volume 3, number 1a, 2013.pdf

Journal of

Agricultural Science

and Technology A

Volume 3, Number 1, January 2013 (Serial Number 21)

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D

Journal of Agricultural Science

and Technology A

Volume 3, Number 1, January 2013 (Serial Number 21)

Contents

Review

1 Biosystems Engineering Curricula in Europe

Pierluigi Febo and Antonio Comparetti

Research Papers

10 Effect of Biofertilizer on Biomass Productivity, Nutrient Balance and Soil Fertility in Rainfed

Organic Ginger Production System

Nongmaithem Jyotsna, Mainak Ghosh, Dulal Chandra Ghosh, Wahengbam Ingo Meitei and Jagadish

Timsina

20 Organic Agriculture: Socioeconomic Sustainability of Brazilian Coffee

Rubia Wegner, Patrícia Helena Nogueira Turco and Flávia Maria de Mello Bliska

33 Enhancing Maize Grain Yield in Acid Soils of Western Kenya Using Aluminium Tolerant

Germplasm

Ouma Evans, Ligeyo Dickson, Matonyei Thomas, Agalo Joyce, Were Beatrice, Too Emily, Onkware

Augustino, Gudu Samuel, Kisinyo Peter and Philip Nyangweso

47 Response of Peach (Prunus persica) cv. to Foliar Application of Potassium and Copper

Shawkat Mustafa Mohammed Al-Atrushy and Sarfaraz Fatah Ali Al-bamarny

53 Carboxylesterase and Glutathione-S-Transferase (GST’s) Induced Resistance to Bacillus

thuringiensis Toxin Cry1Ab in Rice Leaf Folder, Cnaphalocrocis medinalis (Guenee) Populations

Veegala Ramesh Babu, Vemuri Shashi Bhushan, Chintalapati Padmavathy, Muthugonder Mohan, Sena

Mahendran. Balachandran and Bellamkonda Ramesh

60 Environmental Impacts of Feeding High-fiber Diet to Pigs

Abraham Woldeghebriel, Shanequa Smith, Teo Barios, Brad Pope and Sebhatu Gebrelul

66 Effects of Feeding Siamese Neem Leaves and Zanthoxylum Pods, on Dry Matter Intake, Dry

Matter Digestibility, Milk Production and Composition in Thai Holstein Dairy Cows, Fed Rice

Straw as Fiber Source

Penjor, Virote Pattarajinda, Suporn Katawatin, Chaiyapas Thamrongyoswittayakul and Wandee

Gritsanapan

72 Feeding Effect of Triticale Fodder as Replacement of Straw on Production Performance of Dairy

Cows

Nathu Ram Sarker, Mohammad Asaduzzaman, Khan Shahidul Huque, Mohammad Toyebur Rahman,

Nazrul Islam, Mohammad Enamul Haque and Stephen R. Waadington

Journal of Agricultural Science and Technology A 3 (2013) 1-9 Earlier title: Journal of Agricultural Science and Technology, ISSN 1939-1250

Biosystems Engineering Curricula in Europe

Pierluigi Febo and Antonio Comparetti

Dipartimento dei Sistemi Agro-Ambientali, Università di Palermo, Palermo 90128, Italy

Received: September 26, 2012 / Published: January 20, 2013.

Abstract: This paper describes the history of the harmonisation of agricultural/biosystems engineering degree study programs in Europe from 1989, when the need for this process was widely felt, until now, when this need was partly satisfied through the implementation of the projects of two EU funded thematic networks, i.e., USAEE-TN and ERABEE-TN. The objective of this paper is to contribute to promote, in each EU country and elsewhere, the process of harmonisation of agricultural/biosystems engineering degree study programs, and student and graduate mobility within the EU, as well as between the EU and the USA. At present, in Europe, this harmonisation process is aided by the key results of the projects of USAEE-TN, ERABEE-TN and POMSEBES. USAEE developed some core curricula, to be used as benchmarks for European agricultural/biosystems engineering degree study programs, and a web-based database of these study programs. ERABEE promoted the transition from agricultural engineering to biosystems engineering and established the recognition procedures of new European study programs in biosystems engineering. The EU-US POMSEBES consortium built up a platform for exchange of experiences and ideas between the USA and the EU, aimed at: enhancing the quality and linkage of research and education; establishing appropriate policy oriented measures; promoting compatible degree study programs in biosystems engineering, within the EU as well as between the EU and the USA. Key words: Harmonisation, degree study programs, agricultural/biosystems engineering, student and graduate mobility.

1. Agricultural Engineering Curricula: from 1989 to USAEE-TN

1.1 The Need for the Harmonisation of Agricultural

Engineering Curricula

At the end of 1989, the International Commission

of Agricultural Engineering (CIGR), under the

chairmanship of Prof. Giuseppe Pellizzi, with the

cooperation of the former Italian Association of

Agricultural Engineering (AIGR, now AIIA) and the

University of Milan, sponsored a project designed to

compare university curricula in Agricultural

Engineering in the 12 countries of the former

European Community (EC). The aim of this project

was to facilitate the creation of academic

harmonisation, in view of the Unique Market,

beginning in 1993, and to facilitate the free exchange

of university graduates in agriculture and agricultural

Corresponding author: Antonio Comparetti, researcher,

research field: agricultural machines. [email protected].

engineering throughout the EC.

As a consequence, two study seminars, attended by

representatives of EC countries, were held at

Gargnano (Italy), in May 1991, and Silsoe (UK), in

May 1992; several papers were presented at

conferences or published in Italian or international

journals [1-6]; two working groups were created,

called WG 1, within CIGR, and SIG 12 “Education

and Communication”, within the European

Association of Agricultural Engineers (EurAgEng).

From 1990 to 1994, surveys were carried out in

several countries, in order to investigate the

organisation of the university degree study programs

or specialisations, with special regard to agricultural

engineering [7-10].

From 1996 to 1999, the surveys were updated and

extended to other countries and universities [11, 12].

In June 2000, the results of the last survey of the

study programs in agricultural engineering were

presented in the report “The University Structure and

D DAVID PUBLISHING


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Curricula on Agricultural Engineering. An overview

of 36 Countries”, published by the Food and

Agriculture Organization of the United Nations (FAO);

this work was presented in July 2000, during the

EurAgEng Conference, held in Warwick (UK) [13].

1.2 Towards a European Standard for Agricultural

Engineering Curricula

In 2001, the working package 3 of the EU Socrates

thematic network for agriculture, forestry, aquaculture

and the environment (AFANet) issued the report

“Towards a European Standard for Agricultural

Engineering Curricula”, which outlines the basis for

four European core curricula:

1) 5-year diploma degree, more scientifically

oriented;

2) 3-year Bachelor degree, more

application-oriented;

3) Master’s degree, corresponding to the long term

5-year diploma degree;

4) Master’s degree, corresponding to the short term

3-year Bachelor degree.

In this report, an accreditation system is also

proposed and the European university faculties and

departments offering diplomas in agricultural

engineering, agriculture with specialisations in

agricultural engineering and engineering (agricultural

engineering courses) are listed [14].

In Europe, the beginning of the third millennium

brought a crisis in the agricultural engineering sector.

Several institutes, departments and research centres of

agricultural engineering were closed or had their staff

significantly reduced.

On the other side of Atlantic Ocean, a process of

transition from agricultural engineering into

biosystems engineering, started in the 1960s (when it

was recognised that both biomedical engineering and

agricultural engineering could perhaps be included as

disciplines of a broader biological engineering), was

in progress. Since then, several agricultural

engineering departments had modified their degree

study programs towards biological engineering

discipline and included the term “Biological

Engineering” (or similar) in the department and/or

curriculum names. This process finished in 2005,

when the American Society of Agricultural Engineers

(ASAE), after changing its name in 1993 to the

Society for the Engineering of Agriculture, Food and

Biological Systems, changed it again to the American

Society of Agricultural and Biological Engineers

(ASABE).

Meanwhile in Europe, following the above process,

with the advent of new topics (e.g., precision

agriculture, robotics, information systems for

agriculture), several departments of agricultural

engineering changed their name, course contents and

research topics towards applied biology. This trend

also led to the progressive substitution of the name

“Agricultural Engineering” with “Bio-Engineering” or

“Biosystems Engineering”. In order to take into

account this trend, in 2002, EurAgEng changed the

name of its official journal from “Journal of

Agricultural Engineering Research” to “Biosystems

Engineering”.

In agricultural engineering study programs, the

learning outcomes (knowledge, competencies and

skills) of many courses are integrated with each other,

so that graduates can:

develop new technologies and materials, in order

to improve the quality and reliability of agricultural

products;

plan field operations with high energy efficiency;

control electronically agricultural production;

design environmental structures and systems;

develop efficient technologies for processing

agricultural products.

In several European countries (e.g., Italy), the

university study programs in agricultural engineering

show a high variability of curriculum structure and

course contents. Often, they are a specialisation of a

degree in agricultural sciences rather than a specific

study program in agricultural engineering, so that the


3

engineering learning outcomes are limited and,

therefore, the graduates are agronomists rather than

agricultural engineers.

The third millennium also brought the new structure

of the study programs (3 + 2) (1st cycle or 3-year

Bachelor, 2nd cycle or 2-year Master), according to

the Bologna Declaration of 1999. Several EU

countries felt the need to update all the university

study programs, including those in agricultural

engineering, in order to satisfy the general economic

conditions, the scientific and technological

development and the need to develop competitive

study programs.

1.3 A European Thematic Network on Agricultural

Engineering

From the above background, the need to establish a

European thematic network on agricultural

engineering was felt, as it is described in the report of

AFANet-Working Package 3.

Therefore, the idea of carrying out, at European

level, a project aimed at developing basic core

curricula, to be used as benchmarks for local

development of agricultural engineering and for

training future agricultural engineers, was born.

In 2002 the thematic network University Studies of

Agricultural Engineering in Europe (USAEE),

comprising 31 institutions from 27 European countries,

was established with the aim of developing this

project, approved and supported by EurAgEng

through the SIG RD12, and funded by the

Socrates-Erasmus EU programme.

The main objectives of USAEE-TN were to:

define and develop core curricula of 1st and 2nd

cycles, to be used as benchmarks for agricultural

engineering studies in Europe;

determine a set of minimum criteria/requirements,

against which any curriculum can be tested, in order to

decide whether it meets these criteria/requisites and,

therefore, can be recognised as a program in

agricultural engineering;

define common accreditation procedures, also in

terms of European Credit Transfer System (ECTS)

credits, and establish the bodies/committees for

carrying out these procedures.

In order to be recognised, a core curriculum must

meet both the criteria of the European Federation of

the National Associations of Engineers (FEANI) for

an engineering study program, concerning the basic

engineering course contents and the related ECTS, and

the criteria of EurAgEng, concerning the agricultural

and biological course contents and the related ECTS

[15].

In 2005, the USAEE-TN produced the draft report

“Core Curricula of Agricultural/Biosystems

Engineering for the First Cycle Pivot Point Degrees of

the Integrated M.Sc. or Long Cycle Academic

Orientation Programs of Studies”.

In this report, it is recognised that the weak area of

agricultural engineering studies in Europe is the

inadequate engineering foundation of the

corresponding curricula. Therefore, the main

challenges are to:

enhance the engineering part of the European

core curricula, so that they meet the FEANI criteria

for engineering study programs;

significantly reduce the agricultural and/or

biological sciences part of the core curricula.

In several European countries, intermediate 3-year

degree study programs, named “pivot point”, were

established, in order to facilitate the exchange of

students between universities and countries. These

study programs are different from those “relevant for

the job market”, defined by Bologna Declaration.

The degree study programs should be adapted to the

Bologna Declaration Scheme and coexist with the new

intermediate 3-year “pivot point” degree study

programs (Bachelor’s Science), according to the

history, industrial and social conditions, and the

traditions of each country.

The main challenge is to agree on a set of minimum

standards for core curricula and to clearly describe the


4

criteria to be used for professional and academic

applications. In this respect the work carried out by

the Thematic Network Enhancing Engineering

Education in Europe (E4), run by the University of

Florence in cooperation with the European Society for

Engineering Education (SEFI) and other organisations,

is relevant. Therefore, from the outset the USAEE-TN

established strong collaboration with both SEFI and

E4 TN towards common objectives.

In the first step of the development of agricultural

engineering core curricula, the 1st study cycle was

examined and two different schemes were defined and

focused in a draft report.

Scheme A, with academic orientation, consists of:

core curricula of integrated 5-year degree study

programs (M.Sc.);

core curricula of “pivot-point” 1st cycle 3-year

degree study programs (B.Sc.).

Scheme B, with application-technological orientation,

is represented by the core curricula of professional 1st

cycle (mostly 3-year) degree study programs.

This report contains not only the core curricula (Fig.

1), but also seven modules or specialisations in

agricultural engineering:

Water Resources Engineering;

Mechanical Systems and Mechanisms used in

Agricultural and Bioprocess Engineering (Tables 1

and 2);

Structural Systems and Materials in Agricultural

and Bioprocess Engineering;

Waste Management in Agricultural and

Bioprocess Engineering;

Bioprocessing;

Energy Supply and Management in Agricultural

and Bioprocess Engineering;

Information Technology and Automation in

Agricultural and Bioprocess Engineering.

In September 2004, this draft report was distributed

to the Executive Committees of FEANI and

EurAgEng for evaluation and comment. At the end of

2005, the European Monitoring Committee (EMC) of

FEANI assessed this draft and, then, requested some

modifications:

to explain the contents of “general” within basic

sciences;

to specify the number of ECTS of mathematics

(which must be at least 24);

to specify the percentage of engineering basic

sciences (which must be at least 20% and 36 ECTS)

of the study program;

to provide all the seven specialisations with at

least 60% of engineering subjects;

Fig. 1 Agricultural engineering core curricula of 1st cycle “pivot point” integrated degree study programs (3 + 2) and 5-year degree study programs with academic orientation.

General courses (adopted from E4-TN) + optional courses

Engineering

Basic courses

Agricultural/BiologicalSciences

Engineering

Specialisation courses

Agricultural/Biological Sciences

Courses not included in the core curricula: needed to achieve the

University strategic objectives

31-44 %

22-28%

13-17 %

11-14%

9-11 %


5

Table 1 Proposed module or specialisation in “Mechanical Systems and Mechanisms used in Agricultural and Bioprocess Engineering” within the 1st cycle “pivot point” degree study programs.

Engineering part of the core curricula : optional courses

Agricultural/Biological Sciences part of the core curricula : optional courses

24-30 ECTS credits: equal to 13-17% of total 180 ECTS credits 16-20 ECTS credits: equal to 9-11% of total 180 ECTS credits Assuming 6 course units with 4 or 5 ECTS credits per unit, respectively, or equivalent, the learning outcomes that follow may be delivered through the following structured coursework.

Assuming 4 course units with 4 or 5 ECTS credits per unit, respectively, or equivalent, the learning outcomes that follow may be delivered through the following structured coursework.

1. Kinematics of Mechanisms 1. Crop Science and Management

2. Power Generation Engines 2. Crop Protection

3. Mechatronics 3. Agro-chemicals

4. Soil Mechanics 4. Animal Science and Management

5. Electrotechnics 5. Environmental Impact Assessment

6. Electronic Circuits

7. Instrumentation and Measurements

8. Engineering Surveying - GIS

Learning outcomes and contents follow this table; Source: USAEE-TN.

Table 2 Indicative list of agricultural engineering courses included in the proposed module or specialisation in “Mechanical Systems and Mechanisms used in Agricultural and Bioprocess Engineering”.

1. Agricultural Machinery Design

2. Farm Power Units

3. Farmstead Equipment

4. Analysis and Design of Biomachinery

5. Techniques in Precision Agriculture

6. Automatic Controls

7. Computer Control of Machines and Processes

8. Ergonomics, Health and Safety

9. Design Methods for Machines for Biosystems

10. Remote Sensing

11. Soil Erosion

12. Landscape Planning

13. Free Technical or Agricultural/Biological Electives

Source: USAEE-TN.

to specify the percentage of non-technical subjects

(which must be at least 10% of the study program).

The EMC of FEANI also implicitly required an

accreditation process for agricultural/biosystems

engineering curricula, as well as an overview of

academic and professional qualification of the

teaching staff and laboratory facilities.

EurAgEng agreed to undertake the task of

establishing the recognition process of the core

curricula.

Since it was necessary for the results of the

USAEE-TN project to be widely disseminated and

promoted, in August 2005, the dissemination proposal

submitted to the DG for Education and Culture of the

EU was selected, so that on the October 1, 2005 the

4th and last year of the USAEE-TN project, mainly

aimed at the dissemination of its results, started.

Therefore, the duration of USAEE-TN project was

four years (01/10/2002-30/09/2006).

The main outputs achieved during the USAEE-TN

dissemination year were to:

develop a web-based database, containing the

courses or modules (set of courses) of the study

programs, including the course ECTS, in order to

facilitate the recognition of the core curricula and,

therefore, promote student mobility throughout the EU

(http://sunfire.aua.gr:8080/ects/Welcome.do); this

database will be continuously updated and made

available using a specific authorisation;

enhance the USAEE web-site, by creating links

with organisations, other related thematic networks

and projects (Interuniversity Conference of

Agriculture and Related Sciences-ICA, Training &

Resources in Early Education-TREE, Archipelagos

and TUNING, etc.);

disseminate and promote the USAEE-TN results

to the wider area of higher engineering education in

Europe, through synergic activities with

TECHNO/Archipelagos on issues concerning ECTS,


6

quality assessment and employability;

disseminate and promote the USAEE-TN results

to the wider international agricultural/biosystems

engineering community outside Europe, through the

TUNING III web-site and synergic activities with

TUNING III;

disseminate the USAEE-TN results, through

contacts with student associations (in order to promote

student mobility and participation), alumni

associations (in order to promote alumni involvement),

deans, rectors, Erasmus officials, policy makers and

other academic bodies, representatives of enterprises,

companies and industries involved in agricultural

engineering;

cooperate with FEANI and, through FEANI itself,

with the major professional stakeholders in Europe,

aimed at the final approval of the core curricula

developed by USAEE-TN;

cooperate with the Accreditation of European

Engineering Programmes and Graduates (EUR-ACE)

towards a common accreditation system for the higher

engineering education in Europe, according to the

current developments of Bologna process;

organise dissemination events, at national level, to

which the national professional societies of agricultural

engineers, also representing strong national contact and

dissemination points towards the students and the

industrial and the broader non-academic sector of

agricultural engineering, will participate;

develop synergic activities (together with ICA,

SEFI, TREE, etc.), for promoting the USAEE-TN

results to academic and non-academic communities

and targeted groups, including industries and

professional societies;

support short-term student mobility, through the

participation of student associations (e.g.,

International Association of Students in Agricultural

and related sciences-IAAS, Board of European

Students of Technology-BEST) to workshops, with

contributions to presentations and proceedings, and to

the dissemination activities addressed to them, the

European market and the students of

agricultural/biosystems engineering university studies

in Europe (in synergy with the International Relations

Officers’ Network of the Association of European

Life Science Universities-IROICA) [16].

2. From Agricultural Engineering to Biosystems Engineering Curricula: ERABEE-TN

In November 2005, the same partners of

USAEE-TN, and others, proposed a new thematic

network, aimed at using and developing the results

achieved through the previous project.

Thus, in 2007 the thematic network Education and

Research in Biosystems Engineering in Europe

(ERABEE), comprising 35 institutions from 27

Erasmus countries, of which 33 were higher education

area institutions and two were student associations,

was established with the aim of developing this

project, co-funded by EU, under the umbrella of the

Lifelong Learning Programme-LLP

(http://www.erabee.aua.gr).

The objectives of ERABEE-TN project were to:

promote the transition from agricultural

engineering to biosystems engineering;

establish the recognition procedures of the new

European study programs in biosystems engineering

by FEANI and EurAgEng, based on the core curricula

of the first two cycles developed by USAEE-TN;

enhance the compatibility between the new

European study programs in biosystems engineering,

in order to promote their recognition and accreditation,

in synergy with EUR-ACE and in support of the

establishment of European Quality Labels in

bio-engineering;

organise case studies of the implementation of

new European study programs in biosystems

engineering, based on the core curricula of the first

two cycles developed by USAEE-TN, aimed at

recognition by FEANI and EurAgEng;

“map” and promote the 3rd cycle University


7

study programs and the European doctorate in

biosystems engineering, following the recognition by

FEANI and EurAgEng, through the implementation of

the core curricula of the first two cycles developed by

USAEE-TN;

develop synergies for strengthening the link

between research and education in all three cycles of

the university studies (above all in the 3rd cycle) in

biosystems engineering in Europe;

promote the adoption of European Standards on

quality assessment and assurance of European study

programs in biosystems engineering, in accordance

with the emerging European Qualifications

Framework (EQF);

enhance the attractiveness of European study

programs in biosystems engineering, both within and

outside Europe;

promote the mobility of researchers and students

within the EU;

implement the main lines of TUNING, based on

the outcomes of USAEE-TN.

The beneficiary target groups of ERABEE-TN

project are:

universities offering biosystems engineering

graduate and postgraduate studies;

graduates in biosystems engineering, professional

societies, companies and enterprises involved in

agricultural production and processing, the industry

and market in the field of the technical support of

agriculture, etc.;

European and national accreditation bodies,

policy-makers, ministries of education and the

academic society of higher education in Europe;

students, scholars and researchers from regions

outside Europe;

other related disciplines, associations and

thematic networks in synergy with ERABEE-TN

itself.

The main achievements of the ERABEE project, in

each partner country, were to:

define the emerging biosystems engineering

discipline in Europe by describing the situation;

describe the current situation and perspectives of

the development of biosystems engineering study

programs towards the areas of bio-fuels, bio-materials

and quality of products;

describe the current schemes and the possible

structured study programs of the 3rd cycle university

studies in agricultural engineering and in the emerging

discipline of biosystems engineering;

describe the research activities in the first two

cycles of biosystems engineering university studies;

describe the infrastructures for the quality

assessment and accreditation of biosystems

engineering university studies;

describe the tools for enhancing the attractiveness

of European study programs in biosystems

engineering [17-22].

The duration of ERABEE-TN project was three

years (01/10/2007-30/09/2010).

3. A Case of EU-US Cooperation in Biosystems Engineering Curricula: POMSEBES

During the ERABEE-TN project, from 01/11/2006

to 31/10/2008, the consortium Policy Oriented

Measures in Support of the Evolving Biosystems

Engineering Studies in USA-EU (POMSEBES) was

established (http://www.pomsebes.aua.gr).

The project of this consortium, comprising 12

higher education area institutions, of which eight are

from the EU and four from the USA, was funded by

the European Commission, jointly with the US

Department of Education, Fund for the Improvement

of Post Secondary Education (FIPSE), under the

programme “Actions for Transatlantic Links and

Academic Networks for Training and Integrated

Studies” (ATLANTIS), in the framework of the

2006-2013 EU-US Agreement in higher education and

vocational training.


8

The objectives of the POMSEBES project, which

were mostly achieved, were to:

provide a platform for a systematic exchange of

experiences and ideas between the USA and the EU,

in order to contribute to the enhancement of the

quality and linkage of research and education and to

establish appropriate policy oriented measures, i.e.,

the development of biosystems engineering study

programs including strong basic engineering

courses/topics and disseminating these courses into

other study programs in (applied) biological sciences,

in order to open engineering concepts to the

appropriate students;

develop appropriate degree study programs in

biosystems engineering, whereas the relationship

between the quality of these curricula and the learning

outcomes and core abilities of students can be

established and encouraged by EUR-ACE in the EU

and the Accreditation Board for Engineering and

Technology (ABET) in the USA, respectively;

encourage compatible study programs, within the

EU as well as between the EU and the USA, through a

systematic comparison of curricula, aimed at a

standard definition of basic courses, clarification of

areas of application and a common definition of

student course load.

4. Conclusions

At present the harmonisation process of

agricultural/biosystems engineering degree study

programs in Europe benefits from the results of the

projects of USAEE and ERABEE thematic networks.

The main outcomes of USAEE-TN were to: define

and develop core curricula of 1st and 2nd cycles, to be

used as benchmarks for degree study programs in

agricultural engineering in Europe; develop a

web-based database (which will be continuously

updated) containing the courses or modules of the

above study programs, in order to facilitate

recognition of the core curricula and, therefore,

promote student mobility throughout the EU.

The highest achievements of ERABEE-TN, which

developed the results of USAEE-TN, were to:

promote the transition from agricultural engineering to

biosystems engineering, including the areas of

bio-fuels, bio-materials and quality of products;

establish the recognition procedures of new European

study programs in biosystems engineering by FEANI

and EurAgEng, based on the core curricula developed

by USAEE-TN; promote the mobility of researchers

and students within the EU, as a consequence of the

development of compatible study programs in

biosystems engineering and the enhancement of their

attractiveness.

Another important contribution towards the

harmonisation of the European curricula in

agricultural/biosystems engineering was achieved

through the cooperation between EU and US higher

education area institutions, during the project of

POMSEBES consortium.

However, the above process is still in progress and

will also be performed through the dissemination

activities of ERABEE-TN and future projects, which

will be submitted to the EU by the partners in this

network.

References

[1] G. Pellizzi, P. Febo, Degree study programs in agricultural sciences in EC cuntries, Conference “Lo studio e l'insegnamento agrario superiore nella prospettiva dell'Europa integrata” (A higher level of education in agriculture in an integrated Europe), Pisa, La rivista de il dottore in scienze agrarie e forestali 6 (1991) 11-17. (in Italian)

[2] G. Pellizzi, P. Febo, Academic organization of degrees in agriculture and agricultural engineering in EC and European Nordic Countries, “International Symposium Europe-USA: New frontiers in Science and Engineering in a European perspective”, Parigi (France) (1991) 1-20.

[3] G. Pellizzi, P. Febo, Agricultural Engineering university curricula: Results of a survey carried out in 25 countries, International Seminar on “Technological Education (T.E.) Technical and Vocational Education (T.V.E.)”, Teheran (Iran) (1994) 1-11.

[4] G. Pellizzi, P. Febo, The CIGR project for the harmonization of Agricultural Engineering university curricula, European Journal of Agricultural Education


9

and Extension 1 (3) (1994) 59-68. [5] P. Febo, S.M. Ward, Harmonization of university

curricula in Agricultural Engineering International

Conference on “Agricultural and Biological Engineering:

new horizons, new challenges”, Newcastle (UK), 1995.

[6] P. Febo, The agricultural engineering courses in the new curricula, comparisons among the Italian faculties of agriculture and some foreign Universities, Rivista di Ingegneria Agraria 2 (1998) 117-122. (in Italian)

[7] G. Pellizzi, P. Febo, Survey on the University Structure

and Curricula of Agricultural Engineering in the EC

Countries (1st contribution), CIGR, International

Commission of Agricultural Engineering, Milan, 1990,

1-61.

[8] G. Pellizzi, P. Febo, Survey on the University structure and curricula of Agricultural Engineering in the EC countries (2nd draft), CIGR, International Commission of Agricultural Engineering, Milan, 1991, pp. 1-78.

[9] G. Pellizzi, P. Febo, The University structure and curricula on Agricultural Engineering in the European Community and Scandinavian Countries, CIGR, WG Report Series n. 1 (1991) 1-112.

[10] G. Pellizzi, P. Febo, The University structure and curricula on Agricultural Engineering, An overview of 25 countries, CIGR WG Report Seriesn. 2 (1994) 1-175.

[11] P. Febo, D.W. Sun, Report of CIGR WG1 and EurAgEng

SIG 12 meeting on “Harmonisation of Agricultural

Engineering University Curricula”, CIGR Newsletter,

1997, p. 37.

[12] P. Febo, D.W. Sun, CIGR-WG1 and EurAgEng-SIG12 “Harmonisation of Agricultural Engineering University Curricula”, Progress Report, CIGR Newsletter, 1998, P. 43.

[13] P. Febo, D.W. Sun, The University Structure and Curricula on Agricultural Engineering, An overview of 36 Countries, FAO, CIGR, EurAgEng, 2000, pp. 1-236.

[14] D. Briassoulis, H. Papadiamandopoulou, B.S. Bennedsen,

Towards a European Standard for Agricultural

Engineering Curricula, AFANet; Workpackage 3;

Agricultural Engineering, KVL, AgroTechnology,

Agrovej 10, DK-2630 Taastrup, Denmark, 2001, pp.

1-44.

[15] A. Comparetti, P. Febo, G. Scarascia Mugnozza, S. Orlando, The Thematic Network on the University Studies of Agricultural Engineering in Europe (USAEE), Seminar “Prospettive Europee di Studi Universitari in Ingegneria per l’Agricoltura, l’Alimentazione ed il Territorio Rurale” (European Perspectives of University

Studies in Engineering for Agriculture, Food and Rural Land), Roma, 15 Dicembre 2004. Rivista di Ingegneria Agraria, 1 (2005) 93-96. (in Italian)

[16] P. Febo, Agricultural Engineering curricula: Past, present and future, 34th International Symposium “Actual tasks on Agricultural Engineering”, Opatija, Croatia, Feb. 21-24, 2006.

[17] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Definition of the emerging Biosystems Engineering discipline in Europe: The current situation in Italy, in:

Proceedings of the 1st ERABEE WorkshopEducation

and Research in Biosystems Engineering in EuropeA

Thematic Network, Madrid, Spain, Apr. 3-4, 2008, pp. 82-86.

[18] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Develop Biosystems Engineering study programs towards bio-fuels, bio-materials and quality of products: Current situation and perspectives in Italy, in: Proceedings of the

2nd ERABEE WorkshopEducation and Research in

Biosystems Engineering in EuropeA Thematic

Network. Dublin, Ireland, Oct. 13-14, 2008, pp. 79-88. [19] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Third

cycle University studies in Italy: Current schemes and possible structured study programs in Agricultural Engineering and in the emerging discipline of Biosystems Engineering, in: Proceedings of the 3rd ERABEE Workshop, Education and Research in Biosystems Engineering in Europe, A Thematic Network, Uppsala, Sweden, May 4-5, 2009, pp. 111-119.

[20] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Research activities in the first two cycles of Italian Biosystems Engineering University studies, in: Proceedings of the 4th ERABEE Workshop, Education and Research in Biosystems Engineering in Europe, A Thematic Network, La Valletta, Malta, Nov. 16-17, 2009, pp. 98-103.

[21] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Quality assurance and assessment frameworks of Italian Biosystems engineering studies, in: Proceedings of the 5th ERABEE Workshop, Education and Research in Biosystems Engineering in Europe, A Thematic Network, Prague, Czech Republic, Apr. 29-30, 2010, pp. 90-94.

[22] A. Comparetti, P. Febo, G. Scarascia Mugnozza, Enhancing the attractiveness of Italian study programs in Biosystems Engineering, in: Proceedings of the 6th ERABEE Workshop, Education and Research in Biosystems Engineering in Europe, A Thematic Network. Clermont-Ferrand, France, Sept. 9-10, 2010, pp. 85-93.


Effect of Biofertilizer on Biomass Productivity, Nutrient

Balance and Soil Fertility in Rainfed Organic Ginger

Production System

Nongmaithem Jyotsna1, Mainak Ghosh2, Dulal Chandra Ghosh3, Wahengbam Ingo Meitei1 and Jagadish Timsina4

1. College of Agriculture, Central Agricultural University Imphal, Manipur 795001, India

2. Department of Agronomy, Bihar Agricultural University, Sabour 813210, Bihar, India

3. Institute of Agriculture, Visva-Bharati, Sriniketan 731236, West Bengal, India

4. IRRI-Bangladesh Office, Banani DOHS, Dhaka 1206, Bangladesh

Received: November 13, 2012 / Published: January 20, 2013.

Abstract: Farmers of North-Eastern India grow ginger organically and obtain low yield. Biofertilizer may help in increasing yield and maintaining soil fertility. An investigation made with different biofertilizers showed that seed treatment with biofertilizer increased biomass by 18.3%, enhanced N, P and K removal and improved short-term soil fertility status by increasing N and P balance and reducing negative K balance over control plots. Use of high dose (5.0 kg ha-1) of Azotobacter (a3) and medium dose (3.75 kg ha-1) of both Azospirillum (b2) and Phosphotica (c2) increased rhizome biomass by 6.8%-12.5% and shoot biomass by 5.6%-14.3% over other levels. They enhanced N, P and K removal by both rhizome and shoot when compared with other levels. The above biofertilizer treatments improved organic carbon and available N and P status of the soil by increasing N and P balance. The result showed overall strong negative K balance; but biofertilizer treatments greatly reduced the negative K balance in soil as compared to the control plots. Seed treatment with high level of Azotobacter along with medium level of Phosphotica (a3c2) produced the highest biomass yield (7.4 t ha-1), increased N and P balance and fertility status in spite of high N, P and K removal. Key words: Biofertilizer, ginger productivity, nutrient balance, soil fertility.

