Involving Farmers in Agricultural Research Through Farmer Associations

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Involving Farmers in Agricultural Research Through

Farmer Associations: The case from Maputo Province,

Mozambique

Master Thesis, May 2009

Carlos Franscisco Xavier Felimone

Supervisors:

Professor Jens Carl Streibig (Copenhagen University Denmark)

Dr. Roland Brouwer (Eduardo Mondlane University Mozambique)


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Preface

This research has been written as part of Master Degree Thesis, in Agricultural Development

Course at Faculty of Life Sciences, Copenhagen University, Denmark. The research intends to

assess whether agricultural research can use Mozambican Farmer Associations as channels through

which it can access farmers needs, implement the experiments and facilitate the dissemination of

research results. The data to respond the purpose of this research were collected through

questionnaire and semi-structured interview in three districts, Manhia, Marracuene and Namaacha,

located in Maputo, the southern province of Mozambique.

Copenhagen, May 2009

Written by:

_________________________________________________________

Carlos Francisco Xavier Felimone

Student number: ADK07006


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Acknowledgements

I would like to thank my two supervisors, Professor Jens Streibig from Copenhagen University,Denmark and Dr. Roland Brouwer from Eduardo Mondlane University, Mozambique, for their

guidance during all the process of research.

I would like also to thank the Danish International Development Agency (DANIDA) for the

financial support and the Institute of Agricultural Research of Mozambique (IIAM), specifically the

Directorate of Training, Documentation and Technology Transfer (DFDTT) for providing mean of

transport used for the field work.

A very special thanks to my wife Arlete, for her collaboration during the field work and for keeping

me going when the times got tough; and also to my friend Sandre Macie for instructing me on how

to use the statistical program SPSS, employed in analysis of data.

Many thanks go to farmers and their organizations and to Directorates of Agriculture in the three

districts, Manhia, Marracuene and Namaacha, where the research was conducted, for their

collaboration during the data collection phase.

At last but not least, I thank my friend Cesarino Benjamim for reading my thesis and giving some

interesting ideas and my colleagues from Master course Quintino Lobo and Enoque Manhique, for

their collaboration. Many thanks to everybody not mentioned but who have helped me during the

research process.


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Summary

Worldwide it has been recognized that non adoption of technologies by smallholder farmers is

mainly due to the lack of involvement of farmers and extension services in agricultural research

process. As part of the reform from 2005, the Institute of Agricultural Research of Mozambique hascommitted itself to work closely with farmers and extension services in the development and

dissemination of agricultural technologies. But even so, little or no attention has been given to

understanding how to communicate with farmers. Experiences from other countries have shown

some advantages to work with farmer groups, in particular, established farmer organizations (FOs).

These organizations can transmit farmers needs to the research system and facilitate the

dissemination of research results. But the current situation of FOs in Mozambique, in term of

whether they have the capacity to fulfil these functions is unknown. This case research conducted inManhia, Marracuene and Namaacha districts has the purpose to assess whether agricultural

research can use Mozambican Farmer Associations (FAs) as channels through which it can access

farmers needs, implement the experiments and facilitate the dissemination of research results.

The research was conducted through two kinds of questionnaires (one for representatives of FAs

another for individual farmers). The questionnaire for the representatives of FAs was designed toget the characteristics and functioning of FAs. It involved twenty six FAs. The individual

questionnaire was designed to get socio-economic characteristics of farmers, their priority problems,their access to agricultural services providers and to services provided by/or through FAs. It

involved 214 farmer members from the twenty six FAs selected for the case and sixty nine non-member farmers, from the areas where these FAs operate. The research also involved semi-

structured interviews with fourteen key informants, which were used to obtain more profoundinformation about the characteristics of FAs and to get explanations of some issues that arose in the

questionnaire phase. The statistical analysis employed was mainly non parametric tests, except invariable age where was used the parametric t-test.

The findings show that member and non-member farmers have different farming conditions, crops

and destination of their production. They also show that farmer members and their organizations arein better conditions to be involved in the research process because they are more preoccupied with

the improvement of their production and they have mechanism of communication which can ensurethe conveying of farmers constraints to research and disseminate research results. There is,

however, a risk that the involvement of FAs representatives in the agricultural research process

leads to the exclusion of the non-members constraints, priorities and farming conditions. It remains

therefore, important to find ways that will allow non-members constraints and farming conditions

to be addressed in research. And also it is important to take some special consideration to female,illiterate and farmers from FAs out of FOs network, as these groups have shown less access to

research services provided through FAs.


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List of abbreviations

DFDTT: Direco de Formao, Documentao e Transferncia de Tecnologias (Directorate of

Training, Documentation and Technology Transfer)

FAs: Farmer Associations

FOs: Farmer Organizations

FGs: Farmer Groups

FRG: Farmer Research Group

FU: Farmers Union

IIAM: Instituto de Investigao Agrria de Moambique (Institute of Agricultural Research of

Mozambique)

IK: Information and Knowledge

NGOs: Non Government Organizations

UNAC: Unio Nacional dos Camponeses (National Farmers Union)


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Table of Figures

Figure 1: Mozambique farmer organizations structure, adapted from UNAC, 2004 ........................................... 7

Figure 2: Map of Maputo province with indication of the three districts selected for the study ......................... 9

Figure 3: Conduction of questionnaire in farmers field.......................................................................................12

Figure 4: Frequency distribution of farmer associations according to the objectives of their membership......17

Figure 5: Frequency distribution of farmer associations according to the origin of the initiative of their

formation ................................................................................................................................................................. .18

Figure 6: Frequency distribution of farmer associations according to the way they use to share information

and knowledge .........................................................................................................................................................19

Figure 7: Farmer field school in common farm of Bloco 1 Farmers Association .............................................19


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Table of tables

Table 1: List of farmer associations selected for the study by location ...............................................................10

Table 2: Descriptive statistics of farmer associations based in their composition and functioning...................16

Table 3: Frequency distribution of farmer associations according to their status, linkage and farming ...........16

Table 4: Comparison of socio-economic characteristics of members and non-members ..................................20

Table 5: Relationship between the location of farmland and membership..........................................................21

Table 6: Comparing members and non-members based on crops they usually grow .........................................22

Table 7: Destination of farm production, comparing farmer members and non-members ................................22

Table 8: Mann-Whitney mean ranks based on how important is the constraints for members and non-

members................................................................................................................................................................ ...23

Table 9: Mann-Whitney mean ranks based on number of times that farmers have demanded services ...........24

Table 10: Comparing members and non-members in term of their access to agricultural information and

knowledge ................................................................................................................................................................2 5

Table 11: Relationship between the socio-economic characteristics of farmers and the access to information,

knowledge and services ..........................................................................................................................................26

Table 12: Comparing farmers from farmer associations with and without common farm in term of theiraccess to information and knowledge ....................................................................................................................27

Table 13: Comparing farmers from farmer associations network and out of network in term of their access to

information, knowledge and services .....................................................................................................................28

Table 14: Comparing farmers from farmer associations formed by different entities in term of their access to

information and knowledge ....................................................................................................................................29

Table 15: Comparing farmers from farmer associations that had and had no linkage with extension service in

term of their access to extension services ..............................................................................................................29

Table 16: Comparing farmers from farmer associations that had and had no linkage with research, in term of

their access to research services .............................................................................................................................30


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Table of Content

I. Introduction ............................................................................................................................................................ 1

1.1 Research objectives......................................................................................................................................... 2

