1)

followed by tine cultivator (24.80 g m-2 d-1), hoeing (24.60 g m-2 d-1), Nominee 100 SC

(24.35 g m-2 d-1) and spike hoe (19.36 g m-2 d-15 ) at 90 DAS. Minimum CGR at 90 DAS was

recorded in no weeding (17.99 g m-2 d-1).

4.27 Leaf area duration

The Fig. 4.17 showed that different weed management strategies significantly affected

the cumulative leaf area duration (LAD) at 105 DAS during the year 2008. The maximum

LAD was noted in hand pulling (136.65 days) followed by hoeing (133.83 days), tine

cultivator (129.95 days), Nominee 100 SC (124.08 days) and spike hoe (105.53 days). The

minimum LAD was observed in no weeding (104.49 days).

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63

Fig. 4.15 Periodic changes in leaf area index of different weed management

strategies

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

60 75 90 105

L A

I

D A S

(a) 2008

No weeding

Hand pulling

Hoeing

Tine cultivator

Spike hoe

Nominee

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

60 75 90 105

L A

I

D A S

(b) 2009

No weeding

Hand pulling

Hoeing

Tine cultivator

Spike hoe

Nominee

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64

Fig. 4.16 Periodic changes in crop growth rate of different weed management

strategies

0.0

5.0

10.0

15.0

20.0

25.0

30.0

75 90 105

C G

R (

g m

-2d

-1)

D A S

(a) 2008

No weeding

Hand pulling

Hoeing

Tine cultivator

Spike hoe

Nominee

0.0

5.0

10.0

15.0

20.0

25.0

30.0

75 90 105

C G

R (

g m

-2d-1

)

D A S

(b) 2009

No weeding

Hand pulling

Hoeing

Tine cultivator

Spike hoe

Nominee

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65

Fig. 4.17 Cumulative leaf area duration of different weed management strategies at

105 DAS

0

20

40

60

80

100

120

140

160

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

L A

D (

day

s)

(a) 2008

0

20

40

60

80

100

120

140

160

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

L A

D (

day

s)

(b) 2009

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Different weed management strategies also significantly affected the cumulative leaf

area duration (LAD) at 105 DAS during the year 2009. The maximum LAD was noted in

hand pulling (136.93 days) followed by hoeing (134.87 days), tine cultivator (129.88 days),

Nominee 100 SC (124.30 days) and spike hoe (101.33 days) at DAS 105. The minimum LAD

was observed in no weeding (101.06 days).

4.28 Total dry matter

The data (Fig 4.18) revealed that during the year 2008 different weed management

strategies significantly affected total dry matter (TDM) production at 105 DAS. Maximum

TDM was noted in hand pulling (905 g) followed by hoeing (850 g), tine cultivator (806.67

g), Nominee 100 SC (737.67 g) and spike hoe (573.67 g). Minimum TDM was recorded in no

weeding (528.33 g).

Different weed management strategies significantly affected total dry matter (TDM)

production at 105 DAS during the year 2009. The maximum TDM was recorded in hand

pulling (894.83 g) followed by hoeing (842.23 g), tine cultivator (796.69 g), Nominee 100 SC

(724.20 g) and spike hoe (562.945g). The minimum TDM was observed in no weeding

(518.72 g).

4.29 Net assimilation rate

The fig 4.19 showed that different weed management strategies significantly affected

net assimilation rate (NAR) at 105 DAS during the year 2008. Maximum NAR was noted in

hand pulling (6.62 g m-2 d-1) followed by hoeing (6.35 g m-2 d-1), tine cultivator (6.20 g m-2 d-

1), Nominee 100 SC (5.94 g m-2 d-1) and spike hoe (5.45 g m-2 d-1). Minimum NAR was

recorded in no weeding (5.06 g m-2 d-1).

During the year 2009 different weed management strategies also significantly affected

net assimilation rate (NAR) at 105 DAS. The maximum NAR was recorded in hand pulling

(6.53 g m-2 d-1) followed by hoeing (6.24 g m-2 d-1), tine cultivator (6.13 g m-2 d-1), Nominee

100 SC (5.82 g m-2 d-1) and spike hoe (5.55 g m-2 d-1). The minimum NAR was observed in

no weeding (5.13 g m-2 d-1).

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Fig. 4.18 Total dry matter of different weed management strategies at 105 DAS

300

400

500

600

700

800

900

1000

1100

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

T D

M (

g)

(a) 2008

0

200

400

600

800

1000

1200

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

T D

M (

g)

(b) 2009

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Fig. 4.19 Net assimilation rate of different weed management strategies at 105 DAS

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

N A

R (

g m

-2d-1

)

(a) 2008

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

No weeding Hand pulling Hoeing Tine cultivator Spike hoe Nominee

N A

R (

g m

-2d-1

)

(b) 2009

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4.30 Economic analysis

During the year 2008 maximum net returns were obtained by hand weeding (Rs.

43188) followed by hoeing (Rs. 41035), tine cultivator (Rs. 39525), Nominee (Rs. 16639)

and spike hoe (Rs. 1326). Maximum benefit cost ratio (BCR) was obtained by tine cultivator

(1.62) followed by hoeing (1.58), hand weeding (1.58), Nominee (1.26) and spike hoe (1.02).

During the year 2009 maximum net returns were obtained by hand weeding (Rs.

56905) followed by hoeing (Rs. 53713), tine cultivator (Rs. 50958), Nominee (Rs. 13942).

Maximum benefit cost ratio (BCR) was obtained by tine cultivator (1.75) followed by hoeing

(1.72), hand weeding (1.72), Nominee (1.20).

4.31 Marginal rate of return

During the year 2008 maximum marginal rate of return was found in tine cultivator

(6731%) which was followed by Nominee (3126%), hand pulling (54%) and hoeing (24%).

During the year 2009 maximum marginal rate of return was found in tine cultivator (10887%)

which was followed by Nominee (3154%), hand pulling (80%) and hoeing (43%).

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Table 4.17 Effect of different weed management strategies on economic returns during the year 2008

Treatments

Paddy yield (t ha-1)

Adjusted paddy yield (t ha-1)

Value (Rs ha-1)

Straw yield (t ha-1)

Adjusted straw yield (t ha-1)

Value (Rs. ha-1)

Gross income (Rs. ha-1)

*Variable cost (Rs. ha-1)

Total cost (Rs. ha-1)

Net return (Rs. ha-1)

BCR

No weeding

1.47

1.32 36960 4.55

4.1 2878 39838 0 62587 -22749 0.64

Hand pulling

4.45

4.01 112280 8.72

7.85 5495 117775 12000 74587 43188 1.58 Hoeing

4.21

3.79 106120 8.73 7.86 5502 111622 8000 70587 41035 1.58

Tine cultivator

3.91

3.52 98560 8.18 7.36 5152 103712 1600 64187 39525 1.62

Spike hoe

2.44

2.20 61600 6.21 5.59 3913 65513 1600 64187 1326 1.02

Nominee 100 SC

3.02

2.72 76160 6.87 6.18 4326 80486 1260 63847 16639 1.26

Paddy price per kg = Rs. 28

Straw price per ton = Rs. 700

Fixed cost of production = Rs. 62587 (Appendix 1)

*Appendix 2

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70

Table 4.18 Effect of different weed management strategies on economic returns during the year 2009

Paddy price per kg = Rs. 33

Straw price per ton = Rs. 850

Fixed cost of production = Rs. 66770 (Appendix 4)

*Appendix 2

Treatments

Paddy yield (t ha-

1)

Adjusted paddy yield (t ha-1)

Value (Rs ha-1)

Straw yield (t ha-1)

Adjusted straw yield (t ha-1)

Value (Rs. ha-1)

Gross income (Rs. ha-1)

*Variable cost (Rs. ha-1)

Total cost (Rs. ha-1)

Net return (Rs. ha-1)

BCR

No weeding

1.27 1.14 37620 4.39 3.95 3357 40977 0 66770 -25793 0.61

Hand pulling

4.35 3.92 129360 8.26 7.43 6315 135675 12000 78770 56905 1.72 Hoeing

4.11 3.69 122100 8.34 7.51 6383 128483 8000 74770 53713 1.72

Tine cultivator

3.81 3.42 113157 8.07 7.26 6171 119328 1600 68370 50958 1.75

Spike hoe

2.05 1.84 60885 6.07 5.46 4641 65526 1600 68370 -2844 0.96

Nominee 100 SC

2.59 2.33 76923 6.60 5.94 5049 81972 1260 68030 13942 1.20

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71

Table 4.19 Effect of different weed management strategies on dominance analysis during 2008

Treatments Variable cost (Rs. ha-1) Net field benefits (Rs. ha-1)

No Weeding 0 39838

Chemical control 1260 79226

Spike Hoe 1600 63913 D

Tine Cultivator 1600 102112

Hoeing 8000 103622

Hand pulling 12000 105775

Table 4.20 Effect of different weed management strategies on marginal analysis during 2008

Treatments Cost that

vary (Rs. ha-1)

Marginal cost that

vary (Rs. ha-1)

Net field benefits

(Rs. ha-1)

Marginal net

benefits (Rs. ha-1)

Marginal rate of return

(%)

No Weeding 0 0 39838 - -

Chemical control 1260 1260 79226 39388 3126

Tine Cultivator 1600 340 102112 22886 6731

Hoeing 8000 6400 103622 1510 24

Hand pulling 12000 4000 105775 2153 54

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72

Table 4.21 Effect of different weed management strategies on dominance analysis during 2009

Treatments Variable cost (Rs. ha-1) Net field benefits (Rs. ha-1)

No Weeding 0 40977

Chemical control 1260 80712

Spike Hoe 1600 63926 D

Tine Cultivator 1600 117728

Hoeing 8000 120483

Hand pulling 12000 123675

Table 4.22 Effect of different weed management strategies on marginal analysis during 2009

Treatments Cost that

vary (Rs. ha-1)

Marginal cost that

vary (Rs. ha-1)

Net field benefits

(Rs. ha-1)

Marginal net

benefits (Rs. ha-1)

Marginal rate of return

(%)

No Weeding 0 0 40977 - -

Chemical control 1260 1260 80712 39735 3154

Tine Cultivator 1600 340 117728 37016 10887

Hoeing 8000 6400 120483 2755 43

Hand pulling 12000 4000 123675 3192 80

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73

Discussion

This experiment was conducted during 2008 and 2009 at Agronomic Research Farm,

University of Agriculture Faisalabad. Seed of variety Super Basmati with good vigor and

germination percentage was dry direct seeded using automatic drill (seed-cum-fertilizer drill)

after land preparation. It allowed line sowing maintaining 22.5 cm row to row distance and

facilitated manual and mechanical weeding. Drill tilled the soil at shallow depth (4-5 cm),

sowed the seeds and covered them with soil for better seed to soil contact, all in a single pass.

Kumar and Ladha (2011) also reported that drill sowing facilitated weed control between

rows, saved seed and placed the fertilizer at proper depth. Placing seeds below soil surface

also reduced seed damage caused by high rainfall. High Quality seed was used because larger

seeds with greater carbohydrate reserves have increased ability to emerge even from greater

burial depths, similar findings were reported by Baskin and Baskin (1998). Within rows

distance was maintained at 22.5 cm because ppin this range growth and seed production of

various weeds in aerobic conditions was less as compared to wider rows as reported by

Chauhan and Johnson (2010a). Similarly Akobundu and Ahissou (1985) reported that row

spacing (15–45-cm) in direct-seeded rice had little effect on the paddy yield of the crop in the

absence of weeds but in competition with weeds the wider spacing resulted in significantly

lower grain yield.

Weeds are one of the major biological constraints to direct seeded rice production and

are notorious yield reducers, in many situations economically more important than insects,

fungi or other pest organisms (Savary et al., 1997). Weed biomass differed significantly in all

weed control treatments. Weeds were removed manually in hand pulling treatment, four

times weeding resulted in the lowest weed dry weight (at 45 DAS) among all treatments.

Sharma (1997) and Johnson et al. (2004) also reported minimum weed dry weight in hand

weeding. Hoeing by kasula produced less weed dry weight than no weeding, spike hoe,

Nominee 100 SC and tine cultivator. Hoeing removed inter row weeds which might be the

reason of low weed dry weight. Similar results were observed by Akbar et al. (2011). More

weed dry weight than hand pulling was possibly due to within the rows weeds that were

remained uncontrolled.

Weed dry weight in tine cultivator was less than no weeding, spike hoe and Nominee

100 SC possibly because it uprooted and removed inter row weeds, controlling early flushes

of weeds. Second reason of less weed biomass might be beushaning which killed the weeds

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with single stem. This was also reported by Rao, et al. (2007) and Sharma (1997). Tine

cultivator produced more weed dry weight than hoeing and hand pulling possibly because

weeds that were within rows not controlled. Results of Fazlollaalh et al. (2011), Remington

and Posner (2000) and Sharma (1997) were also in line with above findings.

Application of Nominee 100 SC resulted in less weed biomass than spike hoe and no

weeding. Reason might be because Nominee (bispyrabic sodium) is an acetol-actate synthase

inhibitor which controlled weeds. Similar observations were reported by Fischer et al. (2000).

Nominee 100 SC produced more weed dry weight than hand pulling, hoeing and tine

cultivator. Increased weed dry weight in this study might have been due to increased critical

period of weed infestation. Nominee 100 SC was applied at 20 DAS and weeds might have

competed with rice crop for a longer period. This prolonged competition period possibly

provided a considerable opportunity for weeds to emerge subsequently and produce seeds.

Studies by Chauhan and Johnson (2011) revealed that in direct seeded rice weed competition

period was prolonged. Findings of Johnson et al., (2004) were contradictory who expressed

that critical period for weed competition in aerobic rice was 29-32 days.

Weed dry weight recorded in spike hoe treatment was higher than hand pulling,

hoeing, tine cultivator and Nominee 100 SC; reason might be because it neither uprooted nor

pulled weeds. Spike hoe produced lower weed biomass than no weeding, possibly due to

beushaning effect because the whole crop and weeds were laid down with soil surface after

inter row cultivation resulting in death of single stem weeds. Similar findings were reported

by Rao et al. (2007). These results showed some contradictions with Sharma (1997) who

reported beushaning as a very effective technique and had a complete control over most of

the rice weeds.

Highest weed biomass was recorded in no weeding, might have been due to several

reasons. Firstly aerobic soil conditions were conducive to the germination and growth of

weeds as reported by Rao et al. (2007). Secondly emerging direct seeded rice seedlings were

less competitive with concurrently emerging weeds (Kumar et al., 2008a). Third reason of

highest weed biomass might be competitive advantage of C4 weeds which increased their

efficiency to use crop nutrients more than rice. Findings of Holm et al. (1991) were in

support of this reason. Heavy and quicker second flush of weeds might be another reason of

highest weed biomass. Almost similar results were reported by Ekleme et al. (2009), Singh et

al. (2008) and Mann et al. (2007).

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75

Although plant height is a genetic character but height of aerobic rice substantially

decreases when dry weed biomass exceeds (Zhao et al., 2006). Taller plants in all weed

management treatments as compared to weedy check were observed during this study. Higher

plant height in hand pulling, hoeing, tine cultivator and Nominee 100 SC might be attributed

to availability of proper nutrients and space resulting in good leaf canopy because of low

weed infestation. Phoung et al. (2005) found that N uptake was maximum with good weed

control practices in direct seeded rice, resulting in taller plants. Correlation between weed

biomass and plant height was negative and also supported by studies of Ekleme et al. (2009).

Shorter plants in no weeding and spike hoe were recorded in current study. This might have

been due to more weeds, less available space and nutrients. Phoung et al. (2005) reported that

when weeds were more than more N uptake by weeds as compared to rice plants. Negative

correlation between plant height and weed biomass is also strengthening our results. Similar

findings were observed by Mann et al. (2007).

Variation in fertile tillers among all treatments was observed in current studies. Less

fertile tillers were observed in no weeding as compared to all other treatments. In general

number of effective tillers decreased as the weed-infested period was extended, reasons might

be; Firstly aerobic soil conditions were conducive to the germination and growth of weeds as

reported by Rao et al. (2007). Secondly emerging direct seeded rice seedlings were less

competitive with concurrently emerging weeds (Kumar et al., 2008a). Third reason of less

fertile tillers might be competitive advantage of C4 weeds which increased their efficiency to

use crop nutrients more than rice. Findings of Holm et al. (1991) are in support of this reason.

Heavy and quicker second flush of weeds might be another reason of lees fertile tillers.

Similar findings were reported by Sharma et al. (1977). Negative co relation between weed

dry weight and fertile tillers is supporting but in spike hoe more number of productive tillers

with high weed infestation this might have been due to beushaning effect which increased

fertile tillers. More fertile tillers in hand pulling, hoeing and tine cultivator were observed.

This increase in fertile tillers might have been due to less early competition of crop with

weeds and more availability of moisture and nutrients. Increase in fertile tillers with

decreased weed biomass was also observed by Phoung et al. (2005). These Results were also

in line with findings of Ekleme et al. (2009), Mann et al. (2007), Singh et al. (2007) and

Fischer et al. (2001).

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The panicle of rice is an organ of photosynthesis as well as storage place of

photosynthetic products (Hirota et al., 1990) and panicle size is closely related to yield

formation. Rice yield is often constrained by panicle size especially in aerobic rice culture

(Kato et al., 2006a). Panicle length in this study varied significantly in all weed control

treatments. Longer panicle length was observed in hand pulling, hoeing, tine cultivator and

Nominee 100 SC. Reasons might be; good crop stand, taller plants, good canopy and less

weed competition. Singh et al., 2007 also reported longer panicles with good weed control

treatments as compared to weedy check. Shorter panicle length in no weeding and spike hoe

may be due to dwarf plants, low photosynthetic activity and more weed infestation.

Correlation between panicle length and weed biomass is also negative. These Results are in

line with findings of Mann et al. (2007).

Rice grain yield is determined by three yield components, number of panicle, kernel

weight and number of kernels per panicle. Kernels per panicle are a key component of the

grain yield (Zhang et al., 2011). Crop with high number of kernels per panicle was found

more resistant to lodging (Liu et al., 2009). Variation in kernels per panicle was observed

among all weed control treatments in our study. Higher number of kernels per panicle in hand

pulling, hoeing tine cultivator and Nominee 100 SC might have been due to taller plants more

photosynthetic activity and proper availability of nitrogen. Kernel formation is usually

affected by the nitrogen availability at panicle initiation. In current studies more kernels per

panicle might have been due to increased nitrogen availability at panicle initiation. Similar

findings were observed by Yang et al. (2005). Less number of kernels per panicle in no

weeding and spike hoe with higher weed biomass attributed to competition amongst the crop

and weeds. The growth of weeds in no weeding and spike hoe went unchecked that might

have been reduced the availability of moisture and other plant nutrients like nitrogen to the

crop plant and eventually resulted in reduced size of panicles with less number of kernels also

reported by Phoung et al. (2005). The number of kernels per panicle correlated negatively

with weed dry weight. Singh et al. (2007) also observed less number of kernel panicle-1 with

poor weed management strategies. Similar results were also observed by Fazlollah et al.