1. Introduction

Ginger (Zingiber officinale Rosc.) is an aromatic

spice crop grown in almost all the states of the

North-Eastern region of India. The climatic condition

of the region is highly suitable for cultivation of

ginger [1]. It is the main cash crop supporting the

livelihood and improving the economic level of many

ginger growers in the region. However, it is a heavy

feeder and an exhaustive crop, and requires large

quantities of manures and fertilizers for its proper

growth and development. Inorganic fertilizers besides

being costly are causing problems to the ground water

Corresponding author: Jagadish Timsina, Ph.D., research

field: agronomy. E-mail: [email protected].

and environment as well as quality of the produce.

Majority of the farmers in the region involved in

ginger production can not afford to purchase the

fertilizers. The ginger production in the region is

organic by default because the farmers only apply the

locally available farmyard manures and do not apply

any chemical fertilizers or pesticides to ginger crop [2].

In this way, the ignorance of the farmers about the

technological advances is turning out to be a key to

prosperity because of increasing demand for organic

produce all over the world [3].

Organic farming has attracted increasing attention

among our environmental protectionists, improving

quality and reorientation of agriculture towards areas

of market demands [4]. The beneficial effects of

D DAVID PUBLISHING

Effect of Biofertilizer on Biomass Productivity, Nutrient Balance and Soil Fertility in Rainfed Organic Ginger Production System

11

organic manures are manifested through increase in

soil organic matter and humus over the period. Soil

organic matter and humus act in several ways. They

serve as slow release source of plant nutrients to the

crops, increase water holding capacity of the soil and

act as a buffer against change in soil pH [5]. However,

ginger cultivated with only organic manures, though

has the potential to improve rhizome quality, is unable

to obtain high yield. In recent years, biofertilizers have

emerged as a promising source of nutrient supply in

organic agriculture [6]. Biofertilizers, being essential

components of organic farming, play vital role in

improving the soil nutrient supplying capacity and

maintain soil fertility and sustainability by fixing

atmospheric dinitrogen (N2) and mobilizing fixed

macro- and micro-nutrients [7]. They are also

responsible for converting insoluble P in the soil into

forms available to plants and producing plant growth

hormones and vitamins by microorganisms thereby

increasing their efficiency and availability [8, 9].

Azotobacter, Azospirillum and Phosphotica are found

very important in soil nutrient supply system and

enhance atmospheric N2 fixation, mineralization and

mobilization of plant nutrients due to greater

microbial activities and thereby increasing the nutrient

removal by the crop [10]. Son et al. [11] also noticed

that application of organic and biofertilizers together

in rice-soybean-rice cropping system increased N, P,

and K uptake by the crop and maintained higher level

of organic carbon and available N, P and K of the soil

as compared to only inorganic fertilizers. The soils of

the North-Eastern region are acidic to strongly acidic

due to leaching of bases owing to high rainfall (>

2,000 mm). The low availability of P due to fixation

as Fe/Al- complex is the major problem of crop

production in the region [1]. Biofertilizers like P

solubilizing bacteria (PSB), Azotobacter and

Azospirillum may be useful for improving P and N

nutrition to the crops [11, 12]. Organic manures and

biofertilizers not only improved crop nutrition, but

also increases nutrient removal by the crop and

improved organic carbon and available N, P and K

contents in soil through greater microbial activities

[13, 14]. However, information in detail about the

effect of different biofertilizers on biomass

productivity, nutrient removal, nutrient balance and

soil health are limited particularly in ginger

production in the North-Eastern region of India.

Keeping this idea in view and considering the

importance of the problem, an effort has been made to

study the effect of different biofertilizers (Azotobacter,

Azospirillum and Phosphotica) on biomass

productivity, nutrient removal, nutrient balance and

soil fertility status in rainfed organic ginger

production system in the North-Eastern region of

India.

2. Materials and Methods

2.1 Experimental Site

The field experiment was conducted during 2007

and 2008 at the Horticulture Experimental Farm,

College of Agriculture, Central Agricultural

University, Imphal, Manipur. The place is located at

24°45′N latitude, 93o56′E longitude with an altitude of

790 m above mean sea level. The experimental soil

was acidic in reaction (pH 5.5), clayey in texture

(15.5% sand, 21.2% silt and 61.1% clay), medium in

fertility (230, 13.3 and 267 kg ha-1 available N, P and

K, respectively), well-drained with gentle slope. The

experimental site comes under warm humid moist

region where monsoon normally starts from April and

extends up to September. The weather conditions

during the two years of study are provided in detail in

a companion paper [15]. The crop was grown on

rainfed condition. Briefly, stated, the crop received

1,341 and 1,207 mm rainfall during its growing period

in 2007 and 2008, respectively. The maximum

temperature ranged from 24.1 to 29.6 °C, while the

minimum temperature ranged from 9.6 to 22.5 °C

during the cropping seasons. The relative humidity of

the cropping season varied from 58.5% to 84.7% in

2007 and 58.9% to 88.5% in 2008. Both temperature


12

and relative humidity remained very conducive for

growth and rhizome productivity of ginger.

2.2 Experimental Details

The experiment was laid out in complete

randomized block design with three biofertilizers each

at three levels along with a common control (no use of

biofertilizer) in three replications in 3.6 m 3.0 m

plots. The three levels of three biofertilizers are (1)

Azotobacter at 3 levels (2.5, 3.75 and 5.0 kg ha-1); (2)

Azospirillum at 3 levels (2.5, 3.75 and 5.0 kg ha-1) and

(3) Phosphotica at 3 levels (2.5, 3.75 and 5.0 kg ha-1).

Altogether, there were 28 treatment combinations. The

treatment details for this study are presented in a

companion paper [15]. Briefly stated, culture solutions

of different biofertilizers were prepared by dissolving

10 g, 15 g and 20 g of each biofertilizer and their

combinations in 500 mL of water separately for each

biofertilizer treatment. Thus, a total of 27 biofertilizer

culture solutions were prepared. Each biofertilizer

treatment (culture solution) was mixed thoroughly

with 8 kg ginger setts (required for each treatment) of

variety Bhaisey and dried in shade before planting.

The rhizomes (20 g sett) were planted on March 16,

2007 and March 18, 2008 with a spacing of 30 cm

30 cm in 3.6 3.0 m plots. A general dose of 20 t

FYM ha-1 containing 0.50% N, 0.133% P and 0.55%

K was applied during land preparation. The crop

received hand weeding twice along with light earthing

up on May 25 and July 14 in 2007 and May 27 and

July 16 in 2008. No chemical fertilizer, pesticide and

irrigation water was applied under this investigation.

2.3 Shoot and Rhizome Biomass

Five clumps from each plot were collected at 210

days after planting (DAP) for determination of dry

matter yield (DMY) and its partitioning. The plant

samples were cleaned and washed in water to remove

surface contamination and separated into shoot (leaves

+ stem) and rhizome. Fresh weight of rhizome of each

plot was recorded and converted into g m-2. A piece of

rhizome of each plot was taken; its fresh weight was

recorded before chopping. Thereafter, shoot and

chopped rhizome were kept in separate paper packets

which in turn were placed in an oven for drying at

65-70 °C till constant weight was obtained. The dry

weight of shoot (shoot biomass) and rhizome (rhizome

biomass) were recorded. The sum of shoot biomass

(SB) and rhizome biomass (RB) was the total biomass

(TB). Biomass partitioning (BP) was estimated as: BP

= RB (kg ha-1)/TB (kg ha-1) 100, and expressed in

percentage. The crop was harvested on November 12

in 2007 and November 14 in 2008 when the leaves

turned yellow and started drying up. Fifty clumps

from each plot were lifted carefully with the help of a

spade and the rhizomes were separated and kept in

shade for two days. The fresh weight of rhizome was

recorded in t ha-1.

2.4 Nutrient Removal and Soil Fertility

Plant samples (shoot and rhizome) collected at

maturity were oven dried and ground properly for N,

P and K determination in the laboratory following

micro-kjeldahl, spectrophotometer and flame

photometer methods respectively as described by

Jackson [16]. N, P and K removal by shoot and

rhizome were then estimated by multiplying shoot and

rhizome dry weights with their respective N, P and K

contents. Soil samples collected from 0-15 cm depth

before start of the experiment and after harvest of 2nd

year of ginger were used for determining organic

carbon (OC) following Walkley and Black method

[17], available N by alkaline potassium permanganate

method [18], available P by Bray’s method [19] and

available K by ammonium acetate extraction method

[16]. The data were used for determining N, P and K

balances and fertility status of the experimental soil.

2.5 Data Analysis

All data were analyzed statistically following the

standard procedure as described by Gomez and

Gomez [20]. The data were tested for analysis of


13

variance and least significant difference (P = 0.05) to

compare the effect of biofertilizer treatments on

biomass productivity, nutrient content and nutrient

removal by ginger crop, nutrient balance and soil

fertility status were calculated for various treatments.

The interaction effects were presented wherever they

were significant.

3. Results and Discussion

3.1 Biomass Productivity and Partitioning

Biomass productivity of ginger is a function of

growth and development of the crop during its

growing period. Seed treatment with biofertilizers

exerted significant effect on rhizome biomass (RB),

shoot biomass (SB) and total biomass (TB)

productivity of ginger during both years. Biofertilizers

increased RB by 17.6% to 19.5%, SB by 17.8% to

18.3% and TB by 17.7% to 18.9% over control but

biomass partitioning (BP) did not differ among the

different treatments in either of the two years. The RB,

SB and TB increased gradually with increase in each

level of Azotobacter up to 5.0 kg ha-1 (a3) during both

the years (Table 1). It increased RB, SB and TB by

12.5%, 14.3% and 12.9% of over the low level and by

8.6%, 10.3% and 9.3% of RB, SB and TB over the

medium level. The biomass productivity of ginger

between medium and low levels of Azotobacter

application did not vary significantly in either of the

two years. The seed treatment with Azospirillum and

Phosphotica also markedly influenced the biomass

productivity of ginger. The RB, SB and TB increased

significantly due to application of medium level (3.75

kg ha-1) of Azospirillum (b2) and Phosphotica (c2)

over their lower and higher levels during both years

(Table 1). Application of medium level of

Azospirillum increased RB, SB and TB by 8.6%, 10.6%

Table 1 Effect of biofertilizer on biomass yield and its partitioning in ginger.

Particulars Biomass yield (kg ha-1) Biomass partitioning (%)

Rhizome biomass Shoot biomass Total biomass

2007 2008 2007 2008 2007 2008 2007 2008

Control 3,095 3,122 2,653 2,612 5,748 5,734 53.8 54.3

Treatment 3,697 3,673 3,138 3,078 6,835 6,751 54.1 54.4

S. Em (±) 164 154 152 164 245 231 0.98 0.92

LSD 0.05 465 435 431 465 739 696 NS NS

Azotobacter

a1 3,515 3,482 2,966 2,897 6,481 6,379 54.2 54.6

a2 3,631 3,612 3,068 3,013 6,699 6,625 54.2 54.5

a3 3,944 3,924 3,380 3,324 7,324 7,248 53.9 54.1

S. Em (±) 56 51 51 55 82 75 0.33 0.31

LSD 0.05 158 145 144 155 231 214 NS NS

Azospirillum

b1 3,567 3,546 3,005 2,954 6,572 6,500 54.3 54.6

b2 3,878 3,852 3,332 3,258 7,210 7,110 53.8 54.2

b3 3,645 3,620 3,077 3,021 6,722 6,642 54.2 54.5

S. Em (±) 56 51 51 55 82 75 0.33 0.31

LSD 0.05 158 145 144 155 231 214 NS NS

Phosphotica

c1 3,604 3,582 3,051 2,988 6,655 6,570 54.2 54.5

c2 3,846 3,824 3,277 3,224 7,123 7,048 54.0 54.3

c3 3,639 3,612 3,086 3,021 6,726 6,634 54.1 54.5

S. Em (±) 56 51 51 55 82 75 0.33 0.31

LSD 0.05 158 145 144 155 231 214 NS NS

a = Azotobacter; b = Azospirillum; c = Phosphotica; doses of biofertilizer 1, 2 and 3are 2.5, 3.75 and 5.0 kg ha-1, respectively.


14

and 9.6% over its low level and by 6.4%, 8.0% and

7.2% over its high level. Similarly seed treatment with

medium level of Phosphotica increased RB, SB and

TB by 6.8%, 7.6% and 7.2% over its low level and by

5.8%, 6.5% and 6.1% over its high level. Seed

treatment with Azotobacter and Phosphotica exerted

significant interaction effect on biomass productivity

of ginger. The highest RB, SB and TB were recorded

with the use of high level (5.0 kg ha-1) of Azotobacter

along with medium level (3.75 kg ha-1) Phosphotica

(a3c2) and was significantly higher over other

combinations except for the combinations of high

level of Azotobacter with other levels of Phosphotica

(Table 2). Application of low level of both

biofertilizers was found less efficient resulting in the

lowest biomass productivity of ginger. The increased

shoot and rhizome biomass by biofertilizer use might

be due to higher availability and efficient use of plant

nutrients throughout the growing period as a result of

greater microbial activities [10]. Increased biomass

productivity could be attributed to increase in shoot

and rhizome biomass resulting from higher fixation of

atmospheric N, dissolution of insoluble phosphates in

soil to soluble forms and production of plant growth

hormones and vitamins by microorganisms [21-23].

3.2 Nutrient Removal

The nutrient removal varied widely between

rhizome and shoot of ginger. While N removal shared

equally by rhizome and shoot, the P and K removal

were markedly higher in rhizomes when compared

with shoot. Seed treatment with biofertilizer exerted

significant effect on N, P and K removal by both

rhizome and shoot, and thus, recorded higher N, P and

K removal by 26.7%, 43.3% and 33.0%, respectively

over those of the control plots. The N, P and K

removal increased steadily and significantly as the

level of Azotobacter seed treatment increased and the

highest N, P and K removal by rhizome and shoot was

obtained at high dose of Azotobacter treatment (a3),

and was significantly higher than those obtained at its

medium (a2) and low (a1) levels (Table 3).

Accordingly, seed treatment with high level of

Azotobacter removed N, P and K by 16.3%, 10.1%

and 12.4% higher over its low level and 9.8%, 7.7%

and 9.2% higher over its medium level. The medium

dose of Azotobacter also showed higher N and K

removal by the crop than those obtained at its lower

level. Seed treatment with Azospirillum and

Phosphotica also exerted marked effect on N, P and K

removal by ginger. Use of medium level of both the

biofertilizers removed significantly higher N, P and K

by both rhizome and shoot over their other levels

(Table 3). Medium level of Azospirillum (b2) removed

higher N, P and K by 10.2%, 12.2% and 9.2% over its

low level (b1) and 6.9%, 9.2% and 6.6% over its high

level (b3), respectively. Similarly medium dose of

Phosphotica treatment (c2) removed 8.4%, 13.8% and

8.5% higher N, P and K, respectively over its low

level (c1) and 6.0%, 10.5% and 8.2% more than those

of its high level (c3). Seed treatment with Azotobacter

and Phosphotica exerted significant interaction effect

on N, P and K removal by rhizome, shoot and total

removal by the crop. The highest N, P and K removal

Table 2 Interaction effect of Azotobacter and Phosphotica (axc) on rhizome, shoot, and total biomass productivity of ginger (average of 2 years data).

Phosphotica c1 c2 c3 c1 c2 c3 c1 c2 c3

Azotobacter Rhizome biomass (RB) (kg ha-1) Shoot biomass (SB) (kg ha-1) Total biomass (TB) (kg ha-1)

a1 3,373 3,715 3,408 2,818 3,123 2,854 6,191 6,839 6,262

a2 3,522 3,798 3,545 2,937 3,220 2,964 6,459 7,018 6,509

a3 3,884 3,991 3,925 3,303 3,409 3,343 7,187 7,400 7,268

S Em (+) 76.1 83.1 142.3

LSD 0.05 215.8 235.6 403.4

a = Azotobacter; c = Phosphotica; doses of biofertilizer 1, 2 and 3 are 2.5, 3.75 and 5.0 kg ha-1, respectively.


15

Table 3 Effect of biofertilizer on NPK removal by rhizome, shoot and total plant (average of 2 years data).

Particulars N removal (kg ha-1) P removal (kg ha-1) K removal (kg ha-1)

Rhizome Shoot Total Rhizome Shoot Total Rhizome Shoot Total

Control 39.2 39.1 78.3 9.4 4.2 13.5 69.0 46.2 115.1

Treatment 49.9 49.5 99.4 13.5 6.0 19.4 91.9 61.3 153.2

S. Em (±) 1.17 1.60 3.15 0.50 0.26 0.89 2.44 2.44 3.76

LSD 0.05 3.29 4.51 8.89 1.41 0.74 2.51 6.90 6.90 10.64

Azotobacter

a1 46.6 46.0 92.5 12.9 5.7 18.6 87.7 58.1 145.7

a2 49.3 48.7 98.1 13.2 5.9 19.1 90.2 59.9 150.1

a3 53.8 53.9 107.6 14.2 6.4 20.5 97.9 66.0 163.8

S. Em (±) 0.67 0.54 1.05 0.17 0.09 0.30 0.82 0.62 1.26

LSD 0.05 1.90 1.50 2.96 0.47 0.25 0.84 2.30 1.70 3.55

Azospirillum

b1 47.9 47.3 95.2 12.9 5.7 18.5 88.8 58.8 147.5

b2 52.4 52.5 104.9 14.4 6.5 20.7 96.2 64.8 161.0

b3 49.4 48.7 98.0 13.2 5.9 19.0 90.8 60.3 151.1

S. Em (±) 0.67 0.54 1.05 0.17 0.09 0.30 0.82 0.62 1.26

LSD 0.05 1.90 1.50 2.96 0.47 0.25 0.84 2.30 1.70 3.55

Phosphotica

c1 48.3 47.7 96.0 12.8 5.7 18.4 89.4 59.4 148.8

c2 52.1 52.0 104.0 14.5 6.5 20.9 96.7 64.8 161.5

c3 49.3 48.9 98.1 13.1 5.8 18.9 89.6 59.7 149.3

S. Em (±) 0.67 0.54 1.05 0.17 0.09 0.30 0.82 0.62 1.26

LSD 0.05 1.90 1.50 2.96 0.47 0.25 0.84 2.30 1.70 3.55

a = Azotobacter; b = Azospirillum; c = Phosphotica; doses of biofertilizer 1, 2 and 3 are 2.5, 3.75 and 5.0 kg ha-1, respectively.

by rhizome and shoot were recorded with the

combined use of high dose of Azotobacter with

medium dose of Phosphotica (a3c2). This treatment

combination removed the highest quantity of N

(109.5 ha-1), P (21.5 ha-1) and K (167.8 kg ha-1) and

were significantly higher than those of other

combinations except high level of Azotobacter with

high and low levels of Phosphotica (Table 4). Use of

lower doses of both Azotobacter and Phosphotica

recorded the lowest N, P and K removal (88.5, 17.5

and 140.2 kg ha-1, respectively) by the crop. The

increase in nutrient removal due to biofertilizer

inoculation could be attributed to increase in biomass

yield. The higher removal of nutrients due to

biofertilizer application could be on account of high

nutrient availability in the root zone under high

microbial activities [24]. This showed very vital role

of biofertilizer in the nutrient supply system of

organic farming [25, 26].

3.3 Nutrient Balance

Seed treatment with biofertilizer recorded

significantly greater N (20.4 kg ha-1) and P (3.3 kg

ha-1) balances than that of the control plots. The study

showed overall negative K balance; but biofertilizer

treated plots reduced the negative K balance to a great

extent (-28.5 ha-1) as compared to that of the control

plots (-45.3 ha-1). As same amount of nutrient (200 kg

N, 53.2 kg P and 220 kg K ha-1 through 20 + 20 t

FYM ha-1 in two crop cycles) was added in all the

treatments, the variation in nutrient balance was

primarily due to the variation in soil microbial

activities induced by biofertilizer treatments and

nutrient removal by the crop. N and P balance in soil

increased steadily up to the highest level of

Azotobacter treatment (a3). Accordingly the high level

of Azotobacter treatment (a3) recorded the highest N

(22.4 kg ha-1) and P (3.5 kg ha-1) balance in soil and

was markedly higher than that of its medium (a2) and


16

Table 4 Interaction effect of Azotobacter and Phosphotica (axc) on N, P and K removal (average for 2 years).

Phosphotica c1 c2 c3 c1 c2 c3 c1 c2 c3 Azotobacter N removal by Rhizome (kg ha-1) N removal by shoot (kg ha-1) Total N removal (kg ha-1) a1 44.7 49.6 45.6 43.8 49.1 44.8 88.5 98.8 90.4 a2 47.6 51.9 48.4 46.7 51.7 47.7 94.4 103.6 96.2 a3 52.5 54.7 53.9 52.6 54.9 54.0 105.2 109.5 107.8 S Em (±) 1.17 0.92 1.82 LSD 0.05 3.29 2.60 5.14 Phosphotica c1 c2 c3 c1 c2 c3 c1 c2 c3 Azotobacter P removal by Rhizome (kg ha-1) P removal by shoot (kg ha-1) Total P removal (kg ha-1) a1 12.3 13.5 13.0 5.3 6.1 5.7 17.5 19.6 18.6 a2 12.4 13.8 12.8 5.4 6.2 5.6 17.7 20.0 18.3 a3 14.1 14.9 14.0 6.3 6.7 6.3 21.0 21.5 20.3 S Em (±) 0.31 0.17 0.51

LSD 0.05 0.87 0.49 1.44

Phosphotica c1 c2 c3 c1 c2 c3 c1 c2 c3

Azotobacter K removal by Rhizome (kg ha-1) K removal by shoot (kg ha-1) Total K removal (kg ha-1)

a1 84.4 94.0 84.5 55.8 62.4 56.0 140.2 156.4 140.5

a2 87.4 95.6 87.1 57.6 64.0 57.6 145.0 159.7 144.7

a3 96.5 100.1 97.2 64.9 67.7 65.4 161.5 167.8 162.7

S Em (±) 1.41 1.22 2.18

LSD 0.05 3.98 3.45 6.18

*a = Azotobacter; c = Phosphotica; doses of biofertilizer 1, 2 and 3 are 2.5, 3.75 and 5.0 kg ha-1, respectively.

low level (a1). Seed treatment with low level of

Azotobacter (a1) was found less efficient in

maintaining N and P balance in soil. Use of

Azospirillum and Phosphotica in seed treatment also

showed positive and significant effect on N and P

balance in soil. Medium dose of both Azospirillum (b2)

and Phosphotica (c2) recorded the highest N and P

balance which were significantly greater than that

obtained at their high and low levels (Table 5). Seed

treatment with medium level of both Azospirillum (b2)

and Phosphotica (c2) greatly reduced the negative K

balance in soil. Our results showed that biofertilizer

treatments increased the N and P balance because of

high microbial activities of biofertilizer treated plots.

In spite of high N and P removal, biofertilizer showed

markedly higher N and P balance at high dose of

Azotobacter (a3) and medium dose of both

Azospirillum (b2) and Phosphotica (c2). Ginger is a

heavy K feeder crop and K supply through organic

manure (20.0 t FYM ha-1 year-1) did not match the K

demand of the crop. Biofertilizers though enhanced K

removal, yet they improved K balance over control

plots through greater microbial activities in soil. The

study clearly showed that current level of organic

manuring (FYM 20 t ha-1) was not sufficient to meet

the K requirement of ginger in the North-Eastern

region of India.

3.4 Soil Fertility

The organic carbon and available N and P of the

soil improved considerably over control due to use of

biofertilizer. The available K decreased to a great

extent in all cases as compared to its initial status; but

biofertilizer exerted favourable effect on minimizing

the depletion of soil available K as compared to that of

the control plots (Table 5). Different biofertilizer

treatments responded differently on short-term fertility

of the ginger field. The organic carbon and available

N content of the soil increased gradually due to

increasing the level of Azotobacter and application of

high dose of Azotobacter (a3) increased markedly both

organic carbon and available N over its lower levels;

but it did not influence the available P and K content

in the ginger field. Use of medium dose of Azospirillum


17

Table 5 Effect of biofertilizer on nutrient balance and fertility status of the experimental soil after 2 ginger crop cycles

Nutrient management

Organic C (%)

Nutrient added in 2 crop cycle (kg ha-1)

Nutrient removed by 2 crop cycle (kg ha-1)

Soil available nutrient after 2 crop cycle (kg ha-1)

Actual nutrient gain/loss over initial status (kg ha-1)

N P K N P K N P K N P K

Control 2.41 200.0 53.2 220.0 156.6 27.1 230.2 235.8 14.32 221.7 5.8 1.0 -45.3

Treatment 2.66 200.0 53.2 220.0 198.7 38.8 306.3 250.4 16.61 238.5 20.4 3.3 -28.5

S. Em (±) 0.07 - 6.54 1.39 9.55 4.48 0.59 4.41 1.14 0.21 1.73

LSD 0.05 0.21 - 19.75 4.19 28.85 13.50 1.80 13.30 3.46 0.65 5.22

Azotobactor level

a1 2.62 200.0 53.2 220.0 185.0 37.9 291.4 248.5 16.41 237.5 18.5 3.1 -29.5

a2 2.65 200.0 53.2 220.0 196.1 37.5 300.0 250.4 16.58 238.5 20.4 3.3 -28.5

a3 2.71 200.0 53.2 220.0 215.1 41.0 327.6 252.4 16.84 239.6 22.4 3.5 -27.4

S. Em (±) 0.02 - 2.20 0.46 3.20 1.35 0.20 1.47 0.37 0.07 0.58

LSD 0.05 0.07 - 6.20 1.31 9.00 3.80 NS NS 1.06 0.20 1.63

Azospirillum level

b1 2.64 200.0 53.2 220.0 190.1 36.9 294.9 249.0 16.48 237.7 19.0 3.2 -29.3

b2 2.69 200.0 53.2 220.0 209.7 41.5 321.9 252.9 16.76 239.5 22.9 3.5 -27.5

b3 2.66 200.0 53.2 220.0 196.3 38.0 302.1 249.4 16.59 238.2 19.4 3.3 -28.8

S. Em (±) 0.02 - 2.20 0.46 3.20 1.35 0.20 1.47 0.37 0.07 0.58

LSD 0.05 NS - 6.20 1.31 9.00 3.80 NS NS 1.06 0.20 1.63

Phosphotica level

c1 2.62 200.0 53.2 220.0 191.9 36.8 297.6 249.9 16.26 238.2 19.9 3.0 -28.8

c2 2.72 200.0 53.2 220.0 208.0 41.8 323.0 251.6 17.25 239.3 21.6 4.0 -27.7

c3 2.64 200.0 53.2 220.0 196.2 37.8 298.5 249.8 16.32 238.0 19.8 3.0 -29.0

S Em (±) 0.02 - 2.20 0.46 3.20 1.35 0.20 1.47 0.37 0.07 0.58

C D at 5% 0.07 - 6.20 1.31 9.00 3.80 NS NS 1.06 0.20 1.63

a = Azotobacter; b = Azospirillum; c = Phosphotica; doses of biofertilizer 1, 2 and 3 are 2.5, 3.75 and 5.0 kg ha-1, respectively; Initial fertility status =230, 13.3 and 267 kg N, P and K ha-1, respectively.

(b2) considerably improved the soil available N over

control and its higher and lower levels; but it had very

little effect on organic carbon and available P and K

contents of the experimental soil (Table 5). Similarly,

seed treatment with medium dose of Phosphotica (c2)

improved organic carbon and available P level of the

soil over its other levels and control plots; but it had

no effect on available N and K levels. The results

showed a sharp decrease in available K content of the

experimental soil after two ginger crop cycles in spite

of addition of 20.0 t FYM ha-1 year-1. The high K

removal by the crop was mainly responsible for the

decrease of available K level of the experimental soil

[27]. High dose of Azotobacter (a3) and medium dose

of both Azospirillum (b2) and Phosphotica (c2) were

found the most effective in improving the fertility

status of the ginger field.

4. Conclusions

Use of biofertilizer increased biomass productivity

of both rhizome and shoot, enhanced N, P and K

removal by the crop and helped in improving soil

fertility by increasing N and P balance and reducing

negative K balance over those of the control plots.

Seed treatment with Azotobacter 5.0 kg ha-1 (a3),

Azospirillum 3.75 kg ha-1 (b2) and Phosphotica 3.75

kg ha-1 (c2) increased biomass productivity of rhizome

and shoot, enhanced N, P and K removal through

rhizome and shoot as well as total removal by the crop

as compared to those of the other levels. In spite of

high N, P and K removal, biofertilizers showed

markedly higher N and P balance at high dose of

Azotobacter (a3) and medium dose of both

Azospirillum (b2) and Phosphotica (c2). The study


18

showed overall strong negative K balance; but

biofertilizer treatments greatly reduced the negative K

balance in soil as compared to the control plots. They

improved organic carbon and available N and P levels

of the soil over other treatments. Seed treatment with

high level of Azotobacter along with medium level of

Phosphotica (a3c2) produced high biomass yield (7.4 t

ha-1), removed large quantity of N, P and K from the

soil, increased soil nutrient balance and maintained

high soil fertility responsible for high crop

productivity and sustainability.

References

[1] S. Govind, R. Chandra, G.S. Karibasappa, C.K. Sharma, I.P. Singh, Research on Spices in NEH Region, ICAR Research Complex for NEH Region, Umiam, 1998, pp. 9-22.

[2] S. Angom, Effect of mulching and variety on the growth, development and yield of ginger (Zingiber officinale Rosc.) under clay soil conditions of Imphal, M.Sc. (Ag.) Thesis, Central Agricultural University, Imphal, 2000, pp. 7-10.

[3] H. Rahman, R. Karuppaiyan, K. Kishore, R. Denzongpa, Traditional practices of ginger cultivation in Northeast India, Indian Journal of Traditional Knowledge 8 (2009) 23-28.

[4] D.G. Hole, A.J. Perkins, J.D. Wilson, I.H. Alexander, F. Grice, A.D. Evans, Does organic farming benefit biodiversity?, Biological Conservation 122 (2005) 113-130.

[5] N.C. Upadhayay, J.P. Singh, The potato production and utilization in sub-tropics, in: S.M. Paul Khurana, J.S. Minhas, S.K. Pandey (Eds.), Mehta Publishers, A-16 (East), Naraina II, New Delhi-110028, India, 2003.

[6] R.S. Jat, I.P.S. Ahlawat, Direct and residual effect of vermicompost, biofertilizer and P on soil nutrient dynamics and productivity of chickpea-fodder maize sequence, Journal of Sustainable Agriculture 28 (2006) 41-54.

[7] S.S. Mahdi, G.I. Hassan, S.A. Samoon, H.A. Rather, A.D. Showkat, B. Zehra, Bio-fertilizers in organic agriculture, Journal of Phytology 2 (2010) 42-54.

[8] S.P. Mohod, D.N. Guptha, A.S. Chavan, Effect of P solubilizing organisms on yield and N uptake by rice, Journal of Maharashtra Agricultural Universities 16 (1991) 229-231.

[9] K. Raghu, I.C. Macrae, Occurrence of phosphate-dissolving microorganisms in the rhizosphere of rice plants and in submerged soils, Journal of Applied Bacteriology 29 (2000) 582-586.

[10] B.N. Korla, R.S. Rattan, N.P. Dohroo, Effect of mulches on rhizome growth and yield of ginger (Zingiber officinale Rosc.), South Indian Horticulture 38 (1990) 163-164.

[11] T.T.T. Son, V. Thu, L.H. Man, H. Kobayashi, R. Yamada, Effect of long-term application of organic and biofertilizer on soil fertility under rice-soybean-rice cropping system, Omonrice 12 (2004) 45-51.

[12] K.S. Arun, Bio-fertilizers for sustainable agriculture, in: Mechanism of P-solubilization, 6th ed., Agribios publishers, Jodhpur, India, 2007, pp. 196-197.

[13] R. Prasanna, P. Jaiswal, Y.V. Singh, P.K. Singh,

Influence of biofertilizers and organic amendments on

nitrogenase activity and phototrophic biomass of soil

under wheat, Acta Agronomica Hungarica 56 (2008)

149-159.

[14] M. Kumar, L.K. Baishya, D.C. Ghosh, V.K. Gupta, S.K.

Dubey, A. Das, et al., Productivity and soil health of

potato (Solanum tuberosum L.) field as influenced by

organic manures, inorganic fertilizers and biofertilizers

under high altitudes of eastern Himalayas, Journal of

Agricultural Science, Canada 4 (2012) 223-234.