II. Background ........................................................................................................................................................... 3

2.1 Changes in agricultural research and dissemination of information and knowledge ................................. 3

2.2 Working with farmer groups in agricultural research process ..................................................................... 4

2.3 Experiences on involving farmer organizations in research ........................................................................ 5

2.4 Mozambique Farmer Organizations .............................................................................................................. 6

III. Methodology........................................................................................................................................................ 8

3.1 Research approach .......................................................................................................................................... 8

3.2 Study area ........................................................................................................................................................ 9

3.3 Data collection methods ...............................................................................................................................10

3.4 Sampling and sample size ............................................................................................................................10

3.5 Procedure and time frame.............................................................................................................................11

3.6 Data analysis..................................................................................................................................................12

3.7 Research limitations......................................................................................................................................14

IV. Research results.................................................................................................................................................15

4.1 Profile of farmer associations.......................................................................................................................15

4.2 Type of farmer associations .........................................................................................................................17

4.3 Sharing of agricultural information and knowledge within farmer associations ......................................18

4.4 Socio-economic characteristics of farmers in study area ...........................................................................20

4.5 Farming activities..........................................................................................................................................21

4.6 Access to agricultural information and knowledge ....................................................................................24

4.7 Farmer associations structure and functioning factors that may influence the access to information and

knowledge ............................................................................................................................................................26

V. Discussion ...........................................................................................................................................................31

VI. Conclusion and recommendations ...................................................................................................................37

6.1 Conclusions ...................................................................................................................................................37

6.2 Recommendations .........................................................................................................................................38

References................................................................................................................................................................39

Appendix 1: Individual famers questionnaire ......................................................................................................42

Appendix 2: Famer Associations questionnaire...................................................................................................45

Appendix 3: Socio-economic characteristics that had shown dependence with access to IK and services ......49


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I. Introduction

Mozambique has a wide diversity of soil types and diverse climatic conditions which allow for a

large variety of crops (Southern African Development Community 2008). Agriculture in

Mozambique is almost entirely dominated by smallholders (World Bank 2006). It constitutes the

main source of income for seventy-five percent of the total inhabitants (Food and Agriculture

Organization & World Food Programme 2005). Over the past decade, agricultural growth was

almost entirely driven by farming more land with few technological improvements (World Bank

2006 & Sitoe 2005). Access to and use of improved crop technologies remains limited, and there is

evidence that crop yields are stagnant. Therefore, if appropriate action is not taken, agricultural

growth will slow and rural poverty will remain widespread (World Bank 2006). Some believe that

the slow uptake of new technologies is due to the lack of interaction between research, extension

service and farmer (Kely 2003; Gemo 2007).

The new research institution formed in 2005, Institute of Agricultural Research of Mozambique

(IIAM), integrating all research institutions under the Ministry of Agriculture, has recognized the

lack of interaction with farmers and extension service in the research process. And it decided toadopt participatory approaches, working closely with farmers and extension workers (Direco de

Formao, Documentao e Transferncia de Tecnologias 2006). Nevertheless, little or no attention

has been given to understanding how to communicate with farmers.

Worldwide have been increasing the recommendation for working with farmer groups, particularly

established farmer organizations (Wennink & Heemskerk 2006; Heemskerk & Wennink 2004), due

to their important role in providing farmers constraints and needs to research and for facilitating the

dissemination of information and knowledge to farmers (Heemskerk & Wennink 2004; Mutunga

2008). Thus, it becomes important to assess the possibility to work with farmer organizations (FOs).

Some authors suggest a profound analysis of their structure, functioning and composition, as a first

step before working with them (Del Castello and Braun 2006; Sanginga et al 2005).


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The analysis of the current situation of Farmer Organizations (FOs) in the Mozambican context

seems to be important. Because, there is little information about FOs, and especially there is no

research that clarifies whether these organizations can work in collaboration with research,

conveying the interest and needs of farmers, including smallholders farmers, and disseminating

research results for all social economic groupings in their farming community.

1.1 Research objectives

The overall objective of this study is to assess whether agricultural research can use Mozambican

Farmer Associations as channels through which it can access to farmers needs, implement

experiments and facilitate the dissemination of research results. The aims is to help researchers to

decide whether to work with established Farmer Associations (FAs) and to identify key issues that

are necessary to be resolved before starting to work with them.

Four specifics objectives have been defined:

(i) Assess the profile and functioning of Farmer Associations.

(ii) Assess the profile of the farming community, focusing on socio-economic characteristics,

priority problems and access to agricultural service providers.

(iii) Assess whether farmers have been benefiting on agricultural information and knowledge

provided by/or through Farmer Associations.

(iv) Identify the factors linked to Farmer Associations structure and functioning that may influence

farmers access to agricultural information and knowledge.


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II. Background

2.1 Changes in agricultural research and dissemination of information and

knowledge

In the 1980s there have been shifts in thinking and priority setting in agriculture in most of the Third

World (Chambers et al 1990). This shift was due to the previous experiences that have shown little

adoption of agricultural technologies generated at various research institutions (Chambers et al

1990; Wanyonyi et al 2000). Three reason have been pointed: extension service have been

inefficient in serving farmers; smallholders farmers are traditional and conservative in technology

adoption and resistant to change (Wanyonyi et al 2000); and technologies that have been produced

by research and disseminated by extension services might be inappropriate to the smallholder

farmer conditions (Wanyonyiet al 2000; Heemskerk & Wennink 2004).

However, the reasons for non adoption of technologies by smallholder farmers can be summarized

in two key factors: the lack of involvement of farmers and extension persons in all stages of the

technology generation process including diagnosis, planning, evaluation and dissemination

(Wanyonyi et al 2000) and the development of the technologies under research station conditions,

which are not similar to the smallholder farmers (Chambers et al 1990).

Therefore, in 1990s Sub-Saharan African countries embarked on major agricultural sector reforms,

which led to changes in the roles of the public and private sectors as well as civil society

organizations (Wennink & Heemskerk 2006). Research organizations were encouraged to adopt

participatory research methods. According to Okali et al (1994), most of the restructure of national

agricultural research institutions have emphasized participatory structures to foster more

decentralized decisions.

Literature show different ways of working with farmers in participatory agricultural research

process. For example, there are experiences of working with Farmer Groups (FGs), mainly formed

for research purpose, Farmer Research Groups (FRGs), in Latin America (Ashby et al 1995) and


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Ethiopia (Renda et al 2005; Adamo 2001). There are also experiences of working with existing

Farmer Organizations (FOs) and their networks, in Tanzania (Wennink & Heemskerk 2006).

The concept of Farmer Research Group was introduced in Latin America by the Local Agricultural

Research Community, as an extension methodology for participatory technology development.

FRGs can be formed by farmers themselves to solve their common problems and request research

for help, or by external initiative (Renda et al 2005) for participatory research purpose (Ashby et al

1995; Renda et al 2005; Adamo 2001).

Farmer Organizations are organizations owned and governed by farmers and which work for

farmers' interests. These include farmer associations, farmer unions, agricultural cooperatives and

chambers of agriculture (International Federation of Agricultural Producers 1995). In this research it

will be used the terms Farmer Associations to refer to the grassroots farmer organizations and

Farmer Unions, to the groups of FAs that form a network, at local, district, province and national

level.