(2011) and Mann et al. (2007).

Although rice is known for its relatively constant 1000-kernel weight because of a

rigid hull limiting kernel size and variable proportions of spikelet sterility that are regulated

according to available assimilates (Yoshida, 1981) but in this study 1000 kernel weight was

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77

significantly affected by various weed control methods. Heavier 1000 kernel weight

recorded in hand pulling, hoeing and tine cultivator might be due to less weed competition,

more availability of nutrients with lesser weed dry weight. Due to lower weed biomass the

florets may have utilized the soil nutrients to their fullest extent to develop heavy 1000 kernel

weight. Similar results were observed by Fazlollah et al. (2011) Singh et al. (2007) and

Phoung et al. (2005). Lighter 1000 kernel weight observed in no weeding and spike hoe

might be due to more weed competition and less availability of nutrients. Findings of Singh et

al. (2007) also revealed that poor weed management strategies resulted in lower 1000 kernel

weight.

Significant variation in paddy yield was observed in various weed management

strategies. Yield reduction was in range of 5 - 68% as compared to hand pulling. Similar high

ranges were reported by various researchers. Fujisaka et al. (1993) reported that aerobic soil

conditions are conducive for germination and growth of highly competitive weeds, which

cause grain yield losses of 50 - 91%, similarly Becker et al. (2003) found that yield losses

due to weed competition ranges from 12 - 100%.

Paddy yield in hand pulling and hoeing was 221 and 203% more than no weeding

respectively. This increase in yield might be due to minimum presence of weeds during

critical competition period. Studies of Haefele et al. (2000) suggested that there was a

considerable scope to increase yield with improved weed control in direct seeded rice. Proper

availability of nutrients, space and moisture resulted in more fertile tillers, more kernels

panicle-1 and heavier 1000 kernel weight providing high returns in the form of paddy yield.

Similar findings were observed by Phoung et al. (2005).

Paddy yield observed in tine cultivator was 141, 71 and 37% more than no weeding,

spike and hoe Nominee respectively while 13 and 7% less than hand pulling and hoeing

respectively. Increase in yield might be due to good inter row weed control and low weed dry

weight as compared to no weeding. Fazlollah et al. (2011) reported similar results. Second

reason of increased paddy yield might be due to an increase in soil ventilation resulting in

better growth of root, stem and claw. Findings of Fernandes and Uphoff (2002) favored our

observations. Third reason probably the beushaning effect that was also reported by Sharma

(1997). Similar findings were reported by Kumar (2003); he compared the rotary hand

weeders with the common methods of weeding in India. In that study the mechanical weed

control significantly increased the grain yield of rice plants and mechanical weeding had

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78

advantage of 10.9% yield increase per hectare rather than using hand weeding. Fazlolallh et

al. (2001) an Iranian scientist compared two mechanical weeders in rice; mechanical weeder

with engine power and mechanical weeder without engine power both resulting in good yield

as compared to no weeding. Paddy yield is 12% less than hand pulling probably due to more

weed dry weight than hand pulling because with in row weeds were mostly not controlled.

Yield resulted in weed control by Nominee 100 SC was 105 and 25% more than no

weeding and spike hoe respectively while 58 and 37% less than hand pulling and tine

cultivator respectively. Reduction in yield might be due to more weeds infestation for a

longer period. Nominee was applied at 20 DAS and weeds might have competed for a longer

period. This prolonged competition period possibly provided a considerable opportunity for

weeds to emerge subsequently and produce seeds. Studies by Chauhan and Johnson (2011)

revealed that in direct seeded rice weed competition period was prolonged. Findings of

Johnson et al. (2004) were contradictory who expressed that critical period for weed

competition in aerobic rice was 29-32. Findings of current study are also in line with

Remington and Posner (2000) they done a research about weeds control in the direct

cultivation of rice in Gambia and found that delay in weed control during weed competition

period causes 25 kg ha-1 day-1 decrease in rice yield. Nominee 100 SC resulted in more paddy

yield than spike hoe and no weeding. Reason might be because Nominee (bispyrabic sodium)

is an acetol-actate synthase inhibitor which controlled weeds of rice and rice yield was

increased. Similar observations were reported by Fischer et al. (2000).

Paddy yield recorded in weed control by Spike hoe was 97, 71 and 24% less than

hand pulling, tine cultivator and Nominee respectively, might be due to more weed biomass

resulting in more weed competition. Chauhan and Johnson (2011) also reported that rice yield

was decreased with increase in weed biomass. Paddy yield in our study was 64% more than

no weeding. First reason of increase in yield than no weeding might be low weed dry weight

than no weeding and second reason might be beushaning effect resulting in more tillers and

more yield. Results of Sharma (1997) were similar to our findings.

Paddy yield recorded in no weeding was 221, 203, 141, 105 and 64% less than hand

pulling, hoeing, tine cultivator, Nominee and spike hoe respectively. Low yield in no

weeding might have been due to several reasons. Firstly aerobic soil conditions were

conducive to the germination and growth of weeds, they increased their dry weight and paddy

yield was reduced. Oerke and Dehne, (2004) also found that weeds were major constraint in

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79

reduction of paddy yield. Secondly emerging direct seeded rice seedlings were less

competitive with concurrently emerging weeds resulting in low paddy yield (Kumar et al.,

2008a). Third reason of paddy yield might be competitive advantage of C4 weeds which

increased their efficiency to use crop nutrients more than rice. Findings of Holm et al. (1991)

were in support of this reason. Fourth reason of low yield in no weeding treatment might be

less availability of moisture and nutrients to the crop. Phoung et al. (2005) reported that when

weeds are more as compared to crop then they used more nutrients than rice and reduced the

rice yield. Similar results were also observed by Chauhan and Johnson (2011) who reported

that weed competition throughout the crop growing season reduced crop yield by

approximately 95% as compared to the weed-free conditions. Positive correlation between

yield components and yield and negative correlation between weed dry weight and yield also

strengthens these findings. Similar results are reported by Ekleme et al. (2009), Juraimi et al.

(2009), Hussain et al. (2008), Singh et al. (2008), Mann et al. (2007) and Singh et al. (2007).

Occurrence of sterility, abortiveness and opaqueness varied significantly among

various weed management strategies. Sterility, abortiveness and opaqueness was high in no

weeding and spike hoe reasons; might be due to shorter plants, less availability of nutrients,

low photosynthetic activity and water stress because weed infestation was very high and

weed also competed for water. Xu and Zhou, (2006) reported that rice is more sensitive to

drought stress. Boonrat et al. (2006) found that under mild drought stress during the

flowering stage, 30–40% sterility was increased. Ekanayake et al. (1990) also reported that

water deficit during flowering leaded to spikelet sterility by inhibiting the anther dehiscence

and pollen germination, as well as reduced the pollen viability and pistil water potential and

crop yield was reduced. Sterility, abortiveness and opaqueness percentages were low in hand

pulling, hoeing and tine cultivator might have been due to less number of weeds, taller plants,

more available nutrients and high photosynthetic rate. Results of Akbar et al. (2011) were

also in line with these findings.

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STUDY-II: EVALUATION OF DIFFERENT INTER CULTURAL IMPLEMENTS

FOR WEED MANAGEMENT IN DRILL SEEDED AEROBIC RICE

4.31 Weed biomass of broad leaf weeds (15 DAS)

The fig.4.20 showed that weed control implements and frequency levels significantly

affected weed biomass of broad leaf weeds at 15 DAS during both the years.

Tine cultivator resulted in minimum weed biomass of broad leaf weeds at F1 (0.73 g

m-2) similar to F2 (0.79 g m-2), F3 (0.88 g m-2) and F1 (0.88 g m-2) during the year 2008.

Similar trend was observed during the year 2009. Minimum weed biomass was noted in F1

(0.81 g m-2) similar to F2 (0.87 g m-2), F3 (0.96 g m-2) and F1 (0.96 g m-2).

Spike hoe produced minimum weed biomass of broad leaf weeds when inter

cultivation was carried out at F3 (1.43 g m-2) similar to F4 (1.46 g m-2), F1 (1.48 g m-2) and F2

(1.58 g m-2) during the year 2008. During the year 2009 lowest weed biomass was found in

F3 (1.51 g m-2) similar to F4 (1.54 g m-2), F1 (1.56 g m-2) and F2 (1.66 g m-2).

Plug weeder resulted in minimum weed biomass when operated at F1 (1.55 g m-2)

similar to F2 (1.55 g m-2), F3 (1.62 g m-2) and F4 (1.65 g m-2) during the year 2008. Lowest

weed biomass of broad leaf weeds by plug weeder during the year 2009 was noted at F1 (1.63

g m-2) which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.32 Weed biomass of Sedges (15 DAS)

The fig.4.11 showed that weed control implements and frequency levels significantly

affected weed biomass of sedges at 15 DAS during both the years.

Tine cultivator resulted in minimum weed biomass of sedges at F2 (0.92 g m-2) similar

to F3 (0.96 g m-2), F1 (0.98 g m-2) and F4 (0.98 g m-2) during the year 2008. Similar trend was

observed during the year 2009. Minimum weed biomass was noted in F2 (0.98 g m-2) similar

to F3 (1.02 g m-2), F1 (1.04 g m-2) and F4 (1.04 g m-2).

Spike hoe produced minimum weed biomass of when inter row cultivation was done

at F2 (1.25 g m-2) similar to F1 (1.31 g m-2), F4 (1.32 g m-2) and F3 (1.38 g m-2) during the year

2008. During the year 2009 lowest weed biomass was found in F2 (1.31 g m-2) similar to F1

(1.37 g m-2), F4 (1.38 g m-2) and F3 (1.44 g m-2).

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Fig. 4.20 Effect of different weed control implements on weed biomass of broad leaf weeds (15 DAS) (F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0.0

0.5

1.0

1.5

2.0

2.5

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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Fig. 4.21 Effect of different weed control implements on weed biomass of sedges (15 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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Plug weeder resulted in minimum weed biomass when operated at F2 (1.29 g m-2)

similar to F3 (1.32 g m-2), F4 (1.34 g m-2) and F1 (1.38 g m-2) during the year 2008. Lowest

weed biomass of sedges by plug weeder during the year 2009 was noted at F2 (1.35 g m-2)

which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.33 Weed biomass of broad leaf weeds (30 DAS)

The fig.4.22 showed that weed control implements and frequency levels significantly

affected weed biomass of broad leaf weeds at 30 DAS during both the years.

Tine cultivator resulted in minimum weed biomass of broad leaf weeds at F3 (21.76 g

m-2) similar to F2 (23.65 g m-2) and F4 (24.07 g m-2) followed by F1 (56.63 g m-2) during the

year 2008. Similar trend was observed during the year 2008. During the year minimum weed

biomass was noted in F3 (27.74 g m-2) similar to F2 (29.63 g m-2) and F4 (30.05 g m-2)

followed by F1 (62.65 g m-2).

Spike hoe produced minimum weed biomass of broad leaf weeds when inter

cultivation was carried out at F3 (83.84 g m-2) similar to F4 (88.06 g m-2), F1 (89.01 g m-2) and

F2 (92.12 g m-2) during the year 2008. During the year 2009 lowest weed biomass was found

in F3 (89.82 g m-2) similar to F4 (94.08 g m-2), F1 (95.05 g m-2) and F2 (98415 g m-2).

Plug weeder resulted in minimum weed biomass when operated at F1 (84.65 g m-2)

similar to F2 (88.68 g m-2), F3 (90.36 g m-2) and F4 (87.68 g m-2) during the year 2008.

Lowest weed biomass of broad leaf weeds by plug weeder during the year 2009 was noted at

F1 (90.68 g m-2) which was statistically similar to all other inter cultivation frequencies by

plug weeder.

4.34 Weed biomass of Sedges (30 DAS)

The fig.4.23 showed that weed control implements and frequency levels significantly

affected weed biomass of sedges at 30 DAS during both the years.

Tine cultivator resulted in minimum weed biomass at F3 (17.75 g m-2) similar to F2

(18.32 g m-2) and F4 (19.43 g m-2) followed by F1 (42.76 g m-2) during the year 2008. During

the year 2009 minimum weed biomass was noted in F3 (21.62 g m-2) similar to F2 (22.19 g m-

2) and F4 (23.30 g m-2).

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Fig. 4.22 Effect of different weed control implements on weed biomass of broad leaf weeds (30 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

20

40

60

80

100

120

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

20

40

60

80

100

120

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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85

Fig. 4.23 Effect of different weed control implements on weed biomass of sedges (30 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

10

20

30

40

50

60

70

80

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

10

20

30

40

50

60

70

80

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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Spike hoe produced minimum weed biomass of sedges when inter cultivation was

carried out at F1 (54.25 g m-2) similar to F3 (54.26 g m-2) and F4 (54.77 g m-2) followed by F2

(63.39 g m-2) during the year 2008. During the year 2009 lowest weed biomass was found in

F1 (58.12 g m-2) similar to F3 (58.13 g m-2) and F4 (58.64 g m-2) followed by F2 (67.26 g m-2).

Plug weeder resulted in minimum weed biomass when operated at F4 (60.61 g m-2)

similar to F2 (60.82 g m-2), F1 (61.03 g m-2) and F3 (61.39 g m-2) during the year 2008.

Lowest weed biomass of sedges by plug weeder during the year 2009 was noted at F4 (64.48

g m-2) which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.35 Weed biomass of broad leaf weeds (45 DAS)

The fig.4.24 showed that weed control implements and frequency levels significantly

affected weed biomass of broad leaf weeds at 45 DAS during both the years.

Tine cultivator resulted in minimum weed biomass of broad leaf weeds in F4 (31.22 g

m-2) followed by F3 (41.74 g m-2), F2 (58.04 g m-2) and F1 (121.5 g m-2) during the year 2008.

Similar trend was observed during the year 2008. During the year 2009 minimum weed

biomass was observed in F4 (35.67 g m-2) followed by F3 (46.19 g m-2), F2 (62.49 g m-2) and

F1 (129.60 g m-2).

Spike hoe produced minimum weed biomass of broad leaf weeds when inter

cultivation was carried out at F3 (139.51 g m-2) similar to F4 (139.91 g m-2), F2 (140.77 g m-2)

and F1 (141.79 g m-2) during the year 2008. During the year 2009 lowest weed biomass was

found in F3 (143.96 g m-2) similar to F4 (144.36 g m-2), F2 (145.22 g m-2) and F1 (146.24 g m-

2).

Plug weeder resulted in minimum weed biomass when operated at F3 (134.49 g m-2)

similar to F1 (139.31 g m-2), F2 (141.14 g m-2) and F4 (141.76 g m-2) during the year 2008.

Lowest weed biomass of broad leaf weeds by plug weeder during the year 2009 was noted at

F3 (138.94 g m-2) which was statistically similar to all other inter cultivation frequencies by

plug weeder.

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87

Fig. 4.24 Effect of different weed control implements on weed biomass of broad leaf weeds (45 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

20

40

60

80

100

120

140

160

180

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

20

40

60

80

100

120

140

160

180

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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88

4.36 Weed biomass of Sedges (45 DAS)

The fig.4.25 showed that weed control implements and frequency levels significantly

affected weed biomass of sedges at 45 DAS during both the years.

Tine cultivator resulted in minimum weed biomass of sedges at F4 (56.73 g m-2)

followed by F3 (69.19 g m-2), F2 (111.46 g m-2) and F1 (42.76 g m-2) during the year 2008.

Similar trend was observed during the year 2009. Minimum weed biomass was noted in F4

(60.07 g m-2) followed by F3 (72.53 g m-2), F2 (114.80 g m-2) and F1 (131.26 g m-2).

Spike hoe produced minimum weed biomass of sedges when inter cultivation was

carried out at F4 (144.71 g m-2) similar to F3 (147.76 g m-2) followed by F1 (164.35 g m-2) and

F2 (168.29 g m-2) during the year 2008. During the year 2009 lowest weed biomass was found

in F3 (131.26 g m-2) similar to F4 (132.23 g m-2) followed by F1 (167.54 g m-2) and F2 (171.63

g m-2).

Plug weeder resulted in minimum weed biomass when operated at F2 (162.65 g m-2)

similar to F3 (164.35 g m-2), F1 (165.03 g m-2) and F4 (165.15 g m-2) during the year 2008.

Lowest weed biomass of sedges by plug weeder during the year 2009 was noted at F2 (165.99

g m-2) which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.37 Total weed biomass (15 DAS)

The fig.4.26 showed that weed control implements and frequency levels significantly

affected total weed biomass at 15 DAS during both the years.

Tine cultivator resulted in minimum weed biomass at F2 (1.72 g m-2) similar to F4

(1.72 g m-2), F3 (1.84 g m-2) and F1 (1.87 g m-2) during the year 2008. Similar trend was

observed during the year 2009. Minimum weed biomass was noted in F2 (1.86 g m-2) similar

to F4 (1.87 g m-2), F3 (1.98 g m-2) and F1 (2.01 g m-2).

Spike hoe produced minimum weed biomass when inter cultivation was carried out at

F4 (2.78 g m-2) similar to F1 (2.79 g m-2), F3 (2.82 g m-2) and F2 (2.84 g m-2) during the year

2008. During the year 2009 lowest weed biomass was observed in F4 (2.92 g m-2) similar to

F1 (2.93 g m-2), F3 (2.96 g m-2) and F2 (2.98 g m-2).

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89

Fig. 4.25 Effect of different weed control implements on weed biomass of sedges (45 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

20

40

60

80

100

120

140

160

180

200

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

20

40

60

80

100

120

140

160

180

200

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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90

Fig. 4.26 Effect of different weed control implements on total weed biomass (15 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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91

Plug weeder resulted in minimum weed biomass when operated at F2 (2.85 g m-2)

similar to F1 (2.93 g m-2), F3 (2.94 g m-2) and F4 (3.00 g m-2) during the year 2008. Lowest

weed biomass of broad leaf weeds by plug weeder during the year 2009 was noted at F2 (2.99

g m-2) which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.38 Total weed biomass (30 DAS)

The fig.4.27 showed that weed control implements and frequency levels significantly

affected weed biomass of sedges at 30 DAS during both the years.