[15] N. Jyotsna, M. Ghosh, D.C. Ghosh, W.I. Meitei, J.

Timsina, Effect of biofertilizer on growth, productivity,

quality and economics of rainfed organic ginger (Zingiber

officinale) in North-Eastern region of India, Journal of

Agricultural Science and Technology (communicated).

[16] M.L. Jackson, Soil Chemical Analysis, New Delhi,

Prentice Hall of India, 1973.

[17] A. Walkley, I.A. Black, An examination of the Degtjaroff

method for determining soil organic matter and a

proposed modification of chromic acid titration method,

Soil Science 37 (1934) 29-38.

[18] B.V. Subbiah, G.L. Asajia, A rapid procedure for

estimation of the available nitrogen in soil, Current

Science 25 (1956) 259-260.

[19] R.H. Bray, L.T. Kurtz, Determination of total, organic

and available forms of phosphorus in soils, Soil Science

59 (1945) 39-45.

[20] K.A. Gomez, A.A. Gomez, Statistical Procedures for

Agricultural Research, 2nd ed., John Wiley and Sons,

New York, 1984, pp. 70-101.

[21] C.R. Gupta, O.P. Awasthi, Effect of mulch material on

growth and yield of ginger (Zingiber officinale Rosc.),

Journal of Vegetable Science 24 (1997) 13-15.

[22] N.S. Subba Roa, An appraisal of biofertilizers in India, in: S. Kannaiyan (Ed.), The Biotechnology of Biofertilizers, Narosa Publishing House, New Delhi, 2001, pp. 45-105.

[23] V.A. Parthasarathy, V. Srinivasan, R. Dinesh, Organic production of spices-potentials and prospects, in: G.C. Munda, P.K. Ghosh, A. Das, S.V. Ngachan, K.M. Bujarbaruah (Eds.), Advances in Organic Farming


19

Technology in India, 2007, pp. 259-269. [24] A.K. Bijaya, L.A. do, Effect of fertilizers and biofertilizer

on physiological parameters of multiplier onion (Allium cepa var. aggregatum), Indian Journal of Agricultural Sciences 75 (2005) 352-354.

[25] A.K. Nair, P.C. Gupta, Effect of green manuring and N levels on nutrient uptake by rice (Oryza sativa) and wheat (Triticum aestivum) under rice-wheat sequence, Indian Journal of Agronomy 44 (1999) 659-663.

[26] V. Kumar, I.P.S. Ahlawat, Effect of biofertilizer and nitrogen on wheat (Triticum aestivum) and their after effects on succeeding maize (Zea mays) in wheat-maize cropping system, Indian Journal of Agricultural Sciences 76 (2006) 465-468.

[27] R.K. Yadav, D.S. Yadav, N. Rai, S.K. Sanwal, P. Sarma, Commercial prospects of ginger cultivation in North-Eastern region, Himalayan ecology, ENVIS Bulletin 12 (2004) 1-10.


Organic Agriculture: Socioeconomic Sustainability of

Brazilian Coffee

Rubia Wegner1, Patrícia Helena Nogueira Turco2 and Flávia Maria de Mello Bliska3

1. Institute of Humanities and Social Sciences, Federal Rural University of Rio de Janeiro, Seropédica 23890-000, Brazil

2. Department of Decentralization of Development, São Paulo Agency of Agribusiness Technology, Agriculture Secretary of São

Paulo State, Campinas, P.O. Box 28, São Paulo 13012-970, Brazil

3. Coffee Centre, Agronomic Institute, São Paulo Agency of Agribusiness Technology, Agriculture Secretary of São Paulo State,

Campinas, P.O. Box 28, São Paulo 13012-970, Brazil

Received: October 8, 2012 / Published: January 20, 2013.

Abstract: Worldwide, there is a growing demand for products made by technologies that contribute to environmental preservation and to sustainable rural development. In Brazil, organic farming is one of the most established initiatives in this area. Therefore, it is important to subsidize the decision-making regarding policies for organic coffee production. Thereby, this study analyzed the socio-economic sustainability of this production system in relation to conventional. We applied a semi-structured questionnaire on coffee farms in the Brazilian coffee producers states and analyzed the coffee production cost structure. We identified the reasons that led the producers to organic management, implications of certification on the management, and prices received by organic coffee and the market mechanism. Results showed that there is no standard for organic coffee production and marketing in Brazil. Among the producers, there are different levels of access to technical information and the main limitation of the organic coffee chain is not the technology of production, but the difficulty of coffee marketing. Another important limitation, for medium and large farms, is the cost of manpower, mainly in areas dominated by mountain, where machines operations are not viable. Moreover, the yield of organic coffee system is generally lower than the conventional. Furthermore, soil and climatic differences lead to different regional behavior. Finally, we could conclude that the production of organic coffee can be sustainable in Brazil mainly in two structural conditions: 1) family farmers; and 2) small producers, who employ only one or two workers, preferably only in the harvest time. Key words: Sustainable development, coffee crop, production costs, organic agriculture.

1. Introduction

1.1 Theoretical Fundamentals of Organic Farm

There are many controversies about the roots of

“Agroecology”plans, projects or policies for

economic development. However, there is consensus

that it seeks to understand the complex functioning of

agroecosystems (the units of study), as well as

different interactions present in these systems, with

the principle of biodiversity conservation and

expansion of agricultural systems as a basis for

Corresponding author: Flávia Maria de Mello Bliska,

Ph.D., research field: agricultural sustainability. E-mail: [email protected].

engendering self-regulation and hence sustainability

[1]. In addition, it provides a methodological

framework for this and relies on the incorporation of

the farmer to agricultural practice [2]. However, for

some authors [3] to keep up with good levels of

productivity and profitability in an organic system are

needed technical knowledge about the combination of

fertilizers and biofertilizers. Moreover, the

agroecological strategy could also be defined as the

ecological management of natural resources, which,

by incorporating a social action group with

characteristic participatory, allows designing methods

for sustainable development [4].

Then, formed the following streams: biodynamic

D DAVID PUBLISHING

Organic Agriculture: Socioeconomic Sustainability of Brazilian Coffee

21

farming, organic, organic-biological and natural

agriculture. Such currents promoted from the 1970s,

movements such as ecological agriculture, regenerative,

biological and permaculture, which were agglutinated

in alternative agriculture, then agroecology [5] and,

finally, sustainable agriculture. All these agricultural

practices are covered by the principles of agroecology

and pointed the search for a sustainable production

system in time and space, by managing and protecting

natural resources, without using harsh chemicals to

human health and the environment [6].

Since the 1990s, it has established itself the term

organic farming as a reference to all those forms,

mainly as a synonym of agroecology [7]. But it is also

characterized as a system in which soluble chemical

are removed from inputs, and which seeks to preserve

the biodiversity of agricultural ecosystems involved

[8]. Or else, as a productive system that aims to

prevent and even totally exclude synthetic pesticides

and fertilizers of agricultural production, which

replace external sources, such as chemicals and fuels

purchased commercially, by resources obtained within

the same farm or nearby. But, after all, organic

farmers are characterized by use of certified seed,

modern equipment and practices of soil and water

conservation [5].

Also since the late 1990s, studies that analyze the

organic farming emphasized the importance of

certification to increase its profitability and therefore

their economic, social and environmental benefits.

Organic agriculture is important for marketing,

because it guarantees to the farmer certificate to enter

and remain in the market. For the consumer, the label

“organic” is assured of a product originating from

properties that meet social and environmental values.

Even if the certification homogenizes the farmers in

view of the criteria it establishes, organic systems

production has different characteristics from one

region to another within the same country. Product

differentiation is the core profitability of the organic

chain, i.e., his competitiveness comes from the range

of specific markets and thus guaranteed [7-9]. Organic

agriculture offers opportunities for farmers in

developing countries to increase their income by

exporting agricultural products, as well as reduce its

dependence on other parts of the production chain,

such as agribusiness [10].

1.2 Organic Coffee in Brazil: A Brief Characterization

In Brazil, coffee is one of the most important crops,

particularly regarding job creation and foreign

exchange. Its cultivation is spread over much of the

Brazilian territory, but its production is concentrated

in some regions of Minas Gerais, Espirito Santo, Sao

Paulo, Paraná, Bahia and Rondônia States. Each of

these regions presents competitiveness and production

costs differentiated by the use of different

technological packages.

Most of the Brazilian coffee producers made the

conversion from conventional to organic in the early

2000s, when conventional coffee prices were very low.

These years were marked by optimism among coffee

producers and Brazilian researchers, as to the

profitability of organic coffee, because from 2000 to

2006, its production grew by 5% [11]. Rondônia,

Mato Grosso do Sul, Sao Paulo, Bahia, Paraná and

Espírito Santo are states where we can find coffee

production in agroforestry or organic systems.

In recent years, organic products, especially grocery

are closer to the Brazilian consumer demand. The

main reasons are the “real1 strong”, the boom phase

of the Brazilian economy and the financial crisis,

which spared the producing countries but has reached

the mature economies of Europe and the US, major

buyers of organic [12].

Research conducted by the Brazilian Coffee

Industry [13] referring to 2010 showed that among the

Brazilians, is consolidated into the habit of drinking

coffee, especially for consumption outside the home.

The specialty coffee group where organic coffee is

included grown in preference of consumption: the

1Brazilian currency.


22

participation of this group in the consumption at home

was 1.2%, and outside the home was 3.3%.

However, the concept of organic agriculture was

understood by the Brazilian coffee growers, especially

as non-use of agrochemicals. A controversial point in

the characterization of organic farming in Brazil is the

maintenance of a monoculture, which also affect the

competitive insertion in the market for these products

[14].

The pressure of NGOs (Non-Governmental

Organizations), cooperatives of farmers and certifiers

led in the 1990s, the Federal Government to prepare a

draft law to regulate organic production in Brazil

(Law 10831, 2003). In addition, were created the

Sectorial Camera of Organic Agriculture and the

National Collegiate of Organic Products, to accredit,

monitor and control certification. In the 2000s, the

federal government created the Department of

Agroecology (COAGRE), linked to the Department of

Production Systems and Sustainable Development

Secretariat of Agriculture and Cooperatives, and it is

responsible for the actions of the promotion,

development of standards and implementation of

quality control mechanisms, which must develop

agriculture organic in Brazil.

Based on Article 1 of Law 10,831, Brazil considers

organic agricultural production system, that when

specific techniques are adopted, by optimizing the use of

natural and socioeconomic resources available, and

respect the cultural integrity of rural communities,

aiming at economic and ecological sustainability,

maximizing benefits, minimizing the energy

dependence is not renewable, using, where possible,

cultural methods, biological and mechanical, as opposed

to using synthetic materials, eliminating the use of

genetically modified organisms and ionizing radiation at

any stage of production, processing, storage, distribution

and marketing, and environmental protection.

We can scale the Brazilian public policies with

respect to encouraging conversion to organic

production, and with respect to the support and

infrastructure offered to those who already act as

organic growers. These dimensions are due to the way

the state understands the promotion of sustainable

agriculture, i.e., in that it links the environmental

protection and incentive compensation payments in

order to promote the necessary changes [14]. It

highlights how tenuous a specific policy for organic

farming can be compared to the market. In this area,

the main Brazilian public policy is restricted to the

scope of certification and marketing.

The main certifiers operating in Brazil are

ECOCERT (Organic Certification Organization), the

Biodynamic Institute and BCS Brazil. The

relationship between farmers and certifying that it

comes down to the support and control of matters

related to certification, and not to technical assistance,

that would set off the conflict of interests between the

domestic and international regulatory authorities.


To survey the cost structures and technical

coefficients of production, we use semi-structured

interviews in loco, that is, applied to coffee producers

in their respective farms in the states of Minas Gerais

and São Paulo, where we visited the following regions:

South of Minas Gerais, Mogiana and Pontal do

Paranapanema, in São Paulo, between February and

June 2011. Interviews with producers of Rondônia,

Espirito Santo, Bahia, Paraná and Mato Grosso do Sul

were conducted by telephone. The interviews

consisted of two parts. At first, it was found the

reasons that led the producers to organic management,

the implications of certification on the management

and the prices received by producers, marketing

method, and the main difficulties with this

management. The second part was to search for

information on the structure of production costs, per

hectare of coffee grown and per bag produced. We

evaluated the operations, inputs and materials

consumed and machinery and implements used in the

2009-2010 crops.


23

The description of costs followed the concept of

total operating cost (COT), which consists of variable

costs, expenses for manpower, operations of

machinery and equipment, raw materials used

throughout the year and includes depreciation of

durable goods used in production process. Also

followed the concept of operational cost (COE), which

adds to the total operating cost: 1) social security

contributions; 2) depreciation of machinery, other

fixed costs of machinery related to shelter, insurance

and interest on capital invested in this item; 3) when

applicable, the rate of the National Program for

Strengthening Family Farming (PRONAF). This

method therefore serves to estimate costs and analyze

the economic feasibility [15].

We analyzed the areas of coffee production to

organic management and conventional management,

in terms of hours of hand labor, tractor and equipment,

materials and quantity consumed for each operation

activities, from fertilization through the processing, in

view of the sequence used by the manufacturer

respondent. This systematization is called the matrix

of technical coefficients [15]. Also we attempted to

determine the profitability of both of these

management systems through indicators such as:

(1) Gross Revenue (GR)

GR = R*Pu (1)

Where:

R = yield of activity per unit area;

Pu = unit price of the product of the activity.

(2) Leveling point (LP) determines the minimum

production necessary to cover production costs, given

the unit-selling product price:

LP = TOC/Pu (2)

Where:

TOC = total operating cost

Pu = unit price

(3) Operating profits (OP): measures the

profitability in the short term, is the difference

between gross revenue and total operating cost (COT)

per hectare.

(4) Profitability index shows the relationship

between the operating profit (OP) and the gross

revenue (GR) in percentage. This index shows the rate

of revenue available from activity after paying all

operating costs including depreciation. So:

PI = (OP/GR) 100 (3)

2.1 Measurement of Coffee Production Costs

In a country with the size of Brazil, where each of

the producing regions has specific soil and climatic

characteristics and the producers have totally different

characteristics and objectives, it is expected that

production costs are very different. After all, the cost

of production depends mainly on the following factors:

1) system of production; 2) level of technology; 3)

size of farm; 4) philosophy of life and the producer

objective; 5) national and international economic

conditions (e.g., via changes in relative prices,

exchange rates, international prices, yields in countries

competitors or changes in demand); 6) characteristics

of climate and soil of the original area where the

property is located; 7) climate variations that may

occur in specific years (frosts, prolonged droughts)

and other aspects.

2.2 Factors that Can Interfere with the Yield of Coffee

Plantations

(1) Biennial: it is the physiology of the coffee itself,

that is, the coffee plantations have a high production

year and another year of low and this is established

fact to the producers. The biennial has variations

within the following conditions:

In plantings in full sun, the biennial is very

significant;

In rotation with other crops and forested crops (but

not shaded), the biennial is apparent, though not as

significant as in the unshaded crop;

In shaded plantations, the biennial is not significant.

That is, the variation in productivity from year to year

is so small that it can be considered that, in practice, it

does not exist;


24

In scientific studies, especially in plantings in full

sun, when you want to evaluate the productivity of a

coffee stand, it is important to calculate the average

productivity of this stand for the last four years (two

cycles of high and low yield).

When the plants are young, or are undergoing

strong growth, the Biennale is not significant. For

systems in full sun, this occurs in the first two seasons,

when the plants reach 3.5 years. From the third season

of the biennial becomes significant.

The intensity of the Biennial of coffee depends on

many factors. The main ones are climatic conditions

and the packet technology used (such as variety, pest

and disease management, fertilization, spacing, and

pruning).

The renovation and expansion of the coffee

plantations usually occur at a higher intensity when

coffee prices are considered good. Consequently,

much of the crop is planted or renewed in the same

time, which leads to the existence of “years of low and

high” productivity.

However, in one year “high”, there are producers

with low yields, as well as in years of “low”, there are

producers with high yields. Sometimes, in the same

farm, there are stands of coffee in “year” of “low”

crop and other in “high”.

Frosts, prolonged drought or excessive rainfall can

change the volumes produced annually and therefore

the sequence of high and low yields.

Therefore, despite the implications of the Biennale,

to calculate production costs, we need to do this every

year. The relative prices in the economy vary from

season to season, especially when using imported

inputs, especially fertilizers and pesticides, as in

conventional cultivation of coffee. And for that we

must use the yield of the year. We can not use the

average of four years.

(2) Yield: according to information provided by

farmers and rural extension workers, the productivity

of organic coffee is generally 30% lower than the

productivity of conventional coffee, even though, it is

possible to obtain high yields in the organic system.

In Brazil, today, there are conventional arabica

coffee plantations that produce 70 to 100 bags per

hectare, average four years (for instance, in South and

Cerrado of Minas Gerais State; in Garça and Mogiana

regions, in São Paulo State; or in the Cerrado of Bahia

State). So you can get yields of 30 to 60 bags per

hectare in organic crops.

One situation where we can get regular high yields

in organic crops in normal years (that is, free of frost,

drought or too much rain) is that found in the region

of Serra da Mantiqueira in the State of Minas Gerais,

1,200 m altitude, using variety of coffee rust resistant,

and in soil without nematodes infestation. In that

region, the soils are not sandy, the weather conditions

and temperature inhibit the attacks of leaf miner and

cicadas and natural fertility is high. Thus, the

probability of obtaining high yields and excellent

quality of the beverage is high, since it makes a good

crop management and good work of post-harvest. The

drop in productivity compared to conventional coffee

can occur, but a careful producer can get high yields

and competitive costs.

Many farmers still do not understand that organic

system requires specific management, with investment

in nutrients and control pests and diseases. The most

of organic coffee producers began using this system of

cultivation due to high costs for the conventional and

the initial idea was to reduce production costs. Many

farms still had reserves of available nutrients in the

soil and also in the plants themselves. So even after

three years without chemical fertilizers, necessary for

the conversion to organic system to be recognized, the

crop still had reasonable productivity. However, prices

for organic inputs are competitive with conventional

chemical inputs in years of high prices of conventional,

while in other years the prices of conventional inputs

are lower than those of organic.

Without using organic inputs and without

management of pests and diseases, these coffee

producers observed over the subsequent years, the


25

sharp drop in their productivity. Some of these

producers have abandoned the organic system. Other

producers began to use organic inputs, improved crop

management and persisted in the organic system. In

these situations, the highest prices paid for the bag of

organic coffee represented an incentive for farmers to

remain in this production system.

In general organic crops with low productivity were

not implemented with varieties resistant to rust or leaf

miner did not receive nutritional treatment and

management of pests and diseases adequate or are not

located in regions with favorable climatic conditions

for coffee production or in soil naturally fertile.

3. Results

The results are based on information obtained

through interviews with 21 organic coffee producers,

three organic agroforestry, five conventional, a large

coffee-growing company and exporting of organic and

conventional coffee, cooperatives, and researchers,

institutions of technical assistance and rural extension,

and export companies.

All producers of this sample were clearly

committed to organic practices, although some of

them were dissatisfied with the return of the last

harvest (low season), and conventional coffee resulted

in better pay per benefit bag. All those producers

follow the recommendations of their certification as

fertilizers and pesticides. The machinery used was not

especially developed for organic system. Producers

who are not certified seek to follow the guidelines of

the IBD or the BCS. The main inputs used in organic

coffee in Brazil are:

Fertilizers: fish fertile, castor seeds pie, coffee straw,

chicken manure, castor meal, natural phosphate and

urea.

Pesticides: Bordeaux mixture, cooper hydroxide,

supera, borax, hydrated lime, cooper sulphate,

magnesium sulphate, zinc sulphate, fungi Beauveria

bassiana, caustic, Bordeaux and Viçosa mixture.

Machinery: mowing, sprayer, harvesters, trator and

dryer.

3.1 Characterization of Organic Coffee Producers:

Brazilian States

It was observed that organic growers interviewed

chose this production system due to: 1) its social and

environmental awareness; 2) specific programs

captained by rural technical assistance; 3) the search

for reducing costs; 4) or even, given the expectation of

obtaining higher price compared to the conventional.

Some growers, especially those who remain in the

market with modest production, face this culture

system as a way to contribute to the preservation of

the environment and health of their families.

In general, organic farmers use family labor and,

during the harvest, they hire day laborers. However,

some producers have hired salaried employees. Part of

the organic coffee growers consort with products such

as cassava, banana and honey (which are important

sources of income). Despite the existence of growing

demand for organic products, maintaining its

production scale has been for some producers, a

problem to ensure their profitability and also

continuity in management.

One of the interviewed cooperatives, located in

Minas Gerais State, did not export organic coffee in

the last 10 years because their members were unable

to match the scale of production with good quality

coffee. An exporter of Sao Paulo State, informs that,

even certified, it is difficult to get good prices for

organic coffee, so the producers income. Furthermore,

there is great difficulty in obtaining uniform batches,

especially when, to export, it is necessary a container.

As this exporter marketing only high quality coffees,

lots of heterogeneity prevents their commercial

relationship with cooperatives of small producers.

Since, for organic coffee, sieve mixture is allowed

[14-17], this mixture, in roasting results a lower

quality of drink, therefore, lower prices. So it has

exported coffee regularly only from two organic

farmers, which produce high quality coffees.


26

In Bahia State, two respondents have created a

coffee exporting company to sell their production of

organic coffee. Each one has an average area of 20

hectares of organic coffee, and both invest heavily in

the quality of coffee. In 2009-2010, they exported 640

bags of coffee, priced 100% higher than conventional,

and have sold about 50 bags for national companies

from São Paulo and Bahia States. They are certified

by IBD and claim that organic coffee production is

feasible for them, because they make use of its own

channel of marketing and because their coffee is high

quality standard, i.e., the premium is linked more to

the quality of coffee than the organic seal.

Many growers declined to produce organic coffee

due of the low pay they got. For some, the high cost of

manpower was the biggest obstacle (mainly medium

and large farmers). Others add to that the insufficient

technical assistance (especially in the case of family

farmers) and a significant drop in productivity of the

plantation, after conversion to organic. Table 1 shows

us the main characteristics of organic farmers

surveyed.

In the Southern region of Minas Gerais State, the

organic coffee production is better established in

Brazil. In this region there are predominantly small

farmers, the coffee has great socio-economic

relevance and producers has better knowledge about

the requirements concerning the practice of organic

coffee than in other producing areas, considering

technical or agronomic dimension and marketing. The

cooperative is the element that stimulates this

structure. All of them are connected to the Family

Farmers Cooperative and export all their bags of

organic coffee. These farmers started using the

principles of organic practices in the 2000s. They have

relative understanding that the certification, as well as

Table 1 Characterization of organic coffee production: producer, municipality, Brazilian States, certifying, cultivate, coffee area (ha), number of coffee trees, selling price (*R$/bag of 60 kg).

Producer Municipality/State Certifier Cultivate Area (ha) Coffee (trees/ha)

Price (R$/bag)

1 Andradas/MG Certifica Minas; ECOCERT; BCS

Catuaí, Mundo Novo 9 13200 430

2 Andradas/MG BCS; ECOCERT Catuaí, Mundo Novo 6 18000 480

3 Andradas/MG BCS; ECOCERT Catuaí, Mundo Novo 2 5300 480

4 Poço Fundo/MG BCS; ECOCERT Catuaí, Mundo Novo 2.4 2500 430

5 Poço Fundo/MG BCS; ECOCERT Catuaí, Mundo Novo 06 3500 435

6 Ouro Fino/MG BCS Mundo Novo 03 1500 410

7 Ouro Fino/MG ** ECOCERT Catuaí, Mundo Novo 02 -*** -

8 Paraisópolis/MG** IBD Catuaí, Mundo Novo 25 - 725

9 Santo Antônio do Pinhal/SP

IBD Mundo Novo, Tupi, Obatã

75 3333 650

10 Irupi/ES BCS Arabica 10 2500 380

11 Santa Maria de Jetibá/ES Chão Vivo Arabica 04 4000 250

12 Santa Maria de Jetibá/ES Chão Vivo Arabica 03 2000 380

13 Teodoro Sampaio/SP Not certified Arabica 01 2000 250



16 Lunardelli/PR IBD Obatã, IAPAR-59 Tupi 40 5500 ****

17 Ibicoara/BA** IBD Arabica 25 7000 630

18 Ibicoara/BA** IBD Arabica 20 7500 630

19 Ji-Paraná/RO ECOCERT Conilon 2.5 2100 185

20 Glória dos Dourados/MS Not certified Tupi, Mundo Novo, Catuaí

10 8.000 120

* Reais: currency in Brazil; ** Not cooperate with information on production costs; ***Not cooperate with information; ****Three times the conventional price; Source: Data from the study.


27

the cooperatives, does not guarantee a stable return, at

high levels, since these factors depend on the

international market. They believe that to keep

producing organic coffee, farmers should not

prioritize getting high prices per bag produced. In this

region, the production dynamics is linked to

cooperatives, starting with the certification, BCS and

Ecocert, with direction for the use of inputs and other

components of management and, particularly, with

regard to marketing. In the Cerrado of Minas, there is

only one producer of organic coffee, with 20 hectares

devoted to this production system. It is connected to a

regional cooperative, and he sells his coffee to

national companies.

One of the biggest supporters of organic coffee

production in Brazil also was a major producer of

organic coffee and managed several family farms, all

in the Southern region of Minas Gerais. Their farms

were relatively large, some with 70 to 100 ha of coffee.

By 2006, all the organic coffee produced was sold to

Japan; grains above 14 screens were sold in bulk. The

rest of the coffee was dried and exported to Japan

already packed. About two years the farms managed

by him broke. According to him, the reason was the

extremely high cost of hired labor which prevents the

organic system, on farms of medium to large. Today,

he recommends the organic system only for small

farms, mainly in the family production system.

Interview with the technical manager of a big farm,

in Southern of Minas Gerais, also indicated that the

large production with organic system is not

economically viable. A few years ago, it had converted

50 ha of conventional coffee to organic. The yield, that

was around 30 bags/ha, fall from 15 to 20 bags/ha. In

addition to this low yield, only 50% of the coffee was

sold at the organic price, due to many problems with

its quality. For nearly two years, that farm began to

managing another farm, also in Minas Gerais State, a

coffee exporter, with all the possible certifications for

coffee, including organic. Today, the new

administration excluded the area of organic coffee.

Two years ago, the average yield of the conventional

area was between 30 and 40 bags, while in the area of

organic coffee the yield was 20 bags/ha. Those farms

used inputs as recommended for organic system, but

had great difficulty in applying the products in

mountain area with no possibility of management and

harvest mechanization. All operations needed to be

done manually, which became unviable due to the high

cost of manpower. For him, the organic system is

feasible only for small producers.

In Western of Sao Paulo State, producers of

agroforestry organic coffee sell their coffee in regional

markets, or companies of Paraná State, with the price

of conventional coffee. In the region, known as the

Pontal of Paranapanema, Ipe Foundation is developing

a program called “Coffee with Forest” in settlements

of farmers “landless”. This project has brought great

socioeconomic outcomes. The coffee production in

organic agroforestry system (SAF) has shown a

significant supplemental income source, with

extremely low cost. The coffee is not certified and the

producers are not sensitized to ascertain or to seek

foreign markets. The coffee is sold regionally and in

the State which borders that region. Using a very low

volume of external inputs, farmers have obtained

yields of around 15 benefit bags/ha, which are sold at

the price of conventional coffee.

In Espírito Santo State, the conversion of

conventional coffee to organic was due to the

discomfort that the use of agrochemicals caused to

farmers and their families, and due to the damage,

they cause to the environment. Moreover,

conventional inputs were expensive and the possibility

of the bag of organic coffee to get better pay was an

important persuasive factor. Growers did not receive

technical assistance and they used fertilizers and

biofertilizers on their own, to analyze those were more

efficient, for added profitability and sustainability.

In Paraná State, four farmers were contacted. Two

of them left the organic system. Moreover, they had

not recorded their spending with the crop. The third


28

producer did not provide information about their

production costs. The conversion of this crop for the

organic system followed a severe frost in 1994.

Moreover, prices of inputs required for cultivation of

conventional coffee were high.

In the Bahia State, organic coffee production is also

declining. The main reason is the difficulty face to fit

within the market. The Biodynamic Association of

Farmers (certified by IBD), in the beginning of its

activities consisted of a group of 34 organic growers.

In 2009-2010, this group was reduced to seven

members. Two of them created its own exporting

company, which allowed them to continue to produce

organic coffee. These producers have access to an

important organic raw material, the castor bean and

therefore use manure, which represents a high cost

due to the cleaning process. Their farms have an

average area of 20 hectares of coffee under organic

management. They pointed out that the domestic

market is still inactive and paying lower prices. They

have achieved good export prices, because they invest

heavily in quality and created dedicated channel

marketing, i.e., their export business.

In Rondônia State, much of the marketing of coffee

is made through the Mutual Aid Associations

(ACARAM: Joint Central Rural Associations for

Mutual Aid), present in more than a dozen

municipalities. These associations receive and store

coffee, and generally sell it for a large company in the

Paraná State.

In Mato Grosso do Sul State, there were 200

families associated with APOMS (Association of

Organic Farmers in Mato Grosso do Sul), but only 20

were dedicated to organic coffee and the volume

produced by all of them is between 1,500 and 3,000

bags. They do not export their coffee and they passed

over IBD, due to the high cost to them and because

they do not provide any support or guidance. They sell

their coffee to the price of conventional product,

basically in the local market in trade fairs and coffee

houses. The harvest is manual and selective, so they

hire day laborers during this the harvest time.

3.2 Production Costs of Organic and Conventional

Coffee

The analysis of production costs is a key

management tools available to farmers. It allows

growers to consolidate the monitoring of farming,

streamlining production, and represents a tool to

specific policies for the coffee.

In Table 2, we present the results of two ways of

calculating the cost of organic coffee production. First,

we do not consider the remuneration of family work,

and the gross profit represents the remuneration of

family labor and remuneration of agricultural activity.

Second, we consider the remuneration of family labor

as a value similar to that of daily workers hired in

each region, and net income represents only the

remuneration of agricultural activity.

A first aspect to note is that farmers in agroforestry

systems have very low cost for supplies, which are

restricted mainly to spending on fuel and bags.

Producers needed to spend a little more with

inputsespecially in Minas Gerais in order to achieve

certain productivity with profitability showed higher

production costs. In Espírito Santo, Rondônia and

Mato Grosso do Sul, taking into account differences in

the cultivated area, the farmers faced higher costs in

farming operations. Also, the results indicate that net

income per ha generally decreases sharply when the

remuneration of family labor is added to the cost of

production. In one case examined, the result indicates

a loss.

4. Conclusions

There is not a standard for organic coffee

production in Brazil. The literature available on coffee

production and informations obtained from the

farmers interviewed in this study indicate different

conditions of production and marketing. The

producers have different levels of access to technical

information, especially on the combinations of inputs


29

Table 2 Cost of production of organic and conventional coffee, Brazilian regions, with remuneration of family labor or not, 2009-2010 crop, yield (bags/ha), total cost, total income (R$/ha), gross profit (R$/ha).

Brazilian States

Production systems

Yield bags/hectare (ha)

Remuneration of family labor Total cost Real (R$)* Total income Gross profit

Yes No R$/ha R$/bag R$/ha R$/ha

Minas Gerais

Organic

28 X 3,976 142 12,183 8,207

X 4,592 164 12,183 7,591

41 X 4,018 98 17,853 13,835

X 17,384 424 17,853 469

15 X 3,630 242 6,150 2,520

X 3,705 247 6,150 2,445

10 X 1,560 156 4,720 3,160

X 1,760 176 4,720 2,960

39 X 7,137 183 16,684 9,547

05 X 2,340 468 2,400 60

Conventional

20 X 4,940 247 6,000 1,060

20 X 5,980 299 5,600 -380

22 X 7,634 347 6,006 -1,628

20 X 6,440 322 5,600 -840

20 X 6,420 321 5,600 -820

São Paulo

Organic

49 X 8,036 164 17,333 9,297

15 X 1,020 68 3,750 2,730

X 2,340 156 3,750 1,410

15 X 1,095 73 1,875 785

X 1,890 126 1,875 -15

15 X 1,200 80 3,750 2,550

X 2,175 145 3,750 1,575

Conventional 25 X 6,450 258 7,625 1,175

15 X 4,305 287 4,200 -105

Rondônia Organic 35

X 3,045 87 6,300 3,255

X 3,325 95 6,300 2,975

Conventional 30 X 3,570 119 5,100 1,530

Espírito Santo

Organic

14 X 2,604 186 5,320 2,716

15 X 2,610 174 4,650 2,040

30 X 3,600 120 3,800 200

Conventional

20 X 2,800 140 3,360 560

15 X 3,645 243 4,050 405

16 X 4,336 271 3,840 -496

15 X 2,610 174 3,300 690

14 X 3,808 272 4,130 322

Mato Grosso do Sul

Organic 12 X 1,020 85 8,640 7,620

X 3,348 279 8,640 5,292 *Real: Brazilian currency; Source: Data from the study.

to be used. In addition, soil and climatic differences,

intrinsic to a country of continental dimensions, like

Brazil, lead to different micro-regional or regional

results.

