Farmer groups’ characteristics influence on soybean seeds distribution in Embu, Tharaka-Nithi And Meru Counties, Kenya

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FARMER GROUPS’ CHARACTERISTICS INFLUENCE ON SOYBEAN SEEDS DISTRIBUTION IN EMBU, THARAKA-NITHI AND MERU

COUNTIES, KENYA

ESTHER WANJUE NJAGI (B.ENV.) N50/20702/2012

A Thesis Submitted in Partial fulfilment of the Requirements for

the Award of the Degree of Master of Environmental Science in the

School of Environmental Studies of Kenyatta University

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DECLARATION

This thesis is my original work and has not been presented for a degree in any other university or any other award. No part of this thesis may be reproduced without prior permission from the author and /or Kenyatta University.

--- --- Esther Wanjue Njagi (N50/20702/2012) Date

Department of Environmental Science

SUPERVISORS

We confirm that the work reported in this thesis was carried out by the candidate under our supervision.

--- ---

Dr. Monicah Mucheru-Muna Date

Department of Environmental Science School of Environmental Studies

--- ---

Dr. Jayne Mugwe Date

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DEDICATION

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ACKNOWLEDGEMENT

I acknowledge the invaluable guidance and support I received from my supervisors Dr. Monicah Mucheru-Muna and Dr. Jayne Mugwe throughout the research study. My special thanks go to Alliance for a Green Revolution in Africa (AGRA-SHP 014) through Prof. Daniel Mugendi, for funding my research work. I specially thank Dr. Felix Ngetich and Joseph Macharia for their unfailing support and facilitation.

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TABLE OF CONTENTS

DECLARATION ... ii

DEDICATION.. ... iii

ACKNOWLEDGEMENT ... iv

TABLE OF CONTENTS ... v

LIST OF TABLES ... ix

LIST OF FIGURES ... xi

ACRONYMS AND ABBREVIATIONS ... xii

ABSTRACT…. ... xiii

CHAPTER 1 ... 1

INTRODUCTION ... 1

1.1 Background of the study ... 1

1.2 Problem statement and Justification ... 4

1.3 Research questions ... 5

1.4 Research objectives ... 5

1.5 Research hypotheses ... 6

1.6 Significance of the study ... 6

1.7 Conceptual framework ... 6

1.8 Definition of terms ... 8

CHAPTER 2 ... 10

LITERATURE REVIEW ... 10

2.1 Overview… ... 10

2.2 Past efforts in Soybean promotion ... 10

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2.4 Seeds distribution processes ... 15

2.5 Individual farmer characteristics influence on seeds distribution ... 18

2.6 Influence of group characteristics on technology distribution ... 19

2.7 Literature gaps ... 21

CHAPTER 3 ... 22

RESEARCH METHODOLOGY ... 22

3.1 Study area… ... 22

3.2 Research design ... 25

3.3 Sampling strategy ... 25

3.4 Data collection ... 26

3.5 Data management and analyses ... 27

CHAPTER 4 ... 33

RESULTS AND DISCUSSION ... 33

4.1 Introduction ... 33

4.1.1 Group Composition (gender, age and education of group members, size) ... 33

4.1.2 Groups meeting intervals ... 37

4.1.3 Groups training ... 38

4.1.4 Group leadership ... 39

4.1.5 Group assets ... 40

4.1.6 Group registration ... 41

4.1.7 Group activities ... 42

4.2 Soybean seed distribution process ... 44

4.2.1 Seeds distribution to groups ... 44

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4.2.3 Seeds distribution to group members ... 46

4.2.4 Criteria used in seed distribution to group members ... 47

4.2.4 Level of seed distribution ... 50

4.2.6 Amounts of seeds distributed to group members ... 52

4.2.7 Variations in seed quantities distributed to group members ... 53

4.2.8 Farmer-to-farmer seeds sharing ... 54

4.2.9 Second level soybean seeds sharing by individual farmers ... 56

4.2.10 Soybean seeds retrieval by groups ... 56

4.2.11 Challenges in soybean seeds distribution ... 58

4.3 Individual farmer and farm characteristics effects on soybean seeds distribution by group members in Imenti South, Meru South and Mbeere South sub-counties ... 59

4.3.1 Farmers socio demographic characteristics in Imenti South, Meru South and Mbeere South sub-counties ... 60

4.3.2 Farmers and farm characteristics influencing soybean seeds distribution by individual farmers in Imenti South, Meru South and Mbeere South sub-counties ... 63

4.3.3 Logistic regression model analysis of farmers and farm characteristics influencing soybean seeds distribution by individual farmers ... 65

4.4 Influence of farmer groups characteristics on soybean seed distribution to group members……… ... 68

CHAPTER 5 ... 73

SUMMARY OF FINDINGS, CONCLUSIONS AND RECOMMENDATIONS 73 5.1 Summary of findings ... 73

5.2 Conclusions ... 74

5.3 Recommendations ... 75

5.4 Areas for Further research ... 76

REFERENCES. ... 77

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LIST OF TABLES

Table 3.1: Definition of study variables influencing soybean distribution by individual farmers ... 29 Table 3.2: Definition of study variables influencing soybean distribution within groups………... 32 Table 4.1: Group composition (age, gender and education of group members, group size) in Imenti South, Meru South and Mbeere South sub-counties ... 34 Table 4.2: Groups meeting intervals in Imenti South, Meru South and Mbeere South sub-counties ... 37 Table 4.3: Groups training in Imenti South, Meru South and Mbeere South

sub-counties……… ... 38 Table 4.4: Change of group leadership in Imenti South, Meru South and Mbeere South sub-counties ... 39 Table 4.5: Group assets in Imenti South, Meru South and Mbeere South

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LIST OF FIGURES

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ACRONYMS AND ABBREVIATIONS AGRA - Alliance for a Green Revolution in Africa AMREF - Africa Medical Research Foundation CDD - Community Driven Development FAO Food and Agriculture Organisation GTZ - German Technical Cooperation

ICRAF - International Centre for Research in Agro forestry

LM - Lower Midland

LR - Long Rains

N - Nitrogen

NALEP - National Agriculture and Livestock Extension Programme NGO - Non-Governmental Organization

NS Not Significant

SBP - Soybean Project

SoCo - Soybean and Climbing beans Commercialization Project SPSS - Statistical Package for the Social Sciences

SR - Short Rains

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xiii ABSTRACT

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1 CHAPTER 1 INTRODUCTION 1.1 Background of the study