Tine cultivator resulted in minimum weed at F3 (39.52 g m-2) followed by F2 (41.98 g

m-2), F4 (43.44.46 g m-2) and F1 (99.40 g m-2) during the year 2008. Similar trend was

observed during the year 2009. Minimum weed biomass was noted in F3 (49.39 g m-2) similar

to F2 (51.85 g m-2) and F4 (114.80 g m-2).

Spike hoe produced minimum weed biomass when inter cultivation was carried out at

F3 (138.10 g m-2) followed by F4 (142.84 g m-2), F1 (143.26 g m-2) and F2 (155.52 g m-2)

during the year 2008. During the year 2009 lowest weed biomass was found in F3 (147.52 g

m-2) followed by F4 (152.71 g m-2), F1 (153.13 g m-2) and F2 (165.39 g m-2).

Plug weeder resulted in minimum weed biomass when operated at F1 (145.75 g m-2)

similar to F4 (148.29 g m-2), F2 (149.50 g m-2) and F3 (151.76 g m-2) during the year 2008.

Lowest weed biomass of sedges by plug weeder during the year 2009 was noted at F1 (155.62

g m-2) which was statistically similar to all other inter cultivation frequencies by plug weeder.

4.39 Total weed biomass (45 DAS)

The data presented in table 4.23 pertaining weed biomass at 45 DAS during the years

2008 and 2009 on three weed control implements and four frequency levels of inter

cultivations revealed that weed control implements and frequency levels significantly

affected weed biomass during both the years. Similarly weed control implements and

frequency levels significantly interacted with each other for weed biomass.

Tine cultivator resulted in minimum weed biomass (87.95 g m-2) when tine cultivator

was used at 15, 25, 35 and 45 DAS followed by inter cultivation at 15, 25 and 35 DAS

(110.93 g m-2) and inter cultivation at 15 and 25 DAS (169.51 g m-2) during the year 2008.

Maximum weed biomass (290.94 g m-2) was found in inter cultivation at 15 DAS during the

year 2008.

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92

Fig. 4.27 Effect of different weed control implements on total weed biomass (30 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter crow cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

20

40

60

80

100

120

140

160

180

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

20

40

60

80

100

120

140

160

180

200

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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93

Fig. 4.28 Effect of different weed control implements on total weed biomass (45 DAS)

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

50

100

150

200

250

300

350

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(a) 2008

0

50

100

150

200

250

300

350

400

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

g m

-2

(b) 2009

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94

pSimilar results were recorded during the year 2009; lowest weed biomass (95.74 g m-2) was

found when tine cultivator was operated at 15, 25, 35 and 45 DAS followed by inter row

cultivation at 15, 25 and 35 DAS (118.72 g m-2) and inter cultivation at 15 and 25 DAS

(177.30 g m-2). Maximum weed biomass (292.04 g m-2) was recorded at 15 DAS.

Spike hoe produced minimum weed biomass (284.62 g m-2) when inter cultivation

was carried out at 15, 25, 35 and 45 DAS similar to weed biomass (287.26 g m-2) found in

inter cultivation at 15, 25 and 35 DAS followed by weed biomass (305.99 g m-2) noted in

inter cultivation at 15 DAS and at 15 and 25 (309.06 g m-2) during the year 2008. During the

year 2009 minimum weed biomass (274.60 g m-2) when inter cultivation was carried out at

15, 25, and 35 DAS similar to weed biomass (276.59 g m-2) found in inter cultivation at 15,

25, 35 and 45 DAS followed by weed biomass (313.78 g m-2) noted in inter cultivation at 15

DAS and at 15, (316.85 g m-2).

Plug weeder resulted in minimum weed biomass (298.83 g m-2) when operated at 15,

25 and 35 DAS similar to weed biomass in inter cultivation at 15 and 25 DAS, inter

cultivation at 15 DAS (304.34) and inter cultivation at 15, 25, 35 and 45 DAS (306.92 g m-2)

during the year 2008. Minimum weed biomass (306.62 g m-2) was observed in inter

cultivation at 15, 25 and 35 DAS followed by weed biomass (311.58 g m-2) noted in inter

cultivation at 15 and 25 DAS and in inter row cultivation at 15 DAS during the year 2009.

The highest weed biomass (314.71) by plug weeder during the year 2009 was observed at 15

and 25 DAS.

4.40 Plant height

The data regarding plant height during the years 2008 and 2009 on three weed control

implements and four frequency levels of inter cultivations are given in table 4.24. Data

represents that weed control implements and inter cultivation frequency levels significantly

affected the plant height during both the years. Interactions found significant. So, only

interactions are discussed.

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95

Table 4.23 Effect of different weed control implements on weed biomass at 45 DAS (g)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

290.94 a

169.51 b

110.93 c

87.95 d

164.83 B

Spike hoe

305.99 a

309.06 a

287.50 b

284.60 b

296.73 A

Plug weeder

304.34 a

303.79 a

298.83 a

306.92 a

303.47 A

Mean

300.42 A

260.78 B

232.34 C

226.50 C

LSD= 8.16 (Frequencies)

LSD= 16.90 (Implements)

LSD= 14.14 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implements

Inter row cultivation frequency (DAS) Mean

15 15 & 25

15, 25 & 35

15, 25, 35 & 45

Tine cultivator

292.06 a

177.30 b

118.99 c

95.74 d

170.96 B

Spike hoe

313.36 a

316.85 a

275.22 b

276.59 b

295.61 A

Plug weeder

312.13 a

311.51a

306.62 a

314.71 a

311.26 A

Mean

305.99 A

268.57 B

233.52 C

229.01 D

LSD= 8.61 (Frequencies)

LSD= 15.98 (Implements)

LSD= 14.91 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

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96

Table 4.24 Effect of different weed control implements on plant height (cm)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

70.33 b

69.00 b

94.67 a

95.66 a 82.41 A

Spike hoe

70.00 b

71.00 b

81.00 a

78.67 a

75.16 B

Plug weeder

72.00 a

72.33 a

72.33 a

72.67a

72.33 C

Mean

70.78 B

70.84 B

82.66 A

82.33 A

LSD= 2.11 (Frequencies)

LSD= 2.31 (Implements)

LSD= 3.92 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

65.66 b

64.46 b

89.93 a

91.26 a

77.83 A

Spike hoe

65.46 b

66.20 b

76.40 a

74.06 a

70.53 B

Plug weeder

67.26 a

68.06 a

67.53 a

67.86 a

67.68 C

Mean

66.13 B

62.24 C

77.95 A

77.73 A

LSD= 2.06 (Frequencies)

LSD= 2.37 (Implements)

LSD= 3.87 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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Tine cultivator at 15, 25, 35 and 45 DAS produced maximum plant height (95.66 cm)

during the year 2008 which was at par with plant height (94.67 cm) recorded for inter

cultivation at 15, 25 and 35 DAS. Minimum plant height (69.00 cm) was recorded with inter

cultivation at 15 and 25 DAS. During the year 2009, maximum plant height (91.26 cm) was

recorded in interaction between tine cultivator and inter cultivation at 15, 25, 35 and 45 DAS

which was statistically similar to plant height (89.93 cm) produced in inter cultivation at 15,

25 and 35 DAS. Minimum plant height (65.46 cm) was produced in inter cultivation at 15

DAS.

Spike hoe produced maximum plant height (81.00 cm) when inter cultivation was

carried out at 15, 25 and 35 DAS during the year 2008 which was at par with plant height

(78.67 cm) produced by inter cultivation at 15, 25, 35 and 45 DAS. Minimum plant height

(70.00 cm) was recorded in inter cultivation at 15 DAS. During the year 2009 interaction

between spike hoe and inter cultivation at 15, 25 and 35 DAS produced maximum plant

height (76.40 cm) and minimum plant height (65.46 cm) was observed in inter cultivation at

15 DAS.

Plug weeder produced maximum plant height (72.67 cm) in inter cultivation at 15, 25,

35 and 45 DAS, which is statistically similar to all other inter cultivation frequencies in 2008.

Similar results were observed during 2009, maximum plant height (68.06 cm) was recorded

in inter cultivation at 15 and 25 DAS, which is statistically similar to all other inter

cultivation frequencies by plug weeder.

4.41 Total number of tillers

Data (Table 4.25) revealed that weed control implements and frequency levels of inter

cultivations significantly affected the total number of tillers m-2 during both the years.

Similarly weed control implements and frequency levels significantly interacted with each

other for total number of tillers.

Tine cultivator resulted in significantly maximum total number of tillers (380.59 m-2)

during the year 2008 in inter cultivation at 15, 25, 35 and 45 DAS. While minimum total

numbers of tillers (246.44 m-2) was produced in inter cultivation at 15 DAS. During the year

2009 significantly maximum total number of tillers (371.95 m-2) with tine cultivator was

recorded in inter cultivation at 15, 25, 35 and 45 DAS. Minimum total number of tillers

(235.73 m-2) was observed in inter cultivation at 15 DAS.

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98

Table 4.25 Effect of different weed control implements on total number of tillers (m-2)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

246.44 c

274.32 b

373.97 a

380.59 a

318.83 A

Spike hoe

229.62 d

240.22 c

264.00 b

276.00 a

252.46 B

Plug weeder

228.11a

233.41 a

227.73 a

234.17 a

230.85 C

Mean

234.72 D

249.32 C

288.56 B

296.92 A

LSD= 6.99 (Frequencies)

LSD= 4.01 (Implements)

LSD= 11.19 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

243.26 c

291.62 b

365.59 a

371.96 a

318.11 A

Spike hoe

235.73 b

239.58 b

259.01 a

261.92 a

249.06 B

PlugWeeder

237.60 a

231.80 a

233.97a

235.12 a

234.62 C

Mean

238.87 C

254.34 B

286.19 A

289.67 A

LSD= 4.14 (Frequencies)

LSD= 6.62 (Implements)

LSD= 8.99 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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99

Total number of tillers (276.00 m-2) with spike hoe in inter cultivation at 15, 25, 35

and 45 DAS recorded was maximum during the year 2008 similar to total number of tillers

(264.00 m-2) in inter cultivation at 15, 25 and 35 DAS. The lowest total number of tillers

(229.62 m-2) was observed in inter cultivation at 15 DAS. During the year 2009 maximum

total number of tillers (262.92 m-2) was found in inter cultivation at 15, 25 and 35 DAS,

statistically at par with total number of tillers (259.01 m-2) in inter cultivation at 15, 25 and 35

DAS. Minimum total number of tillers (229.62 m-2) was recorded in inter cultivation at 15

DAS.

During the year 2008 total number of tillers (234.17 m-2) was observed maximum by

spike hoe in inter cultivation at 15, 25, 35 and 45 DAS which is similar to the rest of

treatments with plug weeder. Plug weeder resulted in the highest number of total tillers

(235.12 m-2) when operated at 15, 25, 35 and 45 DAS and was statistically at par with all

other treatments by plug weeder during the year 2009.

4.42 Number of fertile tillers

The data (Table 4.26) regarding number of fertile tillers during the years 2008 and

2009 on three weed control implements and four frequency levels of inter cultivations

showed that weed control implements and frequency levels significantly affected the number

of fertile tillers m-2 during both the years. Similarly weed control implements and frequency

levels significantly interacted with each other for number of fertile tillers m-2.

Results produced by tine cultivator revealed that significantly maximum number of

fertile tillers (349.26 m-2) during the year 2008 were observed in inter cultivation at 15, 25,

35 and 45 DAS, similar to number of fertile tillers (339.97 m-2) in inter cultivation at 15, 25

and 35 DAS, followed by number of fertile tillers (237.65 m-2) observed in inter cultivation at

15 and 25 DAS. Number of fertile tillers (205.77 m-2) recorded in inter cultivation at 15 DAS

were minimum by tine cultivator. During the year 2009 maximum number of fertile tillers

(337.62 m-2) were observed in inter cultivation at 15, 25, 35 and 45 DAS. Significantly

minimum number of fertile tillers (199.59 m-2) was found in inter cultivation at 15 DAS.

Spike hoe produced maximum number of fertile tillers (237.33) in inter cultivation at

15, 25, 35 and 45 DAS followed by inter cultivation at 15, 25 and 35 DAS (224.33 m-2)

during the year 2008. Significantly minimum number of fertile tillers (180.59 m-2) observed

in inter cultivation at 15 DAS. During 2009 highest total tillers (220.26 m-2) recorded in inter

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100

Table 4.26 Effect of different weed control implements on number of fertile tillers (m-2)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

205.77 c

237.65 b

339.97 a

349.26 a

283.16 A

Spike hoe

185.95 c

194.22 c

224.33 b

237.33 a

210.46 B

Plug weeder

187.11 a

191.08 a

185.73 a

189.50 a

188.35 C

Mean

192.94 D

207.65 C

250.01 B

258.70 A

LSD= 7.62(Frequencies)

LSD= 5.0 (Implements)

LSD= 12.43 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

199.59 d

251.95 c

328.59 b

337.62 a

279.44 A

Spike hoe

189.07 b

190.58 b

216.34 a

220.26 a

204.06 B

Plug weeder

193.60 a

186.46 a

188.97 a

187.45 a

189.25 C

Mean

194.09 C

209.66 B

244.63 A

248.44 A

LSD= 4.19 (Frequencies)

LSD= 6.57 (Implements)

LSD= 9.01 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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101

cultivation at 15, 25, 35 and 45 DAS. Minimum number of fertile tillers (189.07 m-2) was

resulted in inter cultivation at 15 DAS.

Plug weeder produced more number of fertile tillers (191.08 m-2) in inter cultivation

at 15 and 25 DAS, similar to rest of treatments during the year 2008. Similar results were

observed during the year 2009, highest number of fertile tillers (193.60 m-2) were found in

inter cultivation at 15 DAS, statistically at par with all other treatments by plug weeder.

4.43 Number of unfertile tillers

The data regarding number of unfertile tillers during the years 2008 and 2009 on three

weed control implements and four frequency levels of inter cultivations are given in table

4.27. It is clear from the data that weed control implements and frequency levels significantly

affected number of unfertile tillers m-2 during both the years. Similarly weed control

implements and frequency levels significantly interacted with each other for number of

unfertile tillers m-2.

Tine cultivator during the year 2008 produced significantly minimum number of

unfertile tillers (31.33 m-2) in inter cultivation at 15, 25, 35 and 45 DAS, similar to number of

unfertile tillers (34.00 m-2) in inter cultivation at 15, 25 and 35 DAS. Significantly maximum

number of unfertile tillers (40.66 m-2) were recorded in inter cultivation at 15 DAS. During

the year 2009 lowest number of unfertile tillers (34.33 m-2) was observed in inter cultivation

at 15, 25, 35 and 45 DAS. Highest number of unfertile tillers (43.66 m-2) recorded in inter

cultivation at 15 DAS.

Spike hoe produced minimum number of unfertile tillers (38.67 m-2) when inter

cultivation was carried out at 15, 25, 35 and 45 DAS during the year 2008. Highest number of

unfertile tillers (46.00 m-2) recoded in inter cultivation at 15 and 25 DAS. During the year

2009 lowest number of unfertile tillers (41.66 m-2) was observed where spike hoe was used at

15, 25, 35 and 45 DAS. Highest number of unfertile tillers (49.00 m-2) recoded in inter

cultivation at 15 and 25 DAS.

Plug weeder resulted in lowest number of unfertile tillers (41.00 m-2) recoded in inter

cultivation at 15 DAS during the year 2008, similar to remaining treatments. Lowest number

of unfertile tillers (44.00 m-2) during the year 2009 was observed at 15 DAS which is

statistically similar to all other inter cultivations by plug weeder.

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102

Table 4.27 Effect of different weed control implements on number of unfertile tillers (m-2)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

40.66 a

36.66 b

34.0 b

31.33 b

35.66 B

Spike hoe

43.66 a

46.00 a

39.66 b

38.66 c

42.0 A

Plug weeder

41.00 a

42.33 ab

42.00 ab

44.66 b

42.50 A

Mean

41.78 A

41.66 A

38.55 bB

38.22 B

LSD= 1.72 (Frequencies)

LSD= 2.21 (Implements)

LSD= 3.37 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

43.66 a

39.66 b

37.00 bc

34.33 c

38.66 B

Spike hoe

46.66 a

49.00 a

42.66 bc

41.66 c

45.00 A

Plug weeder

44.00 b

45.33 a

45.00 a

47.66 a

45.50 A

Mean

44.77 A

44.66 A

41.55 B

41.22 B

LSD= 1.72 (Frequencies)

LSD= 2.21 (Implements)

LSD= 3.37 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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4.44 Panicle length

The data regarding panicle length during the years 2008 and 2009 are given in table

4.28. Data represents that weed control implements and inter cultivation frequency levels

significantly affected the panicle length during both the years. Interactions found significant.

So, only interactions are discussed.

Tine cultivator at 15, 25, 35 and 45 DAS produced maximum panicle length (23.89

cm) during the year 2008 which was at par with panicle length (23.01 cm) produced in inter

cultivation at 15, 25 and 35 DAS. Minimum panicle length (17.63 cm) was found in inter

cultivation at 15 DAS. During the year 2009, maximum panicle length (22.91 cm) was

recorded in interaction between tine cultivator and inter cultivation at 15, 25, 35 and 45 DAS

which was statistically similar to panicle length (22.03 cm) produced in inter cultivation at

15, 25 and 35 DAS. Minimum panicle length (16.65 cm) was produced in inter cultivation at

15 DAS.

Spike hoe produced maximum panicle length (19.97 cm) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS during the year 2008 which is at par with panicle length

(19.21 cm) produced in inter cultivation at 15, 25 and 35 DAS. Minimum panicle length

(16.92 cm) was recorded in inter cultivation at 15 and 25 DAS. During the year 2009

interaction between spike hoe and inter cultivation at 15, 25, 35 and 45 DAS produced

maximum panicle length (18.99 cm) and minimum panicle length (15.94 cm) was observed

in inter cultivation at 15 and 25 DAS.

Plug weeder produced maximum panicle length (18.01 cm) in inter cultivation at 15

DAS, which is statistically similar to all other inter cultivation frequencies during the year

2008. Similar results were observed during the year 2009, maximum panicle length (17.03

cm) was recorded in inter cultivation at 15 DAS, which was statistically similar to all other

inter cultivation frequencies by plug weeder.

4.45 Kernels per panicle

The data (Table 4.29) regarding kernels per panicle during the year 2008 and 2009

showed that weed control implements and frequency levels significantly affected kernels per

panicle during both the years. Similarly weed control implements and frequency levels

significantly interacted with each other for kernels per panicle.