We can summarize the types of organic coffee

producers in Brazil as follows:

Farmers without capital to invest and do not depend

on coffee culture. Coffee results in additional revenue,

but the producer depends, for instance, on honey, milk

or banana production. In many cases, the coffee

culture does not receive any treatment, it is just

harvested, an extractive system. These producers


30

generally sell its product in local or regional fairs and

the coffee is not always of good quality. They may be

certified or not.

Family farmers without capital to invest, but that

depend on coffee plantations. They can not invest in

buying the ideal volume of inputs for farming, but still

use some compost or organic products to control pests

and diseases allowed in the organic system. They are

not expensive in manpower, but hire workers

especially in harvest time. Some can do a good job of

post-harvest and get good quality coffee. They may be

certified or not.

Small producers, which use higher levels of

technology, increasing volumes of inputs, greater care

in post-harvest, which has one or two contract

employees, and sometimes hire more workers at

harvest time, or even who does not contract

employees but hire day laborers for the harvest. Most

of these producers is certified and is associated with a

cooperative and can export the coffee regularly.

Producers of medium size, in general, they have

high production costs due to the high cost of

harvesting. Many of those who used the manual

harvesting system broke in recent years. They need to

invest in mechanized harvesting, but in general they

do not produce volumes of coffee to justify this

investment.

Large producers, farms export various different

kinds of coffee. In general, this type of producer has

organic coffee fields only to have this type of coffee

among the products offered by the company, as

propaganda for social and environmental concern and

not because they are economically viable.

Large producers, who produce coffee with a profit,

but do not worry about the size of that profit; they do

not rely on coffee for survival and have other sources

of income. Organic production is a philosophy of life.

Generally, coffee quality is good, they are not

associated with cooperatives and they export

individually or selling for large companies roasters.

One aspect to be highlighted in the organic system

is the issue of inputs: although the use of natural

fertilizer from other agricultural products of the farm,

constitutes one of the pillars Organic Agriculture

definition, much of the Brazilian coffee growers are

monoculture. Some of them produce coffee in

association with fruit and even in association with

other agricultural activities, but they have no

knowledge about the most appropriate combinations

of fertilizers and biofertilizers allowed by certifiers.

Although in some regions, the average productivity of

organic coffee is around 15 bags per hectare, the

regions where we observe increased use of fertilizers

(biofertilizers), recommended by certification, but not

natural, as the Minas Gerais State, are observed high

levels of productivity, sometimes, around 38 or 40

bags per hectare.

The main conclusions of the study can be

summarized as follows:

The production of organic coffee can be

economically viable in Brazil, mainly in the following

structural conditions;

Small producers who do not rely on hand

labor-hired (family farms);

Small producers who hire fewer workers (one or

two employees), and preferably only at harvest time;

Organic producers, with rare exceptions, do not

receive technical assistance and technological

information in general. Most of them are self-taught.

The differences in yield obtained by farmers are

significant. The objectives of each producer are also

different. Nevertheless, it is considered that the main

problem for organic production is not technological.

The primary limitation to the sustainability of

organic production in Brazil is the difficulty of

marketing:

Producers who are cooperative membership have

better marketing opportunities, because the

cooperatives strengthen the market access, especially

for the international market;

The coffee produced must have excellent standard

quality, so crop management and post-harvest


31

processing should be extremely careful: the quality of

coffee is as important as its own certification seal;

The difficulty to get homogeneous coffee shipments

and to maintain the quality of each crop year after year,

make it difficult for international sales;

The coffee that is not exported could get higher

price than conventional coffee, in the domestic market,

through the development of this niche of market,

currently limited;

The dual certifiedFair-trade and organicresults

in better prices, greater integration into the

international market and increases stability for the

coffee producer.

The main limitation to the sustainability of organic

systems, for medium and large farms, is the cost of

manpower. In areas with better soil and climatic

conditions for coffee production, the South of Minas

Gerais and Mogiana, in São Paulo State, dominated by

mountain coffee production, where machines

operations are not viable and the cost of manpower is

very high.

The yield of organic coffee system is generally

lower than the conventional. The difference between

them depends on the crop management, post-harvest,

characteristics of soil, temperature and rainfall,

especially the natural fertility of soil and altitude.

The organic system can be enhanced through

integrated management with other crops (like bananas)

or other agricultural activities (such as beekeeping and

dairy cattle), provided with manpower family or fewer

employees.

The agroforestry systems have great potential in

relation to the productive capacity and income

generation. However, lack support to producers and,

especially regarding the dissemination of information

and credit for its implementation. Such a system could

assist in the sustainable development of areas that are

highly disturbed by man.

As recommendation, programs to support

sustainable coffee production in Brazil should

prioritize:

Sustainable production systems, whether organic or

not, because the definition of sustainable agriculture

does not imply exclusively organic production;

Family and small farmers located in regions with

soil and climatic characteristics suitable for coffee

production, such as the southern region of Minas

Gerais State and Mogiana region, in São Paulo State;

Family farming, agro-forestry system, in highly

degraded areas by human activities, with marginal soil

and climatic conditions for growing Arabica coffee, as

the Western region of the São Paulo State (Alta

Paulista);

Access to technological and market information, for

achieving higher productivity and, especially, higher

quality (organic management, harvesting and post

harvest), to meet the requirements of the international

market (minimum volumes, homogeneous coffee

shipments, excellent quality of coffee grain and drink);

The approximation between Brazilian organic

coffee producers and buyers, especially international

buyers;

The promotion of organic coffee in the domestic

market, seeking alternative market and higher prices

for coffee that is not exported, once today, much of

this coffee is sold on the domestic market at the price

of conventional coffee.

The access to sources of credit: dissemination of

information on available sources, support to prepare

the documentation required by funding agencies or

implementation of alternative sources.

Incentive certifications, which allow simultaneous

access to other niche markets, beyond organic, as well

as Fairtrade and the geographical indication.

In summary, the promotion of organic coffee

production needs to be done very carefully, because

organic agriculture is sustainable for some situations

and for very specific Brazilian regions. We can not

encourage the cultivation of organic coffee without

analyzing each producer (or producers’ association) in

particular, because there is strong risk of the producer

to be financially distressed.


32

Acknowledgments

Tierra Nova Fonds, Netherlands, the funding for the

study.www.tierranova.nl.

References

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[2] M. Altieri, Agroecology: The scientific basis of alternative agriculture (Agroecologia: as bases científicas da agricultura alternativa), Rio de Janeiro: PTA-FASE, 1998, p. 237.

[3] A.M. Buainain, Family agriculture, agroecology and sustainable development: Issues for debate (Agricultura familiar, agroecologia e desenvolvimento sustentável: questões para debate), Brasília: IICA, 2006.

[4] E.S. Guzmán, Origin, evolution and prospects of sustainable development (Origem, evolução e perspectivas do desenvolvimento sustentável), in: J. Almeida, Z. Navarro (Eds.). Rebuilding the agriculture: ideas and ideals in the context of sustainable rural development (Reconstruindo a agricultura: idéias e ideais na perspectiva de um desenvolvimento rural sustentável), Porto Alegre: University Publish Housing (Ed. Universidade)/UFRGS, 1998, pp. 19-32.

[5] A.M. Altieri, Organic agriculture (Agricultura orgânica), in: M.A. Altieri (Ed.), Agroecology: The Scientific Bases for Sustainable Agriculture (Agroecologia: Bases Científicas Para una Agricultura Sustentável), Montevideo-Uruguai: Nordan Comunidad, 1999, pp. 165-183.

[6] M.R. Darolt, The dimensions of sustainability: A study of organic agriculture in the metropolitan region of Curitiba, Paraná (As dimensões da sustentabilidade: um estudo da agricultura orgânica na região metropolitana de Curitiba, Paraná), Ph.D. Thesis, (Tese de Doutoramento): Federal University of Paraná (UFPR), University of Paris 7 (2003) 310.

[7] A.M. de. Aquino, R.L. de. Assis, Organic agriculture in urban and peri-urban based on agroecology (Agricultura

orgânica em áreas urbanas e periurbanas com base na agroecologia), Environment and Society (Ambiente e Sociedade), Campinas-SP, Jan.-July 2007, pp. 137-150.

[8] J.L.H. de. Carvalho, Program to upright smallholder

farming (Programa de verticalización de la pequeña

producción agrícola), Urban Agriculture Magazine

(Revista Agricultura Urbana), Quito, 2002, pp. 35-36.

[9] S.R. Penteado, Introduction to Organic Agriculture:

Policies and Cultivation Techniques (Introdução à

Agricultura Orgânica: Normas e técnicas de cultivo),

Campinas: Grafimagem Publish Housing (Editora

Grafimagem), 2000, p. 110.

[10] C. Zundel, L. Kilcher, Organic agriculture and food

availability, International Conference on Organic

Agriculture and Food Security, Rome, May 3-5, 2007.

Retrieved Jan. 2011, from

www.fao.org/ORGANICAG/ofs/index_en.htm.

[11] A.M. Batalha, A.M. Buainain, Supply chain of organic

products (Cadeia produtiva de produtos orgânicos),

Agribusiness series (Série Agronegócios): IICA e

MAPA/SPA, 2007, p. 108.

[12] BARROS, Bettina, Organic products winning space in

the domestic market (Produtos orgânicos ganham terreno

no mercado doméstico), Economic Value (Valor

Econômico), 2010.

[13] ABIC, Brazilian Association of Coffee Industry

(Associação Brasileira da Indústria do Café), Trends of

coffee consumption (Tendências de consumo de café),

2010, p. 108.

[14] G. Paulus, The modern standard for alternative

agriculture: Opportunities for transition (Do padrão

moderno à agricultura alternativa: possibilidades de

transição), Dissertation (Dissertação de mestrado).

Florianópolis-SC: Federal University of Santa Catarina

(Universidade Federal de Santa Catarina) (UFSC), 1999,

p. 185

[15] N.T.C. de. MELLO, Proposed new methodology of

production costs of the Institute of Agricultural

Economics (Proposta de nova metodologia de custo de

produção do Instituto de Economia Agrícola). São Paulo:

SAA/IEA, Research Report (Relatório de Pesquisa), 1988,

p. 14.


Enhancing Maize Grain Yield in Acid Soils of Western

Kenya Using Aluminium Tolerant Germplasm

Ouma Evans1, Ligeyo Dickson2, Matonyei Thomas3, Agalo Joyce1, Were Beatrice3, Too Emily3, Onkware

Augustino3, Gudu Samuel4, Kisinyo Peter4 and Philip Nyangweso1

1. Department of Biological Sciences, Moi University, P.O. Box 3900-30100, Eldoret, Kenya.

2. Kenya Agricultural Research Institute (KARI) Kitale Centre, P.O. Box 460-30200, Kenya

3. Department of Biological Sciences Chepkoilel University College, P.O. Box 1125-30100, Eldoret, Kenya

4. Department of Agronomy, Rongo University College, P.O. Box 103-40404, Rongo-Kenya


Abstract: Maize (Zea mays L.) is one of the world’s most important cereals and is a staple food for many people in developing countries. However, in acid soils (pH < 5.5), its productivity is limited by aluminium (Al) toxicity, besides other factors. The objectives of this study were to: develop Al tolerant maize inbred lines for a maize breeding program in Kenya, develop single cross hybrids (SCHs) from some of the tolerant inbred lines and determine Al tolerance levels of the SCHs. One hundred and seventy five inbreds and 49 SCHs were developed and screened in nutrient culture containing 0 or 222 µM using Relative Net Root Growth (RNRG), hematoxylin staining (HS) and under Al saturated field conditions (44%-45.6%) at Sega and Chepkoilel. Seedling root growth was inhibited in 95% of the inbreds. F1 hybrids obtained from inbreds varying in Al tolerance, exhibited tolerance equal to or greater than that of the more tolerant parent indicating a positive transgressive inheritance to Al toxicity. Fifty eight percent of the F1 SCHs were heterotic for tolerance to Al toxicity. Al tolerance estimated by RNRG was well correlated to that of HS (r2 = 0.88, P < 0.005) but minimally correlated with the field estimates (r2 = 0.24-0.35), implying that RNRG can predict field selection under Al toxic soils by between 24% and 35%. Plant breeders should therefore employ both approaches in selecting cultivars under Al stress. This study has developed and identified Al tolerant inbreds and SCHs for use in the acid soils of Kenya and similar regions.

Key words: Maize, inbred lines, hybrids, heterosis, aluminium toxicity, acid soils.

1. Introduction

Aluminium (Al) toxicity and low available P are

some of the most limiting plant growth factors on

most acid soils worldwide [1]. Highly weathered acid

soils occupy 40% of the world’s arable soils [2]. They

are found mainly in South America (26.7%), North

America (19.4%), Africa (19.1%) and Asia (15.1%).

The rest occur in Australia and New Zealand, Europe

and Central America [3]. On highly acidic soils, (pH <

5.5), the rhizotoxic aluminum species, Al3+ is

solubilized, inhibiting root growth and function in the

majority of crops [4]. Al toxicity limits plant growth

Corresponding Author: Ouma Evans, Ph.D., research fields:

plant breeding and genetics. E-mail: [email protected].

mainly through its adverse effects on root growth and

development [5]. In addition, it increases drought

susceptibility and limits plant access to subsoil

nutrients, which restricts the full expression of the

genetic potential of the plant [6]. According to Giller

et al. [7], Al toxicity reduces the agronomic and

recovery efficiencies of nutrients such as P by plants.

As a result, crops grown in tropical acid soils with

high Al toxicity can only recover and utilize between

10% and 25% of the P fertilizer applied due to its high

fixations by Al and Fe oxides [8]. The level of Al

saturation in Kenyan acid soils ranges between 20%

and 45% which is too high for most crop species to

tolerate [9]. According to these authors, most

D DAVID PUBLISHING

Enhancing Maize Grain Yield in Acid Soils of Western Kenya Using Aluminium Tolerant Germplasm

34

improved maize varieties and landraces grown by

farmers are sensitive to high Al saturation (> 20%)

commonly found in most maize growing areas in the

region. This implies that such germplasm are unable

to efficiently utilize the native soil phosphorus (P) or

added P fertilizer as a result of reduction in root

growth due to Al toxicity [10]. Moreover, these

farmers incur up to 16.8% grain yield loss due to Al

toxicity [11]. Acid soils cover over 13% of maize

growing areas in Kenya [12]. In these areas

(especially the marginal rainfall medium altitude

areas), maize yields are very low, with averages of

1.0-1.5 t ha-1 compared to the research potential of

over 5.0 t ha-1 in the same regions [13]. Al toxicity is

partly responsible for the declining yields.

Conventionally, acid soils are mainly managed by

liming the top soil layer to neutralize the exchangeable

Al [14]. Besides, the use of lime is highly

recommended for the management of acid soils in

Kenya [12]. Lime reduces the levels of exchangeable

Al3+, Fe3+ and Mn4+ in acid soils and thus reduces P

sorption. This makes both the native soil P and

applied P fertilizers available for plant uptake [15].

Besides, lime is known to have longer residual effects

on acid soils compared to other soil amendments such

as organic and inorganic materials [16]. However, the

adoption of such input technologies has largely been

restricted to large scale farmers who can afford them

despite the fact that such technologies would be best

suitable for low input agriculture practiced by small

scale farmers in the maize ecosystems of Kenya. For

example, most resource-poor small holder farmers,

who are also the majority in the acid soil areas of

Kenya where maize is grown, have hardly adopted

such technologies due to lack of credit and the relative

high cost [17]. The two main sources of lime in Kenya

(Homa and Athi lime) are located approximately 250

km away from the major maize growing regions in the

country, where Al toxicity is a problem. This makes it

expensive to transport the large tonnage of lime

needed to mitigate Al toxicity in these regions.

Furthermore, the few farmers who apply lime do not

apply the recommended rates; hence this approach has

been ineffective in managing Al toxicity in these

regions [13].

There is therefore a challenge and need for

alternative, affordable and integrated approaches in

the management of the problem of Al toxicity in order

to increase maize productivity among the small holder

farmers in the marginalised areas of Western Kenya.

Selection, development and utilization of Al-tolerant

maize genotypes, together with minimal inputs, are

proposed as potentially sustainable and viable options

for managing Al toxicity in such regions.

Screening of maize genotypes in nutrient solution

using Relative Net Root Growth (RNRG) and

hematoxylin staining (HS) has been successful over

the past decade in selecting Al tolerant and sensitive

genotypes [18-20]. Root staining with hematoxylin

solution is a quick, rapid, efficient and reliable method

of discerning among Al-tolerant and Al-sensitive

maize genotypes since it is highly specific to Al

accumulation [20]. The method allows for rapid

evaluation of a large number of genotypes without

destroying the root apical meristem [21]. Besides,

field screening is one of the most direct screening

methods for tolerance to Al toxicity in cereals as it

allows a direct measurement of tolerance [22].

Accordingly, this study adopted these approaches in

assessing various maize germplasm for tolerance to Al

toxicity.

Genetic variation for aluminum (Al) tolerance in

crop species can allow the development of cultivars

that can give high yields when grown on acidic soils

with high Al toxicity problems. In fact, such traits

have been used to develop high-yielding, Al-tolerant

maize hybrids for use in acid soils [23]. Kenyan

farmers who grow maize on Al toxic soils do not yet

have access to such cultivars. Earlier screening of

Kenyan maize germplasm for Al toxicity showed that

some of the Kenyan landraces are tolerant [24]. This

study focussed on: developing maize inbred lines from


35

various sources including landraces and Brazilian

introductions which contained CATETO (Al-tolerant

Brazilian inbred line); selecting some of the inbred

lines for tolerance to Al toxicity; using them to

develop single crosses and testing the Al-tolerance in

the single crosses.


2.1 Genetic Materials Used

Maize germplasm used in this study were developed

from various sources: Kenya Agricultural Research

Institute (KARI)-Kitale, KARI-Kakamega and

KARI-Muguga. Others were Brazilian introductions to

Kenya (single crosses) and derivatives of CATETO

(Brazilian most Al tolerant inbred line) while the rest

were local collections including Al tolerant 203B

landrace, collected from Al toxic soils of Muranga

county in central Kenya. All the sources were obtained

in the year 2002 and were used to develop 175 inbred

lines between the year 2003 and 2007 (Table 1). The

inbred lines were either developed from single cross

hybrids from the various sources or from topcrosses of

these single cross hybrids crossed with the Kenyan

testers for medium and high altitude. All the sources

were individually selfed to F6 to obtain the respective

inbred lines which were screened for tolerance to Al

toxicity in nutrient culture solution according to

Magnavaca et al. [18] and also under field conditions

(0 t ha-1 and 4 t ha-1 of lime).

Fourteen inbred lines were selected for tolerance to

Al toxicity based on relative net root growth (RNRG),

hematoxylin staining (HS) and grain yield at high Al

saturation (43.1%-45%) (data not shown). The single

cross hybrids were then generated in 2009 by crossing

the selected Al tolerant inbred lines using North

Caroline II mating design as described by Comstock

and Robinson [25]. A total of 49 single crosses were

developed. One of the single crosses, however, did not

yield enough seeds and was therefore not included in

the screening work. Forty-eight single cross hybrids

and one commercial variety grown under Al toxic

soils of Western Kenya (HD614) were therefore tested

for tolerance to Al toxicity in nutrient solution culture.

CON 5, 203B and K4 were used as Al tolerant checks

while SCH 3 and REGNUR 0114 were used as

susceptible checks [11].

2.2 Description of Experimental Sites

Chepkoilel site is located at 0o34′37.24″N;

35o15′10.04″E, 2,143 m above sea level (a.s.l), and

has between 900 and 1,100 mm rainfall with a 10-26 oC temperature range. The soils are chromic ferralsols

characterized by low pH 4.8, and Al saturation of

45.6% with P levels of 4.4 mg P kg-1 of soil [13]. Sega

site is located at 0o15′N and 34o20′E. It has an

elevation of between 1,140 and 1,400 m (a.s.l) with a

bimodal annual average rainfall pattern of between

800 and 1,200 mm. The mean minimum temperature

ranges between 15 and 17 oC, while the mean

maximum range is 27-30 oC. The soils are

OrthicAcrisols characterized by low pH 4.5 and a

mean Al saturation of 43.1% and 2.2 mg P kg-1 of soil

[13].

2.3 Experimental Design and Procedures

Seeds of each line were surface sterilized in 1%

sodium hypochlorite and rinsed thoroughly with sterile

Table 1 Description of maize inbred lines used as parents of the single cross hybrids.

Original source of germplasm No. of inbred lines developed from various sources

Brazilian single crosses 95

Landrace (203B) 34

KARI-Muguga lines 18

KARI-Kakamega lines 14

KARI-Kitale lines 14

Al standards from Kenya and Brazil 5


36

distilled water to remove all traces of the hypochlorite.

The seeds were set to germinate inside paper rolls

moistened with aerated distilled water. These were

placed vertically on plastic trays covered with

aluminium foil, which were incubated in darkness for

three days in a growth chamber set at 26 ± 3 °C. The

experiment was conducted at the Botany laboratory in

Chepkoilel University College. The setup was a

completely randomized design (CRD) replicated three

times. Treatments consisted of single cross maize

hybrids (49) or inbred lines (175) and two levels of Al

(0 µM or 222 µM Al). Eight litre trays were used to

hold nutrient solution under continuous aeration.

The nutrient solution was prepared according to

Magnavaca et al. [18]. Three days old uniform-sized

seedlings with no visible injury or damage on their

roots were transferred to the cups on a perforated

styrofoam sheet and stabilized for 24 h in nutrient

solution without added Al at pH 4.0 after which the

Initial root length (IRL) was measured. The seedlings

were then transferred to fresh nutrient solution where

Al was added to the trays as Al K (SO4)2 12H2O to

attain the stated concentration which corresponds to

free Al3+ µM activities of (0) and (39) respectively

[26]. The seedlings were then grown in a growth

chamber at a photoperiod of 14 h of light and 10 h of

darkness. The day length growth room conditions

were approximately 340 µmol photons m-2 s-1 of light

intensity, 30 ± 2 °C and 70% relative humidity; the

dark conditions were 22 ± 2 °C and 90% relative air

humidity.

Seventy two hours after transplanting, final seminal

root length (FSRL) was measured and the net seminal

root length (NSRL) calculated from the difference

between FSRL and initial seminal root length ISRL

[18]. The tolerance level was assessed using relative

net root growth (RNRG), where,

RNRG = NSRL under Al treatment/NSRL under

control 100 (1)

The heterosis for the F1 single crosses was

calculated using both mid-parent heterosis (MPh) and

high parent heterosis (HPh) for comparison [27]. The

two indices were expressed in percentages as:

×F1- M

MP% = 100MP

(2)

×F1- HP

HP = 100HP

(3)

Where, F1 = performance of hybrid, MP = average

performance of both parents and HP = performance of

high parent.

Hematoxylin staining was used as a confirmatory

test for tolerance to Al toxicity in selecting the Al

tolerant inbred lines. The seedlings of 20 selected

(tolerant, moderately tolerant and sensitive) maize

inbred lines were subjected to hematoxylin staining as

described by Cancado et al. [20]. Visual scores for

root staining intensity were made on a scale of 1-5, as

follows: non-stained roots were classified as very

tolerant (Scale 1), faintly stained roots as tolerant

(Scale 2), moderately stained roots as moderately

tolerant (Scale 3), well stained roots as sensitive

(Scale 4) and those with deeply stained roots as very

sensitive (Scale 5) [20].

The experiment for screening inbred lines for

tolerance to Al toxicity under field conditions was set

up in a randomized complete block design (RCBD)

with 4 treatments in 3 replications at 2 sites. Some

plots received phosphorus (P) and lime (L) (P + L);

while others received either P (+P) or L (+L). The

control plot received neither P nor L. Phosphorus was

applied as triple super phosphate (TSP) at the rate of

26 kg P ha-1. Agricultural lime from Koru liming

company in Kisumu containing approximately 21%

CaO was applied 2 months before planting at the rate

of 4 t ha-1. CaO in the plots was to receive lime at each

site as recommended by Kisinyo et al. [13]. Planting

was done in March 2010 at Chepkoilel and Sega sites

at a spacing of 0.75 m between the rows and 0.3 m

within the row in a 3 m long plot comprising 2 rows

each. Nitrogen was used in top dressing six weeks

after planting on all the plots in the form of calcium

ammonium nitrate (CAN) at the rate of 75 kg N ha-1.

Weeding was done manually thrice and the crop


37

protected from stalk borer (Buseola fusca L.) damage

using 2-3 granules of Beta-cyhalothrin (Bulldock GR

0.05) at a rate of 6 kg ha-1 applied in the whorl of each

plant after thinning. Data was recorded on grain yield

(t ha-1) plant height (cm), ear height (cm), days to 50%

tasseling and days to 50% silking.

2.4 Statistical Analysis

The RNRG and hematoxylin staining data was

subjected to 1-way analysis of variance using the

General Linear Models procedure of Genstat and

means compared using Tukey’s range test using the

following model:

Xijk = µ +αi +Ʃij (4)

Where, Xijk: plot observation, µ: overall mean; αi:

treatment effect; Ʃi: experimental error due to

treatments [28, 29]. Grain yield and yield component

data were subjected to 2-way analysis of variance by

fitting the following model:

Xijk = µ +αi +βj +Ʃij (29)

Where, Xijk: plot observation, µ: overall mean; αi:

treatment effect; βj: block effect; Ʃij: experimental

error due to treatments and blocks [30].

Phenotypic correlation between RNRG and

hematoxylin staining and between RNRG and grain

yield were computed by regression and correlation

analysis, using Genstat software (Payne et al., 2009).

The regression and correlation were analyzed based

on the model:

Yi = βo +βiXi +Ʃi (6)

where, Yi: the ith observation of the response Y; βo:

population parameter giving the intercept; β1:

population parameter giving the slope; Ʃi: error term.

Correlation coefficient r was calculated using the

equation:

X Y

COV X,Yr =

S S (7)

where, COV (X, Y): Covariance X (predictor) and

Y = predicted parameter, Sx: standard deviation of the

predictor parameter; Sy: standard deviation of the

predicted parameter [31].


3.1 Phenotypic Variation for Tolerance to Aluminium

Toxicity among the Inbred Lines

Significant phenotypic variation (P > 0.05) in

tolerance to Al toxicity was observed among the

inbred lines based on an Al tolerance threshold of

50% RNRG (Figs. 1 and 2). Root growth inhibition

occurred in 95% of the inbred lines. However, root

growth in nine tolerant inbred lines (203B, 203B-14,

CATAL 237/67X63-5, CON 5, HASR, 203B-30, HS

53x280-16, HS 26x294-6 and 203B-15) remained

unaffected after exposure to 39 µM Al3+ (Fig. 2).

Similar observations were reported in Sesbania

(Sesbania sesban (L.) Merr, sorghum (Sorghum

bicolor (L.) Moench and in maize but at lower

concentrations of between 148 and 200 µM [32, 33].

Such resistance is partly a result of maintaining cell

wall and plasma membrane integrity [34]. Landrace

203B which was used as one of the tolerant standards

(Fig. 3a) had the highest root growth followed by

some of its derivatives, such as 203B-14 and 203B-39.

However, other inbred lines derived from the same

landrace (203B-25 and 203B-28) were among the

most Al sensitive lines. These results imply that these

lines could have initially received pollen from other

Al sensitive lines owing to the out crossing nature of

maize since the starting material was an open

pollinated variety (OPV) and hence such segregants

could have emerged. The 203B landrace and its inbred

lines remains an invaluable source of Al tolerance

which can be exploited in production of acid tolerant

maize varieties.

CON 5, which was used as another Al tolerant

standard, expressed a RNRG of 105% under similar

conditions compared to 203B, 203B-14 and others.

CON 5 is an elite homogenous population from KARI

which has been classified as Al tolerant [23]. A study

by this author indicated that 55% of tolerance to Al

toxicity in CON 5 is attributed to exclusion of Al from

the root tips owing to the activity of ZmMATE1 gene.

The highly tolerant CATAL 237/67XL3-5 is a


38

0

5

10

15

20

25

30

35

9-1

9.

20-2

9

30-3

9

40-4

9

50-5

9

60-6

9

70-7

9

80-8

9

90-9

9

100-1

09

110-1

19

RNRG (%)

Num

ber of in

div

iduals

Fig. 1 Percent of relative net root growth (RNRG) frequency distribution for maize inbred lines. The double arrowed line depicts the threshold for Al sensitivity (RNRG < 50%) and tolerance (RNRG > 50%). 175 maize inbred lines were grown in nutrient solution containing µM Al3+ for three days.

Fig. 2 Relative net root growth of selected 20 inbred lines after 3 days of exposure to Al treatment. Percent of relative net root growth (RNRG) values are the means of three replications (seven plants per replication). The error bars are standard error bars (SE). Selection was based on clustering of the means of 175 inbred lines into three homogenous categories; the inbreds therefore represented each of the categories.

Fig. 3 a, b: Root growth response to Al stress by inbred line 203B and sensitive inbred line SCH3.

O µM Al 222 µM Al O µM Al 222 µM Al

(a) 203B inbred line (b) SCH3 inbred line


39

derivative of CATETO, the Brazilian Al tolerant

standard. Studies have shown that CATETO has high

expression of ZmMATE1, the Al tolerance gene [23].

This suggests that CATAL 237/67XL3-5 may be using

a similar Al tolerance mechanism as CATETO. Studies

on CATETO have indicated that two genes

(ZmMATE1 and ZmMATE2) co-localize to major Al

tolerance Quantitative Trait Loci (QTLs) in maize [23].

As to whether the Al tolerance in 203B, CON5 and K4

is as a result of ZmMATE allele or a separate gene is

yet to be determined. Interestingly, studies by Matonyei

[23] showed that CON 5, 203B and some of its

derivatives were apparently more tolerant than

CATETO, even though, they expressed lower

ZmMATE1 activity than the latter. These findings

clearly point to the possibility that the Kenyan sources

could have a different gene in play. The least root

growth response (17%) was observed in inbred line

SCH3 (Al sensitive line from Brazil) (Fig. 3b) as

expected.

3.2 Variations in Staining Rate of Hematoxylin in

Maize Inbred Lines

The inbred lines differed significantly with regard

to hematoxylin staining adsorption when subjected to

Al stress. Al tolerant lines had lower adsorption rate

(< 3) compared to the sensitive ones (≥ 4). The very

sensitive line, A089, showed an intense dark-blue

coloration indicating deeply stained roots, the

sensitive line REGNUR 00114 showed blue

coloration in the roots indicating well stained roots,

while the tolerant line CATAL 237/67XL3-5 showed

clear root apices, i.e., non-stained roots (Figs. 4a and

b). These findings compare well with previous

observations in pea roots [36], maize roots [20, 21]

and in rice [37]. According to these authors, the

sensitive lines tend to accumulate more Al in their root

tips, hence adsorbing more hematoxylin stain. These

results into the blue coloration compared to the tolerant

lines which do not bind the hematoxylin stain and

exclude Al from the cells.

The correlation between RNRG and hematoxylin

staining showed a negative trend (Fig. 5) probably

because sensitive seedlings have low RNRG as a

result of high quantities of accumulated aluminium in

the root cap and, therefore, they normally show high

hematoxylin adsorption rate. The tolerant genotypes

have some mechanisms to avoid aluminium toxicity,

therefore, they express higher RNRG and lower

hematoxylin absorption rate. These findings are in

agreement with those of Cancado et al. [20] who

reported a strong negative correlation (r = -0.693 and

-0.816) between hematoxylin absorption rate (HS),

NSRL and RNRG, respectively.

A regression analysis of RNRG on the hematoxylin

adsorption rate indicated that 88% of all the observed

variance in tolerance could be explained by

hematoxylin adsorption rate. Therefore, the

colouration of the root apices with hematoxylin can be

employed, without restriction as an informative index

of Al tolerance.

3.3 Performance of Inbred Lines under Field

Condition and Correlations with Al Screening Data

At Sega, under control (No P, No L), the inbred

lines produced grain yields of between 0 and 2.4 t ha-1.

However, with the addition of lime (4 t ha-1), the grain

yield increased to between 0.4 and 3.9 t ha-1. Under

control (no P, no L), majority of the inbred lines (70%)

expressed grain yields of between 0.0 and 0.9 t ha-1

while the rest yielded between 1.0 and 2.4 t ha-1 (Figs.

