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ASSESSMENT OF FACTORS INFLUENCING CHEMICAL TREATMENT OF HOME SAVED SEED AMONG WHEAT FARMERS IN UASIN GISHU COUNTY OF KENYABYBETT WILLIAMA PROPOSAL SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY INAGRICULTURAL ECONOMICS MOI UNIVERSITY

SEPTEMBER, 2013

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DECLARATIONDeclaration by CandidateThis thesis is my original work and to the best of my knowledge has not been presented for the award of a degree in any other University. No part of this thesis may be reproduced without the prior written permission of the author and / or Egerton University.

Bett William SignatureDate

Declaration by SupervisorsThis thesis has been submitted for examination with our approval as University Supervisors.

Department of Agricultural Economics and Resource Management, School of Business and Economics,Egerton University.

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Department of Agricultural Economics and Resource Management,Egerton University..SignatureDate

TABLE OF CONTENTSDECLARATIONiTABLE OF CONTENTSiiLIST OF TABLESivLIST OF FIGURESvABBREVIATIONS AND ACRONYMSviACKNOWLEDGEMENTSviiABSTRACTviiiCHAPTER ONE11.1Background of the Study11.2 Statement of the Problem51.3Objectives of the study61.3.1Broad Objective61.3.2Specific objective71.4Research hypothesis71.5Significance of the study71.6Scope and Limitation of the Study8CHAPTER TWO92.1Concepts and the Theoretical Framework92.1.1. Seed92.1.2.Seed System102.1.3. Formal Seed System122.1.4. Informal Seed System132.2 Home Saved Seeds142.3 Treated Home Saved Seeds142.4Adoption of New Technologies142.5Nature of Seed Marketing172.6 Literature Review202.7Theoretical Framework222.8 Conceptual Framework24CHAPTER THREE253.0Introduction253.1 Study Area253.2 Research Design273.3Target Population273.4Sample Frame283.5Sample Size283.6Sampling Procedures293.7Data Collection Tools303.7.1Validity313.7.2Reliability.313.8Primary Data323.8.1Secondary Data323.8.2Type of Data Collected323.9 Data Collection Procedures323.9.1Type of Data Collected323.10 Data Collection Procedures333.10.1Data Analysis Techniques393.10.2Descriptive Statistics403.11Empirical Model403.11.1Theoretical Model and Empirical Specification403.12Data Sources and Types403.13The Heckman Two-Step Method423.14Propensity Score Matching (PSM)433.15Estimating the Production Function45REFERENCES46APPENDICES52APPENDIX I : QUESTIONNAIRE52

LIST OF TABLESTable PageTable 3.1: Population Distribution in the Uasin Gishu County26Table 3.2 Divisional Statistics of the Study Area27Table 3.3 Sample Size29

LIST OF FIGURESFigure PageFigure 2.1: Conceptual Framework24Figure 3.1 Map of Uasin Gishu26

ABBREVIATIONS AND ACRONYMSAAKAgrochemicals Association of KenyaCIMMYTInternational Maize and Wheat Improvement CenterFAOSTATFood and Agricultural Organization Statistical DatabaseGDPGross Domestic ProductGOKGovernment of KenyaIFDCInternational Center for Soil Fertility and AgricultureKARIKenya Agricultural Research InstituteKNBS Kenya National Bureau of StatisticsNPBRCNational Plant Breeding Research CentreSPSS Statistical Package for Social SciencesUK United KingdomUS$ United States DollarsUSA United States of America

ACKNOWLEDGEMENTSAll through this time, my yearning to complete and give educative output was as a result of the guiding spirit of my father, George Kibet Chumoh, who though not around, has been my inspiration throughout my entire life. This work is dedicated to him.

ABSTRACTSeed dressing agrochemicals play a big role in increasing yields from a given unit of farm size. Given that Kenya is a net importer of wheat, dressing of wheat seeds remains one of the avenues of unblocking potential wheat yields, so as to remedy this situation. This study aims at determining factors affecting treatment of home saved wheat seeds in Uasin Gishu County. Respondents will be interviewed in different zones of Uasin Gishu district so as to get pertinent information on the subject matter. Primary data will therefore be key in understanding factors that influence farmers towards adopting seed treatment as a way of boosting productivity of home saved wheat seeds. Secondary data will al0so be used where relevant, so as to understand past undertakings that explain issues influencing wheat farmers to treat or not to treat their home saved wheat seeds. Descriptive statistics and maximum likelihood method using the Statistical Package for Social Scientists (SPSS) will be used to analyze the data. Findings will enable policy makers and all stakeholders involved in wheat production to formulate strategies which will lead to higher productivity of wheat farms.