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Table 4.28 Effect of different weed control implements on panicle length (cm)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator 17.63 c

19.08 b

23.01 a

23.89 a

20.90 A

Spike hoe

17.01 b

16.92 b

19.21 a

19.97 a

18.28 B

Plug weeder

18.01 a

17.27 a

17.26 a

17.00 a

17.38 B

Mean

17.52 B

17.76 B

19.83 A

20.29 A

LSD= 0.60 (Frequencies)

LSD= 1.16 (Implements)

LSD= 1.45 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

16.65 c

18.10 b

22.03 a

22.91 a

19.92 A

Spike hoe

16.03 c

15.94 b

18.23 a

18.99 a

17.30 B

Plug weeder

17.03 a

16.29 a

16.28 a

16.02 a

16.40 B

Mean

16.57 B

16.78 B

18.84 A

19.30 A

LSD= 0.60 (Frequencies)

LSD= 1.16 (Implements)

LSD= 1.46 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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Table 4.29 Effect of different weed control implements on kernels per panicle

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

62.40 b

65.14 b

74.46 a

76.33 a

69.58 A

Spike hoe

63.92 a

63.79 a

62.37 a

65.55 a

63.91 B

Plug weeder

65.99 a

62.33 a

63.67 a

62.67 a

63.67 B

Mean

64.10 B

63.75 B

66.83 A

68.18 A

LSD= 2.66 (Frequencies)

LSD= 3.55 (Implements)

LSD= 5.30 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

61.62 b

63.88 b

70.12 b

73.12 a

67.18 A

Spike hoe

61.01 ab

60.23 b

63.19 a

61.90 ab

61.58 B

Plug weeder

60.93 a

61.47 a

60.90 a

60.82 a

61.03B

Mean

61.18 B

61.86 B

64.74 A

65.28 A

LSD= 1.39 (Frequencies)

LSD= 1.59 (Implements)

LSD= 2.60 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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Results produced by tine cultivator revealed that significantly highest kernels per

panicle (76.33) during the year 2008 were recorded in inter cultivation at 15, 25, 35 and 45

DAS, similar to kernel per panicle (74.46) in inter cultivation at 15, 25 and 35 DAS. Kernels

per panicle (62.39) recorded in inter cultivation at 15 DAS were minimum by tine cultivator.

During the year 2009 maximum kernels per panicle (73.12) were observed in inter cultivation

at 15, 25, 35 and 45 DAS. Significantly minimum kernels per panicle (61.62) were found in

inter cultivation at 15 DAS.

Spike hoe produced maximum kernels per panicle (65.55) in inter cultivation at 15,

25, 35 and 45 DAS similar to all other frequencies during the year 2008. During the year

2009 highest kernels per panicle (63.19) recorded in inter cultivation at 15, 25 and 35 DAS.

Minimum kernels per panicle (60.23) were resulted in inter cultivation at 15 and 25 DAS.

Plug weeder produced more kernels per panicle (65.99) in inter cultivation at 15 DAS,

similar to rest of treatments during the year 2008. Similar results were observed during 2009,

highest kernels per panicle (61.47) were found in inter cultivation at 15 and 45 DAS,

statistically at par with all other treatments by plug weeder.

4.46 1000 kernel weight

Data (Table 4.30) revealed that weed control implements and frequency levels of inter

cultivations significantly affected 1000 kernel weight during both the years. Similarly weed

control implements and frequency levels significantly interacted with each other for 1000

kernel weight.

Tine cultivator resulted in significantly maximum 1000 kernel weight (19.56 g)

during the year 2008 in inter cultivation at 15, 25, 35 and 45 DAS similar to 1000 kernel

weight (18.67 g) in inter cultivation at 15, 25 and 35 DAS . While minimum 1000 kernel

weight (15.68 g) was recorded in inter cultivation at 15 DAS. During the year 2009

significantly maximum 1000 kernel weight (19.69 g) by tine cultivator was recorded in inter

cultivation at 15, 25, 35 and 45 DAS. Minimum 1000 kernel weight (15.49 g) was observed

in inter cultivation at 15 DAS.

1000 kernel weight (17.71 g) by spike hoe in inter cultivation at 15, 25, 35 and 45

DAS recorded was maximum during the year 2008. Lowest 1000 kernel weight (15.69 g) was

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107

Table 4.30 Effect of different weed control implements on 1000 kernel weight (g)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

15.68 b

16.66 b

18.67 a

19.56 a

17.65 A

Spike hoe

15.69 b

15.82 ab

17.10 ab

17.71 a

16.58 B

Plug weeder

15.75 a

16.08 a

16.49 a

16.73 a

16.26 B

Mean

15.70 C

16.20 BC

17.42 AB

18.0 A

LSD= 1.26 (Frequencies)

LSD= 0.66 (Implements)

LSD= 1.99 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

15.49 b

16.32 b

18.72 a

19.69 a

17.56 A

Spike hoe

15.13 b

15.58 ab

16.09 ab

16.54 a

15.84 B

Plug weeder

15.44 a

15.58 a

15.78 a

15.47 a

15.56 B

Mean

15.35 B

15.83 B

16.86 A

17.23 A

LSD= 0.52 (Frequencies)

LSD= 0.85 (Implements)

LSD= 1.14 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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108

observed in inter cultivation at 15 DAS. During the year 2009 maximum 1000 kernel weight

(16.54 g) was found in inter cultivation at 15, 25, 35 and 45 DAS. Minimum 1000 kernel

weight (15.13 g) was recorded in inter cultivation at 15 DAS.

During the year 2008 1000 kernel weight (16.72 g) was observed maximum by spike

hoe in inter cultivation at 15, 25, 35 and 45 DAS which is similar to the rest of treatments.

Plug weeder resulted in highest 1000 kernel weight (15.78 g) when operated at 15, 25 and 35

DAS, statistically at par with all other treatments by plug weeder during the year 2009.

4.47 Biological yield

The data regarding biological yield during the years 2008 and 2009 are given in table

4.31. Data represents that weed control implements and inter cultivation frequency levels

significantly affected the biological yield during both the years. Interactions found

significant. So, only interactions are discussed.

Tine cultivator at 15, 25, 35 and 45 DAS produced maximum biological yield (12.46 t

ha-1) during the year 2008 which was at par with biological yield (11.75 t ha-1) produced in

inter cultivation at 15, 25 and 35 DAS. Minimum biological yield (7.22 t ha-1) was found in

inter cultivation at 15 DAS. During the year 2009 maximum biological yield (11.34 t h-1) was

recorded in inter cultivation at 15, 25, 35 and 45 DAS which was statistically similar to

biological yield (10.61 t ha-1) produced in inter cultivation at 15, 25 and 35 DAS. Minimum

biological yield (6.19 t ha-1) was produced in inter cultivation at 15 DAS.

Spike hoe produced maximum biological yield (9.31 t ha-1) when inter cultivation was

carried out at 15, 25 and 35 DAS during the year 2008. Minimum biological yield (7.06 t ha-

1) was recorded in inter cultivation at 15 DAS. During the year 2009 interaction between

spike hoe and inter cultivation at 15, 25 and 35 DAS produced maximum biological yield

(11.34 t ha-1) and minimum biological yield (6.05 t ha-1) was observed in inter cultivation at

15 DAS.

Plug weeder produced maximum biological yield (7.49 t ha-1) in inter cultivation at

15, 25, 35 and 45 DAS, which is statistically similar to all other inter cultivation frequencies

during the year 2008. Similar results were observed during the year 2009 maximum

biological yield (6.28 t ha-1) was recorded in inter cultivation at 15, 25, 35 and 45 DAS,

which is statistically similar to all other inter cultivation frequencies by plug weeder.

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109

Table 4.31 Effect of different weed control implements on biological yield (t ha-1)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

7.22 b

8.13 b

11.75 a

12.46 a

9.89 A

Spike hoe

7.04 b

7.19 b

8.43 a

9.31 a

7.99 B

Plug weeder

7.17 a

6.76 a

6.87 a

7.49 a

7.07 C

Mean

7.15 C

7.36 C

9.02 B

9.75 A

LSD= 0.51 (Frequencies)

LSD= 0.87 (Implements)

LSD= 1.15 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

6.19 c

7.30 b

10.61 a

11.34 a

8.86 A

Spike hoe

6.05 b

6.29 b

7.23a

7.91 a

6.87 B

Plug weeder

6.10 a

5.78 a

5.77 a

6.28 a

5.98 C

Mean

6.11 C

6.46 C

7.87 B

8.51 A

LSD= 0.45 (Frequencies)

LSD= 0.76 (Implements)

LSD= 1.01 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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110

4.48 Paddy yield

Data (Table 4.32) pertaining paddy yield during the years 2008 and 2009 on three

weed control implements and four frequency levels of inter cultivations indicated that weed

control implements and inter cultivation frequency levels significantly affected the paddy

yield during both the years. Interactions found significant. So, only interactions are discussed.

Tine cultivator at 15, 25, 35 and 45 DAS produced maximum paddy yield (3.93 t ha-1)

during the year 2008 which was at par with paddy yield (3.71 t ha-1) produced by inter

cultivation at 15, 25 and 35 DAS. Minimum paddy yield (1.52 t ha-1) was recorded in inter

cultivation at 15 DAS. During the year 2009, maximum paddy yield (3.79 t ha-1) was

observed in interaction between tine cultivator and inter cultivation at 15, 25, 35 and 45 DAS

which was statistically similar to paddy yield (3.55 t ha-1) produced by inter cultivation at 15,

25 and 35 DAS. Minimum paddy yield (1.47 t ha-1) was found in inter cultivation at 15 DAS.

Spike hoe produced maximum paddy yield (2.25 t ha-1) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS during the year 2008 which was at par with paddy yield

(1.96 t ha-1) produced by inter cultivation at 15, 25 and 35 DAS. Minimum paddy yield (1.47

t ha-1) was recorded in inter cultivation at 15 DAS. During the year 2009 interaction between

spike hoe and inter cultivation at 15, 25, 35 and 45 DAS observed maximum paddy yield

(1.84 t ha-1) and minimum paddy yield (1.46 t ha-1) was produced by inter cultivation at 15

DAS.

Plug weeder produced maximum paddy yield (1.57 t ha-1) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS during the year 2008 which is statistically similar to all

other interactions between spike hoe and inter cultivation frequencies. During the year 2009

maximum paddy yield (1.51 t ha-1) was recorded in inter cultivation at 15 and 25 DAS, which

is statistically similar to all other inter cultivation frequencies by plug weeder.

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111

Table 4.32 Effect of different weed control implements on paddy yield (t ha-1)

(a) 2008

Implement

Inter Cultivation Frequencies Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

1.52 c

2.22 b

3.71 a

3.93 a

2.84 A

Spike hoe

1.47 b

1.48 b

1.96 a

2.26 a

1.79 B

Plug weeder

1.53 a

1.51 a

1.54 a

1.57 a

1.54 C

Mean

1.51 D

1.74 C

2.40 B

2.58 A

LSD= 0.15 (Frequencies)

LSD= 0.22 (Implements)

LSD= 0.32 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

1.47 c

2.36 b

3.55 a

3.79 a

2.79 A

Spike hoe

1.46 b

1.57 b

1.74 ab

1.84 a

1.65 B

Plug weeder

1.44 a

1.51 a

1.41 a

1.34 a

1.42 C

Mean

1.46 C

1.81 B

2.23 A

2.32 A

LSD= 0.16(Frequencies)

LSD= 0.12 (Implements)

LSD= 0.27 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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112

4.49 Straw yield

Data (Table 4.33) revealed that weed control implements and frequency levels of inter

cultivations significantly affected straw yield during both the years. Similarly weed control

implements and frequency levels significantly interacted with each other for straw yield.

Tine cultivator resulted in significantly maximum straw yield (8.53 t ha-1) during

2008 in inter cultivation at 15, 25, 35 and 45 DAS similar to straw yield (8.07 t ha-1) in inter

cultivation at 15, 25 and 35 DAS . While minimum straw yield (5.70 t ha-1) was recorded in

inter cultivation at 15 DAS. During 2009 significantly highest straw yield (7.55 t ha-1) by tine

cultivator was recorded in inter cultivation at 15, 25, 35 and 45 DAS. Minimum straw yield

(4.72 t ha-1) was observed in inter cultivation at 15 DAS.

Straw yield (7.05 t ha-1) by spike hoe in inter cultivation at 15, 25, 35 and 45 DAS

recorded was maximum during 2008 similar to straw yield (6.47 t ha-1) in inter cultivation at

15, 25 and 35 DAS. Lowest straw yield (5.57 t ha-1) was observed in inter cultivation at 15

DAS. During 2009 maximum straw yield (6.07 t ha-1) was found in inter cultivation at 15, 25,

35 and 45 DAS, statistically at par with straw yield (5.49 t ha-1) in inter cultivation at 15, 25

and 35 DAS. Minimum straw yield (4.59 t ha-1) was recorded in inter cultivation at 15 DAS.

During 2008 straw yield (5.92 t ha-1) was observed maximum by spike hoe in inter

cultivation at 15, 25, 35 and 45 DAS which is similar to the rest of treatments. Plug weeder

resulted in highest straw yield (4.94 t ha-1) when operated at 15, 25, 35 and DAS, statistically

at par with all other treatments by plug weeder during 2009.

4.50 Harvest index

Data (Table 4.34) pertaining harvest index during 2008 and 2009 on three weed

control implements and four frequency levels of inter cultivations indicated that weed control

implements and inter cultivation frequency levels significantly affected the harvest index

during both the years. Interactions found significant. So, only interactions are discussed.

Tine cultivator at 15, 25 and 35 DAS produced maximum harvest index (31.66) during 2008

which was at par with harvest index (31.54) produced by inter cultivation at 15, 25, 35 and 45

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113

Table 4.33 Effect of different weed control implements on straw yield (t ha-1)

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

5.70 b

5.91 b

8.03 a

8.53 a

7.04 A

Spike hoe

5.57 b

5.71 b

6.47 ab

7.05 a

6.20 B

Plug weeder

5.63 a

5.25 a

5.33 a

5.92 a

5.53 B

Mean

5.63 C

5.62 C

6.61 B

7.16 A

LSD= 0.49 (Frequencies)

LSD= 0.66 (Implements)

LSD=0.98 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

4.72 b

4.93 b

7.05 a

7.55 a

6.06 A

Spike hoe

4.59 b

4.72 b

5.49 ab

6.07 a

5.22 B

Plug weeder

4.65 a

4.27 a

4.35 a

4.94 a

4.55 B

Mean

4.65 C

4.64 C

5.63 B

6.18 A

LSD= 0.49 (Frequencies)

LSD= 0.66 (Implements)

LSD=0.99 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

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114

Table 4.34 Effect of different weed control implements on harvest index

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

20.88 c

27.2 b

31.66 a

31.54 a

27.84 A

Spike hoe

21.09 ab

20.72 b

23.32 ab

24.20 a

22.33 B

Plug weeder

21.53 a

22.43 a

22.41 a

21.02 a

21.14 B

Mean

21.14 C

23.47 B

25.61 AB

25.80 A

LSD= 2.20 (Frequencies)

LSD= 1.18 (Implements)

LSD= 3.50 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

24.12 b

32.38 a

33.55 a

33.45 a

30.87 A

Spike hoe

24.27 a

25.13 a

24.24 a

23.30 a

24.24 B

Plug weeder

23.78

26.21

24.56

21.37

23.98 B

Mean

24.06 B

26.04 AB

27.45 A

27.91 A

LSD= 3.19 (Frequencies)

LSD= 1.66 (Implements)

LSD= 5.05 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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115

DAS. Minimum harvest index (20.88) was recorded in inter cultivation at 15 DAS. During

2009, maximum harvest index (33.55) was observed in interaction between tine cultivator

and inter cultivation at 15, 25 and 35 DAS which was statistically similar to (33.45) observed

in inter cultivation at 15, 25, 35 and 45 DAS. Minimum harvest index (24.12) was produced

by inter cultivation at 15 DAS.

Spike hoe resulted in maximum harvest index (24.20) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS during 2008 which was at par with harvest index

(23.32) produced by inter cultivation at 15, 25 and 35 DAS. Minimum harvest index (20.72)

was recorded in inter cultivation at 15 and 25 DAS. In 2009 interaction between spike hoe

and inter cultivation at 15, 25, 35 and 45 DAS produced maximum harvest index (25.13),

similar to rest of inter cultivations.

Plug weeder produced maximum harvest index (22.43) by inter cultivation at 15 and

25 DAS, which is statistically similar to all other inter cultivation frequencies in 2008. During

2009 maximum harvest index (25.13) was observed in inter cultivation at 15 and 25 DAS,

which is statistically similar to rest of inter cultivation frequencies by plug weeder.

4.51 Opaque kernels

The data regarding opaque kernels % during 2008 and 2009 on three weed control

implements and four frequency levels of inter cultivations are given in table 4.35. It is clear

from the data that weed control implements and frequency levels significantly affected during

both the years. Similarly weed control implements and frequency levels significantly

interacted with each other for opaque kernels %.

Tine cultivator during 2008 produced significantly minimum opaque kernels (7.79 %)

in inter cultivation at 15, 25, 35 and 45 DAS, similar to opaque kernels (7.89 %) in inter

cultivation at 15, 25 and 35 DAS. Significantly maximum opaque kernels (8.42 %) were

recorded in inter cultivation at 15 DAS. During 2009 minimum opaque kernels (7.66 %) were

observed in inter cultivation at 15, 25, 35 and 45 DAS. Highest opaque kernels (8.43 %) were

recorded in inter cultivation at 15 DAS.

Spike hoe produced minimum opaque kernels (8.35 %) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS in 2008. Highest opaque kernels (8.82 %) were recorded

in inter cultivation at 15 and 25 DAS. During 2009 least opaque kernels (8.51 %) were found

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116

Table 4.35 Effect of different weed control implements opaque kernels

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

8.42 a

8.07 b

7.81 c

7.79 c

8.02 C

Spike hoe

8.82 a

8.78 a

8.43 b

8.35 b

8.60 B

Plug weeder

8.83 a

8.76 a

8.79 a

8.68 a

8.76 A

Mean

8.69 A

8.54 B

8.34 C

8.27 C

LSD= 0.12 (Frequencies)

LSD= 0.08 (Implements)

LSD= 0.18 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

8.43 a

8.03 bc

7.82 c

7.66 c

7.98 B

Spike hoe

8.83 a

8.84 a

8.53 b

8.51 b

8.68 A

Plug weeder

8.86 a

8.87 a

8.83 a

8.48 b

8.76 A

Mean

8.70 A

8.58 A

8.39 B

8.22 C

LSD= 0.15 (Frequencies)

LSD= 0.08 (Implements)

LSD= 0.25 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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117

where spike hoe was used at 15, 25, 35 and 45 DAS. Highest opaque kernels (8.81 %)

recoded in inter cultivation at 15 and 25 DAS.