6 and 7).

Regression of grain yield under additional

phosphorus in Al toxic soils on percent RNRG

showed positive, but non-significant trend P ≤ 0.05

with coefficient of determination (R2 = 0.24 and 0.35)

for Sega and Chepkoilel sites, respectively (Fig. 8).

However, regression of grain yields under control on

percent RNRG also showed positive trend with lower

R2 values (R2 = 0.11 and 0.30) for Sega and Chepkoilel

sites respectively (data not shown). This showed the

extent of amelioration effects of additional P on


40

Fig. 4a Mean hematoxylin staining (Hs) values of selected 20 maize inbred lines.

Fig. 4b Maize seedling root apices stained with hematoxylin stain after a 72 h exposure to 222 µM Al in nutrient solution:

CATAL 237/67XL3-5tolerant; REG NUR 00114Sensitive; A089Very sensitive.

Fig. 5 Relationship between RNRG and hematoxylin staining of selected inbred lines after exposure to Al containing 222 µM concentration for 3 days.


41

0

5

10

15

20

25

30

35

40

Nu

mb

er o

f in

bre

d li

ne

s

Inbred line grain yield ranges (t/ha)

26 kgP/ha+ 4 t/ha lime 4 t/ha lime 26 kg P/ha Control

Fig. 6 Trends in grain yield of maize inbred lines screened in Aluminium toxic soils at Sega.

Fig. 7 Effects of various treatments on maize growth at Sega site during the long rains of 2010.

Fig. 8 Relationship between grain yield with additional P in the field (26 kg P ha-1) and RNRG of maize inbred lines grown with P in nutrient solution under Al stress (222 µM Al).

tolerance to Al toxicity under field conditions. It also

showed that solution culture screening could predict

the response of maize cultivars when tested under Al

toxic soils culture by up to 35%, although this would

depend on available P and percent Al saturation in the

soil. These findings imply that plant breeders should

employ an integrated approach of using both solution

culture and field screening conditions when selecting

cultivars for tolerance to Al toxicity. The low

correlation between solution culture screening and

field screening could be due to higher interaction of

Al and P in nutrient solution since Al imposed in

nutrient solution, was higher than that found naturally

under field conditions.

These findings compareed well with those of Liao

et al. [36] who reported that P-efficient genotypes

were more Al tolerant than P-inefficient genotypes.

These authors suggested that P could help ameliorate

Control +Lime + P +L+P

(a) Sega site (b) Chepkoilel site


42

Al toxicity through Al complexation and possible

precipitation of Al in the rhizosphere, in addition to

the Al-P interactions in the root apoplast.

The coefficient of determination (R2 = 24%)

observed in Sega was much lower than the one

observed at Chepkoilel (R2 = 35%) probably because

of the lower available soil P levels at Sega (2.2 mg P

kg-1 of soil) compared to Chepkoilel (4.4 mg P kg-1 of

soil).

3.4 Phenotypic Variation for Tolerance to Aluminium

Toxicity among Single Crosses

The phenotypic expression of NSRL and RNRG

showed transgressive inheritance. The F1s showed

positive, negative and no heterosis (Table 2). Most of

the F1s (58%) were more tolerant to Al toxicity than

either of their parents (Table 3). This can be attributed

to heterosis for RNRG in which the hybrid F1

exhibited a RNRG that is superior to the means of the

two parents (mid-parent heterosis), or the better of the

two parents (better/high-parent heterosis) [39]. The

genetic basis of heterosis includes dominance, over

dominance or epistatic gene effects [40].

The remaining 42% of the single crosses were not

heterotic for RNRG. This observation could have

been due to negative transgressive inheritance

where the offspring performed worse than both

parents. HD614, a Kenyan commercial variety bred

for high altitude areas, was found to be among the

moderately tolerant accessions; however, 32% of

the single crosses developed were more tolerant

than this variety. The great genetic potential for Al

tolerance expressed in the F1 single crosses could be

exploited further to develop varieties (Double

crosses, 3-way crosses and synthetics) with

tolerance to Al toxicity. These may be more

attractive to farmers growing maize in the acid soil

regions of Kenya. Fig. 9 shows root growth

response of selected single cross maize hybrids in

Al stress.

Table 2 Mid-parent and high-parent heterosis of selected F1 single cross maize hybrids tested for tolerance to Al toxicity in nutrient solution.

F1 Single crosses NRL 0 µM Al NRL 222 µM Al RNRG

MPh (%) HPh (%) MPh (%) HPh (%) MPh (%) HPh (%)

KML 036 MUL 863 13.85 -15 134 92.7 110.8 90.1

S596-41-2-2 REG 007-361 -3.8 10.6 57.5 29.9 63.2 37.9

KML 036 S396-15-1 -40 -43.2 -2.1 -20.6 55.9 19.4

MUL 863 MUL 1007 72 32.8 115.4 67.7 50 35.4

MUL 125 POOLB 26-1 -47.6 -64.5 36 -56.6 39.6 24.6

MUL 817 MUL 863 134 87 100 83.4 34 26.7

MUL 817 MUL 216 51 15.8 101.27 80.5 33.3 14.2

MUL 817 MULX125 4.5 -27.2 8.8 -27.3 23.3 13.8

MUL 822 S558-2-2-3-7 19.5 -13.4 -1.7 -4.4 23 14.2

CML 181 MUL 817 116.4 108 146.9 134.1 18.75 5.5

MUL 216 CML 202 44.9 -18.4 35 14.2 14 -8

KML 026 MUL817 219 183.2 237 209.5 2.8 -15.2

MUL 125 MUL 863 23.4 -18.3 7.5 -31 -0.8 -12.3

REG N007-361 MUL 817 110.8 100 102.2 93.5 -7 -8.6

MUL 116 MUL 104 -12.6 -14.2 -4.3 -13.9 7.6 5.6

CML 181 REG N007-361 79.6 65.5 90.7 73.5 -10.7 -19.4

POOL B26-1 MUL 817 65.3 35.8 27.2 12.9 -22 -25

POOL A6-1 CML 202 108.3 95.2 67.2 54.5 -22.5 -22.5

MUL 817 S558-2-2-3-7 88.6 69.9 0 -9.3 -41 -47

RNRG: Relative net root growth, NSRL 222 µM Al Net seminal root length in Al at 222 µM concentration; NRL0µM A Net

seminal root length at no Al; MP%Percent mid-parent heterosis; HP%Percent high parent heterosis.


43

Table 3 Means for net root lengths, relative net root growth, root reduction and Al tolerance status of selected maize single crosses and their parents.

Single crosses and Parents

Net root Net root Relative Percent Al

Length Length Net root Root Status

0 µM 222 µM Growth Reduction

KML 036 MUL 863 37.8a-h 34.7j-o 0.97g 3.2a T

KML 036 S396-15-1 25.0a-c 23b-m 0.92fg 7.6 ab T

KML O26 20.2a 16.7a-h 0.85e-g 14.6a-c T

MUL 863 MUL 1007 53.1e-j 34.9k-o 0.84d-g 15.7a-d T

MUL 125 POOLB 26-1 23.8a-c 17.8a-i 0.81c-g 19.3a-e T

MUL 817 MUL 125 48.8a-i 30.1g-n 0.74b-g 25.9a-f T

S558-27-2-1 29.4a-f 17.1a-i 0.68a-g 32.2 a-g MT

MUL 125 67.1h-j 41.4n-p 0.65a-g 34.5 a-g MT

MUL 817 MUL 216 57.2e-i 31.6i-o 0.64a-g 35.8 a-g MT

MUL 1007 39.9a-h 20.8a-k 0.62a-g 37.8 a-g MT

CML 202 23.7a-c 12.1a-d 0.62a-g 38.4 a-g MT

MUL 822 33.4a-g 18a-i 0.6a-g 39.5 a-g MT

POOL A6-1 27.1a-d 14.3a-f 0.6a-g 39.7 a-g MT

REG 007-361 23.7a-c 12.7a-e 0.58a-g 41.6 a-g MT

CML 181 REG N007-361 47.6a-i 26.9e-n 0.58a-g 41.9 a-g MT

MUL 817 REG 007-361 52.6c-i 28.7f-n 0.58a-g 42.3 a-g MT

MUL 216 CML 202 40.3a-h 20a-j 0.57a-g 43.1 a-g MT

MUL 125 MUL 863 54.8d-i 28.5f-n 0.57a-g 43.1 a-g MT

MUL 817 26.3a-d 13.9a-f 0.56a-g 43.6 a-g MT

MUL 116 MUL 104 44a-h 22.8b-l 0.56a-g 44.4 a-g MT

MUL 125 MUL 1007 57.3e-j 28.2f-n 0.55a-g 44.8 a-g MT

MUL 228 MUL 216 64.3h-j 33.2j-o 0.53a-f 47.1 b-g MT

MUL 116 49.6a-i 21.2a-k 0.53a-f 47.1 b-g MT

REG N007-361 MUL 817 52.7c-i 26.9e-n 0.53a-f 47.4 b-g MT

POOL B26-1 37.4a-h 14.4a-f 0.52a-f 47.9 b-g MT

POOL A6-1 CML 202 52.9c-i 22.1b-l 0.48a-e 52.2 b-g S

S558-2-2-1-4 87.1j 37.8m-p 0.43a-d 57.1 c-g S

POOL B26 - 1 MUL 817 50.9b-i 20.1a-k 0.42a-d 57.9 d-g S

KML 036 44.3a-h 18.3a-k 0.42a-c 58.4 e-g S

S596-41-2-2 25.3a-d 8.5ab 0.41a-c 59.2 e-g S

MUL 216 49.4a-i 17.5a-i 0.41a-c 59.2 e-g S

POOL A6-1 S558-2-2-1-4 49.6a-i 17.9a-i 0.39a-c 61.1 e-g S

MUL 817 S558-2-2-3-7 48.1a-i 15.5a-g 0.37ab 63.3fg S

REG NUR-00114 23.5a-c 7a 0.32a 68.3g S

Grand mean 42.6 23.3 0.62 38 S

SE 0.8 0.4 0.01 1.1

Means in the same column followed by the same letter are not significantly different at P ≤ 0.05 according to Tukeys range test.

Ttolerant to Al toxicity; MTmedium tolerant to Al toxicity; Ssensitive to Al toxicity

4. Conclusions

There is a wide variation for tolerance to Al toxicity

among the inbreds and the single crosses. Using this

variation, this study has developed both Al tolerant

inbred lines and single crosses from diverse sources.

Nutrient culture screening for Al toxicity can predict

field selection under Al toxic soils by between

24%-35% depending on the Al saturation of the

particular soil and the levels of available phosphorus.

This implies that plant breeders should employ an

integrated approach of using both solution culture and


44

Fig. 9 Root growth response to Al stress by the sensitive Al standard (REG NUR-00114) and the most tolerant Single cross

(KML 036 MUL 863).

field screening conditions when selecting cultivars for

tolerance to Al toxicity. Some of the Kenyan inbreds

identified in this study were more tolerant than the

inbreds derived from CATETO. These include 203B

and some of its derivatives which remain the most Al

tolerant genotype among Kenyan maize germplasm.

Additionally, some of the single cross hybrids

identified in this study showed superior tolerance to

Al toxicity and could be used directly or as parental

material for future hybrids for acid soils. They include:

KML 036 MUL 863, KML 036 S396-15-1, MUL

863 MUL 1007, MUL 125 POOLB 26-1, MUL 817

MUL 125.

Acknowledgments

The authors acknowledge financial support from

Generation Challenge (GCP) project, KARI and

EMBRAPA for providing the initial germplasm for

the study and Moi University for the Research

facilities used to conduct the research.

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Response of Peach (Prunus persica) cv. to Foliar

Application of Potassium and Copper

Shawkat Mustafa Mohammed Al-Atrushy and Sarfaraz Fatah Ali Al-bamarny

Department of Horticulture, Faculty of Agriculture and Forestry, University of Duhok, Iraq


Abstract: The experiment was carried out in a private orchard situated at Atrush town, Duhok Governorate Kurdistan Region-Iraq during 2011 season to study the effect of foliar application of three concentrations of potassium (0.0%, 0.5% and 1%) and three

concentrations of copper (0.0%, 0.02% and 0.04%) on an eight years old peach cultivar, planted in clay soil, spaced at 4.0 m 4.0 m.

The foliar application was done twice, on April 24, 2011 and May 25, 2011. The results showed that spraying of potassium at both concentration (0.5% and 1%) or copper at high concentration (0.04%) had a positive effect on leaf area, leaf fresh weight, leaf dry weight, total chlorophyll, fruit weight, fruit number and yield per tree as well as fruit diameter, pith thick, pulp weight, seed weight and total soluble solid. The interaction between potassium and copper significantly enhanced all detected traits, since trees receiving 1% and sprayed with 0.04% of copper was characterized by the highest values of all growth and yield characteristics compared to the lowest values at untreated trees (control). Key words: Potassium, copper, peach, Atrush.

1. Introduction

The peach tree (Prunus persica) is a species of

Prunus native to China that bears an edible juicy fruit

called a peach [1]. It is a deciduous tree growing to

4-10 m tall, belonging to Rosaceae family.

The scientific name Persica, along with the word

“peach” itself and its cognates in many European

languages, derives from an early European belief that

peaches were native to Persia [2]. The modern

botanical consensus is that they originate in China,

and were introduced to Persia and the Mediterranean

region along the Silk Road before Christian times [3].

All commercial cultivars belong to P. persica L.

Batsch, are primarily grown in temperate zones

between latitudes 30º and 45º N and S and in the

tropics and subtropics at higher elevation [4].

Potassium has many general functions in plants, it

is involved in the synthesis of proteins, where it plays

Corresponding author: Sarfaraz Fatah Al-Bamarny, assistant professpr, research fields: pomlogy, fruit production and improving fruit quality. E-mail: [email protected].

several roles, including the assisting in the transport of

amino acids to the sites of protein synthesis,

Potassium activates a number of enzymes and the

promotion of normal cell division and growth,

potassium improves health and resistance to disease

and adverse environmental conditions, like drought,

cold and flooding. Potassium also helps to regulate

both the electrical balance and the water balance

within the plant [5].

Copper, affects on plant physiology at wide ranging,

including interference with fatty acid and protein

metabolism and inhibition of respiration and nitrogen

fixation processes. At the whole plant level, Cu is an

effective inhibitor of vegetative growth and induces

general symptoms of senescence. Latter appears to

constitute the most widespread response of plants to

stresses provoked by metals, including Cu [6].

Numerous researchers studied the effect of various

concentrations of potassium and copper on peach in

aim to improve its yield and quality. Leece [7] studied

the effects of fertilizer nitrogen, phosphorus and

D DAVID PUBLISHING

Response of Peach (Prunus persica) cv. to Foliar Application of Potassium and Copper

48

potassium on the leaf composition on Hale-haven

peach trees, on a sandy loam soil. Fertilizer nitrogen

increased the leaf concentrations of nitrogen, iron,

copper, manganese and zinc, and decreased the

concentrations of potassium, calcium, magnesium and

boron. Effects of fertilizer phosphorus and potassium

on leaf composition were very slight and would not

have been of practical importance in diagnosis by leaf

analysis. Awasthi [8] found that application of 500,

600 and 700 g K2O tree-1 progressively increased

significantly the fruit yield and weight; Potassium

application affected fruit quality by significantly

increasing total soluble solids and fruit sweetness and

decreased titratable acidity. Ahmed et al. [5] studied

the effect of adding potassium via foliage at

0.25%-1.0% and/or via fertigation at 0.25-1 g vine-1

on growth and fruiting of flame seedless grapevine.

Results showed that adding potassium via foliage or

fertigation was very effective in improving growth

characters and yield compared with control treatment.

Chatzitheodorou1 et al. [9] studied the response of the

peach cultivars “Spring Time” and “Red Haven”

grown in clay loam soil, to nitrogen, phosphorus and

potassium fertilizers, manure, as well some

combinations of these. They noted that significant

increase on fruit yield as well as on fruit quality and

fruit size of both cultivars. However, total soluble

solids content (%) of the cultivars “Spring Time” and

“Red Haven” did not alter significantly in comparison

to the control for all the fertilizer combinations used.

Mimoun et al. [10] studied the effects of potassium

foliar spray on peach cultivar Royal Glory grafted on

GF677 Rootstocks and the plum cultivar Black Star

grafted on Mariana rootstocks. At the beginning of the

season, result showed that the use of potassium foliar

fertilization increased fruit weight, total soluble solid

and improved fruit quality of Black Star plum and

Royal Glory peach, at harvest indicates that the fruit

maturity was earlier with the foliar application.

Al-Dulaimi [11] showed that foliar application of

copper at 10-20 mg L-1 to pear cv. Le-Conte caused

significant increases in growth characters as well as

yield and its physical and chemical characteristics

compared with control treatment. Al-Atrushy [12]

studied the effect of copper sulphate at 0.02 and 0.04 g

Cu L-1 on growth and yield of grapevine cv. Zark. His

results indicated that spraying with copper at 0.04 g

Cu L-1 was superior in all vegetative growth

characteristics, yield as well as physical and chemical

characteristics of fruits.

The objectives of this are to study the effect of

foliar application of potassium and copper on the

vegetative and yield of peach cv. Dexired under the

conditions of Atrush region conditions.


This experiment was conducted during 2011 season

on peach trees (Prunus persica L.) cv. Dexired. Trees

were selected to be as uniform as possible in vigor and

grown in a private orchard situated at Atrush town,

Duhok Governorate-Iraq. The trees were 8 years old

planted in clay soil spaced at 4.0 m 4.0 m, the trees

were trained on open central vase form system with

four primary scaffold branches. This experiment

included two factors; the first factor included the

following three concentrations of potassium (0%,

0.5% and 1%). The second factor was represented by

three concentrations of copper (0%, 0.2% and 0.4%).

So, the experiment involved nine various treatments.

A completely randomized blocks design was followed

in the experiment arrangement and every treatment

was done on the same trees. Every treatment consisted

of one tree per replicate with three replications, so the

number of trees used was 27 trees.

A detergent powder as wetting agent at 1-2 g L-1

was added to all the spraying solution including 0.0%

control to reduce surface tension of solution. The

sprays were done to drip point at two times on April

24, 2011 and May 25, 2011, using 16 L hand sprayer.

Horticultural practices were used as usual. Potential

effects of potassium and copper were evaluated in

terms of the change in growth tree; leaf area was


49

calculated by Leaf area meter [13], leaf dry weight,

chlorophyll content according to ASPD, yield and

fruits quality. All results were analyzed statistically by

using SAS programs [14]. Duncan’s multiple tests at

5% level of portability was to compare the treatment

according to Al-Rawi and Khalafalla [15].


3.1 Vegetative Growth Characteristics

Data presented in Table 1 shows that leaf area, leaf

fresh and dry weight and total chlorophyll for trees

sprayed with potassium are superior significantly on

that untreated trees. The highest area leaf, fresh and

dry weight and total chlorophyll (15.17 cm2, 0.881 g,

0.497 g and 52.4%) respectively, were given by

spraying trees with potassium at level (1%) compared

with the lowest values (13.05 cm2, 0.815 g, 0.426 g

and 40.9%) respectively at untreated trees. Various

levels of potassium were also differed significantly

among each others. These results are in agreement

with what has been concluded by the researchers [7, 8].

The significant effect of spraying potassium may be

due to the main role of potassium in the synthesis of

proteins and activates a number of enzymes and the

promotion of normal cell division and growth, which

are important components in the synthesis of

chlorophyll [2]. Data in the Table 1 also show that the

leaf area, leaf fresh and dry weights and total

chlorophyll for trees sprayed with copper are superior

significantly on that untreated. Highest values (14.72

cm2, 0.880 g, 0.488 g and 50.4%) respectively, were

obtained in trees sprayed with copper at 0.04%

compared with the lowest values (13.33 cm, 0.813 g,

0.424 g and 41.8%) respectively at untreated trees.

Various levels of copper were also differed

significantly among each others, except these of leaf

area do not show significant differences between the

two levels of copper. The reason behind the increase

of leaf area, leaf fresh and dry weight and total

chlorophyll with increasing copper levels could be due

to do the positive role of copper in the process of

photosynthesis, through the entering in the structure of

proteins private chloroplast [12, 16] which considered

a part of the cycle of electron transition that linking

Table 1 Effect of foliar application with potassium and copper on vegetative growth characteristics of peach (Prunus persica L.) cv.

Treatment Parameters

Potassium Leaf area Leaf fresh Leaf dry Total

(%) (cm2) Weight (g) Weight (g) Chlorophyll

0.0 13.05 c 0.815 c 0.426 c 40.9 c

0.5 13.95 b 0.846 b 0.450 b 46.0 b

1.0 15.17 a 0.881 a 0.497 a 52.4 a

Copper (%)

0.0 13.33 b 0.813 c 0.424 c 41.8 c

0.02 14.12 a 0.850 b 0.462 b 46.9 b

0.04 14.72 a 0.880 a 0.488 a 50.7 a

Potassium × Copper

K 0 × Cu 0 12.30 e 0.759 d 0.400 e 35.1 d

K 0.0 × Cu 0.02 13.10 de 0.833 bc 0.427 de 43.0 c

K 0.0 × Cu 0.04 13.75 cd 0.854 bc 0.451 cd 44.7 bc

K 0.5 × Cu 0.00 13.21 de 0.825 c 0.425 de 40.1 cd

K 0.5 × Cu 0.02 14.07 d-d 0.851 bc 0.456 cd 45.0 bc

K 0.5 × Cu 0.04 14.57 bc 0.862 bc 0.469 cd 52.9 a

K 1.0 × Cu 0.00 14.49 bc 0.855 bc 0.445 cd 50.3 ab

K 1.0 × Cu 0.02 15.20 ab 0.866 b 0.504 b 52.6 a

K 1.0 × Cu 0.04 15.83 a 0.923 a 0.542 a 54.3 a

Means with the same letter are not significantly different according to Duncan multiple ranges test at 5% level.


50

both systems of photosynthetic reaction to the process

of photosynthesis [17] and the exploitation of these

materials in increase growth characteristics.

For the interaction, data in Table 1 show that the

highest value of leaf area, leaf fresh and dry weight

and total chlorophyll (15.83 cm2, 0.923 g, 0.542 g and

54.3%) were obtained in trees spraying with

potassium at 1% and copper at 0.04% compared with

the lowest value (12.30 cm2, 0.759 g, 0.400 g and

35.1%) in the untreated trees.

3.2 Yield and Fruit Characteristics

Data in Table 2 indicated that spraying of 0.5% and

1% of potassium, 0.02 and 0.04 of copper

progressively increased fruit weight and yield per tree

over amounts obtained with control. Fruit weight and

yield per tree increased significantly as potassium

application was raised from 0.5% to 1% and copper

from 0.02 to 0.04. The highest fruit weight and yield

were 99.71, 98.94 g and 20.10, 19.94 kg tree-1 with 1%

potassium and 0.04% copper, respectively. Negligible

increase was occurred on number of fruit per tree with

potassium and copper application. Whereas,

potassium application beyond 1% and copper beyond

0.04% only increased fruit diameter. Yield, fruit

weight and diameter and number of fruit per tree

increased with increasing the rate of application of

potassium may be due to the role of potassium in

activating meristematic growth, photosynthesis and

activates a number of enzymes, including those

involved in the synthesis of carbohydrates, and is also

involved in the neutralization of organic acids and the

promotion of normal cell division and growth [8, 10,

18]. The reason beyond the effect of copper on

increasing yield, fruit weight and diameter and

number of fruit per tree may be due to the role of

copper in influencing photosynthesis [19] and provide

important materials that have helped to improve the

qualities of fruits [20].

For the interaction, data presented in Table 2 clearly

show that the highest value of fruit weight, fruit

number, yield per trees and fruit diameter (105.26 g,

203.5, 21.41 kg tree-1 and 57.87 cm) were obtained in

trees sprayed with potassium at 1% and copper at

Table 2 Effect of foliar application with potassium and copper on yield and fruit characteristics of peach (Prunus persica L.) cv.


Potassium Fruit weight Fruit number Yield Fruit diameter

(%) (g) (Fruit/Tree) (kg/Tree) (cm)

0.0 85.66 c 194.4 a 16.65 c 52.17 b

0.5 93.42 b 200.8 a 18.76 b 53.22 b

1.0 99.71 a 201.7 a 20.10 a 56.68 a

Copper (%)

0.00 86.96 c 196.1 a 17.05 c 51.78 c

0.02 92.89 b 199.2 a 18.52 b 54.27 b

0.04 98.94 a 201.6 a 19.94 a 56.01 a

Potassium × Copper

K 0 × Cu 0 77.09 e 194.4 a 14.99 e 49.70 e

K 0.0 × Cu 0.02 84.89 d 194.8 a 16.55 de 52.44 ef

K 0.0 × Cu 0.04 95.01 bc 193.9 a 18.40 bc 54.37 ce

K 0.5 × Cu 0.00 89.19 cd 194.4 a 17.31 cd 50.58 fg

K 0.5 × Cu 0.02 94.52 bc 200.6 a 18.96 bc 53.29 de

K 0.5 × Cu 0.04 96.55 b 207.4 a 20.02 ab 55.81 ac

K 1.0 × Cu 0.00 94.59 bc 199.3 a 18.85 bc 55.07 bd

K 1.0 × Cu 0.02 99.26 ab 202.1 a 20.04 ab 57.09 ab

K 1.0 × Cu 0.04 105.26 a 203.5 a 21.41 a 57.87 a



51

(0.04%) level as compared with the lowest values

(77.09 g, 194.4, 14.99 kg tree-1 and 49.70 cm) in the

untreated trees.

3.3 Fruit Quality Characteristics

Data in Table 3 clearly shows that foliar application

of potassium at 0.5% and 1% was accompanied with

improving quality of the peach fruits in terms of

increasing pith thick, pulp weight, seed weight and

total soluble solids percentage. The best results were

obtained by the addition of potassium via leaves at 1%.

Copper sprays also was of measurable influence on

fruits quality in terms of increasing pith thick, pulp

weight, seed weight and total soluble solids percentage

and the promotion on quality of the fruits was

correlated with increasing concentration of copper

application, the highest values of pith thick, pulp

weight, seed weight and total soluble solids percentage

resulted in fruits of trees received copper at 0.04%.

For the interaction, the best results were regarded

when potassium was sprayed at 1% and copper at

0.04%, the highest values of pith thick, pulp weight,

seed weight and total soluble solids percentage (19.87

g, 94.00 g, 1.26 g and 14.84%) respectively, were

detected on trees received potassium at 1% and copper

at 0.04%, compared with the lowest values (14.39 g,

69.43 g, 7.66 g and 12.00%) respectively, at the

control treatment. The increases in fruit quality traits

may be due to the role of potassium influencing

meristematic growth, photosynthesis and activates a

number of enzymes, including those involved in the

synthesis of carbohydrates, and is also involved in the

neutralization of organic acids and the promotion of

normal cell division and growth [8, 10, 21].

The positive effects of copper on fruit quality of

peach could be due to increase the process of

photosynthesis and other enzymatic processes, which

reflected in the processing of fruits materials

necessary to improve fruit quality characteristics [11].

4. Conclusions

According to the experimental results of this study,

the most important conclusions can be expressed as

follows:

Table 3 Effect of foliar application with potassium and copper on fruit quality characteristics of peach (Prunus persica L.) cv.


Potassium Pith thick Pulp weight Seed weight TSS

(%) (mm) (g) (g) (%)

0.0 15.32 b 76.92 c 8.75 b 12.84 c

0.5 17.48 a 84.10 b 9.32 b 13.40 b

1 18.90 a 89.26 a 10.44 a 14.25 a

Copper (%)

0 16.13 b 78.20 c 8.75 b 12.77 c

0.02 17.41 ab 83.29 b 9.60 ab 13.64 b

0.04 18.16 a 88.79 a 10.16 a 14.09 a

Potassium × Copper

K 0 × Cu 0 14.39 d 69.43 e 7.66 d 12.00 e

K 0.0 × Cu 0.02 15.63 cd 76.08 d 8.81 cd 13.14 d

K 0.0 × Cu 0.04 15.95 bd 85.24 bc 9.77 ac 13.38 cd

K 0.5 × Cu 0.00 16.12 bd 79.94 cd 9.25 bd 12.53 e

K 0.5 × Cu 0.02 17.65 ac 85.25 bc 9.27 bd 13.63 bd

K 0.5 × Cu 0.04 18.66 ac 87.11 b 9.44 bc 14.03 b

K 1.0 × Cu 0.00 17.87 ac 85.25 bc 9.35 ac 13.76 bc

K 1.0 × Cu 0.02 18.95 ab 88.53 b 10.73 ab 14.16 b

K 1.0 × Cu 0.04 19.87 a 94.00 a 11.26 a 14.84 a



52

Potassium and copper markedly increased leaf area,

leaf fresh weight, leaf dry weight, total chlorophyll,

fruit weight, fruit number and yield per tree as well as

fruit diameter, pith thick, pulp weight, seed weight and

total soluble solid.

Potassium at 1% allowed maintenance of yield

without important loss in fruit quality.

Potassium when applied at 1% and Cu at 0.4%,

markedly increased yield and hence fruit quality such

as pith thick, pulp weight, seed weight and TSS

percent.

References

[1] Thacker, Christopher, The history of gardens, Berkeley: University of California Press, 1985, p. 57, ISBN9780520056299.

[2] Wikipediam, Grape Wikipedia, the free encyclopedia, 2011, pp. 1-5.

[3] A. Huxley, New RHS Dictionary of Gardening, Macmillan, 1992, ISBN 0-333-47494-5.

[4] F.A. Hammerschlag, Peach growing and germplasm in china, Acta Hort. 173 (1986) 51-55.

[5] H. Ahmed, Abd-Elaal, F. Faissal Ahmed, The necessity of potassium for ‘Flame Seedless’ grapetrees irrigated with saline water, The fifth Arabian Horticulture Conference, Ismailla, Egypt, 2001, pp. 75-82.

[6] Anon, Micronutrient Fertilizer, Satyajit Chemicals Pvt.1td., 2002, pp. 1-3.

[7] D.R. Leece, Effects of fertilizer nitrogen, phosphorus, and potassium on leaf composition of peach, Australian Journal of Experimental Agriculture and Animal Husbandry 16 (82) (1996) 775-779.

[8] R.P. Awasthi, V.P. Bhutani, M.S. Mankotia, N.S. Kith, G. Dev, Potash improves the yield and quality of July Elberta peach, Better Crops Intern. 12 (1998) 30-33.

[9] I.T. Chatzitheodorou1, T.E. Sortiropoulosi, G.I. Mouhtaridou1, D.A. Greece, Effects of nitrogen, phosphorus and potassium on fruit drop, fruit size and total yield of peach, Pomology Institute, Naoussa, Greece, 2004.

[10] B.M. Mimoun, M. Ghrab, M. Ghanem, O. Elloumi, Effects of Potassium Foliar Spray on Olive, Peach and Plum, Part 1: Olive Experiments, Research Findings 17 (2008) 14-17.

[11] M.N.H. Al-Dulaimi, Response of pear cv. ly-count to foliar-feeding with Zink and copper Master Thesis, Faculty of Agriculture, University of Tikrit, Iraqm, 2000.

[12] S.M. Al-Atrushi, Effect of eyes number and foliar spray

of Potassium and Copper on the vegetative growth,

productivity and quality of Grape (Vitis vinifera L.) cv.

Zark under non-irrigated condition, Ph.D. Thesis, The

Council of the College of Agriculture and Forestry,

University of Mosul. Iraq, 2009.

[13] Leaf area meter AM 300: ADC BioScientific Ltd. 1st

Floor Charles House, Furlong Way, Great Am-well,

Hertfordshire SG12 9TA, UK.

[14] SAS programs, Proprietary soft ware release, 6.12 TS

Licensed to North Carolina state University, By SAS

Institute Inc., Cary. USA, 2007.

[15] M.K. Al-Rawi, M.A. Khalafalla, Agricultural experimental design and analysis, Ministry of Higher Education and Scientist Research, Mosul University, Iraq, 2000.

[16] W. Bergmann, Nutritional disorder of plant development, visual & analytical diagnosis-jena. Stuttgart, NewYork: G. Fischer, 1992, pp. 204-282.

[17] S.N.A. AL-Niemi, Fertilizers and soil fertility Dar- AL- kutub publication, Mosul Univ. Iraq, 1999.

[18] M.S. Khan, F.K. Wazir, M. Ayaz, Effect of nitrogen, phosphorus and potassium on fruit drop, fruit size and total yield of peach, Sarhad j. Agric. 16 (2000) 25-32.