2.2 Working with farmer groups in agricultural research process

Under reforms made in most of the research and extension organizations, there were adoption of

participatory research approaches and shifts from working with individual farmers to collaboration

with groups and, increasingly, with FOs. Therefore, at the grass-roots level, research and extension

organizations, they are working with farmer associations, producer groups and cooperatives, as well

as specially created farmer research groups. At higher levels, unions, federations and syndicates are

involved in planning research and extension activities (Wennink & Heemskerk 2006).

According to Knox et al (2004), working with group or collective action approach has proved to be

an effective way for motivating participation, coordinating the actions of the multi-resource users

and enhancing empowerment of farmers in the innovation system. Collective action may be aimed

at different purposes and functions (generating, spreading, sharing, utilizing and applying

knowledge and information). For the spreading and sharing of information and knowledge,

Heemskerk & Wennink (2004), argue that working with FGs they can provides opportunity to share

information and thus, create a multiplier effect, which facilitates the spread of technology.


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Involving FGs is also important for communicate farmers constraints to the research system and

provide an information and communication network (Wennink & Heemskerk 2006). In developing

countries, FGs, specifically the established FOs, can be an effective alternative for provision of

agricultural services for farmers. As the reform that held in some developing countries, a range of

services that were provided by public sector are privatized and in many countries private sector did

not replace public in provision of those services and where it did, it often did not reach the poors

(Naranjo et al 2007).

The importance of working with FGs seems to be clear. The question now is which kind of FGs will

really be effective in development and dissemination of agricultural technologies? Literature

suggests working with: exiting FGs; groups with representation of all categories of households

(Heemskerk & Wennink 2004); with representation at high level; and with efficient communications

channel, what can be through networking (Mutunga 2008).

The advantage of working with existing groups is because they already know each other and they

have proven their ability to work together. The representation of all categories of households,

including the poor, is to ensure that the needs of all categories can be addressed in the research(Heemskerk & Wennink 2004). Working with FOs networked from local to high level and with

efficient communications channels, will guarantee effective and efficient regular flow of

information and convey of the interests and concerns of farmers to the appropriate government

decision makers (Mutunga 2008).

2.3 Experiences on involving farmer organizations in research

Experiences from Benin, Rwanda and Tanzania show that FOs are increasingly being solicited to

participate in planning (priority-setting and resource allocation), but their contribution is still limited

due to the lack of skills of their representatives to formulate a mission statement (Shapland &

Kampen 2006).


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In Tanzania, the representative network of FOs, Mtandao wa Vikundi vya Wakulima wa Wilaya ya

Monduli (MVIWATA), emerged in 1993, is strongly involved in agricultural research and

development, and actively approach different sources of information. This farmers network has

developed experience with farmer-to-farmer knowledge exchange for innovation (Lema & Kapange

2006), including the dissemination of farmers best practices through written materials, radio

programmes and newsletters (Kaburire & Ruvuga 2006).

Nevertheless, Cote dIvoire had not been successful in their participatory framework adopted with

objective to involve all categories of farmers and FGs in agricultural research process. The poorest

farmers (those are engaged in subsistence farming and livestock keeping), did not have any

important roles in the research process, because they are not organized and also due to the

complexity of their farming systems (Inter Academy Council 2004).

Farmer research groups formed by Participatory Research for Improved Agro ecosystem

Management Project, in Ethiopia, were successful in their involvement in research process but less

in sharing research results with their community; they were sharing the research results among

members of FRGs (Adamo 2001).

2.4 Mozambique Farmer Organizations

Mozambique has long history of working in groups, mainly in agriculture sector. In 1950s there

was a growing numbers of FOs, promoted by the Portuguese government, with objective to bring

together prosperous farmers, so that they can get help from the government (Hedges 1999). After

the independence in 1975, the new government led by the socialist party, also suggested farmers to

work together in farmer cooperatives (Gotschi 2007, citing Vugt 2001).

With the transition of the country into market economy, farmer cooperatives were transformed in

farmer associations (Gotschi 2007, citing Vugt 2001). And, in 1987 leaders of the farmer

associations decided to form Farmers National Union (Unio Nacional dos Camponeses), which

was officially establish in 1994 (UNAC 2007). Among several functions, it was created to promote

and defend farmers interest, serve as farmers voice and facilitate the sharing of experience and

information (UNAC n.d).


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The Unio Nacional dos Camponeses (UNAC) is compound by farmer associations and farmer

unions (Figure 1), (UNAC 2004). In 2005, there was four Provincial Farmer Unions (Nampula,

Tete, Manica and Sofala); three provincial committees (Cabo Delgado, Niassa and Maputo); 1.300

farmer associations, cooperatives or other local form of organizations (UNAC n.d). These figures

show that in this period, not all provinces have joined the network of FOs formed by UNAC.

Figure 1: Mozambique farmer organizations structure, adapted from UNAC, 2004

Despite the long history of FOs in Mozambique and the existence of a structured movement of FOs,

Woodhouse (1997) reviewing Mozambique agriculture technology development, from 1975 to

1993, showed no evidence of active involvement of farmers and their organizations in agriculture

research process.


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III. Methodology

A combination of social research methodologies have been used to achieve the purpose of this

research assess whether agricultural research can use Mozambican Farmer Associations as

channels through which it can access farmers needs, implement the experiments and facilitate the

dissemination of research results. In this chapter it will be described in detail.

3.1 Research approach

The research approach applied in the study is mixed methods. A mixed method is a research

approach that combines quantitative and qualitative methods in a single research project. It can be

used for improving the accuracy of the finding, to give fuller and more complete picture of the

issues that are being studied, to develop the analysis through addressing the issues that arise during

the research, and compensate the strengths and weakness of each method (Denscombe 2007).

In this research, the mixed methods have been used for two reasons: (i) to give the full picture of the

FAs, through the collection of complementary data that may be difficult to be collected throughquantitative method; (ii) to develop the analysis of the findings through seeking explanation of some

issues that arose during data collection, with quantitative method.


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3.2 Study area

The research had been conducted in three districts (Manhia, Marracuene and Namaacha) belonging

to Maputo province (Figure 2), the southern province of Mozambique. Maputo province is located

in agro-ecological zones one and two, characterized mainly by sandy soil and annual precipitation

between 500 600 mm (Ministry of Agriculture and Fisheries 1996, cited in Walker et al 2006).

Figure 2: Map of Maputo province with indication of the three districts selected for the study

Agriculture is the main income activity for the population in the study area, with the following

percentage of the people involved: seventy-seven in Manhia (Ministrio da Admistrao Estatal

2005a), eighty in Marracuene (Ministrio da Admistrao Estatal 2005b) and sixty-eight in

Namaacha district (Ministrio da Admistrao Estatal 2005c). The three districts have a total of 119

FAs; with 9.313 members, 70% of them are women (Direco Provincial de Agricultura de Maputo

2007).


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3.3 Data collection methods

For data collection, have been used a questionnaire (quantitative method) and semi-structured

interview (qualitative method).

Two kinds of questionnaires were used, one to get information from individual farmer and another

for the representatives of FAs. The first questionnaire was designed to get the socio-economic

characteristics of farmers, their priority problems, access to agricultural services providers and to

information and knowledge provided by/or through FAs (see appendix 1). The second questionnaire

was designed to collect information about the characteristics and functioning of FAs (appendix 2).

The semi-structured interview was used to obtain more profound information about the

characteristics of FAs and get explanation of some issues that arose in the research. The following

issues were addressed: Farmer associations and farmers union structure and functioning and farmer

association sharing agricultural information and knowledge.