Soybean is considered to be a very important grain legume world-wide (Ahmed et al., 2010; Hartman et al., 2010). It is a multipurpose crop grown for industrial oil production, human food, while it‟s by- products can be used as livestock feed and as a source of bio-energy (Myaka et al., 2005). In addition some varieties of soybean fix 44 to 103 kg N ha-1 annually through biological nitrogen fixation process (Maingi, 2009; Sanginga & Woomer 2009). Tinsley (2009), recommended the need to enhance soybean production by farmers in Kenya following the multiple benefits. However, while USA accounts for 40-45% of the world‟s total soybean production, Sub-Saharan Africa (SSA) accounts for about 1% (Collombet, 2013). In Kenya, soybean has had little or no policy attention, unlike maize and the traditional export crops such as tea and coffee leading to low production (Chianu et al., 2010). Soybean produced in Kenya is below the market demand of food processors, animal feed millers and domestic human consumption. This indicates that part of the demand for soybean is being fulfilled through imports (Chianu et al., 2010; Mahasi

et al., 2011). Additionally, past projects aimed at promoting soybeans in Kenya were

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Access to seed is crucial for the farmers since seeds are the basic agricultural inputs. Access to seed by farmers varies considerably between households due to the influence of the seed exchange/distribution approach, institutional/organizational arrangements and socio-economic conditions of farmers (McGuire, 2008). In most countries worldwide, the vast majority of seed still comes from farmers themselves and other informal channels (Rubyogo et al., 2008). In Africa, farmers mainly get their seeds from informal channels which include farm saved seeds, seed exchanges among farmers and local grain seed market. Cromwell (1997) in Mali and Malawi found that, farmer to farmer seed exchange is an effective means of disseminating new crop varieties to smallholder farmers. However, farmer-to-farmer seed diffusion, left alone, tends to be localized, partly due to inadequate information flows and more so seed exchange and gift-giving among farmers have been declining, as commercial transactions rise in importance (Rubyogo et al., 2010).

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distribution activities. These activities have a wide range of objectives including improved distribution of modern varieties, improving seed availability and reducing the cost of seed (Soniia, 2004).

One of the channels used by the collaborators to disseminate the crop varieties is through farmer groups as it is a way to reach many in the community (Reyes et al., 2014). Today there is much emphasis on community based mechanisms of distribution in order to bring sustainable change. Group approaches to distribution of innovations is more preferred than farmer to farmer approach since it has helped in strengthening seed systems and tailoring them towards specific agro-ecological and socio-economic environments (Lauren et al., 2007). This facilitates coordination in seed distribution, genetic management, monitoring performance and seed production by the groups.

The groups‟ experiments allow farmers to explore new products with limited risks and expense as well as having more influence in the selection process (Ochieng‟, 2012). However, it should not always be assumed that groups are the most appropriate vehicles for technology development and distribution since in some cases farmer groups are not always successful thus the need to better understand under what conditions are farmer groups useful and viable (Kiptot, 2007; Markelova

et al., 2009). In the quest of promoting soybean crop in Eastern Kenya, existing and

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4 1.2 Problem statement and Justification

Soybean is among the world‟s most important legumes but has not been taken up well by farmers in Kenya since its introduction in the 1950‟s even though conditions in many parts of the country support domestic production (Mathu et al., 2010). Several food and feed processing industries using soybean as raw material are located in various parts of Kenya and have continued to import huge quantities of soybean (Chianu et al., 2008). This could be attributed to lack of availability of certified soybean seeds in Kenyan markets and the methods used in promoting and disseminating soybean seeds to the smallholder farmers. Thus a considerable challenge is the mechanisms for promoting legume production such as soybean considering the limitations of seed systems used to distribute new crop varieties.

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seeds distribution process within groups and the effects of individual farmer and group characteristics on soybean seed distribution in the research area.

1.3 Research questions

The study sought to answer the following questions:

i. What are the farmer groups‟ characteristics in Mbeere South, Meru South and Imenti South sub-counties?

ii. How do farmer groups distribute soybean seeds in the three South sub-counties?

iii. How do individual farmer and farm characteristics influence soybean seeds distribution by group members within groups?

iv. How do farmer groups‟ characteristics affect soybean seeds distribution within groups?

1.4 Research objectives

The broad objective of this study was to assess the influence of farmer groups‟ characteristics in soybean seeds distribution in Embu, Tharaka-Nithi and Meru Counties. To achieve this broad objective the study addressed the following specific objectives;

i. To evaluate and document farmer groups characteristics in Mbeere South, Meru South and Imenti South sub-counties.

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iii. To assess individual farmer and farm characteristics influencing soybean seeds distribution by group members.

iv. To assess the effect of group characteristics on soybean seeds distribution.

1.5 Research hypotheses

The research was guided by the following hypotheses:

i. There is a significant relationship between individual farmer and farm characteristics and soybean seed distribution.

ii. There is a significant relationship between group characteristics and soybean seed distribution within groups.

1.6 Significance of the study

The findings of this study will assist to identify and document farmer groups‟ characteristics and their influence on soybean seeds distribution. This will guide extension agents on areas that groups need empowerment in seeds distribution and other technologies in the future. The information will also guide other stakeholders working with or targeting farmer groups in distribution of seeds and other technologies.

1.7 Conceptual framework

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Government, partner organizations, research and

development agencies, NGO‟s

Famer groups

Farmer group characteristics (age,

size, composition, activities, trainings)

Individual farmer and farm characteristics

(age, gender, education, farm

size)

Distribution of soybeans

Effective soybean distribution

Poor soybean distribution

Figure 1.1: Conceptual framework on soybean seeds distribution through farmer groups

1.8 Definition of terms

Farmer group: A local organization of farmers who have banded together to take advantage of social and economic benefits.

Distribution: The sharing of seeds through various means.

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9 Group size: The number of members in a group.

Group age: The number of years the group has existed since formation.

Collective action: It‟s action taken by a group either directly or on its behalf through an organization

Self-help: Activities in which members provide each other with various types of help for a particular shared characteristic such as labor in putting up water projects for development purposes in the villages.

Cereal banking: Involvement in buying, storing and selling basic food grains such as maize, beans among others.

Table banking: This is a group funding strategy where members of a particular group meet once a month, place their savings, loan repayments and other contributions on the table then borrow immediately either as long term or short term loans.

Merry-go-round: It is a continuous cycle of activities among group members and involves rotating savings where the members agree to contribute a fixed amount at each meeting. The funds are collected and certain members are paid the entirety of the collected money on a rotating schedule.

Social capital: Norms and networks that enable collective action which involves the management of resources by groups.

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10 CHAPTER 2 LITERATURE REVIEW 2.1 Overview

Social capital in the form of groups is used in communities worldwide especially in rural areas as safety nets to cope with risks and for mutual assistance (Kristin & Negash, 2005). The group approach has attracted the attention of many research and development organizations, government devolution policies and community-driven development programs (Lauren et al., 2007). Groups are considered by both the Kenyan government and donors to be vehicles and entry points for new technologies and training for farmers (Kristin et al., 2004). Informal self-help groups have historically been an important tool of community development in Kenya. A study done in central Kenya by Place et al. (2002) revealed that most adults belonged to groups. However, the success of groups is influenced by various factors such as, group characteristics, institutional arrangements and external environment (Agrawal & Goyal, 2001; Place et al., 2002; Kristin et al., 2004). Therefore, there is a need for a study the role groups play in technology distribution and evaluation of factors influencing the same.