[19] A. Gobara, Response of Le-conte Pear trees to foliar

application of some nutrient. (Egypt) Hort. Dept. Fac.

Agric. Minia University, Hort. 25 (1) (1998) 55-70.

[20] M.A.H. Abdel Hady, A.H. Ibrahim, Effect of

usingascorbic acid with some macro and micronutrients

on yield and quality of ‘Red Roomy’ grapes, The Fifth

Arabian Horticulture Conference, Ismailia, Egypt, Mar.

24-28 (2001) 9-15.

[21] K.C. Taylor, Stone Fruit Horticulturist, 21 Dunbar Road, Byron, Georgia, The University of Georgia and Ft. Valley State University, the U.S. Department of Agriculture and Counties of the State Cooperating, 2005.


Carboxylesterase and Glutathione-S-Transferase (GST’s)

Induced Resistance to Bacillus thuringiensis Toxin

Cry1Ab in Rice Leaf Folder, Cnaphalocrocis

medinalis (Guenee) Populations

Veegala Ramesh Babu1, Vemuri Shashi Bhushan1, Chintalapati Padmavathy2, Muthugonder Mohan2, Sena

Mahendran. Balachandran3 and Bellamkonda Ramesh1

1. AINP on Pesticide Residues, Acharya N.G. Ranga Agricultural University, Andhra Pradesh, Rajendranagar, Hyderabad 500030,

India

2. Division of Crop Protection, Directorate of Rice Research, Rajendranagar, Andhra Pradesh, Hyderabad 500030, India

3. Division of Crop Improvement, Directorate of Rice Research, Rajendranagar, Andhra Pradesh, Hyderabad 500030, India

Received: July 9, 2012 / Published: January 20, 2013.

Abstract: The rice leaf folder (RLF), Cnaphalocrocis medinalis (Guenee) (Insecta: Lepidoptera: Pyralidae), is an important pest, widely distributed in many rice growing areas of Asia. The over-use of broad-spectrum chemical insecticides has been cited as a major cause of outbreaks of C. medinalis as excessive spraying of insecticide disrupts natural biological control insecticides still remain the major control tactics against leaf folder. Carbofuran and fenthion, bendiocarb, acephate, carbosulfan, quinolphos, monocrotophos, phosphamidon and fenvalerate are the common ones used against rice leaf folder. Genetically, modified rice lines expressing B. thuringiensis insecticidal crystal proteins produced are highly tolerant to leidopteran pests. Though economic and environmental benefits of GM crops is well established, the matter of concern is the possibility of target insect pest developing resistance to this B. thuringiensis insecticidal toxins, evident from many laboratory and field experiments against many insect pests. The involvement of GSH S-transferase, carboxylesterase, and microsomal monooxygenase in insecticide resistance has been reported in insecticide-resistant strains of many insect species. Hence, the present study was taken up to monitor for cross resistance between B. thuringiensis cry toxins and synthetic insecticides in larvae of leaf folder as it is mediated by carboxylesterase titre and other enzymes by bioassay for two selected rice leaf folder field populations at the Entomology division of Directorate of Rice Research which showed 2-fold resistance ratio. Qualitative and quantitative changes of carboxylesterase (CarE) and glutathione-s-transferase (GST’s) were worked out with midguts extracts of the two C. medinalis populations in the presence of α-napthyl acetate and chlorodi-nitro benzene substrates. Key words: Cnaphalocrocis medinalis, carboxylesterase and glutathione-s-transferase, isozymes, B type esterases.

1. Introduction

Carboxylesterases (CES, EC 3.1.1.1) are members

of a superfamily of serine hydrolases that hydrolyze

ester, amide and carbamate bonds. Several different

CarE genes exist with evidence of multiple gene

Corresponding author: Vemuri Shashi Bhushan, Ph.D.,

research fields: entomology, insect toxicology and pesticide residues. E-mail: [email protected].

duplication in insects. Esterases hydrolyse ester bonds

from various substrates with a carboxylic ester.

Esterases are frequently implicated in the resistance of

insects to organophosphorus, carbamates, pyrethroids,

neonicotinoids and many other new classes of

insecticides through gene amplification, up regulation,

coding sequence mutations or a combination of these

mechanisms [1].

D DAVID PUBLISHING

Carboxylesterase and Glutathione-S-Transferase (GST’s) Induced Resistance to Bacillus Thuringiensis Toxin Cry1Ab in Rice Leaf Folder, Cnaphalocrocis medinalis (Guenee) Populations

54

The rice leaf folder (RLF), Cnaphalocrocis

medinalis (Guenee) (Insecta: Lepidoptera: Pyralidae),

is an important rice pest, widely distributed in many

rice growing areas of Asia [2]. There have been

frequent and serious outbreaks of this pest in many

countries including India, Korea, Japan, China,

Malaysia, Sri Lanka and Vietnam [3]. The over-use of

broad-spectrum chemical insecticides, such as methyl

parathion, monocrotophos and endosulfan has been

cited as a major cause of outbreaks of C. medinalis

because excessive spraying of insecticide disrupts

natural biological control [3]. Insecticides still remain

the major control tactics against leaf folder. Carbofuran

and fenthion [4], bendiocarb, acephate and carbosulfan,

quinolphos, monocrotophos and phosphamidon [5] and

fenvalerate [6] were the common insecticides used

against the control of rice leaf folder.

Genetically, modified rice lines expressing B.

thuringiensis insecticidal crystal proteins have been

produced that are highly tolerant to leidopteran pests.

In China, three GM rice lines transformed with

cry1Ac/cry1Ab genes (GM Minghui 63),

cry1Ac/CpTI genes (GM Minghui 86) and cry1Ab

genes (GM Kemingdao) effective against S. incertulus,

C. medinalis and C. suppressalis are tested both at

field and laboratory levels and are on verge of

commercialization [7-9]. Though economic and

environmental benefits of GM crops is well

established, the matter of concern is the possibility of

target insect pest developing resistance to this B.

thuringiensis insecticidal toxins as it is evident from

many laboratory and field selection experiments

against many insect pest. Though a couple of

resistance mechanisms have been reported for

conferring resistance to B. thuringiensis viz. reduced

binding of the crystal toxins to the brush border

membrane vesicles (BBMV’s) of midgut epithelium

and alteration in the midgut proteases that cleave the

protoxin to active toxin. Recent report indicates that a

new resistance mechanism to B. thuringiensis cry

toxins is identified and associated with increased

activity of midgut carboxylesterase activity [10]. The

involvement of GSH S-transferase, carboxylesterase,

and microsomal monooxygenase in insecticide

resistance has been reported in insecticide-resistant

strains of many insect species. Hence, the present

study was taken up to monitor if any cross resistance

between B. thuringiensis cry toxins and synthetic

insecticides occur in larvae of leaf folder as is

mediated by carboxylesterase titre and other enzymes.


2.1 Insecticide Bioassay

Two field populations of C. medinalis were

collected from Directorate of Rice Research,

Rajendranagar and ICRISAT, Patancheru. C.

medinalis adults were collected from rice fields during

the boot leaf stage in Rabi 2011. The collected adults

were released into the pots containing TN-1 plants for

egg laying and were covered with a muslin cloth for

aeration, 20% honey solution was also provided for

feeding. About ten pairs of C. medinalis adults were

released into each TN-1 pot. C. medinalis populations

from different locations were reared separately and

after larval hatching, the 3rd instar larvae were used

for bioassay.

Leaf-dip bioassay method was used. 3-4 cm long

tender leaves from TN-1 rice variety were used in the

bioassay. The leaves were first washed with distilled

water and then were dipped in monocrotophos

solution and thoroughly air dried for about 10 min

different concentrations of insecticide were prepared,

bioassays were carried out first at 10 fold variation.

Based on 20%-80% mortality, concentrations were

prepared at narrow range of five-fold for further

bioassays. Six concentrations were tested with 10

third instar larvae per treatment and replicated thrice.

Larvae were allowed to feed on insecticide treated

leaves for 24 h, and mortality was recorded for 24 h

after treatment. Control treatments with larval

mortality more than 20% were discarded and bioassay

was repeated. Statistical analysis for calculating the


55

LC50 values for the bioassay was estimated using

maximum likelihood programme MLP 3.01 [11]. The

corrected percent mortality was calculated by using

Abbott’s formula [12].

2.2 Preparation of Enzyme Homogenate

Fifth instar larvae of C. medinalis were used for

enzyme preparation. Larval midguts were excised

with replicate samples and were homogenized in 500

L homogenization buffer (50 mM sodium phosphate

buffer, pH 7.4). After centrifugation at 10,000 rpm for

20 min, the clear supernatant was collected and used

as enzyme sources for analysis of the activity of

carboxylesterase. All the operations were carried out

on ice and centrifugation at 4 °C to minimize losses of

enzyme activity. The protein content of enzyme

extract was estimated by Coomassie Brilliant Blue

G-250 dye binding method using bovine serum

albumin as the standard [13].

2.3 Carboxylesterase Assay

Carboxylesterase activity was determined by the

method of Van Asperen [14] with necessary

modifications and α-naphthyl acetate as a substrate. A

0.3 mM substrate solution of 1-naphthyl acetate was

prepared in acetone. The assay mixture contained 15

L of enzyme preparation, 0.5 mL of 50 mM sodium

phosphate buffer pH 7.4, and 800 L of 0.3 mM

substrate solution. The mixture was incubated at 30 C

for 30 min. Finally, 200 μL of 0.1% tetrazotized

o-dianisidine (fast blue B) in 3.5% SDS was added

and incubated for 20 min at room temperature in the

dark. The α-naphthol formation was measured at 590

nm. The enzyme activity was calculated from

α-naphthol standard curve.

2.4 Esterase Isozyme Studies

Native PAGE with 10% resolving gel was

performed to separate esterase isozymes. Qualitative

changes in esterase banding pattern was performed

using the F2 generation larvae that were reared after

surviving the insecticidal bioassay with

monocrotophos. 5 µg protein concentrations of the

mid-gut homogenate per well were loaded onto the

native PAGE and run at a constant voltage of 90 for

45 min. Gels were stained briefly for esterase activity

with freshly prepared 0.05% (w/v) α-napthyl acetate

and 0.1% (w/v) fast blue B in 50 mM phosphate

buffer pH 7.4. For inhibition studies, gels were cut

into strips and incubated in 10-4 M and 10-6 M eserine

sulphate and 10-4 M DDVP individually in 50 mM

phosphate buffer pH 7.4 for 30 min at 28 °C with

occasional shaking. Control gels were incubated for

30 min in buffer alone. All the gel strips were stained

incubated for 30 min in α-napthyl acetate substrate

diazonium mixture for confirming the esterase

activity.

2.5 Glutathione-S-Transferase Activity Estimation for

Insecticide Resistance

Glutathione-S-Transferase assay was performed

by using reduced glutathione (50 mM), mid-gut

homogenate supernate (10,000 g) from the F2

generation larvae that were reared after surviving the

insecticidal bioassay with monocrotophos, chloro

dinitro benzene (CDNB) 50 mM, sodium phosphate

buffer (pH 6.5, 100 mM) and EDTA (1 mM). The

assay mixture contained 50 µL of 50 mM CDNB,

150 µL of reduced glutathione and 2.77 mL of 100

mM, pH 6.5 phosphate buffer containing 1 mM of

EDTA. To the above assay 30 µL of enzyme

(mid-gut homogenate) was added and the contents

were shaked gently and incubated for 2-3 min at

25 °C, then the contents were transferred to 4 mL

cuvettes and absorbance was recorded for 6-7 min at

340 nm. Based on the increase in absorbance over

five minutes the enzyme activity was calculated in

µmol min-1 mg-1 protein.


Bioassays results for the two selected C. medinalis

populations, DRR, Rajendranagar and ICRISAT,


56

Patencheru revealed LC50 of value 60 ppm for

ICRISAT C. medinalis population and showed 2-fold

resistance ratio over the DRR population which

showed LC50 30 ppm against monocrotophos (Table 1).

3.1 Qualitative and Quantitative Changes of

Carboxylesterase and Glutathione-S-Transferase in C.

Medinalis Populations

Qualitative and quantitative changes of CarE and

GST’s for DRR population in the presence of α-napthyl

acetate and CDNB revealed a titre of 114.3 µmol min-1

mg-1 protein and 5.66 µmol min-1 mg-1 protein, while

that ICRISAT population showed 155.2 µmol min-1

mg-1 protein and GST titre of 12.598 µmol min-1 mg-1

protein, respectively. The results revealed that

ICRISAT C. medinalis population had 1.35 folds

greater carboxylesterase and 2.245 folds more GST’s in

its midgut homogenates over DRR population (Table 2).

Similar findings were reported by Mohan and Gujar [15]

where 1.2 to 1.8 fold increased CarE activity was

observed in P. xylostella for monocrotophos, cartap and

fipronil resistant populations, over the laboratory strain

IARI 17-65. Yamamoto et al. [16] reported that GST

from RLF, C. medinalis was inhibited by fenitrothion,

permethrin, and deltamethrin, suggesting GST may be

involved in metabolizing organophosphorus and

pyrethroid insecticides.

3.2 Esterase Isozyme Studies

Esterase activity visualized in native PAGE

following incubation in substrate solution (0.05%

α-naphthyl acetate in 0.1% fast blue (R) revealed two

isozyme bands. The major band with diffused esterase

activity was relatively of more molecular mass than

the other esterase activity band which was faint in

nature (Fig. 1). Difference in esterase banding pattern

in ICRISAT, C. medinalis population was observed

when using midgut and whole body extracts. The

midgut produced all three types of esterase bands

while whole body homogenates produced only two

bands (Fig. 1). Inhibitor studies with the esterase

isozymes separated under native PAGE when

subjected to inhibition by incubating with class

specific esterase inhibitors in buffers containing

dichlorvos (DDVP) 10-4 M, eserine sulphate, 10-6 and

10-4 M concentrations indicated that these two esterase

isozymes are B type esterases as eserine sulphate, a

specific inhibitor of cholinesterase did not inhibit the

esterase activites at 10-6 and 10-4 M concentrations and

esterases were characterized to have carboxylesterase

activity (Fig. 2).

In insects, the esterase bands separated

electrophoretically under native condition are classified

into three types by the substance which inhibits their

activity [14, 17]. The results of the present study are in

conformity with that of cypermethrin resistant P.

xylostella strain, where in the carboxylesterase levels

from 1st to 4th instar, pupa and adult showed 2.64,

3.16, 2.61, 3.04, 2.93 and 2.75 folds higher

carboxylesterase activity in comparison to P.

xylostella susceptible strain [18] and also reported

monocrotophos, profenofos, quinalphos and phenthoate,

Table 1 Toxicity of monocrotophos to 3rd instar larvae of C. medinalis 24 HAT.

Location LC50 (ppm) R R Slope ± SE “F” Limits

χ2 (Degrees of freedom)Lower Upper

DRR population 30 1.00 1.29 ± 0.21 0.0018 0.0057 4.0 (4)

ICRISAT population 60 2.00 1.14 ± 0.21 0.002 0.011 2.31 (4)

R R: Resistance ratio over one generation, “F” Limits: fiducial limits.

Table 2 Carboxylesterase and GST activity of 3rd instar larvae of C. medinalis.

Location CarE (µmol min-1 mg-1 protein) CarE folds GST (µmole min-1 mg-1 protein) GST folds

DRR population 114.39 1.00 5.660 1.00

ICRISAT population 155.2 1.35 12.598 2.245


57

Fig. 1 Carboxylesterase, profiles from whole body and midgut homogenates of ICRISAT, C. medinalis population. Lanes 1-5 are whole body homogenates showing two bands of esterase isozymes, Lanes 6-10 are midgut homogenates showing three bands of esterase isozymes.

Fig. 2 Characterization of C. medinalis carboxylesterase with specific substrates. Lane: 1-DDVP (10-4 M), Lanes: 2, 3 and 4-Eserine(10-4M), Lanes: 5, 6-Eserine(10-6M), Lanes: 7, 8-Control.

as it showed 54.34%, 72.54%, 78.71%, 80.82% and

82.94% inhibition of carboxylesterase titres associated

with cypermethrin resistance at 0.01, 0.1, 1, 5 and 10

mg mL-1 concentration, and suggested that DDVP is

the best synergist to mitigate cypermethrin resistance

in P. xylostella whereas Rashad [19] reported high

titres of esterase activity in brain, fore-gut, mid-gut

and ovary of 2-day old adults of Schistocerca

gregaria, while in 13 day old adults hind gut exhibited

high esterase levels. Inhibitory studies with EDTA

and profenofos depicted high levels of both

carboxylesterase and phosphotriesterases in the brain

tissues of two ages that attributed to play a role in

insecticide resistance.

In the present study correlation between LC50 value

of monocrotphos of third instar larvae and

carboxylesterase activity was similar to that obtained

by Kranthi et al. [20] who studied the seasonal

dynamics of metabolic mechanisms responsible for

pyrethroid resistance in H. armigera and assigned it

due to involvement of microsomal oxidase and

esterases. Young et al. [21] reported pyrethroid


58

resistance in H. armigera (Hubner) and attributed to

overproduction of esterase isoenzymes that metabolise

and sequester pyrethroid insecticides and found out

that pyrethroid-resistance-associated esterases were

inhibited by piperonyl butoxide (PBO) and maximum

inhibition achieved 3-4 h after dosage and again

restored by 24 h.

Esterase zymogram in the present study showed an

additional fast moving band by midgut extracts in

comparison with whole body homogenates is in

conformity with the findings on DBM [15] where no

major difference in banding pattern was identified

except for three additional slow moving faint bands

for all field populations and were associated with

resistance based on intensity of banding, and

characterized to be as B-esterase similar to P.

xylostella.

4. Conclusions

In the present study, the carboxylesterase present in

ICRISAT population was calibrated in vitro to be

155.2 µmol min-1 mg-1 protein and the esterase

zymograms showed intensely stained bands depicting

resistance association. The median lethal

concentration, LC50 for this strain was 60 ppm, though

more than the discriminating dose for monocrotophos,

0.35 µg per larvae [22]. The base-line LC50 estimate

for the ICRISAT population with cry1Ab toxin is 0.50

µg/mL, the matter of concern in this regard is that

indiscriminate usage of insecticides for control of C.

medinalis may futher bring an elevation in the esterase

titre which may bind to cry1Ab toxin receptors and

sequester the toxin before it reaches the target site as

exemplified in the case of “silver strain” H. armigera

towards cry1Ac expressed by transgenic cotton

Ingard® in Australia, where sequestration by esterases

was recognized as a potential resistance mechanism

apart from previous resistance mechanisms viz.

reduced binding by the cry toxin to BBMV’s of

midgut epithelium and alteration in midgut proteases

that cleave protoxin to active toxin [10].

References

[1] X. Li, M.A. Schuler, M.R. Berenbaum, Molecular mechanisms of metabolic resistance to synthetic and natural xenobiotics, Annual Review of Entomology 52 (2007) 231-253.

[2] J.A. Cheng Rice Pests, China Agricultural Press, Beijing, China, 1996.

[3] D. Dale, Insect pests of rice planttheir biology and

ecology, in: E.A. Heinrichs (Ed.), Biology and Management of Rice Insects, Wiley Eastern Limited, New Delhi, India, 1994, pp. 363-485.

[4] N. Chandramohan, S. Jayaraj, Evaluation of certain granular and foliar insecticides against rice leaf folder, Cnaphalocrocis medinalis (Guenee), Madras Agricultural Journal 63 (1976) 364-366.

[5] N. Raju, M. Gopalan, G. Balasubramanian, Ovicidal action of insecticides, mould inhibitors and fungicides in the eggs of rice leaf folder and stem borer, Indian Journal of Plant Protection 18 (1990) 5-9.

[6] K. Ramaraju, K. Natarajan, Control of leaf folder under extreme weather conditions, Madras Agricultural Journal 66 (1997) 252-254.

[7] J. Tu, G. Zhang, K. Datta, Y. He, Q. Zhang, G.S. Khush et al., Field performance of transgenic hybrid rice expressing Bacillus thuringiensis delta-endotoxin, Nature Biotechnology 18 (2000) 1101-1104.

[8] G.Y. Ye, H.W. Yao, Q.Y. Shu, X. Cheng, C. Hu, Y.W. Xia, et al., High levels of stable resistance in transgenic rice with cry1Ab gene from Bacillus thuringiensis Berliner to rice leaf folder, Cnaphalocrocis medinalis (Guenee) under field conditions, Crop Protection 22 (2003) 171-178.

[9] L.Z. Han, K. Wu, M. Peng, Y.F. Wang, Y.Y. Guo, Efficacy of transgenic rice expressing Cry1Ac and CpTI against the rice leaf folder, Cnaphalocrocis medinalis (Guenee), Journal of Invertebrate Pathology 96 (2007) 71-79.

[10] R.V. Gunning, H.T. Dang, F.C. Kemp, I.C. Nicholson, G.D. Moores, New resistance mechanism in Helicoverpa armigera threatens transgenic crops expressing Bacillus thuringiensis Cry1Ac, Applied and Environmental Microbiology 71 (2005) 2558-2563.

[11] G.E.S. Ross, Maximum Likelihood Programme. The Numerical Algorithms Group, Rothamsted Experimental Station, Harpenden, UK, 1987.

[12] W.S, Abbott, A method of computing the effectiveness of an insecticide, Journal of Economic Entomology 18 (1925) 265-267.

[13] M.M. Bradford, A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding, Analytical


59

Biochemistry 74 (1976) 248-254. [14] K. Van Asperen, A study of house flies esterase by means

of a sensitive colorimetric, 1962. [15] M. Mohan, G.T. Gujar, Local variation in susceptibility

of the diamondback moth, Plutella xylostella (Linnaeus) to insecticides and role of detoxification enzymes, Crop Protection 22 (2003) 495-504.

[16] K. Yamamoto, S. Teshiba, Y. Aso, Characterization of glutathione S-transferase of the rice leaffolder moth, Cnaphalocrocis medinalis (Lepidoptera: Pyralidae): Comparison of its properties of glutathione S-transferases from other lepidopteran insects, Pesticide Biochemistry and Physiology 92 (2008) 125-128.

[17] W.N. Aldridge, Serum esterases. 1. Two types of esterase (A and B) hydrolysing p-nitrophenyl acetate, propionate and butyrate, and a method for their determination, Biochemistry Journal 53 (1953) 110-117.

[18] M. Moharil, P. Prasad, A.W. Nagarjuna, G.V. Rao, N.T. Sachin, M.K. Rai, S.A. Nimbalkar, Detection of a carboxylesterase-mediated resistance mechanism in Plutella xyloestella (L.) by diagnostic microplate assay,

Research Journal of Agriculture and Biological Sciences 4 (2008) 623-629.

[19] E.M. Rashad, Esterase activity and detection of carboxylesterase and phosphotriesterase in female desert locust Schistocerca gregaria (Forskal) in relation to tissues and ages, Egyptian Academy of Journal of Biological Science 1 (2008) 135-143.

[20] K.R. Kranthi, N.J Armes, N.G.V. Rao, S. Raj, V.T. Sundaramurthy,Seasonal dynamics of metabolic mechanisms mediating pyrethroid resistance in Helicoverpa armigera in central India, Pesticide Science 50 (1997) 91-98.

[21] S.J. Young, R.V. Gunning, D.M. Graham, The effect of piperonyl butoxide on pyrethroid resistance associated esterases in Helicoverpa armigera Hubner (Lepidoptera: Noctuidae).Pest Management Science 61 (2005) 397-401.

[22] G.K. Anandan, A. Regupathy, Assessment of acute toxicity of insecticides for monitoring insecticide resistance in rice leaf folder, Cnaphalocrocis medinalis (Guenee) in Tamil Nadu, India, Resistant Pest Management Newsletter 16 (2007) 3-5.


Environmental Impacts of Feeding High-fiber Diet to

Pigs

Abraham Woldeghebriel1, Shanequa Smith2, Teo Barios1, Brad Pope1 and Sebhatu Gebrelul3

1. North Carolina A&T State University, Greensboro, NC 27411, USA

2. North Carolina Central University, Durham, NC 27707, USA

3. Southern University, Baton Rouge, LA 70809, USA


Abstract: The concentration of volatile fatty acids (VFA) determined from a previous study was used to determine the concentration of carbon dioxide (CO2) and methane (CH4) in pig digesta using the model developed for ruminant animals. Digesta from the stomach, cecum and colon of pigs (n = 3 diet-1) were used for the determination of VFA. The pigs were fed either a low fiber diet (LFD; 8.3% aNDF) as control, or one of the high-fiber diets (HFD, 22.4% aNDF; D1, D2 and D3) containing 1:2, 1:1 and 2:1, oats to barley ratios, respectively. Results indicated that the concentrations of CO2 and CH4 in pigs fed HFD were, on the average, 25.8 and 24.2%, respectively lower (P < 0.05) than pigs fed LFD. Pigs fed the highest oat to barley ratio also showed higher (P < 0.05) levels of CO2, (8.3%) and CH4 (5.1%), compared to the average of the two lower ratios (CO2, 5.3% and CH4, 3.3%). Molar proportions of VFA, CO2 and CH4 in the gut were in the order of VFA > CO2 > CH4, at 53.0%, 28.6% and 18.4%, respectively, and CO2 and CH4 combined represented 47% of total gas. Key words: Environment, fiber, methane, pig, volatile fatty acids.

1. Introduction

Ruminant nutrition research has for so long been

focused on reduction of enteric CH4 emission not

because of its effect on global warming but because of

its inefficiency in animals [1]. Even though

production of CH4 in the rumen and lower digestive

tract of animals is influenced by a number of factors

[2], the average yearly production estimates of a

typical beef and dairy cow is in the range of 60-70 kg

and 109-126 kg, respectively [3]. As a consequence,

the combined economic loss in the range of 2%-12%

of energy intake in ruminant animals and its

significant contribution to the greenhouse gas (GHG)

effect and global warming [4, 5] are glaring evidences.

A sizable number of approaches including vaccination,

enzyme inhibitors phages, homoacetogens,

Corresponding author: Abraham Woldeghebriel, Ph.D., research fields: animal nutrition, digestive physiology. E-mail: [email protected].

defaunation and animal selection pressure have been

investigated and yet, it seems like more than one

strategy may have to be used to have any significant

impact on reducing enteric CH4 emission [6].

Traditionally, diets high in fiber were exclusively

used for ruminant animals while pigs on the other hand

were fed mainly cereal-based concentrate diets. While

exclusive uses of low-fiber diet (LFD) improve

productivity and pollution from excreted nutrients

feeding LFD could be detrimental to the health of the

animal [7]. Also in recent years, higher feed prices and

availability of relatively cheaper co-products on the

market has provoked interest in alternative feed

ingredients including those that are high in fiber. It was

also noted that over the last few years due to public

demand for less intensive farming systems and rising

capital costs on indoor pig housing, outdoor pig farms

started to grow in large numbers. However, given our

current level of production systems and mitigation

D DAVID PUBLISHING

Environmental Impacts of Feeding High-fiber Diet to Pigs

61

strategies we have in place, raising pigs on pasture

could impact environmental protection goals due to

increases in CH4 emission from pigs with free access

to forages and other vegetative parts of plant materials

that could inherently be high in fiber. When high-fiber

diets (HFD) are fed to pigs, more substrates enter the

large intestine. According to Varel and Yen [8],

microbial activity in the digestive tract of pigs fed

HFD was 5.5 times higher and resulted in a 5-9 fold

increase in CO2 and CH4 production than in pigs fed

LFDs. Similar observation was also reported by Jensen

and Jorgensen [9] where CH4 excretion rate of a

7-month old barrow fed HFD was 12.5 L d-1 compared

to 1.4 L d-1 when the same animal was fed LFD

indicating that the concentration of the fiber was the

main dietary contributor to enteric CH4 emission in

pigs [7]. In terms of actual production, while a mature

cow produces up to 250 L of CH4 d-1 (60 kg year-1),

depending on the feeding levels and types of fiber, a

dry gestating sow fed at maintenance level produces

approximately 10.2 L day-1 which is approximately

0.6%-2.7% of gross energy intake of the animal [7]. A

recent study conducted in Denmark highlighted the

relative contribution of enteric CH4 emission from

livestock and manure management at 86%, 10% and

3% from cattle, pig and horses, respectively [4].

Carbon dioxide and CH4 are two of several

anthropogenic and naturally occurring greenhouse

gases (GHG) in the atmosphere. The IPCC [10]

developed a global warming potential index (GWPI)

to estimate and compare the ability of GHG to trap

heat in the atmosphere using CO2 as a reference with

GWPI of 1 and others expressed as CO2 equivalents.

Methane the second most significant contributor to the

GHG effect traps outgoing terrestrial infrared

radiation 21 times more effectively than CO2 [11, 12],

increases surface temperatures and indirectly affects

the atmospheric oxidation reactions that produces CO2

[13]. Measurements of gaseous exchanges such as

CO2 and CH4 production in animals have traditionally

been carried out in respiratory chambers. However,

respiratory chambers are expensive, restrictive to

movement of animals and the system relies on indirect

measurements but other less expensive indirect

measurements of fermentation indices exist. For

example, France and Siddon [14] used CH4 production

to obtain an estimate of VFA production. Also, Wolin

[15], Van Nevel and Demeyer [16] each developed

similar model by which emission of CH4 from

ruminants was calculated using VFA concentration

data from ruminant animals. Therefore, we

hypothesized that the model developed by Wolin for

ruminant animals can be used to indirectly estimate

CO2 and CH4 concentration in the digestive tract of

pigs. The aim of the study was to test the hypothesis

that the model developed by Wolin for ruminant

animals can be used to determine the amount of CO2

and CH4 concentration in digesta using VFA

concentration data from pigs.

2. Methods

2.1 The Mathematical Model

The equation developed by Wolin [15] and later

validated by Blummel et al. [17] to estimate CH4

production in ruminant animals was used to determine

the concentration of CO2 and CH4 in the digestive

tract of growing pigs. The reactions shown below

summarize the basic methanogenic processes on

which the model was conceptualized [15]:

Hexose → 2 pyruvate + 4H

Pyruvate → acetate + CO2 + 2H+

2 pyruvate → butyrate + 2CO2

Pyruvate + 4H2 → propionate + H2O (propionate is

a potent “H” sink)

CO2 + 8H+ → CH4 + 2H2O

Molar concentrations of the three most abundant

VFAs (acetate, propionate and butyrate) in the

digestive tract of the pigs obtained from one of our

previous unpublished data were used to calculate the


62

fermentative concentration of CO2 (Eq. 1) and CH4

(Eq. 2) as follows.

2.2 Equations

CO2 (mol) = A/2 + P/4 +1.5B (1)

Where A, P and B are moles of acetate, propionate

and butyrate, respectively and,

CH4 (mol) = (A + 2B) – CO2 (2)

Where CO2 is moles of carbon dioxide estimate in

Eq. 1.

2.3 Data Analysis

Data collected were analyzed using the SAS’s

Glimmix procedure [18] with diet as the main fixed

effect and digestive organs from animals as random

effects. The statistical model investigated the main

effects: diet, digestive organs and associated

interactions. Data presented in the table are least

square means, means were compared using paired

T-test, and statistical significance was accepted at P <

0.05. Probability values between 0.06 and 0.10 were

considered trends.


The individual VFA used to determine the

concentration of CO2 and CH4 in the digestive tract of

the pigs were acetate (C2), propionate (C3) and

butyrate (n-C4). Bacteria in the hindgut metabolize

carbohydrates to obtain energy and proteins to N

through anaerobic fermentation for their own growth

and maintenance requirements. Results of such

anaerobic fermentation were summarized by Ewing

and Cole [19], and the molar ratios of the major VFA

were expressed as 1:0.31:0.23 for C2, C3 and n-C4,

respectively. The average molar ratio of the VFAs in

pigs in the current study was in complete agreement

(1:0.32:0.17, respectively) with the general equation

reported earlier except for n-C4 which was 26% lower

than the general equation indicating that n-C4 might

have been depleted at a relatively faster rate than the

other VFAs when availability of fermentable fiber in

the hindgut of the pigs might probably be on the

decline. According to Fitch and Fleming [20]

transport of n-C4 from the lumen into the blood

increases linearly with increasing concentration of C4,

while transport and metabolism of C2 are significantly

lower than C4. Butyrate has also been shown to be

oxidized to CO2 more readily than C2 or C3, and,

while C4 oxidation is not suppressed by the presence

of other substances, presence of C4 reportedly

suppressed the oxidation of other VFA including C2

[21]. It is also important to note that C4 is

preferentially metabolized by colonocytes for energy

[22], is more effective than C2 and C3 in enhancing Na

absorption [23], and plays an important role in the

prevention of diarrhea in young pigs [24]. Therefore,

given its physiological and multifunctional roles in the

body of the animal, it seems reasonable to assume that

C4 would be depleted at a much faster rate than the

other VFAs, which are relatively less important than

C4 to the pig.