Plug weeder resulted in lowest opaque kernels (8.68 %) in inter cultivation at 15, 25,

35 and 45 DAS during 2008, similar to remaining treatments by this implement. Lowest

opaque kernels (8.48% ) in 2009 were observed in inter cultivation at 15, 25, 35 and 45 DAS

and maximum opaque kernels (8.87 %) in inter cultivation at 15 and 25 DAS.

4.52 Abortive kernels

Data (Table 4.36) revealed that weed control implements and frequency levels significantly

affected abortive kernels % during 2008 and 2009. Similarly weed control implements and

frequency levels significantly interacted with each other for abortive kernels %.

Tine cultivator during 2008 produced significantly minimum abortive kernels (3.50

%) in inter cultivation at 15, 25, 35 and 45 DAS, followed by abortive kernels (3.59 %) in

inter cultivation at 15, 25 and 35 DAS. Significantly maximum abortive kernels (3.4 %) were

recorded in inter cultivation at 15 DAS. During 2009 lowest abortive kernels (3.52 %) were

observed in inter cultivation at 15, 25, 35 and 45 DAS. Highest abortive kernels (3.77

abortive kernels %) were recorded in inter cultivation at 15 DAS.

Spike hoe produced minimum abortive kernels (3.72 %) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS in 2008. Highest abortive kernels (3.86 %) recoded in

inter cultivation at 15 and 25 DAS. During 2009 lowest abortive kernels (3.68 %) were

observed where spike hoe was used at 15, 25, 35 and 45 DAS. Highest abortive kernels (3.87

%) recoded in inter cultivation at 15 and 25 DAS.

Plug weeder resulted in lowest abortive kernels (3.77 %) in inter cultivation at 15, 25,

35 and 45 DAS during 2008, maximum abortive kernels (3.88 %) were observed in inter

cultivation at 15, 25 and 35 DAS. Lowest abortive kernels (3.78 %) in 2009 were observed at

15, 25, 35 and 45 DAS. Maximum abortive kernels (3.87 %) were observed in inter

cultivation at 15 and 25 DAS.

4.53 Normal kernels

The data (Table 4.37) regarding normal kernels % during 2008 and 2009 on three weed

control implements and four frequency levels of inter cultivations revealed that weed control

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118

Table 4.36 Effect of different weed control implements abortive kernels

(a) 2008

Implement

Inter row cultivation frequency (DAS) Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

3.74 a

3.69 a

3.59 b

3.50 c

3.63 B

Spike hoe

3.86 a

3.86 a

3.77 b

3.72 b

3.80 A

Plug weeder

3.83 a

3.87 a

3.88 a

3.77 b

3.83 A

Mean

3.81 A

3.80 A

3.74 B

3.66 C

LSD= 0.07 (Frequencies)

LSD= 0.03 (Implements)

LSD= 0.09 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter Cultivation Intensities DAS Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

3.77 a

3.67 b

3.56 c

3.52 c

3.63 B

Spike hoe

3.86 a

3.87 a

3.72 b

3.68 c

3.78 A

Plug weeder

3.86 a

3.87 a

3.84 b

3.78 c

3.84 A

Mean

3.83 A

3.80 A

3.70 B

3.66 B

LSD= 0.05 (Intensities)

LSD=0.07 (Implements)

LSD= 0.10 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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119

Table 4.37 Effect of different weed control implements normal kernels

(a) 2008

Implement

Inter Cultivation Intensities DAS Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

54.05 c

55.70 b

59.97 a

60.03 a

57.44 A

Spike hoe

53.60 b

53.68 b

55.62 a

55.87 a

54.69 B

Plug weeder

54.07 a

53.43 a

54.12 a

53.98 a

53.90 C

Mean

53.90 B

54.27 B

56.57 A

56.62 A

LSD= 0.48(Intensities)

LSD= 0.34 (Implements)

LSD= 0.73 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter Cultivation Intensities DAS Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

54.03 c

57.15 b

60.10 b

61.14 a

58.10 A

Spike hoe

53.72 b

54.07 b

57.63 a

57.95 a

55.84 B

Plug weeder

54.05 a

53.89 a

54.20 a

54.17 a

54.08 C

Mean

53.93 D

55.04 C

57.31 B

57.75 A

LSD= 0.32 (Intensities)

LSD= 0.26 (Implements)

LSD= 0.54 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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120

implements and inter cultivation frequency levels significantly affected the normal kernels %

during both the years. Interactions found significant. So, only interactions are discussed.

Tine cultivator at 15, 25, 35 and 45 DAS resulted in maximum normal kernels (60.03

%) during 2008 which was at par with normal kernels (59.97 %) observed in inter cultivation

at 15, 25 and 35 DAS. Minimum normal kernels (54.05 %) were found in inter cultivation at

15 DAS. During 2009, maximum normal kernels (61.14 %) were recorded in interaction

between tine cultivator and inter cultivation at 15, 25, 35 and 45 DAS which was statistically

similar to normal kernels (60.10 %) produced in inter cultivation at 15, 25 and 35 DAS.

Minimum normal kernels (54.03 %) were recorded in inter cultivation at 15 DAS.

Spike hoe produced maximum normal kernels (55.87 %) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS during 2008 which was at par with normal kernels

(55.62 %) produced by inter cultivation at 15, 25, 35 DAS. Minimum normal kernels (53.60

%) was recorded in inter cultivation at 15 DAS. In 2009 interaction between spike hoe and

inter cultivation at 15, 25, 35 and 45 DAS resulted in maximum normal kernels (57.95 v) and

minimum normal kernels (53.72 %) were observed in inter cultivation at 15 DAS.

Plug weeder produced maximum normal kernels (54.12 %) in inter cultivation at 15,

25 and 35 DAS, which is statistically similar to all other inter cultivation frequencies in 2008.

Similar results were observed during 2009, maximum normal kernels (54.20 %) were

recorded in inter cultivation at 15, 25 and 35 DAS, which is statistically similar to all other

inter cultivation frequencies by plug weeder

4.54 Sterile spikelets

Data (Table 4.38) revealed that weed control implements and frequency levels

significantly affected sterile spikelets % during 2008 and 2009. Similarly weed control

implements and frequency levels significantly interacted with each other for sterile spikelets

%.

Tine cultivator during 2008 produced significantly minimum sterile spikelets (8.95 %)

in inter cultivation at 15, 25, 35 and 45 DAS, similar to sterile spikelets (8.97 %) in inter

cultivation at 15, 25 and 35 45 DAS. Significantly maximum sterile spikelets (11.37 %) were

recorded in inter cultivation at 15 DAS. During 2009 lowest sterile spikelets (9.38 %) found

in inter cultivation at 15, 25, 35 and 45 DAS. Highest sterile spikelets (12.00 %) recorded in

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121

Table 4.38 Effect of different weed control implements on sterile spikelets

(a) 2008

Implement

Inter Cultivation Intensities DAS Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

11.37 a

10.03 b

8.97 c

8.95 c

9.83 C

Spike hoe

11.52 a

11.45 a

10.26 b

10.19 b

10.85 B

Plug weeder

11.70 a

11.59 a

11.85 a

11.81 a

11.74 A

Mean

11.53 A

11.02 B

10.36 C

10.31 C

LSD= 0.31 (Intensities)

LSD= 0.28 (Implements)

LSD= 0.54 (Interactions) Any two means not sharing a common letter with in rows differ significantly (p ≤ 0.05)

(b) 2009

Implement

Inter Cultivation Intensities DAS Mean

15

15 & 25

15, 25 & 35

15, 25, 35 & 45 Tine

cultivator

12.00 a

11.58 a

9.44 b

9.38 b

10.64 C

Spike hoe

12.41 a

12.46 a

10.36 b

10.20 b

11.36 B

Plug weeder

12.46

12.40

12.34

12.27

12.37 A

Mean

12.29 A

12.15 A

10.71 B

10.62 B

LSD= 0.30 (Intensities)

LSD= 0.47 (Implements)

LSD= 0.64 (Interactions) Any two means not sharing a letter in similar with in rows differ significantly (p ≤ 0.05)

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122

inter cultivation at 15 DAS.

Spike hoe produced minimum sterile spikelets (10.19 %) when inter cultivation was

carried out at 15, 25, 35 and 45 DAS in 2008. Highest sterile spikelets (11.52 %) recoded in

inter cultivation at 15 DAS. During 2009 lowest sterile spikelets (10.20 %) were observed

where spike hoe was used at 15, 25, 35 and 45 DAS. Highest sterile spikelets (12.46 %)

recoded in inter cultivation at 15 and 25 DAS.

Plug weeder resulted in lowest sterile spikelets (11.59 %) in inter cultivation at 15 and

25 DAS during 2008, similar to remaining treatments by this implement. Lowest sterile

spikelets (12.27 %) in 2009 were observed at 15, 25, 35 and 45 DAS which is statistically

similar to all other inter cultivations by plug weeder.

4.55 Leaf area index

The fig.4.29 showed that weed control implements and frequency levels affected the

leaf area index (LAI) during the years 2008 and 2009.

Tine cultivator attained maximum LAI in F4 (3.86) at 90 DAS followed by F3 (3.81),

F2 (3.67) and F1 (3.31) during the year 2008. Similar trend was observed during the year

2009, maximum LAI was attained in F4 (3.80) at 90 DAS followed by F3 (3.75), F2 (3.61) and

F1 (3.25).

Spike hoe attained maximum LAI in F3 (3.42) at 90 DAS followed by F4 (3.41), F2

(3.33) and F1 (3.27) during the year 2008. Similar trend was observed during the year 2009,

maximum LAI was attained in F3 (3.36) at 90 DAS followed by F4 (3.35), F2 (3.27) and F1

(3.21).

Plug weeder attained maximum LAI in F4 (3.28) at 90 DAS followed by F1 (3.28), F2

(3.27) and F3 (3.26) during the year 2008. Similar trend was observed during the year 2009,

maximum LAI was attained in F4 (3.22) at 90 DAS followed by F1 (3.22), F2 (3.21) and F3

(3.20).

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123

Fig. 4.29 Effect of different weed control implements on periodic changes in leaf

area index

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

60 75 90 105 60 75 90 105 60 75 90 105

Tine cultivator Spike hoe Plug weeder

L A

I

(a) 2008

F1

F2

F3

F4

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

60 75 90 105 60 75 90 105 60 75 90 105

Tine cultivator Spike hoe Plug weeder

L A

I

(b) 2009

F1

F2

F3

F4

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124

4.56 Crop growth rate

The fig.4.30 showed that weed control implements and frequency levels affected the

crop growth rate (CGR) during the years 2008 and 2009.

Tine cultivator attained maximum CGR in F4 (25.69 g m-2 d-1) at 90 DAS followed by

F3 (25.65 g m-2 d-1), F2 (24.35 g m-2 d-1) and F1 (20.89 g m-2 d-1) during the year 2008. Similar

trend was observed during the year 2009, maximum CGR was attained in F4 (24.84 g m-2 d-1)

at 90 DAS followed by F3 (24.66 g m-2 d-1), F1 (20.75 g m-2 d-1) and F2 (18.66 g m-2 d-1).

Spike hoe attained maximum CGR in F3 (20.24 g m-2 d-1) at 90 DAS followed by F1

(20.15 g m-2 d-1), F4 (20.06 g m-2 d-1) and F2 (19.84 g m-2 d-1) during the year 2008. Similar

trend was observed during the year 2009, maximum CGR was attained in F3 (20.55 g m-2 d-1)

at 90 DAS followed by F2 (20.15), F4 (19.92 g m-2 d-1) and F1 (18.39 g m-2 d-1).

Plug weeder attained maximum CGR in F1 (20.20 g m-2 d-1) at 90 DAS followed by

F2 (19.96 g m-2 d-1), F3 (19.71 g m-2 d-1) and F4 (19.55 g m-2 d-1) during the year 2008. Similar

trend was observed during the year 2009, maximum CGR was attained in F1 (20.06 g m-2 d-1)

at 90 DAS followed by F2 (19.82 g m-2 d-1), F3 (19.57 g m-2 d-1) and F4 (19.41 g m-2 d-1).

4.57 Leaf area duration

The fig.4.31 showed that weed control implements and frequency levels significantly

affected cumulative leaf area duration (LAD) at 105 DAS during the years 2008 and 2009.

Tine cultivator during the year 2008 resulted in significantly maximum LAD at F4

(123.23 days) similar to F3 (121.70 days). Minimum LAD was observed in F1 (99.30 days).

During the year 2009 maximum LAD was noted in F4 (120.30 days) similar to F3 (118.78

days). Minimum LAD was observed in F1 (96.38 days).

Spike hoe during the year 2008 resulted in significantly maximum LAD at F3 (102.75

days) similar to F4 (101.25 days), F2 (96.95 days) and F1 (96.80 days). Similar trend was

observed during 2009 maximum LAD was attained by F3 (99.83 days) similar to F4 (98.33

days) and F2 (94.03).

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125

Fig. 4.30 Effect of different weed control implements on periodic changes in crop

growth rate

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

5

10

15

20

25

30

75 90 105 75 90 105 75 90 105

Tine cultivator Spike hoe Plug weeder

C G

R (

g m

-2d-1

)

(a) 2008

F1

F2

F3

F4

0

5

10

15

20

25

30

75 90 105 75 90 105 75 90 105

Tine cultivator Spike hoe Plug weeder

C G

R (

g m

-2d-1

)

(b) 2009

F1

F2

F3

F4

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126

Fig. 4.31 Effect of different weed control implements on cumulative leaf area

duration at 105 DAS

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

20

40

60

80

100

120

140

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

L A

D (

day

s)

(a) 2008

0

20

40

60

80

100

120

140

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

L A

D (

days

)

(b) 2009

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127

Plug weeder resulted in maximum LAD at F4 (97.57 days) similar to F3 (97.25 days),

F1 (96.22 days) and F2 (96.07 days) during the year 2008. During the year 2009 maximum

LAD was noted in F4 (94.64 days) similar to F3 (94.33 days), F1 (93.30 days) and F2 (93.15

days).

4.58 Total dry matter

The fig.4.32 showed that weed control implements and frequency levels significantly

affected total dry matter (TDM) at 105 DAS during the years 2008 and 2009.

Tine cultivator during 2008 resulted in significantly maximum TDM at F4 (806.29 g)

similar to F3 (797.59 g). Minimum TDM was observed in F1 (526.90 g). During the year 2009

maximum TDM was noted in F4 (800.12 g) similar to F3 (791.42 g). Minimum TDM was

observed in F1 (520.73 g).

Spike hoe during the year 2008 resulted in significantly maximum TDM at F4 (573.01

g) similar to F3 (560.94 g), minimum TDM was observed in F2 (520.75 g). Similar trend was

observed during 2009 maximum TDM was attained by F4 (566.84 g) similar to F3 (554.77 g),

minimum TDM was observed in F2 (514.38 g).

Plug weeder resulted in maximum TDM at F1 (537.49 g) similar to F3 (529.49 g),

during the year 2008. During the year 2009 maximum TDM was noted in F1 (531.32 g)

similar to F4 (524.95 g), F3 (523.32 g) and F2 (514.38 g).

4.59 Net assimilation rate

The fig.4.33 showed that weed control implements and frequency levels significantly

affected net assimilation rate (NAR) at 105 DAS the years 2008 and 2009.

Tine cultivator during 2008 resulted in significantly maximum NAR at F3 (6.55 g m-2

d-1) similar to F4 (6.54 g m-2 d-1). Minimum NAR was observed in F1 (5.31 g m-2 d-1). During

the year 2009 maximum NAR was noted in F3 (6.66 g m-2 d-1) similar to F4 (6.65 g m-2 d-1).

Minimum NAR was observed in F1 (5.40 g m-2 d-1)

Spike hoe during the year 2008 resulted in significantly maximum NAR at F4 (5.65 g m-2 d-1)

similar to F1 (5.50 g m-2 d-1), minimum NAR was observed in F2 (5.36 g m-2 d-1). Similar

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128

Fig. 4.32 Effect of different weed control implements on total dry matter at 105

DAS

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

100

200

300

400

500

600

700

800

900

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

T D

M (

g)

(a) 2008

0

100

200

300

400

500

600

700

800

900

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

T D

M (g

)

(b) 2009

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129

Fig. 4.33 Effect of different weed control implements net assimilation rate at 105

DAS

(F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

0

1

2

3

4

5

6

7

8

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

N A

R (

g m

-2d-1

)

(a) 2008

0

1

2

3

4

5

6

7

8

F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4

Tine cultivator Spike hoe Plug weeder

N A

R (

g m

-2d

-1)

(b) 2009

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trend was observed during 2009 maximum NAR was attained by F4 (5.76 g m-2 d-1 g) similar

to F1 (5.60 g m-2 d-1), minimum NAR was observed in F2 (5.46 g m-2 d-1).

Plug weeder resulted in maximum NAR at F1 (537.49 g) similar to F3 (529.49 g),

during the year 2008. During the year 2009 maximum NAR was noted in F1 (5.70 g m-2 d-1)

similar to F2 (5.61), F4 (5.56 g m-2 d-1) and F3 (5.55 g m-2 d-1).

4.60 Economic analysis

Tine cultivator (Table 4.39 & 4.40) gave maximum net returns in F4 (Rs. 40225)

followed by F3 (Rs.34766), during the year 2008. Similar trend was observed during the year

2009, maximum net returns were obtained by F4 (Rs. 50039) followed by F3 (Rs. 36988), F2

(Rs. 6363). Spike hoe and plug weeder gave negative net returns on all frequencies during

both the years

4.61 Marginal rate of return

During the year 2008 maximum marginal rate of return was found in D1F3 (9621%)

followed by D1F2 (4291%) and D1F4 (1365%). During the year 2008 maximum marginal rate

of return was found in D1F3 (7656%) followed by D1F2 (6548%) and D1F4 (3263%).