2.2 Past efforts in Soybean promotion

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failure of many projects to promote soybean in Kenya to the lack of emphasis given to market organization resulting in difficulties for farmer to sell surplus produce. Also, unlike other grain legumes such as common bean, groundnut or cowpea, soybean is not part of the traditional diet of Kenyans (Collombet, 2013). The household and local human consumption market is very limited because of lack of awareness on nutritional content and on soybean preparation (Chianu et al., 2010).

A summary of past projects aimed at promoting soybean by Chianu et al. (2008) showed that most projects were unsuccessful due to limited scope, poor marketing linkages and withdrawal after funding agencies exited. Africa Medical Research Foundation (AMREF) and German Technical Cooperation (GTZ)–Soybean Project (SBP) promoted soybean in various districts in Kenya but despite achieving much at the time the projects ended, neither the public nor the private sector or stakeholders were prepared to continue independent of external support (Chianu et al., 2008). The possibilities of farmers working together (collective action) to reduce transport and other transaction costs in soybean seeds production and produce marketing were largely not explored in those projects (Chianu et al., 2009). One important need thus, is to determine how community-based mechanisms (farmer groups‟) work, the role they play in distribution of technologies to other farmers and factors that influence their collective action initiatives.

2.3 Farmer groups formation and characteristics

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natural resource base (Penunia, 2011). This has contributed to creating an environment in which farming has frequently been risky and unprofitable for smallholders. Farmers all over the world have tried to address this by organizing themselves into farmers, producers and various self-help groups and associations (Kruijssen et al., 2009). Groups have been a type of social capital used by farmers for generations in Africa (Kristin & Negash, 2005).

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As a governance structure, collective action occurs not only when group members pool resources but also when a group establishes rules. Shared norms, previous success in collective action, effective leadership, and interdependence among group members are factors that can encourage and support effective collective action (Agrawal & Goyal, 2001; Markelova et al., 2009). The process of establishing viable farmer groups is not simple. In some cases, the establishment of farmer organizations incurs transaction costs that imply that farmers may be better off not organizing groups (Stockbridge et al., 2003). The costs and benefits of collective action may be perceived very differently by farmers, so that varying intensities of participation are observed, even among those who have decided to formally join a group (Fischer & Qaim, 2011). Farmer groups‟ characteristics are shaped by the individual members‟ characteristics since they are formed around a common interest where farmers with similar characteristics are able to come together for a common interest (Asante et al., 2011).

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characteristics determine membership to groups and therefore could influence group characteristics and group performance.

It is quite common for a farmer to be a member of some type of group. In addition to women‟s and men‟s farmer groups, others include youths, sports, church, school, cattle dip, political party, water, utensils, merry go rounds, clan, funeral and marketing groups. Membership to groups is participatory and not obligatory thus men and women have an equal opportunity to join groups (Agrawal & Goyal, 2001). The group membership ranges from 15-30 farmers of mixed gender or a single gender. Small group size and homogeneity are pre-requisite for success since larger groups face greater organization problems than smaller ones (Varughese & Ostrom, 2001). Thus self-selection is important and usually leads to more cohesion than when an outsider exerts too much influence on membership.

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groups. According to Lauren et al. (2007), a wide range of group strategies exist (from women-only groups on one end of the spectrum, to gender blind male groups on the other, and mixed sex groups in between), thus raising the question of whether certain strategies may be more effective than others at realizing the group‟s objectives.

The performance of farmer groups depends on a variety of variables which include groups characteristics (group size, composition, leadership), organizational structure (rules and decision making), types of products and markets in which they operate and the external environment (Markelova et al., 2009). Various group characteristics exist as a result of various factors that influence group formation and the external environment in which the groups operate. Thus there is need to evaluate and document famer groups characteristics to act as a guide when using farmer groups in technology distribution.

2.4 Seeds distribution processes

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The predominant model for disseminating crop varieties in most African countries is straight forward (Rubyogo et al., 2010). The national agricultural research systems work to develop successful varieties and after variety release, produce an initial supply of breeder and foundation seed. Government seed parastatals and sometimes a few commercial seed companies then take over subsequent production of certified seed to sell directly to selected customers‟ mainly governmental and non-governmental organizations, which distribute the new materials through developmental and occasionally relief programs (Rubyogo et al., 2010). Once the new varieties reach farmers, generally through subsidized or „free' programs, they then diffuse among communities through gift, exchange, or sale at local markets (Mc Guire, 2008; Rubyogo et al., 2010).

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One of the most promising means of scaling up technologies in the new pluralistic extension environment is through social capital in the form of community-based extension mechanisms (Lauren et al., 2007). A number of community-based approaches have been used in seed multiplication as a means to preserve seed mostly of improved varieties and ensure availability to farmers (Beyes & Wopereis, 2014). Most of the community-based approaches are embedded in the food security programs. The objective of these approaches is to help farmers increase seed supply and improve food security (Ayieko et al., 2006). The initiatives to bulk seed have been implemented through farmer groups with the support of the Ministry of Agriculture and NGOs whereby farmer groups are supplied with starter seed to multiply and distribute to other farmers which implies that social capital is a major asset in distribution (Ayieko et al., 2006).

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the role of social capital and its instrumentality in facilitating seed and information exchange.

2.5 Individual farmer characteristics influence on seeds distribution

Farmers require quality seed of appropriate varieties to produce food for household requirements. Thus their access to seed of appropriate quality for use is of importance (Remington et al., 2002). Access to seed by farmers varies considerably between households depending on the seed exchange approach (McGuire, 2008). The seed exchange approach affects the movement of new varieties and associated information through the farmer system (Rubyogo et al., 2010). One of the approaches involves farmer to farmer seed exchange (Stromberg et al., 2010). The norms of farmer-to-farmer seed exchange vary from one society to another.

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Household characteristics, for instance, are known to influence the day to day farm operations and decision making. Gender is supposed to be one source of difference in farmers‟ access to seed since a female headed household is usually poor and their access to information and social networks is expected to be limited (Katungi, 2006). A study on seed access among farmers in Ethiopia showed that a relatively higher proportion of female headed households obtained seed from another farmer as compared to men headed households who acquired seeds from formal seed sources (Beshir, 2013). Thus gender plays a role in seed distribution among farmers.

Education also plays a key role in seed exchange. A study in Uganda by Beshir (2013) revealed that there was a higher tendency of literate farmers acquiring seed from formal sources as compared to the illiterate farmers who acquired seeds from informal sources like farmer to farmer seed exchange. The individual farmer characteristics such as gender, education level, household size, farm size, farming experience, are very important. They influence a farmer‟s whether to share seeds or not (Ofuoku, 2013). Hence, it is important to determine the socioeconomic factors that influence farmers‟ access and distribution of seeds and other technologies.