The two most abundant VFAs, i.e., C2 and C3, were

present in 1:0.32 ratio. Combined, they represented

89% of the total VFA. The fact that there was 3.13

times more C2 than C3 may indicate a much higher

probability for methanogenesis through one or both of

the following reactions:

Pyruvate → acetate + CO2 + 2H, and

CO2 + 4H2 → CH4 + 2H2O, or

CH3COOH → CH4 + CO2

where CO2 and acetic acid are terminal electron

acceptors.

As in the rumen, methanogenes in colonic

fermentation use H2 to reduce CO2 to CH4 [25].

However, when non-methanogenic fermentation

occurs, H2 is used to reduce CO2 to acetate according

to the following equation [26]. Acetate can then be

used as a source of carbon and energy.

2CO2+ 4H2 →CH3COOH + 2H2

Generally, VFAs are not used as substrates for

methanogenesis, as their conversion to CO2 and H2,

especially in ruminants is lengthy and is inhibited by


63

rumen turnover [27], but also due to the fact that

methanogenesis often uses CO2 and H2 from

carbohydrate fermentation during VFA synthesis [28].

The estimated molar concentration of CO2 and CH4

in the stomach, cecum and colon of the pigs is shown

in Table 1. The concentration of CO2 in the stomach

of pigs fed LFD was 2.6 times higher (P < 0.05) than

the average of the HFD fed pigs. There were no

significant differences among the HFD fed pigs. In the

cecum, the highest (P < 0.05) CO2 concentration was

found in CON and D3 fed pigs, while the lowest

concentration was in pigs fed D2 with no significant

difference between CON and D1 and between D1 and

D2 fed pigs. However, in the colon, the lowest (P <

0.05) CO2 concentration was found in pigs fed D1,

with no significant differences among the remaining

groups of pigs.

The highest (P < 0.05) total concentration of CO2

was observed in pigs fed CON and D3, while the

lower and lowest (P < 0.05) concentrations were

detected in pigs fed D2 and D1, respectively. It was

noted that the concentration of CO2 in pigs fed D2 and

D3 was higher (P < 0.05) than D1 fed pigs, with no

significant differences between D2 and D3, or

between D1 and D2 fed pigs. It was also noted that the

concentration of CO2 in LFD fed pigs was 25.6%

higher than the average of the HFD fed pigs (84.39%

vs. 62.79%). Also, as the amount oats in the diet

increased (D3 > D2 > D1), concentration CO2 also

increased (83.13%, 59.27% and 45.96%, respectively),

indicating that the DF in oats may have been more

readily fermentable by the microorganisms than the

DF in barley. However, differences between D2 and

D3 or between D1 and D2 were not statistically

significant, confirming many of the earlier reports

[29-31] that the amount of CO2 produced by animals

depends mainly on the live body weight, physiological

state, feed intake and physical activity, whereas the

composition of the feed supplied to the animal plays a

minor role.

The CH4 concentration in the stomach of pigs fed

LFD was 40% higher (P < 0.05) than the average

(2.22% vs. 1.33%) of the HFD fed pigs with no

significant differences between CON and D2, between

D1 and D3 and between D2 and D3 fed pigs. Likewise,

in the cecum, the highest (P < 0.05) molar

concentration of CH4 was observed in CON and D3

fed pigs with no significant differences between CON

and D1, or between D1 and D2 fed pigs. On the other

hand, in the colon, the lowest (P < 0.05) concentration

of CH4 was recorded in D1 fed pigs, but there were no

significant differences among the remaining groups of

pigs.

The highest (P < 0.05) total molar concentration of

CH4 was found in pigs fed CON and D3, while the

lower and the lowest (P < 0.05) concentrations were

recorded in pigs fed diets 1 and 2, respectively.

However, there were no significant differences between

CON and D3, between D2 and D3, or between D1 and

D2 fed pigs. It was noted that the concentration of CH4

Table 1 Concentrations of CO2 and CH4 in visceral contents of pigs.

Visceral organs CON D1 D2 D3 SEM1

% CO2

Stomach 3.88a 1.23b 1.33b 1.95b 1.60

Cecum 12.00ab 10.61bc 8.27c 14.53a 2.69

Colon 9.43a 1.95b 6.17a 8.46a 4.19

Total (mol L-1) 84.39a 45.96b 59.27bc 83.13ac 23.83

CH4

Stomach 2.22a 0.92b 1.92ac 1.15bc 0.97

Cecum 6.98ac 6.37bc 4.57b 8.61a 1.94

Colon 6.21a 1.55b 4.41a 5.31a 2.34

Total (mol L-1) 51.12a 29.53b 36.40bc 50.32ac 14.58 a, b, cLeast square means in the same row with different superscripts differ (P < 0.05); 1Standard error of means.


64

in LFD fed pigs was 24.2% higher than the average of

the HFD fed pigs (51.12% vs. 38.75%). It was also

observed that as the amount oats in the diet increased

(D3 > D2 > D1), CH4 concentration increased (50.32%,

36.40% and 29.53%, respectively), which suggests that

the DF in oats was more readily fermentable to the

microorganisms than the DF in barley. However, no

significant differences were observed between D3 and

D2 and between D2 and D1 fed pigs.

4. Conclusions

In summary, we were able to determine the

concentration of CO2 and CH4 in the digestive tract of

the pigs using the model developed for ruminant

animals. It is important to note that there were

quantitative differences and trends of increased molar

concentrations of CO2 and CH4 in the digestive tracts

as the oat to barley ratio in the diet increases (1:2, 1:1

and 2:1). Even though the methodology used was

understandably static it also lacks the capacity to

predict outcome with any degree of certainty.

Therefore, given the interspecies variability that exists

between ruminant and non-ruminant animals, the

usefulness of the model to estimate the molar

concentration of CO2 and CH4 in pigs needs further

investigation.

4.1 Implication

It is important to remember that mathematical

models are tools used to express relationships between

variables that humans sometimes have difficulty

understanding complex systems like the ecosystem of

the digestive tract of animals. It is also important to

note that continuous microbial fermentation in the

digestive tract of animals is not only complex but

information on how dietary composition and intrinsic

animal factors may influence methane production is

still not well understood. Therefore, further validation

of the model using a large dataset representing a wide

variety of diets, pigs of different ages and

management practices used would be appropriate.

Acknowledgments

The authors are grateful for the financial support of

this work through the Evans-Allen Project,

NIFA/USDA.

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[20] M.D. Fitch, S.E. Fleming, Metabolism of short-chain fatty acids by rat colonic mucosa in vivo, Am J. Physiol. (Gastrointest. Liver Physiol. 1), 1999, pp. 31-40.

[21] E.S. Fleming, S.Y. Choi, M.D. Fitch, Absorption of short-chain fatty acids from the rat cecum in vivo, J. Nutr. 121 (1991) 1787-1797.

[22] W.E.W. Roediger, Utilization of nutrients by isolated epithelial cells of the rat colon, Gastroentrol. 83 (1982) 424-429.

[23] W.E.W. Roediger, Moore, Effect of short-chain fatty acid on sodium absorption in isolated human colon per-fused through the vascular bed, Digestive Disease and Sciences 26 (1981) 100-106.

[24] B.A. Williams, M.W.A. Verstegen, S. Tamminga, Fermentation in the large intestine of single-stomached animals and its relationship to animal health, Nutr. Res. Rev. 11 (2001) 207-227.

[25] T.L. Miller, M.J. Wolin, Pathways of acetate, propionate and butyrate formation by the human fecal microbial flora, Appl. Environ. Microbiol. 62 (1996) 1589-1592.

[26] H.L. Drake, Introduction to acetogenesis, in: H.L. Drake (Ed.), Acetogenesis, Chapman & Hall, New York, London, 1994, pp. 3-60.

[27] P.N. Hobson, C.S. Stewart, The rumen microbial ecosystem, Chapman and Hall, London, UK, 1997.

[28] E.R., Hungate, W. Smith, T. Bauchop, I. Yu, J.C. Rabinowitz, Formate as an intermediate in the bovine rumen fermentation, J. Bacteriol. 102 (1970) 389-397.

[29] S.C. Stewart, H.J. Flint, M.P. Bryant, The Rumen Bacteria, in: P.N. Hobson, C.S. Stewart (Eds.), The Rumen Ecosystem Blackie Acad. Prof. London, UK, 1997, pp. 10-72.

[30] A. Mirzaei-Aghsaghali, N. Mahari-Sis, Factors affecting mitigation of methane emission from ruminants I: Feeding strategies, Asian J. Anim. Vet. Adv. 9 (2011) 888-908.

[31] S.M. McGinn, K.A. Beauchemin, Dairy farm methane emissions using dispersion model, J. Environ. Qual. 41 (2012) 73-79.


Effects of Feeding Siamese neem leaves and

Zanthoxylum Pods, on Dry Matter Intake, Dry Matter

Digestibility, Milk Production and Composition in Thai

Holstein Dairy Cows, Fed Rice Straw as Fiber Source

Penjor1, Virote Pattarajinda1, Suporn Katawatin1, Chaiyapas Thamrongyoswittayakul2 and Wandee Gritsanapan3

1. Department of Animal Science, Faculty of Agriculture, Khon Kaen University, 40002, Thailand

2. Faculty of Veterinary Medicine, Khon Kaen University, 40002, Thailand

3. Department of Pharmacognosy, Faculty of Pharmacy, Mahidol University, 10800, Thailand


Abstract: The plant secondary metabolites (PSM) are highly sought compounds for use as an alternative to conventionally used feed additives in animal production these days; Siamese neem leaf (Azadirachta indica A. Juss. var. siamenses Valeton) and Zanthoxylum pods (Zanthoxylum piperatum) are known to contain numerous such compounds.The objectives of this study were to determine effects of feeding Siamese neem leaf and Zanthoxylum pods as feed additives on dry matter intake (DMI), dry matter digestibility

(DMD) and milk production and milk composition. Lactating Thai Holstein cows (n = 8) were arranged in two replicates of 4 4

Latin square designs, housed in individual stall, treatments consisted of Siamese neem 0.5 and 1.5 g kg-1 dry matter (DM), Zanthoxylum0.1 and 0.5 g kg-1 DM added to the total mixed ration (TMR). TMRand drinking water were provided ad lib. There were no significant differences (P > 0.05) in DMI and crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF) digestibility, milk production and composition among the treatments.However, significant difference (P < 0.05) was observed in dry matter (DM) and ether extract (EE) digestibility. Though statistically non-significant, Zanthoxylum at higher dose level tended to show low DMI (14.85 kg) in cows, while promotingmarginally higher milk (14.18 kg) production as compared with lower dose levelwhere DMI and milk production were 16.14 kg and 13.83 kg.This indicated that Zanthoxylum has a potential to improve feed digestion in dairy cows when used as additives. Key words: Plant additive, TMR, DMD, milk production, dairy cows.

1. Introduction

In an attempt to increase milk production, while

lowering the product cost at the same time, dairy

producers have made use of feed additives like

Monensin, Lasolasid and others antibiotics in dairy

production system for the last few decades. However,

the social acceptances for their use have declined in

the recent years on the grounds of the quality and

Corresponding author: Virote Pattarajinda, professor,

research fields: animal nutrition and feed science. E-mail: [email protected],[email protected].

safety of meat and milk products [1]. The consumer

organizations in European Union have criticized

routine use of antibiotics in livestock nutrition and the

ban remained restricted to EU nations [2].Increased

access to information through internet, television and

other media have enhanced the awareness of the

consumers andchanged their outlook [3]. There is

increasing public concern being raised on the use of

antibiotics in animal production systems [4]. The

consumers’ notion that anything natural is good for

the human health has created a desire to look for

plants containing PSM, possessing good capacity to

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Effects of Feeding Siamese Neem Leaves and Zanthoxylum Pods, on Dry Matter Intake, Dry Matter Digestibility, Milk Production and Composition in Thai Holstein Dairy Cows

67

alter nutrient utilization in the rumen as an alternative

to conventionally used antibiotics, where antibiotics as

a source of additives are no longer allowed in animal

production systems [5]. The plants are considered as

potential source of compounds and when fed to dairy

cattle will favorably alter the ruminal fermentation

without causing overall inhibition of fermentation,

thereby enhancing feedstuff degradability and

utilization,promoting microbial growth in rumen,

thereby enhances animal performance. In the current

study, two plants, Siamese neem leaves and

Zanthoxylum pods were selected as additives based on

the results of an in vitro experiment [3]. The doses

were calculated on the basis that DMI of an individual

animal is approximately 3% of body weight. Dosing

of plants on DM basis also reduced the chances of

over dosing animals as may be seen when calculated

on g kg-1 body weight basis. Zanthoxylum was dosed

at lower levels because it is known to cause “tingling”

and “numbing” sensation [6] in the oral cavity in man,

which may result in avoidance of feed by cows due to

this effect.This study evaluated the effects of feeding

Siamese neem leaves and Zanthoxylum pods as plant

based feed additive on DMI, DMD, milk production

and milk composition in lactating Thai Holstein cows

fed rice straw as the source of fiber. Eight lactating

cows were arranged in 4 4 Latin square designs,

housed in individual stall, and fed TMR mixed with

Siamese neem and Zanthoxylum. The TMR and

drinking water were provided ad lib. There were four

periods consisting of 21 days, the data were collected

during the last seven days of each period.


2.1 Plants Preparation and Dose Levels

The Siamese neem leaves were collected at Roi-Et

Agricultural Research and Training Center campus,

Zanthoxylum pods were purchased from a commercial

herbal dealer.The plant materials were dried in forced

air oven at 60 °C for 24 h and ground through 2 mm

screen in Wiley mill. Siamese neem was dosed at 0.5

and 1.5 g kg-1 DM and Zanthoxylum dosed at 0.1 and

0.5 g kg-1 DM.

2.2 Animal and Experimental Design

Eight lactating Thai Holstein cows (420 ± 50 kg)

were housed in individual stall, arranged in two

replicates of 4 4 Latin square design and the

treatments were allotted randomly. The experiment

consisted of four periods of 21 days each, during

which first fourteen days were allotted for

acclimatization of animals to the treatments allotted

and the data were collected during the last seven days

of each period.

2.3 Experimental Feed Formulation and Feeding

The basal diet fed as TMR consisting of rice straw,

premix concentrate and fresh brewer’s grain was

formulated using the computer program KCF 2006 [7].

The composition of the formulated TMR is given in

Table 1. The premix concentrate was prepared on

weekly basis. The premix concentrate consisted of

ricestraw chopped to 4-5 cm length to facilitate easy

mixing and intake by animals, and fresh Brewer’s

grain which were weighed separately and mixed in large

Table 1 TMRfeed ingredients and estimated chemical composition.

Feed ingredients % Composition

Premix concentrate

Soya bean meal 11.09

Cassava meal 18.14

Sugar (FSOW) 9.00

Urea 1.20

Mineral 0.40

Salt 1.00

Calcium oxide 0.50

Fresh Brewer’s grain 28.67

Rice straw 30.00

Chemical composition % Composition of DM

Total digestible nutrient 66.00

Crude protein 16.00 Crude fiber 17.80 Acid detergent fiber 20.79 Neutral detergent fiber 38.02 Ether extract 2.38

FSOW = Factory spill over waste.


68

individual plastic containers, to which plant additives

were added and mixed thoroughly just prior to feeding

individual animal after milking in the morning and

evening, in individual feeding troughs. The TMR and

drinking water were provided ad lib. On 16, 17, 18

and 19 days of each period, 10 g chromic oxide,

divided into two doses of 5 g each was fed in the

morning and evening mixed with TMR diet for

determination of total tract digestibility.

2.4 Data Collection

The daily feed intake was determined by recording

orts weight each morning and deducting it from total

TMR fed. Feed samples were taken once a week

dried in forced air oven at 60 °C until constant

weight was obtained on repeated weighing. Samples

were composited at the end of the study and

subjected to proximate analysis, crude protein (CP),

crude fiber (CF), EE, DM and ash were determined

according to AOAC [8] protocol while ADF and NDF

were analyzed according to Van Soest [9] method. On

day 17, 18 and 19, milk sample (60 mL from

morning and 40 mL from evening milking) were

collected, composited and analyzed by automatic

milk analyzer. On the 19 day blood sample was

collected from coccygeal vein or artery, centrifuged

at 1,500 rpm for ten minutes and paired serum were

prepared and stored at -20 °C for blood glucose (BG)

and blood urea nitrogen (BUN) analysis. Body

weights were measured on day 19 and 20 using

portable weighing balance. Fecal grabs were taken

on day 20 at 3 pm in the evening after milking and

on day 21 at 6 AM after morning milking; as Davis

[10] reported fecal grabs taken at these times

represented nearly mean chromic oxide content in 24

h period. The fecal samples were composited, dried

in the forced air oven and the chromic oxide was

measured by atomic absorption spectrometry, using

potassium dichromate as a standard. The total tract

digestibility was calculated using the concentrations

of the nutrients and chromic oxide in the diet and

feces [11].


Data were analyzed by analysis of variance using the

general linear model (GLM) procedure of statistical

analysis system [12]. Treatment means were compared

by Duncan’s New Multiple Range Test and the level of

significance was determined at P < 0.05.


3.1 Dry Matter Intake and Digestibility

The result of the TMR feed analysis is shown in

Table 2, the CP and ADF were higher than the

estimated values while NDF content was below

estimated value.DMI was not significantly (P > 0.05)

different among the treatments. However DMI tended

to be higher in low levels of both Siamese neem and

Zanthoxylum, while higher dose levels showed low

DMI (Table 3). The reduced DMI at higher dose

levels of Zanthoxylum may be attributed to “tingling”

and “numbing” sensation caused by sanshool

compounds of Zanthoxylum. However, DMI in Siamese

Table2 Chemical composition of TMR Feed.

Items (%) Feed samples

NM 0.5 NM 1.5 Zantho 0.1 Zantho 0.5

DM 53.66 53.89 57.11 54.24

GE, kcal 4.32 4.60 4.48 4.32

CP 19.08 18.25 19.12 19.47

EE 3.25 3.61 3.25 3.57

NDF 31.38 33.76 32.48 33.19

ADF 25.55 24.00 22.71 22.32

TA 6.85 6.33 6.65 6.37

NM = Siamese neem, Zantho = Zanthoxylum, GE = Gross energy, CP = Crude protein, EE = Ether extract, NDF = neutral detergent fiber, ADF = Acid detergent fiber, TA = Total ash.


69

neem was not different between two doses, and bitter

taste cannot be responsible for low DMI at higher

dose, because cattle possess fewer genes coding for

bitter taste and therefore are tolerant [13] unlike in

human being where bitter taste cause strong aversion

to that particular food [14]. Therefore, this small

difference in DMI in Saimese neem may be attributed

to individual animal differences.

There were no significant difference in CP, ADF

and NDF digestibility among the treatments.

Significant differences (P < 0.05) were observed for

EE and DM digestibility. Zanthoxylum at 0.5 g kg-1

DM had the highest DMD (84.58%), followed by

Siamese neem at 1.5 g kg-1 DM (84.15%), and the

lowest DMD was found in Siamese neem at 0.5 g

kg-1 DM (82.26%). According to Hutjens [15], the

PSM favorably alter the ruminal fermentation

without causing overall inhibition of fermentation in

rumen or cause a desired animal response in a

non-nutrient role like shift in rumen pH. In the

current study, the high value of DMD in

Zanthoxylum is attributed to salivation induced by

sanshool compounds in Zanthoxylum, which is

reported to cause “tingling” and “numbing”

sensation in the oral cavity through stimulation of

sensory nerves [16]. The saliva of ruminants

contains phosphates and bicarbonates making it

appropriate medium for buffering rumen pH [17],

thereby enhancing microbial fermentation.

Furthermore, it is reported that PSM added to

ruminant feed can enhance or inhibit specific

microbial population in rumen, thereby increasing

efficiency in energy and protein utilization [18].

Also maintaining a ratio of soluble carbohydrate and

soluble protein may improve both palatability and

rumen ecology [19] therefore in current study both

the plants added have probably influenced the DMD

in the rumen in a similar way.

3.2 Milk Yield and Chemical Composition

There were no significant difference (P > 0.05) in

milk yield and chemical composition of milk (Table

3). However, in Zanthoxylum, milk yield tended to be

higher at higher dose levels albeit lower DMI. It can

be deduced that in Zanthoxylum, in spite of lower

DMI, higher dry matter digestibility have resulted in

similar milk yield or slightly higher yield in cows

receiving higher doses of Zanthoxylum than those

receiving lower doses. The percent composition of

milk constituents were unaffected and within normal

range. However, total solid content was below 12%,

this was attributed to early lactation of the animals,

and was expected to improve as lactation approached

peak. Bhosale [20] reported that in a comparative

studyinvolving goats at different lactation, goats

at thirdand fourth lactation produced hightotal solids

Table 3 Effects of Siamese neem and Zanthoxylum on milk yield and composition.

Items (%) Siamese neem Zanthoxylum

SEM P-value 0.5 g/kg DM 1.5 g/kg DM 0.1 g/kg DM 0.5 g/kg DM

DMI (kg) 15.28 14.95 16.14 14.85 0.25 0.29

DMD 82.26c 84.15ab 82.34bc 84.58a 0.24 0.03

Milk (kg) 13.68 13.07 13.83 14.18 0.22 0.36

Fat 3.71 3.63 3.78 3.60 0.04 0.58

Protein 2.95 2.96 2.98 2.99 0.01 0.59

Lactose 4.18 4.20 4.24 4.23 0.01 0.41

SNF 7.93 7.94 8.01 8.01 0.02 0.34

TS 11.64 11.56 11.59 11.63 0.05 0.93

Mineral 0.75 0.75 0.76 0.76 0.02 0.57

ADG (g) 320 710 330 490 0.06 0.08

DMI = Dry matter intake, DMD = Dry matter digestibility, SNF = Solid not fat, TS = Total solid, ADG = Average daily gain. a, b, cMeans within a row without a common superscript letter differ (P < 0.05).


70

13.19%and 13.67% than those at first and second

lactation 12.33% and 12.59%, respectively, in the

current study, all animals were in first lactation and

therefore, low total solid content. Mech [21] reported

that the total solid and other milk constituent content

increased towards the end of lactation in Mithun

cows (Bos forontlis). There were positive average

daily gain in all treatments, especially in

Zanthoxylum at higher dose level, higher DM

digestibility has promoted higher weight gain in

animals receiving Zanthoxylum.

3.3 Blood Metabolites

The blood metabolites such as blood glucose were

unaffected in all treatments, but blood urea nitrogen

levels were elevated at 0 (before feeding), 1, 2 and 3 h

after feeding in all treatments. The elevated blood urea

nitrogen in animals were probably due to presence of

high levels of crude protein in the TMR diet; estimated

crude protein in TMR diet was 16%, while the crude

protein content in TMR diet was 18% to 19% (Tables

1 and 2). Hammond [22] reported that increased

protein in feed with constant energy supply can cause

increased BUN as energy is required for utilization of

nitrogen by microbes in the rumen. In the current study,

sugar (Factory spill over waste) was supplied as the

energy source; either sugar added was inadequate or

was rapidly fermented by microbes rendering it

unavailable as energy source. While dehydration is

another factor that could lead to elevated BUN, this is

unlikely in the current study as clean drinking water

was made available all times. Therefore it may be

reasonably suggested that the probable cause for

elevated BUN was the high CP content in TMR diet,

importantly animals showed no signs of toxicity during

the entire period of study in spite of high BUN levels.

This indicated that dairy cows can tolerate high BUN

levels without any ill effects.

4. Conclusions

In the current study, feeding Siamese neem leaves

and Zanthoxylum pods as feed additives in dairy cows

had no effect on DMI when rice straw was the main

source of fiber, however, there was significant (P <

0.05) effect on DM and EE digestibility. The DMI

was lower in higher dose levels of Siamese neem and

Zanthoxylum compared to lower dose levels, but the

DMD was higher in higher dose levels of Siamese

neem and Zanthoxylum. Highest DMD (84.58%) was

noticed in Zanthoxylum at 0.5 g kg-1 DM. This

probably was due to the increased salivation caused

through “tingling” and “numbing” sensation in oral

cavity by sanshool compounds of Zanthoxylum, which

aided in buffering ruminal pH thereby favoring

digestibility in the rumen. The milk yields were not

significant; however, when compared within plant at

two dose levels higher doses tended to promote higher

milk yields, which were due to increased DMD, in

spite of low DMI at the same dose levels. Therefore,

Siamese neem and Zanthoxylum are potential plants

for use as additives in dairy production system.

Acknowledgments

The study was funded by Thailand International

Development Cooperation Agency (TICA) and

supported in part by Thermo-tolerant Dairy Cattle

Research Group, and Food and Functional Food

Research Cluster, Faculty of Agriculture, Khon Kaen

University.

References

[1] L.P. Broudiscou, Y. Papon, A.F. Broudiscou, Effects of dry plant extracts on feed degradation and the production of rumen microbial biomass in a dual outflow fermenter, Anim. Feed Sci. Technol. 101(2002) 183-189.

[2] European Union, Agriculture Council, Press Release No. 14127.

[3] V.Penjor, S.Pattarajinda, C.Katawatin, W. Gritsanapan, In vitro evaluation of ruminal fermentation of diet with high fiber content using Drumstick, Siamese neem, Turmeric and Zanthoxylum as plant feed additives,in: Proceedings of the 3rd International Conference on Sustainable Animal Agriculture for Developing Countries, Suranare University of Technology, Thailand, 2011, pp. 288-291.

[4] S. Rochfort, A.J. Parker, F.R. Dunshea, Plant bioactives


71

for ruminant health and productivity, A review, Phytochemistry 69 (2) (2008) 299-322.

[5] M. Casewell, C. Friis, M.E. Granell, P. McMullin, I. Phillips, The European ban on the growth-promoting antibiotics and emerging consequences for animal and human health, J. Antimicro. Chemother 52 (2003) 159-161.

[6] E. Sugai, Y. Morimitsu, Y. Iwasaski, A. Morita, T. Watanabe, K. Kubota, Pungent qualities of sanshool-related compounds evaluated by sensory test and activation of rat TRP1, Biosci. Biotechnol. Biochem. 69 (2005) 1951-1957.

[7] V. Pattarajinda, M. Duangjind, Dairy Cattle Management and Feed Formulation Program, Department of Animal Science, Khon Kaen University, 2006.

[8] AOAC, Official Methods of Analysis, 11th ed., AOAC: American Chemical Society, Washington, 1985.

[9] P.J. Van Soest, J.B. Robertson, B.A. Lewis, Methods for dietary fiber, neutral detergent fiber, and non-starch polysaccharides in relation to animal nutrition, J. Dairy Sci. 74 (1991) 3583- 3597.

[10] C.L. Davis, J.H. Byers, L.E. Luber, An evaluation of the chromic oxide method for determining digestibility, J. Dairy Sci. 41 (1958) 152-259.

[11] L.A. Maynard, J.K. Loosli, H.F. Hintz, R.G. Warner, Digestive processes in different species,in: Animal Nutrition, McGraw-Hill Inc., New York, 1979.

[12] SAS, The SAS system, Version 6.2, SAS Institute, Inc., Cary, NC, 1996.

[13] C. Ginane, R. Baumont, A. Favreau-Peign, Perception and hedonic value of basic tastes in domestic ruminants, Physiol. Behav. 104 (2011) 666-674.

[14] C. Drewnowski, Gomez-Carneros, Bitter taste, phytonutrients, and the consumer: A review, Am. J. Clin. Nutr. 72 (2000) 1224-1435.

[15] M.F. Hutjens, Feed additives in dairy nutrition and management [Online], 2002, Retrieved Apr. 3, 2011, http://www.livestocktrail.uiuc.edu/dairynet/paper Display.cfm?ContentID=642.

[16] D.M. Bautista, Y.M. Sigal, A.D. Milstein, J.L. Garrison, J.A. Zorn, P.R. Tsuruda, et al., Pungent agents from Szechuan peppers excite sensory neurons by inhibiting two-pore potassium channels, Nature Neuroscience 11 (2008) 772-779.

[17] J.R. Aschenbach, G.B. Penner, F. Stumpff, G. Gäbel, Ruminant nutrition symposium: Role of fermentation acid absorption in the regulation of ruminal pH, J. Anim.Sci. 89 (2011) 1092-1107.

[18] S. Calsamiglia, M. Busquet, P.W. Cardozo, L. Castillejos, A. Ferret, Invited review: Essential oils as modifiers of rumen microbial fermentation, J. Dairy Sci. 90 (2007) 2580-2595.

[19] B. Sirirat, V. Pattarajinda, M.A. Froetshel, M. Duanjinda, Y. Opatpattanakit, The effects of soluble protein and sugar concentration on ruminal fermentation and nutrient digestibility in crossbred steers, J. Anim. Vet. Adv. 10(13) (2011) 1724-1730.

[20] S.S. Bhosale, P.A. Kahate, K. Kamble, V.M. Thakare, S.G. Gubbawar, Effect of lactation on physico-chemical properties of local goat milk, Vet. World 2 (1) (2009) 17-19.

[21] A.Mech, B.Dhali, C.Prakash, Rajkhowa, Variation in milk yield and milk composition during the entire lactation period in Mithun cows (Bos frontalis)[Online], Retrieved on Sept. 23, 2012, http://www.lrrd.org/lrrd20/5/cont2005.htm.

[22] A.C. Hammond, The use of blood urea nitrogen concentration as an indicator of protein status in cattle, Bov. Practitioner 18 (1983) 114-118.


Feeding Effect of Triticale Fodder as Replacement of

Straw on Production Performance of Dairy Cows

Nathu Ram Sarker1, Mohammad Asaduzzaman1, Khan Shahidul Huque1, Mohammad Toyebur Rahman2, Nazrul

Islam2, Mohammad Enamul Haque3 and Stephen R. Waadington3

1. Animal Production Research Division, Bangladesh Livestock Research Institute, Savar, Dhaka 1341, Bangladesh

2. Livestock Officer, Department of Livestock Services, Krishi Kamar Sarak, Dhaka 1207, Bangladesh

3. Programm Officer and CIMMYT Regional Agronomist, CIMMYT Bangladesh Office, Uttara, Dhaka, Bangladesh

Received: July 27, 2012 / Published: January 20, 2013.

Abstract: Twenty lactating cows of two to five parity having an average live weight of 290.00 to 330.00 kg and an average milk production of 4.54 kg/head/day to 4.66 kg/head/day were selected from the Central Cattle breeding Station and Dairy Farm. The four dietary treatment were: S100T0 (Straw 100: Triticale 0 as control); S50T50 (Straw 50: Triticale 50); S25T75 (Straw 25: Triticale 75) and S0T100 (Straw 0: Triticale 100). It was observed that the roughage dry matter intake (DMI) (2.61 ± 0.07 kg) in percent live weight was significantly (P < 0.05) higher in S25T75 and the lowest (1.76 ± 0.018 kg) in the control group (S100T0) and the differences were significant among the dietary treatments except S50T50 and S0T100. The total DMI was significantly (P < 0.05) higher in S0T100 (13.36 ± 0.13 kg) followed by S25T75, S50T50 and S100T0, respectively. The digestibility of crude protein (CP) was slightly higher in S25T75 (75.48 ± 0.96) compared to S0T100 (75.31 ± 1.45) and the difference was non-significant (P > 0.05). Milk production was significantly (P < 0.05) the highest in S50T50 and the lowest in S100T0 followed by S0T100, S25T75, respectively. The percent increased in milk yield was also the highest in S50T50 (67.68%) and the lowest in S100T0 (28.85%). The 4% fat corrected milk was also significantly (P < 0.05) higher in S50T50 followed by S0T100, S25T75 and S100T0, respectively. Therefore, it can be concluded that triticale and straw at a ratio of 50:50 may be fed for better production performance of dairy cows.

Key words: Triticale green fodder, production performance, replacement, milk yield.

1. Introduction

Feed scarcity is one of the major problem and most

limiting factor in livestock and poultry production in

Bangladesh, especially, during lean season from

March to May for ruminants livestock and throughout

the year for poultry. It has been estimated that in each

year, Bangladesh requires about 27 million tons of

roughage to achieve reasonable production levels from

its current herds. But, the existing supply meets only

50% of the total demand [1]. Imports to meet the gaps

are neither always feasible nor economic and seasonal

feed shortages mean high fodder prices and as a

Corresponding author: Nathu Ram Sarker, Senior Scientist,

research fields: animal nutrition, fodder production, preservation & utilization. E-mail: [email protected].

results poor in livestock production performance. The

situation is mostly aggravated during lean season and

in areas recurrently affected by drought and salinity.