3.4 Sampling and sample size

The research was based in a case of twenty six farmer associations from 119 existing in the three

districts. The twenty six farmer associations involved in research were selected through simple

random sampling strategy. The sampling frame used for selection was the list of Maputo Province

FAs, provided by Provincial Directorate of Agriculture.

Table 1: List of farmer associations selected for the study by location

Manhia District Marracuene District Namaacha District

Associao 25 de Setembro Associao 7 de Abril Associao Mpala Wa Socoti

Associao Mimbire Associao Guazamutine Associao dos Regantes Mafuiane

Associao Ex-mineiros Associao 19 de Outubro Associao dos Camponeses Impaputo

Associao Indepncia Morte Associao Bolaze B AMPRODEC

Cooperativa Eduardo Mondlane Cooperativa Eduardo Mondlane Associao Combela

Associao Pateque Associao Bobole 1B Associao Alacache

Associao Bloco 1 Associao Cumbene A Associao de Mafavuca

Associao Francisco Manyanga Associao 4 de Outubro

Cooperativa 25 de Junho

Associao Samora Machel

Associao Xifamba Gwadzi

Source: Adapted from Direco Provincial de Agricultura de Maputo, 2007


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For the individual farmers questionnaire, stratified random sampling strategy was used to select the

respondents. The populations of the two stratums are: farmer members of FAs and farmer

households that are not members of any FAs.

The selection of farmer members were based on subpopulation compounds by members of the

twenty six FAs selected for the study. Thus, 214 farmer members from the total of 2432 were

interviewed through the questionnaire. The selection of farmer non-members were based on

subpopulation compounds by farmer households from the communities where these FAs selected

for the study are operating. Thus, sixty-nine farmers out of 1343 were involved in research. The

lists, from which the samples were drowned, were provided by FAs leaders and by the heads of the

communities where the research was conducted.

The semi-structure interview method involved fourteen key informants, namely:

The head of district agricultural directorate (Marracuene), Three extension officers (two in Namaacha and one in Manhia) Representative of district farmers union (Marracuene) The head of the district farmers union (Manhia) Three heads of local farmer unions (Manhia) Five key farmers (two in Manhia, one at Marracuene and two in Namaacha).

3.5 Procedure and time frame

The field work had been conducted from October to December 2008. At the beginning of the

research, an exploratory visit was done to test the questionnaire, establish contacts with keys

persons in each field location and guarantee that the sampling methods and the research plan canwork in the field conditions. Additionally were collected all preliminary information.

The second stage of the research was the conduction of the questionnaire in the entire field site. As

is known in developing countries the level of education is low, mainly in rural area, where this

research was conducted. As a consequence, the administration of the questionnaire was through

individual interview. To maximize the time and reduce the distance, most farmer members were met

in their field early in the morning, as they farm close to each other and usually they are in the field


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early (Figure 3). At afternoon, the interviews were conducted at homes. This period also was

possible to find non-members farmers, as most of them farm far away from FAs farmlands. FAs

representatives questionnaire was conducted at same time with the individual farmers

questionnaire.

Figure 3:Conduction of questionnaire in farmers field

In the last phase of the field work, semi-structured interviews were conducted with key informants

(farmers, extension staff and representative of agricultural directorate) identified in the second

phase.

3.6 Data analysis

The analyses of the findings from the two questionnaires were done through a statistical programme

SPSS, version 12. The level of significance used in research to test the hypothesis is 95%. The

statistical analyses employed were mainly non parametric (Chi-square, Fisher Exact, Mann-Whitney

and median tests) as the research variables are mainly qualitative. Exception was in one case, age,

where a parametric analysis t-test was employed. The points (a) to (d) explain how the data from

each specific objective were analysed and what types of statistical analyses were used.

a) To assess the profile and functioning of farmer associations, the statistical procedure taken was

descriptive statistics (frequency, average, median, maximum and minimum) to find out whether FAs

possess the characteristics desired to become partners in participatory research. The following


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characteristics were analysed: FAs composition, formation, membership, status, networking and

sharing of agricultural information and knowledge.

b) To get the socio-economic characteristics, priority problems and access to agricultural services

providers, the statistical analysis done was to see whether there is any significant difference between

member and non-member farmers in their socio-economic characteristics. This analysis will help to

conclude if there is any socio-economic group excluded from being members of FAs and

consequently their need may not be addressed by research system. Another analysis done was to

compare farmer members and non members to see whether they have same priority problems and if

there is significant difference on where they communicate their agricultural problems. This will

show whether working with FAs representatives, we can ensure the access of the problems and

priorities of member and non-member farmers.

c) In order to assess whether farmers have been benefiting on agricultural information and

knowledge provided by/or through FAs, the following analyses were done: chi-square test to see

whether there is independence between the access to the service and membership of FAs. The

results from this analysis help understand if the service provided by FAs (sharing of information and

knowledge) and through FAs (research and extension services) are benefiting both, member andnon-member farmers. Furthermore, the same analysis had been done comparing farmers based on

their socio-economic characteristics (gender, age, level of education and farm size). Farm size has

been used as indicator of wealth, based in experience from Ouma et al (2002) in Kenya. Therefore,

the larger the farm size, the more wealth is considered.

d) Finally, to identify the factors linked to Farmer Associations structure and functioning that may

influence farmer access to agricultural information and knowledge, the analysis focused on the

following variables: existence of common farm in FAs, FAs networking, linkage with extension and

research organizations, and the origin of the initiative of FA formation. These variables were cross

tabulated with access to agricultural information and services provided by/through FAs to see

whether there is independence.


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3.7 Research limitations

Some farmers selected for the questionnaire were not found during the survey because they were

engaged in farming activities, as the research was conducted in the beginning of the rain season.

Unfortunately, this inconvenient have reduced the numbers of farmers interviewed through

questionnaire. The group of non-member farmers was the most affected because their farmlands are

disperse and located far away from the area of residence. And usually in the period of intensive

agricultural activities, they come back home late. To interview them in their farms, could imply high

cost and impossible within the resources available.

The leadership of FAs has been indicated as an important factor of FAs functioning to be assessed.

Although it was planned to be assessed through individual questionnaire, it failed due to the fact that

in questionnaire interview it was felt that the respondents were not comfortable to assess the

leadership of their organizations.


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IV. Research results

In this chapter it will be presented the main results of the field work. The findings will show the

main characteristics of FAs, including their composition, formation, networking and ways they use

to share agricultural information and knowledge. And also they will show the characteristics of the

farming community, and the differences between farmer members and non-members in term of

farming activities and access to services provided by FAs and by research and extension services

through FAs.

4.1 Profile of farmer associations

The results in table 2 describe the profile of the twenty six farmer associations involved in this

research in term of number of members, number of meetings established per year and farm size

owned by FAs. The average number of members in FAs is around seventy six, ranging from twelve

to 250. Female members represent the majority, with the average of 59.2 per FA, against 17.2 male

members. In term of the number of regular meetings established in FAs per year, range from zero

(two FAs have no regular meetings established) to twelve. The mean and median is respectively 6.5and 4 meetings per year.

Table 2 also shows that the average land size that FAs own is 67.5 hectares, ranging from zero (one

FA have no land) to 300 hectares. According to key informants, all members that their organization

own land have received a certain farm size from their FA land to use for their farming, while they

are member of the FA.