2.6 Influence of group characteristics on technology distribution

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The size of the group also has been shown to be both positively and negatively associated with the success of farmer groups (Agrawal & Goyal, 2001; Place et al., 2002). Smaller marketing groups have higher internal cohesion because it is easier to monitor members (Lawler et al., 2008). However, larger groups are more likely to achieve economies of scale (Markelova et al., 2009). Place et al. (2005) found that middle sized groups of Kenyan farmers had a higher level of performance, compared both with the smallest and the largest groups. The problem of free riding in groups is more pervasive in larger groups which affect collective good provision. Large groups imply less close social ties among members which increase tendency to free ride on the efforts of others (Fischer & Qaim, 2011). Barham & Chitemi (2009) found no conclusive relationship between group size and marketing success.

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has revealed that groups are very diverse and dynamic taking on new projects and abandoning others especially with withdrawal of donors and if expectations are not met (Onduru et al., 2002; Place et al., 2002). In many cases, collective action has been short lived, linked to accomplishment of the initial goal (Fergus, 2003). Hence the need for a study to determine which characteristics indeed influence soybean seed distribution since various factors influence group activities differently.

2.7 Literature gaps

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22 CHAPTER 3

RESEARCH METHODOLOGY 3.1 Study area

The study was carried out in three sub-counties namely; Mbeere South, Meru South and Imenti South (Figure 3.1).

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Mbeere South sub-county covers an area of 1,321.5 km2 (GOK, 2010) and lies in the Lower Midland Zones three, four and five (LM 3, LM 4 and LM 5) agro-ecological zones (Jaetzold et al., 2007). The area experiences a bimodal rainfall pattern with long rains (LR) occurring from mid-March to June and short rains (SR) from late October to December hence two cropping seasons per year. The average annual rainfall ranges between 700 mm to 900 mm. The area lies within an altitude of approximately 500 m to 1200 m above sea level with annual mean temperature ranging from 21.7oC to 22.5oC (Jaetzold et al., 2007). The population density is approximately 105 persons per km2 with an average farm size of slightly less than 5.0 ha per household (GOK, 2010). The soils are predominantly ferralsols and acrisols (Jaetzold et al., 2007). Crops grown in Mbeere South are maize (Zea mays), beans (Phaseolus vulgaris), cowpea (Vigna unguiculata), soybean (Glycine maxi. L), green grams (Vigna radiata), pigeon pea (Cajanus cajan), and finger millet

(Eleusinecoracana). However Khat („Miraa‟) has also gained a lot of importance in

the area.

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al., 2007). The population density is approximately 205 persons per km2. It is a predominantly maize (Zea mays) growing zone with smallholdings ranging from 0.1 to 2 ha with an average of 1.2 ha per household (Shisanya et al., 2009). Other crops grown in Meru South include; coffee (Coffea Arabica), bananas (Musa spp.), mangoes (Mangifera indica), avocado (Persea americana), beans (Phaseolus

vulgaris), soybeans (Glycine maxi. L), pigeon pea (Cajanus cajan), cowpea (Vigna

unguiculata) and green grams (Vigna radiata).

Imenti South sub-county covers an area of 661.4 Km2 located in Upper zones-Lower highland one (LH1), Upper midland one (UM1), Upper midland two (UM2), Middle zones- Upper midland three (UM3) and Lower zones- Lower midland three (LM3), Lower midland four (LM4) and Lower midland five (LM5) on the eastern slopes of Mount Kenya (Jaetzold et al., 2007). The altitude ranges from 1180 meters in the lower areas to 2200 meters above sea level at the base of Mt. Kenya. Annual mean temperature ranges from 16oC to 23oC with a total annual rainfall of between 500 mm and 2500 mm. The rainfall is bimodal with long rains (LR) occurring from March to June and short rains (SR) from October to December (Jaetzold et al., 2007). The population is 179,604 persons (GOK, 2010). The soils in Imenti sub-county are humic Nitisols while in other parts of the County they are ferrasols and luvisols. Major crops grown in Imenti South include coffee (Coffea Arabica), mangoes (Mangifera indica), pawpaw (Carica papaya), avocado (Persea

americana), bananas (Musa spp.), soybeans (Glycine maxi. L), pigeon pea (Cajanus

cajan), cowpea (Vigna unguiculata), maize (Zea mays), beans (Phaseolus vulgaris),

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Famer groups and individual farmers were interviewed and qualitative and quantitative data on group characteristics influencing soybean distribution obtained. Further, group discussions to enable an in depth investigation into the subject matter under study were also carried out using a checklist. Both primary and secondary data were obtained. Primary sources of data were interview schedules while secondary data sources included government reports, books, journal articles, and theses.

3.3 Sampling strategy

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( - ) ...Equation 1

Where 1.96 is the z-value for a 2-sided 95% confidence interval, c=0.103 is the desired maximal half-width of the confidence interval, and π=0.5 is the population proportion that results in the widest confidence interval for a given sample size (worst-case for a conservative estimate of sample size).

3.4 Data collection

The research instruments used were first pre-tested then revised according to the suggestions made during pre-testing. The pre-testing was done to ensure reliability and validity of the research instruments before the actual data collection exercise. Reliability of research instruments is a measure of the degree to which a research instrument yields consistent results or data after repeated trials while validity is the degree to which the empirical measure or several measures of the concept accurately measure the concept (Mugenda & Mugenda, 1999). This was achieved by conducting a pilot study to evaluate the competency of the research tools. A sample of 4 farmer groups and 12 individual farmers within the groups from Mbeere North sub-county were randomly selected and interviewed. The respondents who participated in the pre-test exercise were excluded in the actual survey.

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soybean seed distribution process while data collected from the individual farmers included farmers‟ demographic and socio economic characteristics and the seed sharing process among the farmers.

Farmer groups‟ and individual farmers survey was guided by structured and semi-structured interview schedules (Appendix 1 and Appendix 2) which were set up and conducted through interviews. Group discussions were conducted using a check list (Appendix 3) which contained open-ended questions. Where necessary, further probing was done so as to get the maximum amount of data and information to help in clarifying the information collected through prior methods.

3.5 Data management and analyses

The first stage of data handling involved checking whether the questionnaires were fully completed and consistently filled. Thereafter, the questions were numerically coded and responses stored in a database using SPSS software (version 16) and STATA software (version 11) (SPSS, 2007; STATA corp, 2009). This was followed by data cleaning. Descriptive statistics -frequency, means, percentages and standard deviation - were used to summarize the data. Cross tabulation and fisher‟s exact test was done for categorical variables while analysis of variance was used to determine significant difference between means of continuous variables at p<0.05. Qualitative data obtained by the use of open-ended questions in interview schedules were summarized according to key themes and illustrated by direct quotes.