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Table 4.39 Effect of different weed control implements on economic returns during the year 2008

Implements

Frequencies

Paddy yield (t ha-1)

Adjusted paddy yield (t ha-1)

Value (Rs ha-1)

Straw yield (t ha-1)

Adjusted straw yield (t ha-1)

Value (Rs. ha-1)

Gross income (Rs. ha-1)

Variable cost ( Rs. ha-1)

Total cost (Rs. ha-1)

Net return (Rs. ha-1)

BCR

Tine

Cultivator

F1 1.52 1.36 38304 5.70 5.13 3591 41895 400 62987 -21092 0.67

F2 2.22 1.99 55944 5.91 5.32 3724 59668 800 63387 -3719 0.94

F3 3.71 3.30 93492 8.03 7.23 5061 98553 1200 63787 34766 1.55

F4 3.93 3.53 99036 8.53 7.68 5376 104412 1600 64187 40225 1.63

Spike Hoe

F1 1.47 1.32 37044 5.57 5.01 3507 40551 400 62987 -22436 0.64

F2 1.48 1.33 37296 5.70 5.13 3591 40887 800 63387 -22500 0.65

F3 1.96 1.76 49392 6.47 5.82 4074 53466 1200 63787 -10321 0.84

F4 2.25 2.02 56700 7.05 6.35 4445 61145 1600 64187 -3042 0.95

Plug

Weeder

F1 1.53 1.37 38556 5.63 5.07 3549 42105 400 62987 -20882 0.67

F2 1.51 1.35 38052 5.25 4.73 3311 41363 800 63387 -22024 0.65

F3 1.54 1.38 38808 5.33 4.80 3360 42168 1200 63787 -21619 0.66

F4 1.57 1.41 39564 5.92 5.33 3731 43295 1600 64187 -20892 0.67

Paddy price per kg = Rs. 28

Straw price per ton = Rs. 700

Permanent cost = Rs. 62587

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Table 4.40 Effect of different weed control implements on economic returns during the year 2009

Implements

Frequencies

Paddy yield

(t ha-1)

Adjusted paddy yield

(t ha-1)

Value (Rs ha-1)

Straw yield

(t ha-1)

Adjusted straw

yield (t ha-1)

Value (Rs. ha-1)

Gross income

(Rs. ha-1)

Variable cost ( Rs. ha-1)

Total cost (Rs. ha-1)

Net return

(Rs. ha-1)

BCR

Tine

Cultivator

F1 1.47 1.32 43659 4.72 4.25 3611 47270 400 67100 -19830 0.70

F2 2.36 2.12 70092 4.93 4.44 3771 73863 800 67500 6363 1.09

F3 3.35 3.02 99495 7.05 6.35 5393 104888 1200 67900 36988 1.54

F4 3.79 3.41 112563 7.55 6.80 5776 118339 1600 68300 50039 1.73

Spike Hoe

F1 1.46 1.31 43362 4.59 4.13 3511 46873 400 67100 -20227 0.70

F2 1.57 1.41 46629 4.72 4.25 3611 50240 800 67500 -17260 0.74

F3 1.74 1.57 51678 5.49 4.94 4200 55878 1200 67900 -12022 0.82

F4 1.84 1.66 54648 6.07 5.46 4644 59292 1600 68300 -9008 0.87

Plug

Weeder

F1 1.44 1.30 42768 4.65 4.19 3557 46325 400 67100 -20775 0.69

F2 1.51 1.36 44847 4.27 3.84 3267 48114 800 67500 -19386 0.71

F3 1.41 1.27 41877 4.35 3.92 3328 45205 1200 67900 -22695 0.67

F4 1.34 1.21 39798 4.94 4.45 3779 43577 1600 68300 -24723 0.64

Paddy price per kg = Rs. 33

Straw price per ton = Rs. 850

Permanent cost = Rs. 66770

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Table 4.41 Effect of different weed management strategies on dominance analysis during 2008

Treatments Cost that

vary (Rs. ha-1)

Net field benefits

(Rs. ha-1)

D3F1 400 41705

D1F1 400 41495 D

D2F1 400 40151 D

D1F2 800 58868

D3F2 800 40563 D

D2F2 800 40087 D

D1F3 1200 97353

D2F3 1200 52266 D

D3F3 1200 40968 D

D1F4 1600 102812

D2F4 1600 59545 D

D3F4 1600 41695 D

(D1= Tine cultivator D2= Spike hoe D3= Plug weeder F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

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Table 4.42 Effect of different weed management strategies on dominance analysis during 2009

Treatments Cost that

vary (Rs. ha-1)

Net field benefits

(Rs. ha-1)

D1F1 400 46870

D2F1 400 46473 D

D3F1 400 45925 D

D1F2 800 73063

D2F2 800 49440 D

D3F2 800 47314 D

D1F3 1200 103688

D2F3 1200 54678 D

D3F3 1200 44005 D

D1F4 1600 116739

D2F4 1600 57692 D

D3F4 1600 41977 D

(D1= Tine cultivator D2= Spike hoe D3= Plug weeder F1= Inter row cultivation at 15 DAS F2= Inter row cultivation at 15 and 25 DAS F3= Inter row cultivation at 15, 25 and 35 DAS F4= Inter row cultivation at 15, 25, 35 and 45 DAS)

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Table 4.43 Effect of different weed management strategies on marginal analysis during 2008

Treatments Cost that

vary (Rs. ha-1)

Marginal cost

(Rs. ha-1)

Net field benefits

(Rs. ha-1)

Marginal net

benefits (Rs. ha-1)

Marginal rate of return

(%)

D3F1 400 0 41705 -

D1F2 800 400 58868 17163 4291

D1F3 1200 400 97353 38485 9621

D1F4 1600 400 102812 5459 1365

Table 4.44 Effect of different weed management strategies on marginal analysis during 2009

Treatments Cost that

vary (Rs. ha-1)

Marginal cost

(Rs. ha-1)

Net field benefits

(Rs. ha-1)

Marginal net

benefits (Rs. ha-1)

Marginal rate of return

(%)

D1F1 400 - 46870

D1F2 800 400 73063 26193 6548

D1F3 1200 400 103688 30625 7656

D1F4 1600 400 116739 13051 3263

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DISCUSSION

This experiment was conducted during 2008 and 2009 at Agronomic Research Farm,

University of Agriculture Faisalabad. Seed of variety Super Basmati with good vigor and

germination percentage was dry direct seeded using automatic rabbi drill (seed-cum-fertilizer

drill) after land preparation. It allowed line sowing maintaining 22.5 cm row to row distance

and facilitated manual and mechanical weeding. Drill tilled the soil at shallow depth (4-5

cm), sowed the seeds and covered them with soil for better seed to soil contact, all in a single

pass. Kumar and Ladha (2011) also reported that drill sowing facilitated weed control

between rows, saved seed and placed the fertilizer at proper depth. Placing seeds below soil

surface also reduced seed damage caused by high rainfall. High Quality seed was used

because larger seeds with greater carbohydrate reserves have increased ability to emerge even

from greater burial depths also found by Baskin and Baskin (1998). Within rows distance was

maintained at 22.5 cm because studies of Chauhan and Johnson (2010a) revealed that in this

range growth and seed production of various weeds in aerobic conditions was less as

compared to wider (30-cm) rows. Similarly Akobundu and Ahissou (1985) reported that row

spacing (15–45-cm) in direct-seeded rice had little effect on the paddy yield of the crop in the

absence of weeds but in competition with weeds the wider spacing resulted in significantly

lower grain yield.

Weeds are one of the major biological constraints to direct seeded rice production and

are notorious yield reducers, in many situations economically more important than insects,

fungi or other pest organisms (Savary et al., 1997). Weed biomass differed significantly in all

weed control implements at various frequencies. Lower weed biomass was observed when

tine cultivator was used at 15, 25, 35, 45 and 15, 25, 35 DAS. Possibly because it uprooted

and removed inter row weeds and controlling early flushes of weeds. Similar findings were

reported by Fazlollaalh et al. (2011). Second reason of less weed biomass might be

beushaning which killed the weeds with single stem. This was also reported by Rao, et al.

(2007) and Sharma (1997). Inter row cultivation with tine cultivator at 15, 25 and 15 DAS

resulted in more weed biomass than the two earlier ones. Increased weed dry weight might

have been due to increased critical period of weed infestation. Weeds might have competed

for more than 25 DAS. This prolonged competition period possibly provided a considerable

opportunity for weeds to emerge subsequently and produce seeds. Studies by Chauhan and

Johnson (2011) revealed that in direct seeded rice weed competition period was beyond 40

DAS. Lower weed biomass was recorded when spike hoe was operated at 15, 25, 35, 45 and

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139

15, 25, 35 DAS. Reason of less weed biomass might be beushaning which killed the weeds

with single stem. This was also reported by Rao, et al. (2007) and Sharma (1997). Plug

weeder produced similar weed biomass at all frequencies of inter row cultivation. It

controlled no weeds resulting in high weed biomass. Reasons of increased weed biomass

might be firstly aerobic soil conditions were conducive to the germination and growth of

weeds as reported by Rao et al. (2007). Secondly emerging direct seeded rice seedlings were

less competitive with concurrently emerging weeds (Kumar et al., 2008a). Third reason of

highest weed biomass might be competitive advantage of C4 weeds which increased their

efficiency to use crop nutrients more than rice. Findings of Holm et al. (1991) were in

support of this reason.

Although plant height is a genetic character but height of aerobic rice substantially

decreases when dry weed biomass exceeds (Zhao et al., 2006). Taller plants were recorded

when tine cultivator was operated at 15, 25, 35, 45 and 15, 25, 35 DAS. Higher plant might

be attributed to availability of proper nutrients and space resulting in good leaf canopy

because of low weed infestation. Phoung et al. (2005) found that N uptake was maximum

with good weed control practices in direct seeded rice, resulting in taller plants. Inter row

cultivation with tine cultivator at 15, 25 and 15 DAS resulted in shorter plants than the two

earlier ones. This might have been due to more weeds, less available space and nutrients.

Phoung et al. (2005) reported that when weeds were more than more N uptake by weeds as

compared to rice plants. Similar findings were observed by Mann et al. (2007).

Taller plants were recorded when spike hoe was operated at 15, 25, 35, 45 and 15, 25,

35 DAS. Reason of taller plants might be less weed biomass due to beushaning which killed

the weeds with single stem and availability of nutrients to rice crop (Phoung et al., 2005).

This was also found by Sharma (1997). Inter row cultivation with spike hoe at 15, 25 and 15

DAS resulted in shorter plants than the two earlier ones. This might have been due to more

weeds, less available space and nutrients. Similar findings were reported by Phoung et al.

(2005).

Plug weeder produced similar plant height at all frequencies of inter row cultivation.

Reason of shorter plants might be less availability of space and nutrients due to increased

weed biomass. Competitive advantage of C4 weeds increased their efficiency to use crop

nutrients more than rice (Holm et al., 1991).

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Variation in fertile tillers among different treatments was observed in current studies.

Less fertile tillers were observed when tine cultivator was operated at 15, 25 and 15 DAS. In

general number of effective tillers decreased as the weed-infested period was extended,

reasons might be; Firstly aerobic soil conditions were conducive to the germination and

growth of weeds as reported by Rao et al. (2007). Secondly emerging direct seeded rice

seedlings were less competitive with concurrently emerging weeds (Kumar et al., 2008a).

Third reason of less fertile tillers might be competitive advantage of C4 weeds which

increased their efficiency to use crop nutrients more than rice. Findings of Holm et al. (1991)

are in support of this reason. Heavy and quicker second flush of weeds might be another

reason of lees fertile tillers. Similar findings were reported by Sharma et al. (1977). More

fertile tillers in tine cultivator when used at 15, 25, 35, 45 and 15, 25, 35 DAS were observed.

This increase in fertile tillers might have been due to less early competition of crop with

weeds and more availability of moisture and nutrients. Increase in fertile tillers with

decreased weed biomass was also observed by Juraimi et al. (2009) and Phoung et al. (2005).

Spike hoe produced more productive tillers at 15, 25, 35, 45 and 15, 25, 35 DAS with high

weed infestation this might have been due to beushaning effect which increased fertile tillers.

Different inter row cultivations by plug weeder had no effect on productive tillers. These

Results are also in line with findings of Ekleme et al. (2009), Mann et al. (2007), Singh et al.

(2007) and Fischer et al. (2001).

Paddy yield in tine cultivator when used at 15, 25, 35, 45 and 15, 25, 35 DAS was

observed more than two other frequencies. This increase in yield might be due to minimum

presence of weeds during critical competition period. Studies of Haefele et al. (2000)

suggested that there was a considerable scope to increase yield with improved weed control

in direct seeded rice. Proper availability of nutrients, space and moisture resulted in more

fertile tillers, more kernels panicle-1 and heavier 1000 kernel weight providing high returns in

the form of paddy yield. Similar findings were observed by Phoung et al. (2005).

Paddy yield recorded in weed control by Spike hoe at 15, 25, 35, 45 and 15, 25, 35

DAS was observed more than two other frequencies, First reason of increase in yield might

be low weed dry weight and second reason might be beushaning effect resulting in more

tillers and more yield. Results of Sharma (1997) were similar to our findings. Paddy yield

was not effected by any inter row cultivation of plug weeder. Low yield might have been due

to several reasons. Firstly aerobic soil conditions were conducive to the germination and

growth of weeds, they increased their dry weight and paddy yield was reduced. Oerke and

Dehne, (2004) also found that weeds were major constraint in reduction of paddy yield.

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141

Secondly emerging direct seeded rice seedlings were less competitive with concurrently

emerging weeds resulting in low paddy yield (Kumar et al., 2008a). Third reason of low

paddy yield might be competitive advantage of C4 weeds which increased their efficiency to

use crop nutrients more than rice. Findings of Holm et al. (1991) were in support of this

reason. Similar results are reported by Ekleme et al. (2009), Juraimi et al. (2009), Hussain et

al. (2008), Singh et al. (2008), Mann et al. (2007) and Singh et al. (2007).

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CHAPTER 5

SUMMARY

Effect of different weed management strategies on agro qualitative traits of direct seeded

rice was studied on a sandy loam soil during the years 2008 and 2009 at Agronomic Research

Farm, University of Agriculture Faisalabad. The study comprised of two sets of field

experiments. Seed of variety Super Basmati with good vigor and germination percentage was dry

direct seeded in a well prepared seed bed using automatic rabi drill (seed-cum-fertilizer drill).

Sowing was done in 22.5 cm apart rows which facilitated manual and mechanical weeding.

Experiment I was laid out in RCBD having five weed control treatments; hand weeding, hoeing

(with kasula), inter row cultivation with tine cultivator, inter row cultivation with spike hoe and

chemical control with Nominee 100 SC along with control (no weeding). Experiment II was laid

out in split plot design randomizing inter row cultivation implements in main plots and inter row

cultivation frequencies in sub plots. Both experiments were replicated thrice. Net plot size was

2.7 m x 6.0 m in both experiments.

Data on various parameters were analyzed using a standard procedure and Fisher’s

analysis of variance technique for statistical analysis. The treatment means were compared using

LSD test at P 0.05. Within the range of the data obtained following inferences and conclusions

are drawn. Salient findings of both the studies are summarized as following

STUDY-I: COMPARISON OF DIFFERENT WEED MANAGEMENT STRATEGIES IN DRILL SEEDED AEROBIC RICE

Different weed management strategies had significant effects on productive tillers, panicle

length, kernels per panicle, 1000 kernel weight, weed biomass, growth parameters, quality

parameters and yield of direct seeded rice.

Weed dry weight in no weeding was 316.61 g m-2 while in hand weeding, hoeing, tine

cultivator and Nominee -300 g m-2, 257 g m-2, 225 g m-2 and 157 g m-2 respectively less

weed dry weight was produces.

Maximum fertile tillers were recorded in hand weeding (369.73 m-2) and were followed

by those recorded for hoeing (356.94 m-2) and tine cultivator (346.78 m-2).

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Hand pulling, hoeing, tine cultivator, Nominee and spike hoe recorded 28, 25, 22, 12 and

6% more number of kernels per panicle respectively as compared with those recorded

under no weeding treatment.

Hand pulling, hoeing, tine cultivator, Nominee and spike hoe recorded 39, 37, 30, 20 and

13% heavier 1000 kernel weight respectively as compared with those recorded under no

weeding treatment.

Paddy yield was 221, 203, 181, 105 and 64% more in hand pulling, hoeing, tine cultivator

and Nominee and spike hoe respectively as compared no weeding.

Different weed management strategies enhanced the growth of DSR. Improved LAI,

LAD, CGR, TDM and NAR were observed in hand pulling, hoeing, tine cultivator and

Nominee as compared to no weeding.

Different weed management strategies not only enhanced the growth of DSR but quality

of harvested paddy was also improved. Employing hand pulling, hoeing, tine cultivator

and Nominee resulted in lower sterile spikelets, opaque kernels and abortive kernels as

compared no weeding.

Highest net returns (Rs. 56905) were obtained by hand weeding while highest BCR

(1.75) was obtained in tine cultivator.

STUDY-II: EVALUATION OF DIFFERENT INTER CULTURAL IMPLEMENTS FOR WEED MANAGEMENT IN DRILL SEEDED AEROBIC RICE

Different weed control implements at various frequencies had significant effect on

productive tillers, panicle length, kernels per panicle, 1000 kernel weight, weed biomass, growth

parameters, quality parameters and yield of direct seeded rice.

Lower weed biomass was observed when tine cultivator and spike hoe were used at 15,

25, 35, 45 and 15, 25, 35 DAS.

Different weed management implements had significant effect on fertile tillers. More

fertile tillers in tine cultivator and spike when used at 15, 25, 35 and 45 DAS were

observed.

Longer panicle length was recorded when tine cultivator and spike hoe were operated at

15, 25, 35, 45 and 15, 25, 35 DAS.

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Heavier 1000 kernel was recorded in tine cultivator and spike when used at 15, 25, 35

and 45.

Different weed management implements enhanced the growth of DSR. Improved LAI,

LAD, CGR, TDM and NAR were observed when tine cultivator was operated at 15, 25,

35 and 45 DAS.

Different weed management implements not only enhanced the growth of DSR but

quality of harvested paddy was also improved. Employing tine cultivator and spike hoe at

15, 25, 35 and 45 DAS resulted in lower sterile spikelets, opaque kernels and abortive

kernels.

Different weed management implements significantly effected paddy yield. More paddy

yield was when tine cultivator and spike hoe were operated at 15, 25, 35, 45 and 15, 25,

35 DAS.

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145

CONCLUSIONS

1. Maximum yield of rice obtained was 4.5 t ha-1 that is satisfactory.

2. Tine cultivator performed well for inter row weed control.

3. Weed control by tine cultivator is the most suitable and economical method.

4. Hand weeding produced maximum yield (4.5 t ha-1) while the befit cost ratio was more

tine cultivator (1.75).

FUTURE RESEARCH NEEDS

1. It is suggested that similar studies should be carried out under different agro climatic

conditions to have site specific and conclusive information.

2. There is need to develop a tractor drawn automatic drill for rice sowing.

3. Tine cultivator should be developed in farmer friendly size.

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146

REFERENCES

Adesina, A.A., D.E. Johnson and E.A. Heinrichs. 1994. Rice pests in the Ivory Coast, West Africa-

Farmers perceptions and management strategies. Int. J. Pest Manage. 40(4): 293-299.