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Table 2: Descriptive statistics of farmer associations based in their composition andfunctioning

FAs characteristics Average Median Maximum Minimum

Number of FAs members 76.5 41 250 12

Number of men in FAs 17.2 7.50 93 0

Number of women in FAs 59.2 35 215 7

Number of regular meetings per year 6.5 4 12 0

Land size belong to FAs (ha) 67.5 51 300 0

Table 3 shows that eighteen FAs out of twenty six are officially registered and the remaining eight,

seven have started the process of registration. Nineteen out of twenty six FAs are networked through

FUs (local, district, provincial and national). But none of the FAs from Namaacha district are in the

network. Five FAs have or had linkage with research (in on-farm trials and/or in farmer field

school) and seven with extension services in on farm demonstrations or in other type of extension

activities.

Table 3: Frequency distribution of farmer associations according to their status, linkage and

farming

FAs characteristics (n=26)

Number of FAs officially registered 18

Number of FAs in process of official registration 7

Number of FAs networked 19

Number of FAs that had linkage with research 5

Number of FAs that had linkage with extension service 7

Number of FAs with common farm 21

Table 3 also shows the number of FAs that have common farm. Common farm here is referring to a

FAs farm where members use to farm together, growing crops for farmer association income.

Therefore, twenty one FAs out of twenty six have about 0.5 to1.0 hectare of land for common

farming. According to key informants, all FAs with common farm meet once a week for common

farming.


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4.2 Type of farmer associations

Farmer associations representatives were asked about the main objectives of their membership.

Figure 4 show that there are two main objectives of FAs membership: (i) access to and mobilization

of production means, such as land, equipment, inputs and water; (ii) lobbing, advocating and

defending farmers interest, when dealing with government authority, public and private sector.

From the twenty six FAs interviewed, twenty five have these two membership objectives. The

second major membership interest of FAs is mobilization of financial means, (nine FAs out of

twenty six). Only six FAs have membership interest in mobilization of information and knowledge

necessary to improve the agricultural production and marketing activities (helping farmers to access

market).

Figure 4: Frequency distribution of farmer associations according to the objectives of their

membership


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Farmer associations representatives were also asked about the origin of the initiative of their FA

formation. The results from figure 5 show that most FAs have been formed by external initiative

(eleven by government and eight by NGOs). Only seven have been formed by farmers initiative.

Figure 5: Frequency distribution of farmer associations according to the origin of the initiative of theirformation

4.3 Sharing of agricultural information and knowledge within farmer

associations

Farmer associations leaders were asked if they use the followings ways for sharing agricultural

information and knowledge: planned regular meetings, extraordinary meetings organized

specifically for sharing information and, field days. The results in figure 6 show that half of FAs

(thirteen out of twenty six) uses the FA regular meetings to share agricultural information and

knowledge. Eleven and ten FAs respectively have used extraordinary meetings and field days.


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Figure 6: Frequency distribution of farmer associations according to the way they use to shareinformation and knowledge

Key informants during the semi-structured interview have pointed another two important ways used

by FAs to share agricultural information and knowledge, within FAs and among FAs, respectively

using common farm/common farming days and through district FU regular meetings. According to

information given by extension workers, common farms have been used by extension personals and

researchers for demonstration and learning. The two farmer field schools found in FAs, during the

research, was implemented on common farm (figure 7); the district FU meetings are organized

monthly, with representative of FAs. In these meetings they share farmers problems, experiences,

and information.

Figure 7:Farmer field school in common farm of Bloco 1 Farmers Association


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4.4 Socio-economic characteristics of farmers in study area

Gender, age, level of education and farm size were used to understand whether there are significant

differences between farmer members and non-members (table 4). The statistical results from gender,

median level of education and farm size show that there is no significant difference between the two

groups of farmers. For average age of farmers, the statistical results show a significant difference

between the two groups. Non-members are relatively younger than farmer members. The average

age of non-members is around 43, while for members is 48 years old.

Table 4: Comparison of socio-economic characteristics of members and non-members

Variables Farmer members Non-members

Gender (Chi-square test: P-value= 0.430)

Number of men 73 (34.1%) 20 (29.0%)

Number of women 141 (65.9%) 49 (71.0%)

Total 214 (100%) 69 (100%)

Age (T- est: t-value= 0.002**)

Age average of farmers 48.4 42.6

Level of education (Median test: P-value = 0.521)

Median level of education (a) 2.5 2.0

Farm size (Chi- est: P-value = 0.261)

Number of farmers with farm size

less than 5 ha

177 (82.7%) 61 (88.4%)

Number of farmers with farm size

of 5 ha or more

37 (17.3%) 8 (11.6%)

Total 214 (100%) 69 (100%)

** significant at 5%

(a) Level of education has been classified as: (1) Illiterate; (2) primary; (3) secondary; (4) High school and (5)

University.


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4.5 Farming activities

To assess the difference between members and non-members in their farming activities, farmers had

been asked about the following aspects: location of their farmland, type of crops they usually grow,

the destination of their farm production, farming constraints and demand of services for solving

their farming constraints, last five years. The answers are summarized in tables 5 to 9.

Table 5 gives the number of farmers with and without farm in lowland or in irrigation system

conditions. The figures show that the majority of farmer members (94.9%) have a farm in lowland

or in irrigation system, whereas non-members the majority (78.3%) farm in upland. The chi-test

shows that this difference is statistical large enough to be considered significant at 5%.

Table 5: Relationship between the location of farmland and membership

Variables Number (%) of farmers by farmland location

Farmer members Non-members

Farming in lowland or in

irrigation system

203 (94.9%) 15 (21.7%)

Not farming in lowland or inirrigation system

11 (5.1%) 54 (78.3%)

Total 214 (100%) 69 (100%)

Chi-square test: P-value = 0.000** significant at 5%

Table 6 gives the results from the question about whether there are differences on the type of crops

that famer members and non-members usually grow. The figures in table represent the number of

farmers growing each kind of crop. The statistical analysis shows that there is significant difference

between members and non-members in numbers of farmers growing cowpea, common beans,

vegetable and banana. For the rest of the crops the difference is not statistical significant. The crops

that show significant difference, there are more members cropping than non-members.


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Table 6: Comparing members and non-members based on crops they usually grow

Crops Number (%) of farmers by type of crop Chi-test: (P-value)

Farmer members Non-members

Maize 210 (98.1%) 67 (97.1%) 0.606

Cassava 181 (84.6%) 63 (91.3%) 0.159

Peanut 115 (53.7%) 31 (44.9%) 0.203

Sweet potatoes 171 (79.9%) 48 (69.6%) 0.074

Cowpea 152 (71.0%) 39 (56.5%) 0.025**

Common beans 163 (76.2%) 21 (30.4%) 0.000**

Vegetable 189 (88.3%) 22 (31.9%) 0.000**

Banana 123 (57.5%) 16 (23.2%) 0.000**

Percentage based on total: farmer members = 214; non-members = 69; (**significant a 5%)

From the question about the destination of the farm production, the figures from table 8 show that

the majority of members (89.3%) are producing for home consumption and to market, while the

majority of non-members (65.2%) are producing only for home consumption. The chi-test shows

that this difference is big enough to be considered statistical significant at 5%.

Table 7: Destination of farm production, comparing farmer members and non-members

Destination of the production Farmer members Non-members

Only for home consumption 23 (10.7%) 45 (65.2%)

Home consumption and to market 191 (89.3%) 24 (34.8%)

Total 214 (100%) 69 (100%)

Chi- est: P-value = 0.000; significant at 5%

Table 8 gives the answer about whether there are differences between members and non-members

on production constraints and priorities. So, farmers were asked to score from one to four according

to the importance they give to the constraints they have faced last five years, in their cropping and

management of the agricultural production (where one is less important and four very important

constraint). The results based on Mann-Whitney test give the mean ranks of each group of the seven

constraints. Non-members have much higher mean of ranks than members in the all constraints.