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variable, seed distribution where a value of 0 was assigned if the farmer did not share seeds and 1 if the farmer shared seeds. In the logistic regression model, B is the estimated coefficient with standard error S.E. The ratio of B to S.E., squared, equals the Wald statistic. Exp (β) is the predicted change in the odds for a unit increase in the predictor. The model was specified as follows;

………Equation 2

Where

Y= Probability of sharing seeds (0= did not share seeds, 1= shared seeds) = Y intercept

= Coefficient of the independent variables = Independent variables

= Error term

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Table 3.1: Definition of study variables influencing soybean distribution by individual farmers

Variables Definition

Dependent variables Did not disseminate seeds Disseminated seeds

0 1 Independent variables

Gender of respondent 0 Male

1 Female

Main Occupation 1 Farming

2 Others(Business, employed)

Household headship 0 No

1 Yes

Age of the respondent Continuous variable

Education level 0 No formal education

1 With formal education Years of farming experience Continuous

Household size (number) Continuous variable

No. of groups a farmer belongs to Continuous

Main crop farmed 0 Not a legume

1 Legume

Total farm size in acres Continuous

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………3

Where

= latent variable for the group for values greater than and censored for values less than or equal to . The Tobit model can be generalized to take account of censoring from below and from above.

= vector of the independent variable postulated to influence distribution.

= coefficient of the parameters to be estimated.

= is the independently distributed error term assumed to be normally distributed

with a mean of zero and a constant variance.

The observed y is defined by the following measurement equation

[ ]………...4

The Tobit model assumes that which means that the data is censored at zero. The distribution ratio of soybeans ranges between 0-1. Thus the in equation is substituted as follows;

[ ] [ ] …….………5

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dependent variable is not normally distributed since its values range between zero to one. Thus the Tobit model for this study took the following form;

P (0 to 1) =β0+ β1 (Group age) + β2 (Group size) + β3 (Group gender) + β4

(average age of group members) + β5 (Education category of group members) + β6

(Group registration) + β7 (No. of group activities) +β8 (Group meeting intervals) +

β9 (No. of trainings) + β10 (Duration of changing leaders) + β11 (Group assets

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32 Definitions of variables are as shown in Table 3.2.

Table 3.2: Definition of study variables influencing soybean distribution within groups

Variables Definition

Dependent variables

Seeds distribution ratio (0-1) Independent variables

Group age Age of group in years (Continuous)

Group gender 0 Females only

1 Both males and females

Group size Total no. of group members (Continuous)

Group members age 1 26-30

2 31-35 3 36-40 4 41-45 5 46-50 6 51-55 7 56-60 8 Above 60 Education category of group

members

1 All members with formal education

2 Both members without and with formal education

Group registration 0 Not registered 1 Registered

Number of group activities Number of group activities carried out by groups (Continuous)

Group meetings intervals 1 Weekly 2 Fortnightly 3 Monthly 4 Occasionally

Number of trainings Number of agricultural trainings in the last five years (Continuous)

Change of group leaders 1 One year 2 Two years 3 Three years 4 Above three years

Groups assets 0 No group owned assets

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33 CHAPTER 4

RESULTS AND DISCUSSION 4.1 Introduction

This chapter contains farmer groups‟ characteristics such as group age, gender, size, education category, meeting intervals, change of group leadership, trainings, activities and assets ownership. These factors were deemed important in this study because they play a vital role in determining the likelihood of a group disseminating seeds to their group members. Further there is evaluation of the soybean seeds distribution process in the study area. Individual farmer and group characteristics influencing soybean seeds distribution are also identified.

4.1.1 Group Composition (gender, age and education of group members, size) Majority of the groups (77%) in the study area were of mixed gender while the female groups were 23% (Table 4.1). In Imenti South, mixed gender groups (both males and females) were 80%, same as Mbeere South while in Meru South the mixed gender groups were 70% (Table 4.1). The female groups in Meru South were 30% while in Imenti South they were 20% and Mbeere South 20% (Table 4.1).

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Table 4.1: Group composition (age, gender and education of group members, group size) in Imenti South, Meru South and Mbeere South sub-counties

Parameters Imenti South Meru South Mbeere South Total Gender composition

Female only 4(20) 6(30) 4(20) 14(23)

Both Male and female 16(80) 14(70) 16(80) 46(77)

Age of group members

20-25 3(1) 0 6(2) 9(1)

26-30 25(4) 14(4) 20(6) 59(5)

31-35 48(8) 26(7) 32(9) 106(8)

36-40 73(13) 35(9) 41(12) 149(11)

41-45 71(12) 51(14) 32(9) 154(12)

46-50 101(17) 48(13) 37(11) 186(14)

51-55 183(31) 148(39) 121(36) 452(35)

56-60 72(12) 47(13) 38(11) 157(12)

Above 60 9(2) 3(1) 12(4) 24(2)

Mean Mean Mean Mean

No. of males 11 6 4 7

No. of females 20 14 14 16

Group size 29 19 17 22

Group age 7 8 10 8

No formal education 6 4 3 5

With formal education 24 16 15 19

Values in parentheses are percentages

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Likewise, Sanginga et al. (2006) in Uganda found that, although there were no exclusively male farmers‟ groups, there were many exclusively female only groups.

Majority of the group members (452) were between 51-55 years (Table 4.1). Group members between 51-55 years in Imenti South were 183 while in Meru South they were 148 and in Mbeere South 121. The age bracket with the least group members (9) was 20-25 years. Imenti South and Mbeere South had 3 and 6 members respectively in the age category of 20-25 years. From the findings the probability of joining farmer groups increases with age to an optimum of 51-55 years and decreases as one gets older. Asante et al. (2011) also found out that younger farmers are more likely to join farmer based organizations, and the older the farmer gets, the less likely he or she is to join social networks. The findings are also consistent with those of Musyoka (2008) in Mwingi district where most farmers in groups were 50 years and fewer farmers above 60 years. Thus the age of the farmer can influence membership to farmer groups.

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Adong et al. (2013) also noted that farmer group‟s sizes could range between 20 to 25 members which is consistent with the findings of this study.

The mean age of the groups in the study area was 8 years (Table 4.1). In Imenti South the mean age of the groups was 7 years, Meru South 8 years and Mbeere South 10 years (Table 4.1). This shows that majority of the groups had been in existence for more than five years thus in the soybean distribution process existing farmer groups were used to disseminate the soybean seeds. The findings are comparable to those reported by Mukindia (2014) who found out that most groups in Imenti South had been in existence between 5 to 10 years.

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advantage of the benefits associated with groups. The mixture of farmers with different education levels is also crucial in group management since various roles require certain knowledge and skills which results to groups having members of different education categories (Mwanzia, 2014). Hence education is a very important factor influencing the farmer‟s decision to be a member of a farmer group.

4.1.2 Groups meeting intervals

There was a significant association between group meetings intervals and sub counties (p=0.010). Majority of the groups (47%) held their meetings on monthly interval while only 2% of the groups met occasionally (Table 4.2). In Imenti South 70% of the groups met monthly while (5%) met occasionally (Table 4.2). Most groups in Meru South (45%) met monthly while in Mbeere South 60% of the groups met weekly (Table 4.2).

Table 4.2: Groups meeting intervals in Imenti South, Meru South and Mbeere South sub-counties

Group meeting intervals

Imenti South

Meru South

Mbeere South

Total Sig.