During these periods, the quantity of fodder is

insufficient and its quality in terms of protein and

energy is very low. The challenge for researchers

working with the small-scale farmers is to identify

fodder technologies that matching the existing

cropping pattern of small holder farmers without

affecting major changes in inputs and risks.

Overcoming this challenge is the key to satisfy the

needs and aspirations of many farmers who want to

rear dairy animals and poultry and its productivity

through improvement of cropping systems. It was

observed that small-scale dairy and poultry production

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Feeding Effect of Triticale Fodder as Replacement of Straw on Production Performance of Dairy Cows

73

have preferred option for small-scale farm households

as an income generating activity and employment

opportunities. Based on the research and field

experiments, it was revealed that triticale, is a crop

with good potential to meet the demands of quality

fodder as well as grain for a significant number of

farmers. Most triticale production is utilized as a feed

grain forage, or both in animal feeding, including

poultry, monogastrics, and ruminants.

The transformation of triticale from a scientific

curiosity to a viable crop in the course of a few

decades has been a remarkable achievement in plant

breeding. However, several grain and non-grain

factors have caused triticale to fail as a commercial

food grain. Overenthusiastic promotion of triticale as a

“great nutritious new grain” in the early 1970s

disappointed those who attempted to exploit it,

commercially, greatly damaging the “image” of a

cereal that was still far from having more stable and

acceptable attributes. Global wheat surpluses, lack of

year to year consistency in the composition of triticale

grain, absence of official triticale grading systems, and

lack of proper promotion are additional factors that

have not permitted the formation of the farmer

industry-consumer chain necessary for triticale to

become established as a commercial food grain. This

resulted in disappointment for both farmers and

researchers in developed and developing countries.

Despite this, efforts to resolve the basic problems of

triticale continued. As a consequence, the areas under

triticale production worldwide during the 1986-1992

periods increased from 1 million to nearly 2.5 million

hectares. At present, most triticale cultivation is in

Europe (78%), followed by North America (7%),

Africa (6%), Latin America (5%), and Australia and

New Zealand (4%). Except for a few planted areas in

China, the crop is not commercially grown in Asia.

Active research in enhancing the productivity and end

product quality and promotion of triticale is underway

in more than 30 countries [2].

Farmers in every part of the world have adopted

new techniques and accepted new crops that are

considered profitable and consistent with their

circumstances. The first factors, which favored

farmers’ adoption of triticale, were its superior

performance under unfavorable production conditions

including acidic soils, severe disease or insect

pressures, or drought. Second, it had the ability to

produce higher biomass and high regrowth capacity

after grazing and ability to grow better under

relatively cool temperatures, making it an excellent

forage crop. Third, and equally important, was the

usefulness of triticale as a feed grain mainly for

monogastric animals.

Interest in triticale has developed around two areas

of potential use for the grain. The first area of interest

is for use as a feed grain because it has proven to be a

good source of protein, amino acids and B vitamins. It

has shown promise as both a forage crop and as an

alternative protein source in formulated rations for

monogastrics, ruminants and poultry. The second area

of interest for triticale is in developing the grain as a

food grain cereal that would exhibit unique baking

traits. As a food grain, Triticale has also been

recognized as a hardy crop capable of helping combat

world hunger.

The versatility that triticale offers as a grain, a

forage, for straw, and as a cover crop adds to the

economic viability that sustains the interest in the crop.

Triticale will likely continue to experience increased

levels of production if it is supported with solid

research in genetics, production and utilization.

Triticale a cross cereal crop of wheat and rye

appears to be a particularly promising “new” crop for

farmers, because of its high yield potential, stress

tolerance (especially drought tolerance), and disease

resistance. Triticale is likely to become an

increasingly important cereal that may, in time, even

supplant wheat or maize in some areas [3].

Triticale possesses nutritional qualities very similar

to those of wheat, though it has a higher lysine content

and a better mineral balance. Triticale’s good protein


74

digestibility and its high content of essential amino

acids make it a suitable substitute for the most cereal

grains used in ruminant and non-ruminant diets.

Triticale contained some anti-nutritional factors such

as trypsin and chymotrypsin inhibitors that may

depress feed intake [4]. Triticale also exhibits special

qualities as a forage crop. It has higher protein content

than oats and produces higher forage and silage yields

than oats, barley, wheat, or rye [5]. Supplementation

is necessary to meet the production needs of

ruminants fed with crop residues. Supplementation

may affect the metabolism of both body and rumen

microbes of ruminants. The principal objectives of

supplementation of fibrous crop residues are to

optimize animal productivity through improved

utilization of the residues by the animal and to meet

the requirements of animal for production. Research

works on supplementation of rice straw by legume

forage have been conducted by the several workers

but very little or no work on utilization of triticale

green fodder supplementation with straw based diet.

Based on the above principles, the effect of triticale

green fodder supplementation to straw based diet of

lactating cows was investigated with the following

objectives: 1) to determine the optimum level of

supplementation of triticale green fodder to a rice straw

diet of dairy cows; 2) to determine effect of feeding

triticale green fodder on milk production and its quality.


2.1 Study Area

The study was conducted at Central Cattle Breeding

Centre and Dairy Farm under the Department of

Livestock Services (DLS) in collaboration with

Bangladesh Livestock Research Institute, Savar, Dhaka.

2.2 Experimental Design

A total of 20 lactating crossbred (F × Deshi) cows

of similar lactation period and with average body

weight ranges from 290.00 to 330.00 kg were selected

for the trial. All the experimental cows were

distributed in the respective dietary treatments on the

basis of individual milk production not on the basis of

body weight. All the experimental animals were

selected from Savar Dairy Farm. Homogeneous

productive (group average milk production of animal

varies from 4.54 kg/head/day to 4.66 kg/head/day)

lactating cows of early lactation were randomly

allotted a total of four dietary treatments having five

replications in each dietary treatment. The design of

the experiment was organized in such way that in one

tail, the design of experiment had four straw based

diets which were supplemented with 0%, 50%, 75%

and 100% of triticale green fodder on DM basis and

all the four diets were assigned to four treatment

groups of lactating cows having five cows in each

group. On the other tail of the experiment, the

concentrate portion of other three straw based diets

were replaced by 25%, 50%, 100% triticale green

fodder. Therefore, a total of four treatment groups

including control in one tails were organized a

Complete Randomized Design (CRD) and other three

treatment groups excluding control were arranged in

Complete Randomized Design separately to determine

the treatment effect of supplementation and

replacement of concentrate by triticale and also data

were analyzed for determining the differences among

the treatment means. All cows were allowed to

concentrate mixture as per actual requirement of milk

production in each treatment group. The experimental

layout and composition of concentrate mixture are

presented in Tables 1 and 2.

2.3 Cultivation of Triticale Fodder

A total of 1.75 hectare of land under Bangladesh

Livestock Research Institute research farm was taken

for triticale cultivation as green fodder. The standard

agronomical practices were followed for cultivation of

triticale fodder. The triticale fodder was cut from the

field at the age of 50 days and feeding to the

experimental cows. Cut and carry method was

followed for feeding the animals. Daily requirements

of triticale were collected every day.


75

Table 1 Experimental layout.

Feedstuff Treatment groups

S100 (T0)S50T50

(T1) S25T75

(T2) S0T100

(T3) Rice Straw 100 50 25 0

Triticale green fodder 0 50 75 100

Concentrate* 100 100 100 100

No. of animals 5 5 5 5

*Supplied from the savar dairy farm, DLS. S = Straw, C = 100% means concentrate mixture was supplied to cows as per milk production.

Table 2 Composition of concentrate mixture used in the feeding trial at Savar dairy farm

Ingredients Percent of concentrate mixture

Maize grain 13.00 Wheat bran 54.00 Khesari bran 15.00 Soybean meal 15.00 Dicalcium phosphate powder (DCP) 1.5 Common salt 1.5 Total 100

2.4 Feeding and Management

To accustom the test diets with experimental

animals, an adjustment period for 15 days was

followed before starting the actual feeding experiment.

De-worming and spraying against mites and others

external parasites were done before starting the

experiment. During the feeding trial, the animals were

confined in their respective feeding stalls for all the

times. During the adjustment period, the amounts of

feed offered to the dairy cows were gradually

increased until they reached to a constant level of

forage intake required for each treatment. The animals

were fed roughage diet thrice in a day and concentrate

was supplied in the morning and evening before

milking as per dietary treatment groups. Fresh clean

drinking water was supplied ad lib. at all times. The

feeding experiment was conducted for period of 45

days. All the animals were weighed at the beginning

and at the end of each of 15 days for calculation of

live weight changes.

2.5 Digestibility Trial

A digestibility trial was conducted at the mid of the

experimental period to determine the digestibility of

nutrients. On the 28th day of the feeding trial was

conducted and collection of fecal output was started.

During the digestibility trial, data were recorded on

the daily amount of feed offered, residues left and

faces voided. The total amount of faces voided for 24

h by the individual animal was collected quantitatively

at 8 am daily. It was weighed and representative

samples of each animal were drown in a polythene

bag and 1/20th the fresh daily sample was taken for

dry matter and crude protein analysis. The faecal

samples were collected daily and stored in freezer

(-20 °C) for their further chemical analysis. Faces

samples, five days total collection were aggregated,

mixed and 10% sample was used for the chemical

analysis.

2.6 Data Collection

Feed offered and feed refusal were recorded daily to

determine voluntary DM intake. Daily milk yield of

cow was weighed individually and recorded. Animals

were also weighed and recorded individually at

fortnightly basis by using floor analog balance. Milk

samples were collected weekly basis immediately

after milking of cows and stored in a deep freeze for

future chemical analysis. The fat percentage of milk

sample was determined at same day of collection. The

representative samples of triticale green, straw,

concentrate mixture and refusals were also collected

for chemicals analysis. Milk samples were collected in

weekly basis in the morning was analyzed for butter

fat, crude protein, acidity and solids-not-fat (SNF)

contents.

2.7 Chemical Analysis

The proximate and other components of feed and

fecal materials were done by following the methods

described [6]. Feed DM was determined by oven

drying at 105 °C for 48 h. Ash was determined by

incinerating 5 g of air-dried sample at 550 °C for 16 h.

Acid detergent fibre was determined Van Soest

method using Labcono [7] (Model 30002 Hot


76

Extractor). Kjeldhal method was used for determining

the Nitrogen (N) content of feed, faeces and milk and

the crude protein content were estimated as N × 6.25.

Gerber method was used for determining the fat

percentage of milk samples.

2.8 Analysis of Milk Fat and Protein

The Kjeldhal method was used for determining the

Nitrogen (N) content of milk and the milk protein

content were estimated as N × 6.25 and milk fat

percentage was determined by the Gerber method.


The collected data will be analyzed through

Completely Randomized Design (CRD) and analysis

of variance was done to determine the treatment

effects. Collected data were analyzed statistically by

using Compare Means (CM) procedure of One-Way

Analysis of variance (ANOVA) [8]. Post Hoc

Multiple Comparisons of SPSS 11.5 for Windows

(SPSS Inc. 2002) [9].


3.1 Chemical Composition of the Feeds

The chemical composition of triticale green fodder,

paddy straw and concentrate mixture are presented in

Table 3. The average proximate component of triticale

fodder such as DM, CP, organic matter (OM) and ash

contents were 23.45%, 11.70%, 93.44% and 6.02%,

respectively. Similarly, the chemical composition of

paddy straw was used in the experiment containing

90.92%, 3.35%, 93.44% and 6.06% DM, CP, OM and

ash, respectively. The concentrate mixture was

Table 3 Chemical compositions (% DM basis) of triticale green fodder, paddy straw and concentrate mixture.

Parameters Triticale fodder

Paddy straw

Concentrate mixture

Dry matter (DM %) 23.45 90.92 89.87

Crude protein (CP) 11.70 3.35 20.83

Acid detergent fibre (ADF) 44.90 44.77 15.22

Ash 6.02 6.06 9.77

Organic matter (OM) 93.98 93.44 90.23

prepared and supplied by the Central Cattle Breeding

and Dairy Farm, contained DM, CP, OM and ash

89.87%, 20.83%, 90.23% and 9.77%, respectively.

The ADF contents of triticale fodder, paddy straw and

concentrate mixture were 44.90%, 44.77% and

15.22%, respectively.

3.2 Dry Matter (DM) Intake

Average intake of dry matter (DM), estimated

metabolizable energy (ME) and estimated

metabolizable protein (MP) by the lactating cows is

shown in Table 3. Overall average daily total

roughage DM intake was increased with the increase

in supplementation of triticale green fodder. It reveals

that DM intake was significantly (P < 0.05) differ

among the treatment groups except 75% and 100%

triticale supplementation but the difference was

significant (P < 0.05) between S100T0 and S50T50

dietary treatments and between S100T0 and S25T75;

S100T0 and S0T100, respectively. Similarly, DM intake

was significantly (P < 0.05) differ between S50T50 and

S25T75; S50T50 and S0T100, respectively. The roughage

DM intake (2.61 ± 0.07 kg) in percent live weight was

significantly (P < 0.05) higher in S25T75 treatment

group and lowest (1.76 ± 0.018 kg) in control group

(S100T0) and differences were significant among the

dietary treatments groups except S50T50 and S0T100

treatments. The concentrate was supplied as per

requirement of the milk production of the animals.

Initially, concentrate requirement as per group average

of milk production was statistically differed among

the treatment groups but later on due to the increased

milk production, the requirement of concentrate

mixture among groups were differ significantly. The

study reveals that the average concentrate DM intake

was significantly higher (5.09 ± 0.08 kg d-1) in S0T100

treatment group followed by S50T50, S25T75 and S100T0

treatment groups, respectively. It also indicates that

average concentrate DM intake between S100T0 and

S25T75 treatment groups (4.47 ± 0.09 kg) vs 4.48 ±

0.07 kg) was not differed significantly (P > 0.05). On


77

the other hand, the average concentrate DM intake

among S100T0, S50T50 and S0T100 treatment groups was

differ significantly (P < 0.05). The values of average

concentrate DM intake for the treatment groups S100T0,

S50T50 and S0T100 were 4.47 ± 0.09, 4.69 ± 0.09 and

5.09 ± 0.08 kg, respectively.

The average total intake of dry matter was

significantly (P < 0.05) higher in S0T100 dietary group

(13.36 ± 0.13 kg) followed by S25T75, S50T50 and

S100T0 dietary treatment groups, respectively. The total

DM intake in percent live weight was significantly (P

< 0.05) higher (4.02% ± 0.04%) in S25T75 treatment

group followed by S0T100, S50T50 and S100T0 dietary

treatment groups, respectively. The average values of

DM intake in percent live weight for S100T0, S50T50,

S25T75 and S0T100 treatments groups were 3.21% ±

0.03%, 3.55% ± 0.03%, 4.02% ± 0.04% and 3.82% ±

0.04%, respectively (Table 4). The total DM intake in

percent live weight was significantly (P < 0.05)

among S100T0, S50T50 and S25T75, but the difference

was statistically non-significant (P > 0.05) between

S50T50 and S0T100 treatment groups. It was reported

[10] that dry matter intake by the lactating cows of

developing countries between 250 and 300 kg body

weight was 6.4-7.3 kg d-1.

The DM intake on the basis of per kg metabolic

body size was significantly (P < 0.05) higher in S25T75

dietary treatment group (170 ± 0.002 g-1 W0.75 kg)

followed by S0T100, S50T50 and S100T0, respectively.

The DM intake g-1 W0.75 was significantly differed

between S25T75 and S0T100 treatment groups and

among S50T50, S25T75 and S0T100 treatment, but there

was no significant difference between S100T0 and

S50T50 treatment groups.

Total estimated metabolizable energy (ME MJ d-1)

intake by the lactating cows of different dietary

treatment groups were 89.15 ± 1.39, 108.27 ± 0.99,

109.26 ± 0.88 and 93.54 ± 0.92 for S100T0, S50T50,

S25T75 and S0T100, respectively. The metabolizable

energy intake was significantly higher in S50T50 and

S25T75 treatment groups, but the difference between

two treatments was non-significant (P > 0.05). While

on the other hand, ME intake was significantly (P <

0.05) differ between S100T0 and S50T50; S100T0 and

S0T100 treatment groups. Similarly, the difference was

significant between S50T50 and S0T100; S25T75 and

S0T100 treatment groups, respectively. The ME intake

kg-1 W0.75 by lactating cows was highest in S25T75

dietary treatment group followed by S50T50, S100T0 and

S0T100 treatment groups, respectively. The values of

ME intake kg-1 W0.75 among different treatment groups

were 1.21 ± 0.001, 1.32 ± 0.008, 1.45 ± 0.013 and

1.16 ± 0.001 for S100T0, S50T50, S25T75 and S0T100 for

treatment groups, respectively [11]. Suggested that the

maintenance requirement of lactating cows is slightly

higher than non-lactating dairy animals. This may be

100 kcal ME kg-1 W0.75 for the non-lactating animal

and 117 kcal ME kg-1 W0.75 for the lactating cows.

The total intake of estimated metabolizable protein

(MP g d-1) by the lactating cows feeding triticale

fodder supplementation with straw based diets reveals

that the highest MP intake was observed in S25T75

diets followed by S50T50, S0T100 and S100T0,

respectively. It also found that MP g day-1 was

non-significant between S50T50 and S25T75 treatment

groups but the difference was significant (P < 0.05)

between S100T0 and S50T50; S100T0 and S0T100; S25T75

and S0T100, respectively. The values of MP intake g

kg-1 W0.75 were 11.62 ± 0.12, 12.76 ± 0.09, 13.96 ±

0.13 and 11.09 ± 0.11 for S100T0, S50T50, S25T75 and

S0T100 treatment groups, respectively. The difference

in MP intake g kg-1 W0.75 was significant among the

treatment groups except S100T0 and S0T100 treatments.

3.3 Production Performance

The production performance of cows fed straw

based diet supplemented with triticale fodder is

presented in Table 5. It indicates that initial milk

production was almost similar in all dietary treatment

groups, but the final milk production was significantly

(P < 0.05) the highest in S50T50 treatment group and

lowest in S100T0 followed by S0T100, S25T75 treatment


78

Table 4 Nutrient intake by lactating cows

Parameters S100T0 (Mean SE) S50T50 (Mean SE) S25T75 (Mean SE) S0T100 (Mean SE) Sig.

Roughage dry matter intake (kg d-1) 5.38a 0.07 7.77b 0.04 8.25c 0.07 8.27c 0.13 * Roughage dry matter intake as % of live wt.

1.76a 0.018

2.24b 0.03

2.61c 0.07

2.37b 0.04

*

Concentrate dry matter intake (kg d-1) 4.47a 0.09 4.69b 0.09 4.48a 0.07 5.09c 0.08 *

Total dry matter intake (kg d-1) 9.86a 0.15 12.45b 0.08 12.73b 0.09 13.36c 0.13 *

Total dry matter intake as % of live wt. 3.21a 0.03 3.55b 0.03 4.02c 0.04 3.82b 0.04 *

Dry matter intake (g/kg W0.75 d-1) 130a 0.001 150a 0.009 170c 0.002 160b 0.002 *

ME intake (MJ d-1) 89.15a 1.39 108.27c 0.99 109.26c 0.88 93.54b 0.92 *

Total MP intake (g d-1) 855.79a 13.44 1039.39c 9.46 1048.89c 8.52 898.05b 8.82 *

ME intake (MJ/kg W0.75 d-1) 1.21a 0.001 1.32b 0.008 1.45c 0.013 1.16a 0.001 *

MP intake (g/kg W0.75 d-1) 11.62a 0.12 12.76 b 0.09 13.96c 0.13 11.09a 0.11 *

SE: Standard error of mean; NS: Non-significant; *Significant at 5% level; Means with different letters in the same row differ significantly. (S100T0: 100% Rice Straw + Zero triticale fodder; S50T50: 50% Rice Straw + 50% Triticale Fodder; S25T75: 25% Rice Straw + 75% Triticale Fodder and S0T100: 100% Triticale Fodder; In addition to the roughages, concentrate mixture was supplied as per milk production of the cows in all treatment groups ).

Table 5 Production performances of lactating cows fed straw based diet supplemented with triticale green fodder.

Parameters S100T0 (Mean SE) S50T50 (Mean SE) S25T75 (Mean SE) S0T100 ( Mean SE) Sig.

Average initial milk yield (L d-1) 4.54 0.74 4.58 0.95 4.60 0.84 4.66 0.89 NS

Average final milk yield (L d-1) 5.85d 1.28 7.68a 1.09 6.65c 0.50 7.00b 0.44 *

Milk yield increase (Ld -1) 1.31d 3.10a 2.05c 2.34b *

Per cent of milk yield increase (%) 28.85d 67.68a 44.56c 50.21b *

Initial body weight (kg) 290.00 23.32 330.00 27.82 303.00 15.62 333.00 20.28 NS

Final body weight (kg) 318.00 22.00 377.00 27.29 333.00 16.04 370.00 18.00 *

Daily live weight gain(kg d-1) 0.65d 0.05 1.12a 0.09 0.75c 0.02 0.89b 0.13 *

SE: standard error of mean; NS: Non-significant; *Significant at 5% level; Means with different letters in the same row differ significantly.

groups, respectively. The difference in milk

production between S25T75 and S0T100 was differed

significantly (P < 0.05). It also reveals that average

milk production increased L d-1 was the highest in

S50T50 treatment group (3.10 L d-1) and the lowest in

S100T0 treatment group (3.10 L d-1) and difference

between the treatment was significant (P < 0.05). In

other two treatment groups, the milk production was

increased by 2.05 and 2.34 L d-1 for S25T75 and S0T100

treatment groups, respectively. The study revealed that

cows received 50% straw and 50% (S50T50) triticale

fodder produced the highest amount of milk compared

to other treatment groups. This highest milk

production may due to the synergistic effect of straw

and triticale green fodder and better nutrients flow for

milk production. In terms of per cent increased in milk

yield was also the highest in S50T50 treatment group

(67.68%) and the lowest in S100T0 treatment group

(28.85%). The differences in percent in milk

production among the treatment groups were differed

significantly (P < 0.05).

The initial average body weight of lactating cows

used in the experiment ranges from 290.00 ± 23.32 to

333.00 ± 20.28 kg. It mentioned here that selection of

cows was done based on milk production of the

animals. During selection, the average Body

Condition Score (BCS) of the experimental was 2.0.

Therefore, all the animals were weight gained in

addition to milk production. The nutrients supplied to

the cows through diet utilized for milk production and

additional nutrients were distributed in the tissue

levels and utilized for the muscle growth. The results

indicate that the highest body weight was observed in

S50T50 treatment group (1.12 ± 0.09 kg d-1) and the


79

lowest in S100T0 treatment group (0.65 ± 0.05 kg d-1).

Further, it was also found that the body weight gain

was significantly (P < 0.05) differed among the

treatment groups (Table 5). The milk production trend

of different dietary treatment groups are shown in Figs.

1-4 and percent increased are shown in Figs. 5-7.

Milk production trend of different treatment groups

of lactating cows fed triticale fodder supplementation

with straw based diets.

3.4 Milk Quality

The effect of triticale feeding with straw based diet

on milk quality is shown in Table 6. It reveals that the

y = -0.0082x + 6.0316R2 = 0.1251

01

23

45

67

1 5 9 13 17 21 25 29 33 37 41

Lactation Period (D)

Milk

Yie

ld (Litre

)

Fig. 1 Average milk yield of cows fed 100% straw + 100% conc.

y = 0.0245x + 7.0322R2 = 0.2089

0

2

4

6

8

10

1 5 9 13 17 21 25 29 33 37 41

Lactation Period (d)

Milk

Yie

ld (

Lit

re)

Fig. 2 Average milk yield of cows fed 50% straw + 50 % Concentrate + 100% conc.

y = 0.021x + 6.1328R2 = 0.1661

0

2

4

6

8

10

1 5 9 13 17 21 25 29 33 37 41


Milk

Yie

ld (

Lit

re)

Fig. 3 Group average milk yield of 25% strew + 75% triticale fodder + 100% concentrate fed cows.

y = -0.0008x + 7.0266R2 = 0.0003

0

2

4

6

8

10

1 5 9 13 17 21 25 29 33 37 41


Milk

Yie

ld (

Lit

re)

Fig. 4 Group average milk yield of 100% triticale fodder + 100% concentrate fed cows.

1.12

0.89

0.750.67

0

0.2

0.4

0.6

0.8

1

1.2

Group A Group B Group C Group D

Group categories

Liv

e w

t. g

ain

(kg

/d)

Fig. 5 Live wt. gain performance.

1.31

3.09

2.092.34

0

0.5

1

1.5

2

2.5

3

3.5


Group Categories

Milk

yie

ld in

crea

sed

(l/d

)

Fig. 6 Milk production performance.

67.47

45.44 50.21

28.85

0

20

40

60

80


Categories

% in

crea

sd o

f m

ilk y

ield

Fig. 7 Percent milk yield increased.


80

Table 6 Feeding triticale fodder with straw based diet on milk quality of lactating cows.

Parameters S100T0 (Mean SE) S50T50 (Mean SE) S25T75 (Mean SE) S0T100 ( Mean SE) Sig.

Fat (%) 3.69d 0.08 4.60a 0.09 4.12b 0.12 4.05c 0.19 *

Milk protein (%) 3.27d 0.07 3.60a 0.06 3.50b 0.07 3.39c 0.09 *

Solids-not-fat (%) 8.14 0.12 8.33 0.06 8.26 0.09 8.05 0.09 NS

Total solids (%) 11.91c 0.10 12.53a 0.09 12.36b 0.16 12.19b 0.24 *

Water (%) 88.03 0.09 87.38 0.11 87.64 0.20 87.87 0.26 NS

Specific gravity 1.029 0.0003 1.029 0.0003 1.029 0.0003 1.029 0.0004 NS

Milk yield (L d-1) 5.85d 0.44 7.51a 0.09 6.59c 0.09 7.00b 0.09 *

4% FCM 5.58d 0.04 8.18a 0.10 6.71c 0.10 7.06b 0.09 *

SE: standard error of mean, *significant at 5% level; Means with different letters in the same row differ significantly; NS: Non-significant. (S100T0: 100% Paddy Straw + zero triticale + Concentrate, S50T50: 50% Paddy Straw + 50% Triticale Fodder + Concentrate; S25T75: 25% Paddy Straw + 75 % Triticale Fodder + concentrate and S0T100: Zero straw + 100% Triticale Fodder + Concentrate).

significantly (P < 0.05) of the highest (4.60 0.09) fat

percent was observed in S50T50 treatment and the

lowest (3.69 0.08) in S100T0 treatment group and the

difference was significantly (P < 0.05) between the

treatment groups. The values for fat percent in S25T75

and S0T100 treatment groups were 4.12 0.12 and 4.05

0.19, respectively and the difference was also

significant (P < 0.05) between them. The SNF, SP and

percent water did not differ significantly (P > 0.05)

among the treatment groups. Further, it observed that

percent of total solids (TS) in milk was differed

significantly (P < 0.05) among the treatment groups.

The significantly (P < 0.05) highest (12.53 0.09) TS

was found in S50T50 treatment group and the lowest

(11.91 0.10) in S100T0 treatment group. The values

for TS in S25T75 and S0T100 treatment groups were

12.36 0.16 and 12.19 0.24, respectively. The milk

protein was significantly (P < 0.05) higher in S50T50

followed by S25T75, S0T100 and S100T0, respectively

and the differences were significant among the

treatment groups. The 4% fat corrected milk was also

significantly (P < 0.05) higher in S50T50 treatment

group followed by S0T100, S25T75 and S100T0 treatment

groups, respectively (Table 6).

3.5 Digestibility of Nutrients

The co-efficient digestibility of nutrients of

different diets fed lactating cows is presented in Table

7. It is indicated that the highest co-efficient of DM

digestibility (73.29 ± 0.80) was found in S25T75

treatment group and the lowest in S100T0 treatment

group (64.98 ± 2.25) and the difference was

significant (P < 0.05) between the treatment groups.

Further, the co-efficient of DM digestibility of S50T50

and S25T75 treatment groups were 66.96 ± 0.69 and

73.29 ± 0.80, respectively and there was a significant

(P < 0.05) difference between them. Though, there

was a non-significant (P > 0.05) difference of

co-efficient DM digestibility between S25T75 and

S0T100 treatment groups but little higher DM

digestibility was observed in 100% triticale

supplemented diet compared to 75% triticale group.

Similarly, the values of OM digestibility were 70.04 ±

1.92, 70.23 ± 0.64, 76.31 ± 0.72 and 76.79 ± 0.88 for

S100T0, S50T50, S25T75 and S0T100 treatment groups,

respectively. The co-efficient of digestibility of OM

did not differ significantly (P > 0.05) between S100T0

and S50T50; S25T75 and S0T100 treatment groups,

respectively. The values for co-efficient of

digestibility of ADF were 62.32 ± 2.31, 64.02 ± 0.71,

72.66 ± 0.79 and 70.63 ± 1.64 in S100T0, S50T50, S25T75

and S0T100 dietary treatment groups, respectively. It

also reveals that the ADF digestibility co-efficient was

significantly (P < 0.05) differ among the treatment

groups. The co-efficient of digestibility of CP was

slightly higher in S25T75 (75.48 ± 0.96) treatment

group compared to S0T100 treatment group (75.31 ±

1.45) and difference between the treatments was

non-significant (P > 0.05). On the other hand,

co-efficient of digestibility of CP in S100T0 and S50T50


81

Table 7 Co-efficient digestibility of triticale fodder supplemented with straw based ration fed lactating cows.

Parameters S100T0 (Mean SE) S50T50 (Mean SE) S25T75 (Mean SE) S0T100 (Mean SE) Sig.

DM (%) 64.98c 2.25 66.96b 0.69 73..29a 0.80 73.64a 1.00 *

OM (%) 70.04b 1.92 70.23b 0.64 76.31a 0.72 76.79a 0.88 *

ADF (%) 62.32d 2.31 64.02c 0.71 72.66a 0.79 70.63b 1.64 *

CP (%) 69.34b 1.94 65.08c 1.68 75.48a 0.96 75.31a 1.45 *

Total ash (%) 22.80c 4.20 26.66b 1.76 35.58a 1.93 35.07a 2.33 *

SE: standard error of mean; *Significant at 5% level.

treatment groups were 69.34 ± 1.94 and 65.08 ± 1.68,

respectively and the difference was significant (P <

0.05) between the treatment groups. This similar

digestibility of DM, OM and CP was observed by

Sarker et al. [12] who compared the DM, OM and CP

digestibility of triticale fodder with triticale hay in

dairy cows. The values for digestibility co-efficient of

ash were 22.80 ± 4.20, 26.66 ± 1.76, 35.58 ± 1.93 and

35.07 ± 2.33 for S100T0, S50T50, S25T75 and S0T100

treatment groups, respectively. The data indicates that

with the increased level of triticale fodder

supplementation, digestibility co-efficient was also

increased. This due to fact that the total minerals

content of rice straw may be more liginified compared

to triticale fodder. Therefore, there was a increasing

trend of digestibility co-efficient of ash among the

different treatment groups. Sutton et al. [13] fed grass

silage and urea treated whole-crop wheat silage was

mixed with the grass silage to replace the 0.0, 0.33,

and 0.67 dry matter of the grass silage and found the

effect of the inclusion of urea treated whole-crop

wheat silage on the overall digestibility coefficients

was significant (P 0.05). The addition of the

UWCWS in the diet decreased the digestibility of the

DM, OM, ADF, and NFE but effect on the protein

digestibility was non significant.

4. Conclusions

Triticale fodder is good roughage that may be used

for dairy cows without any adverse effect on intake

and digestibility. The high digestibility of triticale

fodder suggesting that this is promising forage may be

used as supplementation with straw based at a ratio of

50:50 for harvesting better yield from dairy cows and

as well as proper utilization of straw and reduce the

cost of production by saving extra fodder for future

use.

Acknowledgments

The authors are gratefully to Mr. Nur Islam,

Director (Production), Dr. Santi Ranjan Das, Deputy

Director, Mr. Kazi Asraful Alam, Buyer Officer and

Mr. Md. Shafiqur Rahman, Scientific Officer, Dairy

Section of Central Cattle Breeding and Dairy Farm

under the Department of Livestock Services, for their

heartfelt cooperation in facilitating this experiment by

providing dairy cows. The authors also acknowledge

the contribution of CIMMYT for providing financial

help through DANIDA to carryout this work smoothly

and timely. Authors are also thankful to all milkman

and Goalas for their co-operation, contribution and

help by timely milking the cows and helping data

recording during the whole period of the study.

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