Akbar, N., Ehsanullah, K. Jabran and M.A. Ali. 2011. Weed management improves yield and quality

of direct seeded rice. AJCS 5(6): 688-694.

Akobundu, I.O. and A. Ahissou. 1985. Effect of inter row spacing and weeding frequency on the

performance of selected rice cultivars on hydromorphic soils of West Africa. Crop Prot. 4:

71-76.

Akobundu, I.O. 1980. Weed science research at the International Institute of Tropical Agriculture

and research needs in Africa. Weed Sci. 28: 439-445.

Akobundu, I.O. 1987. Weed Science in the Tropics: Principles and Practices. John Wiley and Sons

Ltd. Great Britain. 533.

Alison, L.E. and C.D. Modie. 1965. Carbonate. pp. 1379-1396. In: C.A. Black (ed.) In: Methods Soil

Anal. Part 2: Chemical and micro biological properties. Soil Sci. Soc. Am. Madison, WI,

USA.

Awan, I.U., H.U. Alizai and F.M. Chaudhry. 1989. Comparative study of direct seeding and

transplanting methods on the grain yield of rice. Sarhad J. Agri. 5: 119-124.

Azmi, M., A.S. Jurami and M.Y.M. Najib. 2007. Critical period of weed competition in direct seeded

Rice under saturated and flooded conditions. J. Tropi. Agric. Food Sci. 35: 319- 332.

Bahar, H.A. and G. Singh. 2004. Effect of herbicides on dry seeded rice (Oryza sativa L.) and

associated weeds. Ind. J. Weed Sci. 36: 269-270.

Balasubramanian, V. and J.E. Hill. 2002. Direct seeding of rice in Asia: Emerging issues and

strategic research needs for the 21st century. In ‘‘Direct Seeding: Research Strategies and

Opportunities’’ (S. Pandey, M. Mortimer, L. Wade, T. P. Tuong, K. Lopez, and B. Hardy,

Eds.), pp. 15–39. International Rice Research Institute, Los Ban˜os, Philippines.

Baltazar, A.M. and S.K. DeDatta. 1992. Weed management in rice. Weed Abstracts. 41: 495-508.

BAS. 2011. Bureau of Agricultural Statistics (BAS), Country STAT Philippines. Available from

URL: http://www.countrystat.bas.gov.ph.

Page 174: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

147

Baskin CC and J.M. Baskin. 1998. Seeds. Ecology, biogeography and evolution of dormancy and

germination. Annals of Botany 86: 705-708.

Becker, M., D.E. Johnson, M.C.S. Wopereis and A. Sow. (2003). Rice yield gaps in irrigated

systems along an agro-ecological gradient in West Africa. J. Plant Nutr. Soil Sci. 166(1): 61-

67.

Bhaghat, K.L., A.K. Dhama and S. Harban. 1989. Herbicidal weed management in irrigated rice.

Gujrat Agricuture University. Res. J. Ind. 15: 81-83.

Bhuiyan, S.I. 1992.Water management in relation to crop production: case study on rice. Outlook

Agric. 21: 293-299.

Bhushan, L., J.K. Ladha, R.K. Gupta, S. Singh, A. Tirol-Padre, Y.S. Saharawat, M. Gathala and H.

Pathak. 2007. Saving of water and labor in a rice wheat system with no-tillage and direct

seeding technologies. Agron. J. 99: 1288-1296.

Bingham, F.T. 1982. Methods of soil analysis, part 2: chemical and mineralogical properties. Amer.

Soc. Agron. 431-448.

Boonrat J, P. Grienggrai, F.K., Shu and F.C., Ken. 2006. Improving drought tolerance in rainfed

lowland rice: An example from Thailand. Agric Water Manage, 80: 225–240.

Bouman, B.A.M. and T.P. Toung. 2001. Field water management to save water and increase

productivity in irrigated low land rice. Agric. Water Manage. 49:11-30.

Bouman, B.A.M., S. Peng, A.R. Castaneda and R.M. Visperas. 2005. Yield and water use of

irrigated tropical aerobic rice systems. Agric. Water Manage. 74: 87-105.

.Bouman, B.A.M and T.P. Tuong. 2003. Rice production in water-scarce environments. In: Kijne,

J.W., Barker, R., Molden, D. (Eds.), Water Productivity in Agriculture: Limits and

Opportunities for Improvement. CABI Publishing, Wallingford, UK. 53-67.

Boayoucos, G.J. 1962 . Hydrometer method improved for making particle size analysis of soil. J

.Agron. 53: 464-465.

Byerlee, D. 1988. From agronomic data to farmer’s recommendations, an economic training manual

CIMMYT, Mexico. 5: 23-33.

Page 175: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

148

Castaneda, A.R. and S.I. Bhuiyan. 1993. Sediment pollution in a gravity irrigation system and its

effects on rice production. Agric. Eco. Environ. 45: 195-202.

Chandra, S., A.N. Tiwari and R. Singh. 1998. Efficacy of herbicides in direct seeded puddled rice.

Ind. Agric. Sci. 18(2): 71-72.

Chang, T.T. 1967. The genetic basis of wide adaptability and yielding ability of rice varieties in the

tropics. Int. Rice. Comm. Newsl. 16: 4-12.

Chauhan, B.S., and D. E. Johnson. 2011. Row spacing and weed control timing affect yield of

aerobic rice .Field Crops Res. 121(2): 226-231.

Chauhan, B.S. and D.E. Johnson. 2010a. Implications of narrow crop row spacing and delayed

Echinochloa colona and Echinochloa crus-galli emergence for weed growth and crop yield

loss in aerobic rice. Field Crops Res. 117: 177-182.

Chauhan, B.S., D.E. Johnson. 2010b. Relative importance of shoot and root competition in dry

seeded rice growing with jungle rice (Echinochloa colona) and ludwigia

(Ludwigiahyssopifolia). Weed Sci. 58: 295-299

Chin, D. V., T.T.N. Son, C.V. Hach, K. Itoh and H. Hiraoka. 2000a. Study on sole and supplemental

hand weeding for weed control in rice. In Annual Workshop of JIRCAS Mekong Delta

Project. P 1-7. Cantho University, Cantho, Vietnam.

Choubey, N.K., S.S. Kolhe, and R.S. Tripathi. 2001. Relative performance of cyhalofopbutyl for

weed control in direct-seeded rice. Ind. J. Weed Sci. 33: 132-135.

CIAP (Cambodia‐IRRI‐Australia Project). 1998. Annual Research Report. 1997. Phnom Penh,

Cambodia.

CIMMYT. 1988. From Agronomic Data to Farmers Recommendations: An Economics Training

Manual. Completely revised edition. Mexico. D.F.

David, W. 2003. World's oldest rice found. BBC News. October 21, 2003.

De Dios, J.L., E.F. Javier, Malabayabas, M.D. Casimero and A.J. Espiritu. 2005. An overview on

direct‐seeding for rice crop establishment in the Philippines. In ‘‘Rice Is Life: Scientific

Perspectives for the 21st Century’’. International Rice Research Institute, Los Ban˜os,

Philippine. 189-193.

Page 176: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

149

Ekleme, F., Y. Kamara, O. Sylvester. O. Lucky, P. Amaza, T. Abdoulaye and D. Chikoye. 2009.

Response of upland rice cultivars to weed competition in the savannas of West Africa. Crop

Prot. 28: 90-96.

Ekanayake, I.J., P.L. Steponkus and S.K. De Datta. 1990. Sensitivity of pollen to water deficits at

anthesis in upland rice. Crop Sci, 30: 310–315.

Elliot, P.C., D.C. Navarez, B.D. Estario, and K. Moody. 1984. Determining suitable weed control

practices for dry-seeded rice. Philipp. J. Weed Sci. 11: 70-82.

FAO. 2004. Rice is Life. Food and Agricultural Organization of the United Nations.

Fazlollah, E.C., H. Bahrami and A. Asakereh. 2001. Evaluation of traditional, mechanical and

chemical weed control methods in rice fields. AJCS 5(8):1007-1013.

Ferrero, A. and N.V. Nguyen. 2004. Constraints and opportunities for the sustainable development of

rice‐based production systems in Europe.In ‘‘FAO Rice Conference’’, FAO, Rome. 14.

Fernandes, E.C. and N. Uphoff. 2002. Summary from conference reports. In Assessment of the

System for Rice Intensification (SRI). Paper presented at the Int Conf held in Sanya, China,

1-4 April.

Fischer, A.J., H.V. Ramirez, K.D. Gibson and S.B. Pinhjeiro. 2001. Competitiveness of semidwarf

upland rice cultivars against Palisade grass (Brachiariabrizantha) and Signal grass (B.

decumbens). Agron. J. 93: 967–973.

Fischer, A.J., E.B. David, D.C. Michael, M.A. Comfort, Y. Kyu-Ock. 2000. Mechanisms of

Resistance to Bispyribac Sodium in an Echinochloa phyllopogon Accession.

Pesticide Biochemistry and Physiology. 68(3): 156-165.

Funakawa, S., R. Suzuki, E.Karbozova, T. Kosaki and N. Ishida. 2000. Salt-affected soils under

ricebased irrigation agriculture in southern Kazakhstan.Geoderma.97:61-85

Fujisaka, S., K. Moody and K. Ingram. 1993. A descriptive study of farming practices for dry seeded

rainfed lowland rice in India, Indonesia and Myanmar. Agric. Ecosyst. Environ. 45, 115–128.

Gee, G.W. and J.W. Bauder. 1982. Particle size analysis. In: A. Klute, (ed.), Methods of Soil

Analysis, Part 1: Physical and Mineralogical Methods, 2nd edition. American Soc. Agron,

Madison, WI. 383-411.

Page 177: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

150

George, T., R. Magbanua, D.P. Garrity, B.S. Tubana and J. Quiton. 2002. Rapid yield loss of rice

cropped successively in aerobic soil. Agron. J. 94: 981-989.

Ghose, R.L.M., M.B. Ghatge and V. Subrahmanyan. 1960. Rice in India. Indian Council of

Agricultural Reasearch, New Delhi.

Ghosheh, H.Z., D. LHolshouserand J.M. Chandler. 1996. The critical period of Johnsongrass

(Sorghum halepense) control in field corn (Zea mays). Weed Sci. 44: 944- 947.

Gianessi, L.P., C.S. Silvers, S. Sankula and J.E. Carpenter. 2002. ‘‘Plant Biotechnology: Current and

Potential Impact for Improving Pest Management in U.S. Agriculture. An Analysis of 40

Case Studies.Herbicide Tolerant Rice.’’The National Center for Food and Agriculture Policy

Washington, D.C. USA.

GOP. 2010. Agricultural Statistics of Pakistan, 2009-10, Ministry of Food and Agriculture,

Economic Wing, Islamabad, Pakistan.

GOP. 2011. Agricultural Statistics of Pakistan, 2010-11, Ministry of Food and Agriculture,

Economic Wing, Islamabad, Pakistan.

Gupta, R. K., J.K. Ladha, S. Singh, R.J. Singh, M.L. Jat, Y. Saharawat, V.P. Singh, S.S. Singh, M.S.

Gill, M. Alam, H. Mujeeb, U.P. Singh, R. Mann, H. Pathak, B.S. Singh, P. Bhattacharya and

R.K. Malik. 2007. Production technology for direct seeded rice. Rice wheat consortium for

the Indo-Gagetic plains. Technical Bulletin 8. New Delhi, India. 16.

Habito, C.F., and R.M. Briones. 2005. Philippine agriculture over the years: performance,policies

and pitfalls. Paper Presented at the Conference Entitled “Policies toStrengthen Productivity in

the Philippines”. Sponsored by the Asia-EuropeMeeting (ASEM) Trust Fund, Asian Institute

of Management Policy Center, Foreign Investment Advisory Service, PIDS and the World

Bank, 27 June 2005, Makati City, Philippines.

Hach, C.V., D.V. Chin, T.V. Dien, N.V. Luat. 1997. Study the effect of water depths and herbicides

on weeds and grain yield of rice. Scientific proceedings of the Vietnam National Institute of

Agricultural Science and Technology. 5: 20-21.

Haefele, S.M., D.E. Johnson, S. Diallo, M.C.S. Wopereis, I. Janin. 2000. Improved soil fertility and

weed management is profitable for irrigated rice farmers in Sahelian Africa. Field Crops Res.

78:119-131.

Page 178: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

151

Harris, D.R. 1996. The Origins and Spread of Agriculture and Pastoralism in Eurasia.Psychology

Press. 565.

Hidejiro, S. 1994. Integrated management of paddy weeds in Japan. National Agriculture research

Center Kannonai, Tsukuba. Ibaraki. 305.

Hirota, O.,M. Oka and T. Takeda. 1990. Sink activity estimation by sink size and dry matter

increase during the ripening stage of barley (Hordeum vulgare) and rice (Oryza sativa). Ann.

Bot. 65: 349-353.

Holm, L.G., Plucknett, D.L., Pancho, J.V., Herberger, J.P., 1991. The World’s Worst Weeds:

Distribution and Biology. The University Press of Hawaii, Malabar, Florida.

Ho,N.K. and Z. Romli. 2000. Impact of direct seeding on rice cultivation: lessons from the Muda

area of Malaysia. (In) Proceedings of Workshop on DirectSeeding: Research Strategies and

Opportunities,held during January, 25-28, 2000, Bangkok, Thailand.

Hunt, R. 1978. Plant growth analysis. Edward Arnold, UK: 26-28.

Hussain, S., M. Ramzan, M. Akhtar and M. Aslam. 2008. Weed management in direct seeded rice. J.

Anim. Pl. Sci. 18: 2-3.

IRRI (International Rice Research Institute). 2004. Rice, Almanac, 3rd Edition. Int. Rice Res. Inst.

Los Banos, Phillipines. 59-235.

Islam, M.S., M.A. Quasem and M.A. Baqui. 2004. Present status and future strategy of farm

mechanization and post-harvest technologies for rice production and processing in

Bangladesh. Agric. Mechan. 35: 59-66.

IWMI (International Water Management Institute). 2007. Comprehensive assessment of water

management in agriculture. Water for food, water for life: A comprehensive assessment of

water management in agriculture. Londonand Colombo.

Johnson, D.E., M.C.S. Wopereis, D. Mbodj, S. Diallo, S. Powers and S.M. Haefele. 2004. Timing of

weed management and yield losses due to weeds in irrigated rice in the Sahel. Field Crops

Res. 85: 31-42.

Johnson, D.E. and A.M. Mortimer. 2005. Issues for weed management in direct-seeded rice and the

development of decision-support frameworks.In: Workshop on Direct-seeded Rice in the

Page 179: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

152

Rice–Wheat system of the Indo-Gangetic Plains. 1–2 February 2005. G.B. Pant University of

Agriculture & Technology, Pantnagar, Uttaranchal. India. 8.

Kabaki, N.H., T.F. Fujimori, H. Morita, B. Uraipong, U. Arromratana and T.N. Nagara. 2003.

Development of a comprehensive series of technologies for lowland cropping systems in

Northeast Thailand. JARQ. 37: 37–44.

Kato, Y., A. Kamoshita and J. Yamagishi. 2006a. Growth of three rice (Oryza sativa L.) cultivars

under upland conditionswith different levels of water supply. 2. Grain yield. Plant Prod. Sci.

9: 435-445.

Kim, J.K., Y.S. Kang, M.H. Lee, S.S. Kim and Park, S.T. 2001. Wet‐seeded rice cultivation

technology in Korea. In ‘‘Rice research for Food Security and Poverty Alleviation’’ (S. Peng

and B. Hardy, Eds.), International Rice Research Institute, Los Ban˜os, Philippines. 545-560

Kim, M. 2008. Multivocality, Multifaceted Voices, and Korean Archaeology.Evaluating Multiple

Narratives: Beyond Nationalist, Colonialist, Imperialist Archaeologies. New York: Springer.

118.

Kukal, S.S. and G.C. Aggarwal. 2003. Puddling depth and intensity effects in rice–wheat system on

a sandy loam soil. I. Development of subsurface compaction. Soil Till. Res. 72: 1-8.

Kumar, V. and J.K. Ladha. 2011. Direct Seeding of Rice: Recent developments and Future Research

Needs. Advances in Agronomy. 111: 297-413.

Kumar, V., R.R. Bellinder, R.K. Gupta, R.K. Malik and D.C. Brainard. 2008a. Role of herbicide-

resistant rice in promoting resource conservation technologies in ricewheatcropping systems

of India: A review. Crop Prot. 27: 290-301.

Kumar, S.l. (2003) Effect of weed control methods on rice cultivars in Indian rice field. Online J

Biol Sci 3: 119- 123.

Kwesi, A.N. and S.K. De Datta. 1991. A hand book weed control in rice. International Rice Research

Institut P.O. Box 933, 1099, Manila, Philippines.

Ladha, J.K., L. Bhushan, R.K. Gupta, S. Singh, A. Tirol-Padre, Y.S. Saharawat, M. Gathala and H.

Pathak. 2007. Saving of water and labor in a rice wheat system with no-tillage and direct

seeding technologies. Agron. J. 99: 1288-1296.

Page 180: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

153

Ladha, J.K., D. Dawe, H. Pathak, A.T. Padre, R.L. Yadav, B. Singh, Y. Singh, P. Singh, A.L.

Kunder, R. Sakal, N. Ram, A.P. Regmi, S.K. Gami, L. Bhandari, R. Amin, C.R. Yadav, E.M.

Bhattaria, S. Das, H.P. Aggarwal, R.K. Gupta and P.R. Hobbs. 2003. How extensive are yield

declines in long-term rice–wheatexperiments in Asia? Field Crops Res. 81: 159-180.

Lindsay, W.L. and W.A. Norvell. 1978. Development of a DTPA soil test for zinc, iron, manganese

and copper. Soil Sci. Am. J. 42: 421-428.

Ling, W.H., Qi, X.C., Jing, M. and W. Tong. 2001."Red and Black Rice Decrease Atherosclerotic

Plaque Formation and Increase Antioxidant Status in Rabbits".Journal of Nutrition. 131 (5):

1421-1426.

Liu, T.M., D.H. Mao, S.P. Zhang, C.G. Xu and Y.Z. Xing. (2009). Fine mapping SPP1, a QTL

controlling the number of spikelets perpanicle, to a BAC clone in rice (Oryza sativa). Theor.

Appl. Genet.118: 1509-1517.

Loc, N.T., H.V. Nghiep, N.H. Luc, N.T. Nhan, N.V. Luat, K.G. Schoenly, A.T. Barrion and K.L.