Difficult to access inputs and production equipments are the two most important agricultural


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constraints for members. For non-members it is the difficult to access technical information

(technical advice) and production facilities. The statistical analysis shows that the difference in

scores given by the two groups, in all constraints, is larger enough to be significant at 5%.

Table 8: Mann-Whitney mean ranks based on how important is the constraints for members

and non-members

ConstraintsMean ranks Mann-Whitney U

(P-values)Farmer members Non-members

Difficult to access production

facilities

128.32 184.41 0.000**

Difficult to access production

equipment

134.22 166.13 0.002**

Difficult to access technical

information

123.51 199.34 0.000**

Difficult to access production inputs 136.36 159.49 0.028**

Difficult to access market 132.32 172.01 0.000**

Difficult to access storage andprocessing facilities

132.58 171.22 0.000**

Difficult to access financial means 132.15 172.56 0.000**

**significant at 5%

Score used in questionnaire: (1) not important; (2) slight important; (3) import; and (4) very important constraint

The question addressed in table 9 is whether there is difference between members of FAs and non-

members in where they demand services to their agricultural difficulties. Farmers were asked to

score from zero to four, according to the number of times they have demanded service in each

institution and organization. The figures based in Mann-Whitney test, show that members have

higher score of ranks than non-members for all the institutions and organizations. The highest mean

ranks from members it is in FAs, while for non-members it is in private companies/organizations.The statistical analyses shows that in four institutions (extension service, research organizations,

FAs and NGOs) the difference is statistical significant. The remaining two institutions (village

authority and private organization), although members have demanded more services than non-

members, the statistical difference is not significant at 5%.


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Table 9: Mann-Whitney mean ranks based on number of times that farmers have demandedservices

Institution/organization Mean ranks Mann-Whitney U

(P-values)Farmer members Non-members

Extension service 164.51 72.17 0.000**

Research organization 147.40 125.24 0.001**

Farmer Associations 170.33 54.12 0.000**

Non Government Organizations 157.81 92.96 0.000**

Village authority 145.85 130.07 0.135

Private organizations/companies 143.33 137.88 0.445

**significant at 5%

Score used in questionnaire: (0) not demanded; (1) demanded once; (2) demanded twice; (3) demanded three times;

and (4) demanded more than three times.

4.6 Access to agricultural information and knowledge

To find out whether there are differences between members and non-members in access to

agricultural services provided by/through FAs, they were asked if they have benefited from the

following services: access to information sharing with other farmers, access to information,knowledge and services provided by extension service and research, through FAs. The figures from

table 10 show the number of farmers that accessed these services. Seventy eight percent of FAs

members and 8.7% of non-members have accessed information and knowledge sharing with other

farmers within FAs. For the services provided by extension services and research organizations also

members have been benefiting more than non-members. And the statistical analysis shows

significant difference between the two groups, members and non-members.


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Table 10: Comparing members and non-members in term of their access to agriculturalinformation and knowledge

Variables Total number (%) of farmers that accessed the service

Farmer members(n=214)

Non-members(n=69)

P-value

Access to IK sharing with other

farmers, promoted by FAs

167 (78.0%) 6 (8.7%) 0.000**

Access to IK andassistance provided by extension

service through FAs

88 (41.1%) 2 (2.9%) 0.000**

Access to IK and

assistance provided by research through

FAs

32 (15.0%) 1 (1.4%) 0.002**

** significant at 5%; Tests used: Chi- est for first variable and Fishers Exact test for second and third variables

The question answered in table 11 is whether there is relationship between the socio-economic

characteristic of farmers (gender, level of education, age and farm size) and access to agricultural

services provided by/through FAs. Farmers were split in two groups (members and non-members).

And the analyses were done within each group.

Within the group of farmer members the results from table 11 and appendix 3 show that there are

significant different between the following variables: (i) Male and female in access to IK and

services provided by research; male had more access than female. (ii) Elder and younger farmers in

access to IK and services provided by extension services; the younger farmer members had more

access than the elderly. (iii) Farmers with different farm size, in access to sharing information;

farmers with small land size had accessed more than those with big farm size. (iv) Farmer with

different level of education in access to IK and services provided by extension services; people with

some level of education had more access than illiterate. Within the category of non-members

farmers, the results show that there are differences between farmers with different farm size in

access to IK and service provide by research and extension service; farmers with farm size less than

5 ha, had not accessed these services.


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Table 11: Relationship between the socio-economic characteristics of farmers and the access toinformation, knowledge and services

Variables Access to IK sharing

with other farmers,promoted by FAs

Access to IK and

assistance provided byextension service through

FAs

Access to IK and

assistance providedby research through

FAs

Within farmer members P-values)

Gender of farmer 0.719 0.562 0.015**

Level of education of

farmer

0.388 0.129 0.002**

Average age of farmer 0.646 0.045** 0.187

Farmers farm size 0.024** 0.136 0.507

Within non-members(P-values)

Gender of farmer 0.235 0.506 0.115

Level of education of

farmer

0.547 0.262 0.517

Average age of farmer 0.428 0.143 0.306

Farmers farm size 0.685 0.000** 0.005**

** significant at 5% (chi- est for gender, level of education and farm size; t- est for age)

4.7 Farmer associations structure and functioning factors that may influence the

access to information and knowledge

The question to be answered in this subchapter is whether there is relationship between the FAs

characteristics and access to information, knowledge and services provided by/or through FAs. The

following FAs characteristics have been analyzed: Existence of common farm, FA networking, the

origin of the initiative for FAs formation and FAs linkage with research and extension service. The

answers are summarized in tables 12 to 16.


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Table 12 shows how many farmers from FAs with and without common farm have accessed

information, knowledge and services provided by/through FAs. And whether there are statistical

differences between farmers from the two groups. The figures show that there are more farmers

from FAs with common farm accessing IK and services provided by/through FAs than farmers from

FAs without common farm. And the chi-test shows that this difference is significant in access to IK

and services provided by FAs and by research through FAs.

Table 12: Comparing farmers from farmer associations with and without common farm in

term of their access to information and knowledge

Variables Number (%) of farmers from P-values

FAs with common farm FAs without common farm

Access to IK sharing with otherfarmers, promoted by FAs 142 (83.5%) 25 (55.0%) 0.000**

Access to IK andassistance provided by

extension service through FAs

72 (42.4%) 16 (35.6%) 0.410

Access to IK andassistance provided by researchthrough FAs

32 (18.8%) 0 (0.0%) 0.002**

**significant at 5%; Test used: Chi-test for first and second variables and Fishers Exact test for third variable

Table 13 shows how many farmers from FAs network and out of network have accessed

information, knowledge and services provided by/through FAs. And whether there are statistical

differences between farmers from the two groups. The figures show that there are more farmers

from FAs network accessing the services than farmers from FAs out of network. The chi-test shows

that this difference is significant in the access to agricultural IK and services provided by FAs and

by research through FAs.