Weekly 2(10) 6(30) 12(60) 20(33) 0.010

Fortnightly 3(15) 5(25) 3(15) 11(18)

Monthly 14(70) 9(45) 5(25) 28(47)

Occasionally 1(5) 0 0 1(2)

Total 20(100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

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groups held regular meeting intervals mainly monthly. Likewise a study by Kristin

et al., (2004) in Meru Central also found out that farmer groups had regular meeting

intervals mainly on weekly and monthly basis for merry go round activities.

4.1.3 Groups training

From the study, most groups (92%) had been trained by agricultural officers on soybean agronomics in the last five years (Table 4.3). All groups in Meru South had been trained while in Imenti South they were 90% and 85% in Mbeere South (Table 4.3). There was a significant difference (p=0.043) between number of trainings across the Sub counties (Table 4.3). Meru South, groups had the highest number of trainings at an average of 6 while in Mbeere South and Imenti South the mean number of trainings was 5 and 3 respectively (Table 4.3).

Table 4.3: Groups training in Imenti South, Meru South and Mbeere South sub-counties

Group trainings Imenti South

Meru South

Mbeere South

Total Sig. Had group trainings 18(90) 20(100) 17(85) 55(92) NS

No group trainings 2(10) 0 3(15) 5(8)

Total 20(100) 20(100) 20(100) 60(100)

Mean Mean Mean Mean Sig.

No. of group trainings 3 6 5 5 0.043

Values in parentheses are percentages

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household investments, agricultural value addition and natural resource management (Mbowa et al., 2012; Mwaura et al., 2012).

4.1.4 Group leadership

According to all respondents interviewed, group leaders were democratically elected by members. Most of the groups (47%) elected their leaders after every one year while only 2% of groups let their leaders hold office for more than three years (Table 4.4). There was a significant association ( p=0.047) on the duration that the elected leaders held office with the sub counties (Table 4.4). In Meru South, 55% of the groups elected their leaders after every one year while 5% of the groups in Imenti South elected their leaders in a period of more than three years (Table 4.4).

Table 4.4: Change of group leadership in Imenti South, Meru South and Mbeere South sub-counties

Change of group leaders

Imenti South

Meru South

Mbeere South Total Sig.

One year 7(35) 11(55) 10(50) 28(47) 0.047

Two years 7(35) 0 2(10) 9(15)

Three years 5(25) 9(45) 8(40) 22(36)

Above 3 years 1(5) 0 0 1(2)

Total 20(100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

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4.1.5 Group assets

Most of the groups (92%) had group owned assets (Table 4.5). The results indicate that, equal number of groups (90%) had group owned assets in Imenti South and Meru South while in Mbeere South groups with assets were 95% (Table 4.5). Majority of the groups (92%) had current assets in form of cash at bank or cash at hand while 77%, 50% and 58% in Imenti South, Meru South and Mbeere South, respectively, also owned fixed assets in the form of farming equipment (jembes, hoes, watering cans, wheelbarrows and water tanks) (Table 4.5). Other group owned assets included buildings, land, household items, posho mill and group farms (Table 4.5).

Table 4.5: Group assets in Imenti South, Meru South and Mbeere South sub-counties

Parameters Imenti

South

Meru South

Mbeere South

Total Sig. Groups assets ownership

With group assets 18(90) 18(90) 19(95) 55(92) NS

Without group assets 2(10) 2(10) 1(5) 5(8)

Types of groups assets

Farming equipment‟s 10(77) 5(50) 7(58) 22(63)

Buildings 0 0 1(8) 1(3)

Land 0 0 1(8) 1(3)

Household items 3(23) 4(40) 2(17) 9(26)

Posho mill 0 1(10) 1(8) 2(6)

Group farm 3(15) 3(15) 5(26) 11(18)

Cash(At bank/at hand) 18(90) 18(90) 19(95) 55(92) Values in parentheses are percentages

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fee charged as a penalty in breaking the set rules such as lateness for meetings. Groups also engaged in group activities that help in income generation for the benefit of group members. Other common assets owned by groups were farming equipment. This could be explained by the fact that projects and extension agents use these groups in disseminating research findings and offering extension services. Mwanzia (2014) found out that most farmer groups in Khwisero Western Kenya had group owned assets in form of cash, utensils, dairy goats, cows and farming equipment mainly acquired through contributions and donations. According to Stubbs et al. (2010) sustainability of farmer groups is more likely in groups able to mobilize their own savings in order to undertake joint activities either through membership fees or revenues generated through economic enterprises.

4.1.6 Group registration

Most groups had registered themselves with the social service department in the Ministry of Labour, Social Security and Services at the sub-county level (Table 4.6). In Imenti South and Mbeere South equal numbers of groups (95%) were registered, while in Meru South all the groups (100%) were registered (Table 4.6).

Table 4.6: Group registration in Imenti South, Meru South and Mbeere South sub-counties

Group registration Imenti South

Meru South

Mbeere South

Total Sig. Groups registered 19(95) 20(100) 19(95) 58(97) NS Groups not

registered

1(5) 0 1(5) 2(3)

Total 20(100) 20(100) 20(100) 60(100)

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Most farmer groups register with the department of social services at the Sub-county level as a way of increasing access to financial support and extension services. The advantage of registering a group is that it will be recognized by law as a body and can transact business in its own name. The findings of this study agrees with those of Place et al. (2002) in Central Kenya where they found that majority of the groups were registered. Formal registration of groups is required by the Kenyan government for them to access services and credit facilities (Kristin, et al., 2004; Mwanzia, 2014). This explains why most groups in the study area were registered.

4.1.7 Group activities

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Table 4.7: Activities carried out by groups in Imenti South, Meru South and Mbeere South sub-counties

Group activities

Imenti South Meru South Mbeere South

Total Sig.

Self help 18(90) 8(40) 15(75) 41(68) 0.002

Merry go round

17(85) 18(90) 18(90) 53(88) NS

Credit facilities

9(45) 2(10) 12(60) 23(38) 0.004

Welfare activities

8(40) 3(15) 8(40) 19(32) NS

Farming 10(50) 9(45) 7 (35) 26(43) NS

Silo banking 3(15) 3(15) 0 6(10) NS

Natural resource management

0 6(30) 4(20) 10(17) 0.035

Marketing 7(35) 8(40) 7(35) 22(37) NS

Buying household items

2(10) 4(20) 0 6(10) NS

Table banking 6(30) 5(25) 9(45) 20(33) NS

Mean Mean Mean Mean Sig.

No. of group activities

4 3 4 4 0.046

Values in parentheses are percentages

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collaborators and donors (Mashavave et al., 2011). The conditions and terms under which members will participate in groups are based on the rewards or incentives they receive, or expect to receive in return in terms of access to services, control over decision-making processes or financial returns (Stubbs et al., 2010). This explains why majority of the groups in the study area engage in multiple activities. Place et al. (2004) in Central Kenya found out that groups do take on several activities. The key aspect in having multiple activities may be according to the felt needs of the group, even if it means changing their focus to be able to successfully perform as a group to the benefits of the more members (Kristin et al., 2004).