Heong. 1998. Effect of crop residue burning on rice predators: a case study in Vietnam. In:

Proceedings of the Integrated Pest Management Conference for Rice, 18-21 November 1996,

Kuala Lumpur, Malaysia. 54-55.

Londo, J.P. and Y. Chiang. 2006. Phylogeography of Asian wild rice, Oryzarufipogon, reveals

multiple independent domestications of cultivated rice, Oryza sativa, PNAS. 103: 78-83.

Luat, N.V. 2000. Integrated weed management and control of weeds and weedy rice in Vietnam. In

‘‘Wild and Weedy Rice in Rice Ecosystems in Asia: A Review’’ (B. B. Baki, D. V. Chin, and

M. Mortimer, Eds.), Limited Proceedings No. 2. International Rice Research Institute, Los

Banos, Philippines.1-3.

Mac, N.R.S. and J. Libby.1995. Origins of Rice Agriculture.Publications in Anthropology No. 13.

Makara, O., M. Sarom and H.J. Nesbet. 2001. Rice production systems in Cambodia. In increased

lowland rice production in the Mekong Region. 43-51.

Mann, R.A. and M. Ashraf. 2001. Improvement of Basmati and its production practices in Pakistan.

In: Special rice of the world: Breeding, production and Marketing. Edited by R.C.

Chaudhary; D.V. Tran and R. Duffy. Food and Agricultural Organization of the United

Nations, Rome. 129-148.

Page 181: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

154

Mann, R.A., S. Ahmad, G. Hassan and M.S. Baloch. 2007. Weed management in direct seeded rice

crop. Pak. J. Weed Sci. Res. 13: 219-226.

Matsushima, S., 1995. Physiology of high yielding rice plants from the viewpoint of yield

components. In: Matsuo, T., Kumazawa, K., Ishii, R., Ishihara, K., Hirata, H. (Eds.), Science

of the Rice Plant, vol. II, Physiology. Food and Agriculture Policy Research Center, Tokyo,

Japan, 737-766.

Matsunaka, S. 1975. Tadpole shrimp: a biological tool of weed control in transplanted rice fields. In

Proceedings of the 5th Asian-Pacific Weed Science Society Conference, Tokyo Japan. 439-

443

Mercado, B.L. 1979. Introduction of weed science. South East Asia Regional Center for Graduate

Study and Research in Agriculture (SEARCA), College Laguna, Philippines. 292 .

Mishra, B., L.V. Subba and S.V. Subbaiah. 2005. Rice varieties for direct‐seeding. In

‘‘Direct‐Seeding of Rice and Weed Management in the Irrigated Rice‐Wheat Cropping

System of the Indo Gangetic Plains’’ (Y. Singh, G. Singh, V. P. Singh, P. Singh, B. Hardy,

D. E. Johnson, and M. Mortimer, Eds.). Directorate of Experiment Station, G.B. Pant

University of Agriculture and Technology, Pantnagar, India. 10.

Molina, J., M. Sikora, N. Garud, J.M. Flowers, S. Rubinstein, A. Reynolds, P. Huang, S. Jackson, B.

A. Schaal, C.D. Bustamante, A.R. Boyko and M.D. Purugganan. 2011. "Molecular evidence

for a single evolutionary origin of domesticated rice".Proceedings of the National Academy

of Sciences. 108 (20): 8351-8356.

Moodie, R.E., R.W. Smith and R.A. Mac Greery. 1959. Laboratory Manual of Soil Fertility. State

College Washington, Mimeograph, Pullman, WA, USA. p.175.

Moody, K. 1990. Post-planting Weed control in direct seeded rice. Paper presented at rice

symposium. Malaysian Agricultural Development Institute, Penang, Malaysia. 25-27.

Moody, K. 1983. The status of weed control in rice in Asia.Plant Protection Bulletin. 30: 119-124.

Morthy, B.T.S. 2003. Evaluation of pyrazosulfuron ethyl alone and in combination with molinate for

controlling weeds in rainfed direct-seeded lowland rice. Ind. J. Weed Sci. 34: 285-286.

Page 182: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

155

Nelson, D.W. and L.E. Sommers. 1982. Total corbon, organic corbon and organic matter. pp-570-

571. In: Methods Soil Anal.Part 2: Chemical and micro biological properties. Agron. Mongr.

9. Soil Sci. Soc. Am. Madison, WI, USA.

Norton, G.W., K.L. Heong, D. Johnson and S. Savary. 2010. Rice pest management: issues and

opportunities. In: Pandey, S. Byerlee, D. Dawe, D. Dobermann, A. Mohanty, S. Rozelle, S.

Hardy, B. (Eds.), Rice in the Global Economy: StrategicResearch and Policy Issues for Food

Security. International Rice ResearchInstitute, Los Baños, Philippines. 297-332.

Oerke, E.C. and H.W. Dehne. 2004. Safeguarding production-losses in major crops and the role of

crop protection. Crop Prod. 23: 275-285.

Oteng, J.W. and R.S. Anna. 1999. Rice production in Africa: Current Situation and Issues. Int. Rice

Comm. Newsl. 48: 41-51.

Pandey, S. and L. Velasco. 2002. Economics of direct‐seeding in Asia: Patterns of adoption and

research priorities. In ‘‘Direct Seeding: Research Strategies and Opportunities’’ (S. Pandey,

M. Mortimer, L. Wade, T. P. Tuong, K. Lopez, and B. Hardy, Eds.). International Rice

Research Institute, Los Ban˜ os, Philippines. 3-14.

Pandey, S. and L. Velasco. 1999. Economics of direct seeding in Asia: patterns of adoption and

research priorities. Mini Rev. Int. Rice Res. Notes. 22: 6-11.

Phoung, L.T., m. Denich, P.L.G. Viek, and v. Balasubramanian. 2005. Suppressing weeds in direct

seeded lowland rice: Effects of methods and rates of seedeing. Agrnomy and Crop Science.

191: 185-194.

Pinheiro, B.S., E. Castro and C.M. Guimaraes. 2005. Sustainability and profitability of aerobic rice

production in Brazil. Field Crops Res. 97:34-42.

Pokharia, A. K., J.N. Pal, N. Srivastava and Alka. 2009. Plant macro-remains from Neolithic Jhusi

in Ganga Plain: evidence for grain-based agriculture. Journal of Current Science. 97: 564-

571.

Ramzan, M. 2004. Evaluation of various planting methods in rice–wheat cropping system, Punjab,

Pakistan. Rice Crop Report. 4-5.

Rao, A.N., D.E. Johnson, J.K. Ladha, B. Sivaprasad and A.M. Mortimer. 2007. Weed management

in direct seeded rice. Advances in Agronomy. 93: 153-255.

Page 183: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

156

Remington, T.R. and J.L. Posner. 2000. On‐farm evaluation of weed control technologies in

direct‐seeded rice in the Gambia. In ‘‘Animal Power for Weed Control. A Resource Book of

the Animal Traction Network for Eastern and Southern Africa (ATNESA)’’ (P. Starkey and

T. Simalenga, Eds.). Technical Center for Agricultural and Rural Cooperation (CTA),

Wageningen, The Netherlands. 255-261.

Rijsberman, F.R. 2006. Water scarcity: fact or fiction? Agri. Water Manage. 80: 5-22.

Savary, S., R.K. Srivastava, H.M. Singh and F.A. Elazegui. 1997. A characterization of rice pests

and quantification of yield losses in the rice wheat system of India. Crop Protect. 16:

387–398.

Sharma, P.K., L. Bhushan, J.K. Ladha, R.K. Naresh, R.K. Gupta, B.V. Balasubramanian and B.A.M.

Bouman. 2002. Crop-water relations in rice-wheat cropping under different tillage systems

and water-management practices in a marginally sodic, medium-textured soil. In ‘Water-wise

Rice Production’.Proceedings of the International Workshop on Water-wise Rice Production,

8-11 April 2002, Los Baños, Philippines. 255-261

Sharma, A.R. 1997. Effect of integrated weed management and nitrogen fertilization on the

performance of rice under flood-prone lowland conditions. J. Agric. Sci. Cambridge 129:

409-418.

Sharma, H.C., H.B. Singh and G.H. Friesen. 1977. Competition from weeds and their control in

direct-seeded rice. Weed Research. 17: 103-108.

Singh, C.V., B.C. Ghosh, B.N. Mittra and R.M. Singh. 2008. Influence of nitrogen and weed

management on the productivity of upland rice. Journal Plant Nutrition. 171: 466-470.

Singh, S., J.K. Ladha, R.K. Gupta, L. Bhushan, A.N. Rao, B. Sivaprasad and P.P. Singh. 2007.

Evaluation of mulching, intercropping with Sesbania and herbicide use for weed management

in dry-seeded rice (Oryza sativa L.). Crop Prot. 26: 518-524.

Singh, S., L. Bhushan, J.K. Ladha, R.K. Gupta, A.N. Rao and B. Sivaprasad. 2006. Weed

management in dry‐seeded rice (Oryza sativa) cultivated in the furrow‐irrigated raised‐bed

planting system. Crop Prot. 25: 487-495.

Page 184: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

157

Singh, G. 2005. Integrated weed management in direct-seeded rice. In Direct Seeding of Rice and

Weed Management in the Irrigated Rice-Wheat Cropping System of the Indo Gangetic

Plains. 15.

Singh, G., Y. Singh, V.P. Singh, R.K. Singh, P. Singh, D.E. Johnson and M. Mortimer. 2003. Direct

seeding as an alternative to transplanting rice for the rice–wheat system of the Indo-Gangetic

Plains: sustainability issues related to weed management. In: The British Crop Protection

Council International Congress on Crop Science and Technology-2003, SECC, Glasgow,

UK. 1035-1040.

Singh, A.K., B.U. Choudhury and B.A.M. Bouman. 2003. Effects of rice establishment methods on

crop performance, water use, and mineral nitrogen. In ‘‘Water-Wise Rice Production’’

(B.A.M. Bouman, H. Hengsdijk, B. Hardy, P.S. Bindraban, T.P. Tuong, and J. K. Ladha,

Eds.).. Proceedings of a Thematic Workshop on Water-Wise Rice Production, 8-11 April

2002 at IRRI Headquarters in Los Banos, Philippines. International Rice Research Institute,

Los Banos, Philippines. 223-235.

Singh, Y., G. Singh, R.S.L. Srivastava, V.P. Singh, R.K. Singh, M. Mortimer, J.L. White and D.E.

Johnson. 2001. Direct‐seeding of rice in the rice‐wheat systems of the Indo Gangetic plains

and the implications for weed management. In ‘‘Proceedings of British Crop Protection

Conference: Brighton, UK. 187-192.

Steel, R.G.D., J.H. Torrie and D.A. Dickey. 1997. Principles and Procedures of Statistics, A

Biometrical Approach 3rd Ed. McGraw Hill Book Co. Inc., New York, USA.

Stessens, J. 2002. Analyse technique ete´conomique des systems de production agricole au Nord de

la Coˆ te d’Ivoire. Katholieke Universiteit Leuven, Leuven. Stewart, G. (1990). Witch weed:

a parasitic weed of grain crops. Outlook Agric. 19(2): 115-117.

Subudhi, E.C.R. 2004. Evaluation of weeding devices for upland rice in the Eastern Ghat of Orissa,

India. Int. Rice Res. Notes. 29: 79-81.

Sungjoon J. and X. Zhimin. 2009. "Lipophilic and Hydrophilic Antioxidants and Their Antioxidant

Activities in Purple Rice Bran".Journal of Agricultural and Food Chemistry. 57(3): 858-862.

Tabbal, D.F., B.A.M. Bouman, S.I. Bhuiyan, E.B. Sibayan and M.A. Sattar. 2002. On-farm strategies

for reducing water input in irrigated rice; case studies in the Philippines. Agric. Water

Manage. 56: 93-112.

Page 185: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

158

Tuong, T.P., B.A.M. Bouman and M. Mortimer. 2005. More rice, less water-integrated approaches

for increasing water productivity in irrigated rice-based systems in Asia. Plant Prod. Sci. 8:

231-241.

Tuong, T.P. and B.A.M. Bouman. 2003. Rice production in water-scarce environments. In: Kijne,

J.W., Barker, R., Molden, D. (Eds.), Water Productivity in Agriculture: Limits and

Opportunities for Improvement. CABI Publishing, Wallingford, UK. 53-67.

Tuong, T.P. and B.A.M. Bouman. 2001. Rice production in water scarce environments. In Water

Productivity in Agriculture: Limits and Opportunities for Improvement. CABI Publishing,

Wallingford, UK. 53-67.

U.S. Salinity Laboratory Staff. 1954. Diagnosis and improvement of saline and alkali soils. USDA

Hand Book No. 60. Washington, D.C. USA.

Vaughan, D.A., L.B. Rong and T. Norihiko. 2008. The evolving story of rice evolution. Plant

Science. 174(4): 394-408.

Victor, V. M., and A. Verma.2003. Design and development of power-operated rotary weeder for

wetland paddy. Agric. Mechan. Asia Africa Latin Am. 34:27-29.

Wang, H. Q., B. A. M. Bouman, D. Zhao, C. G. Wang and P. F. Moya. 2002. Aerobic rice in

northern China: opportunities and challenges. Proceedings of the International Workshop on

water-wise rice production, 8–11 April 2002, Los Banos, Philippines.143-154.

WARDA (1996) Annual Report for 1995. West Africa Rice Development Association.

Watanabe, H.M. Azmi andI. Zuki. 1997. Emergence of major weeds and their population change in

wet-seeded rice fields in Muda area, Peninsular Malaysia. Proceedings of 16th Asian Pacific

Weed Science Society.246-250.

Watson, D.J. 1947. Coparitive physiological studies on the growth of field crops. Variation in net

assimilation rate and leaf area between species and varieties and years. Ann. Bot. 11: 41-76.

Xie, G., J. Yu, J. Yan, H. Wang and X. Zhu.(2005). Direct seeding of aerobic rice in China. In ‘‘Rice

Is Life: Scientific Perspectives for the 21st Century’’ (K. Toriyama, K. L. Heong, and B.

Hardy, Eds.). International Rice Research Institute, Los Ban˜ os, Philippinesand. 186–188.

Page 186: prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/1101/1/1972S.pdf · To, The Controller of Examinations, University of Agriculture, Faisalabad. “We the supervisory committee,

159

Xu Z Z and G.S. Zhou. 2006. Nitrogen metabolism and photosynthesis in Leymus chinensis in

response to long-term soil drought. J Plant Growth Regul, 25: 252-266.

Yamauchi M. 1996. Development of anaerobic direct seeding technology for rice in the tropics. In:

Proceedings of the 2nd Asian Crop Science Conference, Fukui, Japan.198-203.

Yang Y H, Y.J. Zhang and Z.F. Su. 2005. Effects of amount of N fertilizer on yield constitution and

dry matter accumulation of hybrid rice. Journal of Tianjin Agricultural College, 12: 5-8.

Yoshida, S., 1981. Fundamentals of Rice Crop Science. International Rice Research Institute, Los

Ban˜os, Philippines.

Zhang Zhan-ying, Jin-jie LI, Guo-xin YAO, Hong-liang ZHANG, Hui-jing DOU, Hong-li SHI,

Xing-ming SUN, Zi-chao LI. 2011. Fine Mapping and Cloning of the Grain Number Per-

Panicle Gene (Gnp4) on Chromosome 4 in Rice (Oryza sativa L.). Agricultural Sciences in

China,10(12):1825-1833.

Zhang, W., Webster, E. P., Blouin, D. C., and Linscombe, S. D. (2004).Differential tolerance of rice

(Oryza sativa) varieties to clomazone. Weed Technol. 18, 73–76.

Zhao, D.L., G. N. Atlin, L. Bastiaans andJ. H. J. Spiertz. 2006. Cultivar weed-competitiveness in

aerobic rice: heritability, correlated traits, and the potential for indirect selection in weed-free

environments. Crop Sci. 46:372–380.

Zohary, D. and H. Maria. 2000. Domestication of plants in the Old World,3rd edition Oxford

University Press.

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160

Appendix 1 Fixed cost of production 2008

Operation/ Input No./Amount/ Quantity

Rate/Unit (Rs.)

Cost/ ha (Rs.)

1) Land Preparation Ploughing Levelling Planking

2 1 2

750 500 1000

1500 500 2000

2) Sowing Charges Seed rate Drilling

75 1

75

1250

5625 1250

3) Fertilizer DAP Urea SOP Transportation charges Application charges

3.5bags 5.5 bag 4.73 bags 13 bags 13 bags

1/2 man day

3100 700 1400

10 100

10850 3850 6622 130 1300

4) Irrigation Water rates Water course cleaning Application charges

-

2 man days 16

½ man day

200 200 100

200 400 1600

5) Plant protection Insecticide Application charges

2.5 packs

1/4 man days

400 200

1000 50

Total charges from 1-5 - - 36877 Mark up on investment from 1-5 @ 9 % per annum

6 months 276/month 1660

Management charges 6 months 175 1050 Land rent 6 months 3750 22500 Artisan charges - 500 500 Total permanent cost 62587

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161

Appendix 2 Variable cost for experiment 1 during 2008 and 2009

Treatment Weed control charges (Rs. ha -1)

No Weeding 0 Hand pulling

12000

Hoeing

8000

Tine Cultivator

1600

Spike Hoe

1600

Nominee

1260

Appendix 3 Variable cost for experiment 2 during 2008 and 2009

Implements

Frequencies

Weed control charges (Rs.) ha -1

Tine Cultivator

F1 400

F2 800

F3 1200

F4 1600

Spike Hoe

F1 400

F2 800

F3 1200

F4 1600

Plug Weeder

F1 400

F2 800

F3 1200

F4 1600

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162

Appendix 4 Fixed cost of production 2009

Operation/ Input No./Amount/ Quantity

Rate/Unit (Rs.)

Cost/ ha (Rs.)

1) Land Preparation Ploughing Levelling Planking

2 1 2

750 500 1000

1500 500 2000

2) Sowing Charges Seed rate Drilling

75 1

90

1250

6750 1250

3) Fertilizer DAP Urea SOP Transportation charges Application charges

3.5bags 5.5 bag 4.73 bags 13 bags 13 bags

1/2 man day

2400 800 1500 10 100

8400 4400 7095 130 1300

4) Irrigation Water rates Water course cleaning Application charges

-

2 man days 16

½ man day

200 200 100

200 400 1600

5) Plant protection Insecticide Application charges

2.5 packs

1/4 man days

400 200

1000 50

Total charges from 1-5 - - 36575 Mark up on investment from 1-5 @ 9 % per annum

6 months 276/month 1645

Management charges 6 months 175 1050 Land rent 6 months 3750 27500 Artisan charges - 500 500 Total permanent cost 66770