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Table 13: Comparing farmers from farmer associations network and out of network in termof their access to information, knowledge and services

Variables Number (%) of farmers by type of FA P-value

FAs from network

(n=148)

FAs out of network

(n=66)

Access to IK sharing with other

farmers, promoted by FAs 129 (86.6%) 38 (57.6%) 0.000**

Access to IK andassistance provided by extensionservice through FAs

63 (42.3%) 25 (37.9%) 0.545

Access to IK and

assistance provided by research

through FAs

28 (18.8%) 4 (6.2%) 0.017**

**significant at 5%; Test used: Chi- est for first and second variables and Fishers Exact test for third variable

Table 14 shows how many farmers from FAs formed by own farmers initiative, NGOs and

government have accessed IK and services provided by/through FAs. And whether there are

statistical differences among farmers from the three groups. The figures show that about half of

farmers from FAs formed by farmers initiative and NGOs had accessed extension services against

30% of farmers from FAs formed by government. More farmers from FAs formed by farmers idea(36.7%) had accessed research services provided through FAs compared with only 6.5% of farmers

from FAs formed by external initiative (government and NGOs). The statistical analysis show

significant differences among the three groups in access to IK and services provided by research and

extension service.


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Table 14: Comparing farmers from farmer associations formed by different entities in term oftheir access to information and knowledge

Variables Number (%) of farmers that have accessed IK and services

by origin of their FA

P-value

FAs formed by

farmers(n=60)

FAs formed by

NGOs (n=63)

FAs formed by

government(n=91)

Access to IK sharing

with other farmers,promoted by FAs

50 (83.3%) 49 (77.8%) 68 (73.9%) 0.395

Access to IK andassistance provided byextension service

through FAs

28 (46.7%) 33 (52.4%) 27 (29.7%) 0.009**

Access to IK and

assistance provided byresearch through FAs

22 (36.7%) 4 (6.5%) 6 (6.5%) 0.000**

**significant at 5% Test used: Chi- est for first and second variables and Fishers Exact test for third variable

Table 15 gives the number of farmers from FAs that had and that had no linkage with extension

service, last five years (through on-farm demonstration and farmer field school, implemented in

FA), have accessed information and assistance provided by extension service. The results show that

farmers from FAs that had linkage with extension service had more access to their services (62.7%)than those from FAs that had not linkage (34.1%). And the chi-test shows statistical significant

difference at 5%, between the two groups.

Table 15: Comparing farmers from farmer associations that had and had no linkage with

extension service in term of their access to extension services

Variables Number (%) of farmers by type of FA Total

FAs that had linkage

with extension service

FAs that had no linkage

with extension service

Number of farmers that haveaccessed extension services

provided through FAs

32 (62.7%) 56 (34.4%) 88 (41.1%)

Number of farmers that havenot accessed extension servicesprovided through FAs

19 (37.3%) 107 (65.6%) 126 (58.9%)

Total 51 (100%) 163 (100%) 214 (100%)Chi- est (P-value = 0.000; significant at 5%)


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Table 16 shows the numbers of farmers from FAs that had and that had no linkage with research

organization (through on-farm demonstrations or experiment implemented in FAs farms), last five

years, have accessed the services provided by research. The results show that farmers from FAs that

had linkage with research had more access to their services (55%) than those from FAs that had no

linkage (3.6%). And chi-test shows statistical significant difference at 5%, between the two groups.

Table 16: Comparing farmers from farmer associations that had and had no linkage with

research, in term of their access to research services

Variables Number (%) of farmers by type of FA Total

FAs that had linkagewith research

FAs that had no linkagewith research

Number of farmers that haveaccessed research services


26 (55.3%) 6 (3.6%) 32 (15.0%)

Farmers of farmers that havenot accessed research service


21 (44.7%) 161 (96.4%) 182 (85.0%)

Total 47 (100%) 166 (100%) 214 (100%)Chi- est (P-value = 0.000; significant at 5%)


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V. Discussion

This chapter provides the interpretation of the results shown in chapter 4. It provides the information

that show what can be the consequence of involving farmers in research process through farmer

associations. The consequences here addressed are in term of access to farmers needs, implement

experiments and facilitate the dissemination of research results.

Table 2 shows that the average number of member in FAs is about 77 and women represent the

majority (more than of members). This contradicts with the theory that men tend to dominate

community organizations (Sanginga et al 2005 and Kanji et al 2004). For this case, the results might

be influenced by the fact that in the three districts, where the research was conducted, there are more

women engaged in agricultural activities than men (Ministrio da Admistrao Estatal 2005a;

Ministrio da Admistrao Estatal 2005b; Ministrio da Admistrao Estatal 2005c). The

representation of women in farmer associations will guarantee the communication of their needs to

the research system and the access to research results from the experiment implemented with the

representatives of FAs.

The results from table 3 show that not all FAs are officially registered yet. According to extension

workers, this is result of the bureaucracy and high cost involved in previous law, for the registration

of the community organizations. However, the new law, Decreto-Lei 2 /2006, contains less cost

and few official procedures. This will encourage the registration of FAs. Legal status has been

referred as an important key issue to be considered when intending to work with farmer groups or

other community organizations, in development projects (Leisa Magazine 2007).

In term of farmer associations creation, the results from figures 4 and 5 show that most of them

were created by external initiatives, (government and NGOs). And nearly all farmer associations

were created with main objective to access means of production (mainly land) and defend farmers

interest. For instance, almost all FAs members are farming in farmland provided by their

organizations. Three key informants confirmed the fact. Additionally, they indicating that most FAs

created after the independence were formed to access the good farms left by Portugueses farmers.


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This information given by key informants is confirmed by Van de Loo (1984) in his research

conducted in Cabo Delgado province, north of Mozambique.

The results from figure 4 show that most FAs have not been created with the objective to access

information and knowledge needed to improve their agricultural production. Nevertheless, the

results from figure 6 and from key informants show that several FAs are engaged in information and

knowledge sharing through the following strategies or ways: FAs regular meetings, extraordinary

meetings for sharing IK, field days and common farming day. This means that there are some

mechanisms and experiences of sharing information within FAs that can facilitate the dissemination

of research results.

The results from structure and functioning of FAs on table 3, show that nineteen out of twenty six

FAs, representing all FAs from Manhia and Marracuene and none from Namaacha, are networked,

constituting farmer unions (see figure 1). According to Mutunga (2008), the network of FOs from

local to high level is fundamental as it guarantees the effective conveying of the interest and

concerns of farmers to the appropriate sectors. What this mean is that FAs from Manhia and

Marracuene are structured and functioning in the way that will facilitate the communication

between farmers and researchers.

The results from figure 6 and from key informants show that there is regular communication of

farmers within and among FAs. Within FAs it is through FAs regular meetings, field days,

extraordinary meetings and common farming days. Among FAs it is through FU regular meetings,

in Manhia and Marracuene where FAs are networked. The regular communication among farmer

members could act as channel for regular convey of farmers needs to the research system. Mutunga

(2008) highlight the existence of communication channels that guarantee effective and efficient

regular flow of information within and among FOs as key issue to be considered when deciding to

work with FGs.

The socio-economic representativeness of farming community in FAs is also an important factor

considered in research. The results from table 4 show that the proportions of three out of four socio-

economic characteristics (gender, level of education and wealth) are almost equal for the groups of

members and non-members. Nevertheless, the results from average age of famers show significant


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difference. Younger farmers are less represented in FAs than elders, probable because of the

membership objective, which is connected with the access to FAs land. And likely, might not be

land available in FAs to allocate to new members; likewise, the difference between younger and

elders farmers can be associate with other reasons. For example, Dorsey and Muchanga (1999) in

research conducted in Mozambique have found that some FAs after establishment refuse to accept

new members. This means that younger farmers are in risk of not being integrated in already

existing FAs and consequently their needs not addressed in research system. According to Abaru et

al (2006), FAs that are not representing social-cultural and economic structures of their farming

community cannot serve as viable channels through which farmers can take part in decision making.