4.2 Soybean seed distribution process

This section evaluates the soybean seeds distribution process from the point the groups that received seeds. The evaluation of the process was deemed important in this study because it played a vital role in determining the extent of seeds distribution by groups.

4.2.1 Seeds distribution to groups

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Table 4.8: Duration groups received soybean seeds for the first time in Imenti South, Meru South and Mbeere South sub-counties

Year Imenti South Meru South Mbeere South Total

2010 2 (10) 4(20) 1(5) 7(12)

2011 13(65) 7(35) 9(45) 29(48)

2012 5(25) 9(45) 10(50) 24(40)

Total 20(100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

Alliance for a Green Revolution in Afric –Soybean and climbing bean project (AGRA) introduced soybean seeds in the study area in the year 2010 through the Ministry of Agriculture. During that period the groups that received seeds were expected to do seed retrieval through the ministry of agriculture so as to assist in seeds redistribution to other groups. This then explains the increase in number of groups that received the soybean seeds in 2011 and 2012.

4.2.2 Amounts of seeds received by the groups

During seed distribution to groups in the sub-counties, various groups received varying amounts of seeds. The minimum amount of seeds given to the groups was 2 Kg while the maximum amount of seeds given to the groups was 90 Kg (Table 4.9). Groups in Imenti South received the highest amount of seeds with an average of 25.7 Kg, followed by Mbeere South 22.5 Kg and Meru South 16 Kg (Table 4.9).

Table 4.9: Amounts of seeds received by groups in Imenti South, Meru South and Mbeere South sub-counties

Sub County N Min Max. Mean

Imenti South 20 2 90 25.7

Meru South 20 3 90 16.0

Mbeere South 20 2 60 22.5

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Imenti South had the highest amount of seeds distributed possibly because the groups had more group members compared to Meru South and Mbeere South. The access to agricultural services including seeds could be influenced by groups‟ sizes. This agrees with findings of Mwanzia (2014) in Khwisero Western Kenya who found out that an increase in group size leads to an increase in advocated government agricultural services.

4.2.3 Seeds distribution to group members

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Table 4.10: Seeds distribution to group members in Imenti South, Meru South and Mbeere South sub-counties

Distribution Imenti

South

Meru South

Mbeere South

Total Sig. All received seeds 3(15) 12(60) 14(70) 29(48) 0.001 Some received seeds 17(85) 8(40) 6(30) 31(52)

Total 20(100) 20(100) 20(100) 60(100)

Mean Mean Mean Mean

No. of group members who received seeds

14 16 14 15

No. of group members who did not receive seeds

17 9 9 14

Values in parentheses are percentages

It is evident that there was variation in seeds distribution to group members among the groups where in some all members received the soybean seeds while in others not all group members received the seeds. The variation could be attributed to groups‟ operations since once the seed was given to the groups it was up to the groups to decide on the criteria for seed distribution to its members.

4.2.4 Criteria used in seed distribution to group members

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Table 4.11: Criteria used in seeds distribution within groups in Imenti South, Meru South and Mbeere South sub-counties

Seeds distribution criteria

Imenti South

Meru South

Mbeere South

Total Sig.

Position in group 2(10) 0(0) 1(5) 3(5) p<0.001 Participation in

group

2(10) 6(30) 0(0) 8(13)

Presence in meetings‟ during seeds distribution

2(10) 3(15) 0(0) 5(8)

Interested farmers 6(30) 0(0) 5(25) 11(18)

Land size 6(30) 3(15) 0(0) 9(15)

All members 2(10) 8(40) 14(70) 24(40)

Total 20(100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

It is evident that soybean seed sharing was not equal since in some groups not all members benefited which could be attributed to the groups‟ characteristics and mode of operation. Additionally the findings were confrimed by discussions held with farmer groups on criteria used in soybean seeds distribution as shown by captions below.

(Group discussion with Kinoru progressive self-help group in Meru South on 12 December 2014)

„„In the year 2012 we received 8 Kg of soybean seeds as a group from the ministry

of agriculture in Meru South. The seeds were supposed to be distributed to group

members but the decision on how to share the seeds to was upon the group. This was

the first time we heard and saw the soybean seeds thus we were curious about the

new crop variety being introduced. We then decided for fairness, all the group

members then (32) should be given seeds. We shared the seeds equally among the

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(Group discussion with Kangeta enterprises in Mbeere South on 27 January 2015) „„As a group we received 50Kg of soybean seeds in March 2011. All of us as group

members had been called for a meeting so as to receive the soybean seeds on the

day the group leader collected the seeds from the agricultural extension officer. Out

of 20 group members, only 16 of us turned up for the meeting. We decided to share

the seeds only among the members present since the absent members were aware of

the meeting and did not have apologies for absence. We shared the seeds in the

range of 1kg to 5Kg depending on land size. The remaining seeds were returned to

the agricultural extension officer”.

(Group discussion with NeemaMamuru Guardian self-help group in Imenti South on 22 December 2014)

„„In the year 2011 we received 4Kg of soybean seeds as a group from the ministry of

agriculture in Imenti South alongside other seeds for various crops. The seeds were

supposed to be distributed to all group members. After receiving the soybean seeds

we felt that the seeds given were not enough for every member. We thus decided that

the group officials should share the seeds among themselves upon which after

harvesting they would share to other group members. The seeds were shared equally

to four group officials (chair person, secretary, treasurer and vice chairperson)

whereby the group officials received 1kg of the soybean seeds each”.

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50 4.2.4 Level of seed distribution

On distribution levels, 58% of groups distributed their seeds to 75%-100% of their members while 12% disseminated the seeds to less than or equal to 25% of the group members (Table 4.12). There was a significant association (p=0.002) between distribution levels and the Sub counties (Table 4.12). In Mbeere South, 85% of the groups disseminated the soybean seeds at the distribution level of 76%-100% of their members while in Meru South and Mbeere South 5% of the groups disseminated the seeds to 25% and below of their members (Table 4.12).

Table 4.12: Level of soybean seeds distribution in groups in Imenti South, Meru South and Mbeere South sub-counties

Distribution levels Imenti South

Meru South

Mbeere South

Total Sig.

0-25% 5(25) 1(5) 1(5) 7(12) 0.002

26%-50% 5(25) 2(10) 2(10) 9(15)

51%-75% 6(30) 3(15) 0 9(15)

76%-100% 4(20) 14(70) 17(85) 35(58)

Total 20(100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

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enable individuals to have access to capacity building efforts such as training and new agricultural technologies.

4.2.5 Influence of criteria used in seeds distribution on distribution levels Majority of the groups (40%) disseminated the soybean seeds to all members while 5% of the groups considered position in the group (Table 4.13). There was a significant association (p<0.001) between criteria used in seeds distribution and the distribution levels (Table 4.13). The highest distribution level (76%-100%) was achieved by 69% of the groups who distributed the seeds to all members while those who considered participation in the groups were 6% (Table 4.13).

Table 4.13: Influence of criteria used in seeds distribution on distribution levels in groups in Imenti South, Meru South and Mbeere South sub-counties

Seeds distribution criteria

0-25% 26%-50%

51%-75%

76%-100% Total Sig.

Position in group

3(43) 0 0 0 3(5) P<0.001

Participation in group

2(29) 2(22) 2(22) 2(6) 8(13)

Presence during distribution

0 1(11) 2(22) 2(6) 5(8)

Farmers interested

1(14) 4(44) 3(33) 3(9) 11(18)

Land size 1(14) 2(22) 2(22) 4(11) 9(15)

All members were given

0 0 0 24(69) 24(40)

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The findings imply that more persons would receive the seeds if groups opted to distribute them to all group members. The main objective of using groups in seeds distribution is to ensure that more persons are reached. According to Noordin et al. (2001) groups are a means to reach many in the community in technologies distribution. Sinja et al. (2004) also noted that groups are channels for persuading farmers to try and share new technologies and experiences among members.

4.2.6 Amounts of seeds distributed to group members

Majority of the groups (65%) disseminated 0.25 Kg to 1.6 Kg of soybean seeds to their group members while 2% of the groups disseminated 3.1 Kg to 4.4 Kg of the soybean seeds to their members (Table 4.14). Across the Sub-counties 80% of the groups in Meru South, 60% in Mbeere South and 55% in Imenti south disseminated 0.25 Kg to1.6 Kg of soybean seeds to group members (Table 4.14).

Table 4.14: Quantity of seeds distributed to group members in Imenti South, Meru South and Mbeere South sub-counties

Amount of seeds (Kg)

Imenti South Meru South

Mbeere South

Total Sig.

0.25-1.6 11(55) 16(80) 12(60) 39(65) NS

1.7-3.0 5(25) 3(15) 7(35) 15(25)

3.1-4.4 0 0 1(5) 1(2)

4.5-5.8 4(20) 0 0 4(6)

5.9-7.2 0 1(5) 0 1(2)

Total 20 (100) 20(100) 20(100) 60(100)

Values in parentheses are percentages

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considered in distribution. This implies that seeds distribution within farmer groups is not always even.

4.2.7 Variations in seed quantities distributed to group members

During seed distribution 55% of the groups distributed varying amounts of seeds to their members while 45% of the groups distributed equal seeds amounts to the group members (Table 4.15). Among the groups that distributed varying quantities to group members, 97% considered land size of the individual farmers while 3% considered members‟ position in the group (Table 4.15).

Table 4.15: Variation in seeds quantities distributed to group members in Imenti South, Meru South and Mbeere South sub-counties

Parameters Imenti

South

Meru South

Mbeere South

Total Sig. Variation in seeds quantities

distributed

Quantities varied 13(65) 11(55) 9(45) 33(55) NS

Quantities didn‟t vary 7(35) 9(45) 11(55) 27(45) Criteria for varying seeds

quantities

Position in group 0 1(9) 0 1(3) NS

Land size 13(100) 10(91) 9(100) 32(97)

Values in parentheses are percentages

Additionally these findings were confirmed by discussions held with groups on amounts of seeds disseminated.

(Group discussion with Gatugi women group in Meru South on 29 January 2015) “We received a total of 90 Kg of soybean seeds from the ministry of agriculture

officers in Meru South in March 2010. As a group we were supposed to distribute

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the group members in that meeting immediately. During soybean seeds sharing all

the group members (15) received the seeds but at varying amounts. We shared the

seeds in the range of 1kg to 12 Kg among the group members. This was dependent

on the farmer‟s land size where farmers with larger farms got more seeds compared

to farmers with smaller farms”.

(Group discussion with Umoja self-help group on 15 January 2015)

“We received 30 Kg of soybean seeds in March 2010 which we were supposed to

distribute among the group members and other people in the village. As group

members we decided to distribute the seeds to those who wanted or who had land

for planting the seeds whereby after harvesting they were to return a certain amount

of seeds for distribution to other group members. The seeds were thus distributed

among 16 group members out of 20 where the range of distribution was between 1

kg to 6 Kg. There were four group members who did not receive the seeds since they

did not have land for planting the seeds”.

4.2.8 Farmer-to-farmer seeds sharing

Figure

Figure 1.1: Conceptual framework on soybean seeds distribution through farmer groups
Figure 1 1 Conceptual framework on soybean seeds distribution through farmer groups . View in document p.21
Figure 3.1: Map of the study site
Figure 3 1 Map of the study site . View in document p.35
Table 3.1: Definition of study variables influencing soybean distribution by individual farmers
Table 3 1 Definition of study variables influencing soybean distribution by individual farmers . View in document p.42
Table 3.2:
Table 3 2 . View in document p.45
Table 4.1:
Table 4 1 . View in document p.47
Table 4.2:
Table 4 2 . View in document p.50
Table 4.3:
Table 4 3 . View in document p.51
Table 4.4:
Table 4 4 . View in document p.52
Table 4.5:
Table 4 5 . View in document p.53
Table 4.6:
Table 4 6 . View in document p.54
Table 4.9:
Table 4 9 . View in document p.58
Table 4.8:
Table 4 8 . View in document p.58
Table 4.10:
Table 4 10 . View in document p.60
Table 4.11: Criteria used in seeds distribution within groups in Imenti South, Meru South and Mbeere South sub-counties
Table 4 11 Criteria used in seeds distribution within groups in Imenti South Meru South and Mbeere South sub counties . View in document p.61
Table 4.12: Level of soybean seeds distribution in groups in Imenti South, Meru South and Mbeere South sub-counties
Table 4 12 Level of soybean seeds distribution in groups in Imenti South Meru South and Mbeere South sub counties . View in document p.63
Table 4.13:
Table 4 13 . View in document p.64
Table 4.14:
Table 4 14 . View in document p.65
Table 4.15: Variation in seeds quantities distributed to group members in Imenti South, Meru South and Mbeere South sub-counties
Table 4 15 Variation in seeds quantities distributed to group members in Imenti South Meru South and Mbeere South sub counties . View in document p.66
Table 4.16: Farmer to farmer soybean seeds sharing in Imenti South, Meru South and Mbeere South sub-counties
Table 4 16 Farmer to farmer soybean seeds sharing in Imenti South Meru South and Mbeere South sub counties . View in document p.68
Table 4.17:
Table 4 17 . View in document p.69
Table 4.18:
Table 4 18 . View in document p.70
Table 4.19:
Table 4 19 . View in document p.71
Table 4.20: Socio demographic characteristics of farmers in Imenti South, Meru South and Mbeere South sub-counties
Table 4 20 Socio demographic characteristics of farmers in Imenti South Meru South and Mbeere South sub counties . View in document p.73
Table 4.21:
Table 4 21 . View in document p.77
Table 4.22:
Table 4 22 . View in document p.79
Table 4.23:
Table 4 23 . View in document p.82

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