The findings from tables 5 to 9 have also demonstrate the existence of other differences between the

two groups (members and non-members), related to agricultural aspects (location of their farmland,

crops, destination of their production, production constraints and demand of services). These

differences give the meaning and relevance of working with FAs in agricultural research process.

Table 5 shows that the two groups have farmland in different areas, non-members in upland and

members in lowland or in irrigation system. And there is clear difference on these two farmlands;

for example, in Manhia and Marracuene districts the upland is characterized by poor sandy soilsand lowland, along Incomati River, is characterized by rich clay soils (Leeuwen 1987).This means

that members are farming on better soils conditions than do non-members; consequently, they can

have different cropping system, problems and priorities. This poses challenge for the research

system on deciding where to place the experiments. Experiences from Knox and Lilja (2004) and

Sanginga et al (2005), working with farmer groups, the experiments were placed in shared groups

plots, which were either rented by or donated to the groups. For the current research, this implies the

placement of the experiments in lowland or in irrigation system, where FAs have shared plots

(common farms). And this represents a risk of excluding the upland farming conditions, where non-

members are farming.

In term of crops that farmers usually grow, table 6 shows that there is no statistical difference

between the two groups (members and non-members) in four out of five crops usually grown in

upland conditions. But there are statistical significant differences in all crops usually grown in

lowland conditions. In the last group of crops, there are more members cropping than non-members.


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The differences between the two groups of farmers are also found in the destination of their

production. Table 7 shows that 89.3% of members are cropping for home consumption and market,

while non-members (65.2%) are cropping for home consumption only. Garforth et al (2003) have

also found high percentage of members with market objectives. On the current research, two key

factors can justify the difference: (i) Difference in crops that the two groups grow (table 6);

members of FAs are growing crops with high market value, common beans, vegetable and banana,

which easily get the market. (ii) The existence of surplus for the market; non-members are farming

in upland; the soil fertility in upland is low and there is no access to water (Leeuwen 1987); the

farming relies on precipitation, and the amount of rainfall is around 500 600 mm per year

(Ministry of Agriculture and Fisheries 1996, cited in Walker et al 2006). These two characteristics,

soil and availability of water, affect the yield and consequently the availability of marketable

surplus, mainly for Mozambican poor farmers.

The results from table 8 show that there is statistical significant difference in the importance of the

constraints faced by the two groups of farmers, last five years. Non-members have been more

affected than members, by all the constraints assessed in this research. The differences are also

found in the priorities. This can exposes research system in risk of addressing only FAs members

problems, when working with FAs representatives in research process.

There are differences also in demand of agricultural services (table 9): Members demand more

services than non-members from all institutions and organizations that have been providing

assistance to farmers, except in two (Village authority and private organizations), where the

difference is not significant at 5%. Nambiro et al (2005) have found the same results for demand of

the extension service. According to Chipeta (2006), farmers that demand advisory services are

motivated to develop their agricultural production and also, the demand of services is linked to the

existence of market opportunity.

Literature states that more contact with extension service (Sanginga et al 2005) and growing

marketable crops (Wennink & Heemskerk 2006) are key characteristics of farmers that are

appropriate to work with research. For example, Sanginga et al (2005) have found that farmers with

frequent contact with extension service were more likely to be aware of the innovation and

consequently more inclined to experiment new ideas. Based on these two characteristics (frequent


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contact with extension service and growing marketable crops), suggest to say that members of FAs

from this research, seem to be more prepared to be involved in agricultural research process than

non-members.

In term of access to agricultural information, knowledge and services, table 10 shows that FAs share

information and knowledge with their members. And also, the services provided by research and

extension service through FAs, are accessed by farmer members. This prove the statement that

membership organizations have the tendency to restrict services to their members (Del Castello &

Braun 2006). This can be justified by the fact that information access and sharing occur within

framework of existing socio-economic network (Garforth et al 2003). The implication of this is that,

the experiments results implemented with the representatives of FAs will be shared among

members.

The analyses of the results from table 11 and appendix 3 gives the socio-economic characteristics

that have statistical dependence with the access to information, knowledge and services. The groups

representing these characteristics they will need special considerations in order that they can benefit

from involvement of farmers in research process. The following variables have shown dependence:

(i) Gender and education with access to research services. For gender, male had more access to

research services than female. Sanginga et al (2005) and Kanji et al (2004) have found the same

results in access to external services. For education, illiterate farmers had less access to research

services compared to other farmers with some educations. Nambiro et al (2005) have found the

same results in access to extension services.

(ii) Age of the farmers with the access to extension services. The younger farmers have accessed

more extension services than elder farmers. This difference can be due to the fact that younger

farmers have more education, and thus they might be more aware of innovations.

(iii) Wealth, measured in farm size with access to information sharing. People with less than five

hectares have accessed more IK sharing with other farmers within FAs compared to farmers with

big farm size. Matching small farm size with poverty, we can say that poor farmer member have

sought more for information sharing within their organization than wealthier members. Garforth et


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al (2003) argues that people without direct access to external information through mass media,

telecommunications or travel, depend on their gatekeepers and on their own network. In the

current research, this suggests that poor farmer members rely on FAs agricultural information

sharing with other farmers, probably because they are lack of resources to demand external sources

of information. Hence, the improvement of their agricultural production will depend on the

availability of the information in their FAs.

Tables 12 and 13 show that farmers from FAs with common farm and from FAs network have more

access to IK sharing and to research services provided through FAs. For the access to information

sharing: (i) farmers from FAs with common farm have accessed more these services probably

because they have more frequent contact, as they meet once a week, while other farmers from

organizations that have no common farm, they have less frequent meetings; (ii) farmers from FAs

network have accessed more information sharing because they have frequent contact with other

farmers from the network, through monthly FU meetings. For research services, it is not clear why

farmers from FAs with common farm and networked had more access to their services than other

from FAs without common farm and out of network.

Table 14 shows that the origin of the initiative of FA formation has statistical dependence with theaccess to external services provided through FAs. Therefore, FAs formed by own farmers

initiatives have more access to extension services than FAs formed by government, and more access

to research services than the two groups formed by external initiatives (NGO and government).

These results are supported by the statement from Leisa Magazine (2007) that FGs formed by own

farmers initiatives are more likely to be effective than do those formed by external initiatives.

The analysis of tables 15 and 16 show that there are more farmers from FAs that had linkage with

research and extension benefiting to their services than those from organizations that had no linkage

with these two institutions. This means that the results from the experiments implemented in FAs,

will be accessed only by farmers from the organizations that will be involved in research.


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VI. Conclusion and recommendations

6.1 Conclusions

The analysis of the structure and functioning of FAs shows that the involvement of FAs

representatives in the research process will ensure the transmission of farmer members constraints

to the research system, and facilitate the dissemination of research results. As members of FAs have

been reporting their agricultural problems to their organizations and they regularly meet to share

agricultural information.

The access to good farmland is the main objective of membership of FAs in study area as almost all

members of FAs are farming in FAs land. And those farmlands are in areas with availability of

water and with good

Involving Farmers in Agricultural Research Through Farmer Associations

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