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CHAPTER ONE1.1Background of the Study Farmers need seed because without viable seed the survival of their household is endangered. In fact, the ways that farmers obtain seed are as old as agriculture, and most small-scale farmers in developing countries routinely save their seed from one harvest to the next. Nowadays, some 60-70 per cent of seed used by these farmers is still saved on farm. Most of the remaining seed is obtained off-farm, from local sources (Louwaars, 1994; Cromwell, 1996a). In additional, not all farmers can afford to buy improved seed supplied by the organized seed industry. For many farmers, such seed is not available, even if they wanted it and could afford it. In actual fact, the majority of the world's farmers, and crops, are not planted from such seed but from home saved seed which are treated. The average world grain yield in 1950 was 1.1 tons per hectare. In 2011, it was 3.3 tons per hectare, (USDA, 2013). The challenges for all policy makers and researchers are to continually improve and maintain this yield per hectare because of the ever increasing, population. The world population is currently rising rapidly. Virtually the same amount of arable global farmland is expected to support this increasing number of people. Efforts geared towards increasing yield per unit area will therefore help improve and increase food security. In his report to British parliament,()mentioned that the world population is predicted to rise from then 6 billion to over 9 billion by 2050, rising at a rate of 6 million a month. Africas population alone, he projected, was to nearly double from then 1 billion to 2 billion and said that estimates suggest that to meet the most basic of needs for this increased global population, food production will need to double. The report also found that by 2050 there will be 6 people per cultivable hectare of land in Uganda and 14 in Ethiopia by this time. This study aims at finding ways of improving seed dressing of wheat seeds in the area of study and therefore improves yields from wheat farms.According to IFS, 2007, some of the first recorded seed treatments are the use of sap from onion (Allium spp) and extract of cypress in the Egyptian and Roman periods. Salt water treatments have been used since the mid-1600s and the first copper products were introduced in the mid-1700s. Other key milestones were the introduction of arsenic, used from 1740 until 1808 and the introduction of mercury, used from 1915 until 1982. Until the 1960s seed treatments had been only surface disinfectants and protectants. The first systemic fungicide product was launched in 1968. This systemic fungicide had not only seed surface activity but also moved into the plants protecting the young seedlings from airborne pathogens. Since the 1990s the crop protection and seed industries have developed and adopted new classes of fungicide, insecticide, and nematicide chemistry, expanding pest control while reducing user and environmental impact. The seed and seed treatments industries have a long history of partnership and dedication in providing growers with high quality seed. Today the seed must be as pest- and disease-free as possible and the treatment must provide protection against pests and disease during germination, emergence and growth of the plant.Seed treatments have been used in cereals for centuries, mainly as a means of controlling seed borne diseases that cannot be controlled later in the crops development. Diseases such as bunt of wheat (Tilletia tritici) and leaf stripe of barley (Pyrenophora graminea) have been well controlled since the introduction of organomercury in the 1930s when seed-borne diseases like bunt and leaf stripe were common. Modern seed treatment technology now offers very safe and environmentally friendly alternatives to mercury. As a consequence of the availability of safe and cost-effective seed treatments, the UK farming industry embraced the technology and seed treatments became almost universally used by UK farmers. Compared with the cost of foliar fungicides, fungicidal seed treatments have always been relatively inexpensive. However, with increasingly sophisticated seed treatments available, the cost of seed treatment became significant and some farmers began to question the need for seed treatment in all cases (Clark and Cockerill, 2011) Various seed dressings, which are permitted in organic farming, have been developed. In Germany Tillecur, which is based on mustard flour, is used. This agent is effective against bunt (Tilletia tritici(Borgen and Kristensen 2001, Spiess 2000). Experiments with acetic acid (vinegar) as a seed treatment have been carried out and shown to be effective against bunt and leaf stripe (Borgen and Nielsen 2001). Due to the present interpretation of the EU regulations this agent, along with vinegar, is not permitted.The future for wheat seed production appears to be mixed. Wheat is a high-volume, low-profit seed crop and has been produced primarily by heavily subsidized government seed programmes. With privatization and liberalization, many of these programmes are at risk of being closed down. The private sector, however, may not focus on wheat seed due to its characteristics (self-pollinating, high-volume and low-profit). If private seed enterprises exist, they consider wheat seed to be of secondary importance. Furthermore, in most countries there has been no on-going effort to promote the use of improved seed by wheat farmers, and no significant breeding developments have recently taken place to increase yield and quality. Since wheat is a self-pollinating crop and the grain can be used as seed, farmers tend to replant their own seed. It is, therefore, expected that in the future the large majority of resource-poor, small-scale farmers in many developing countries will have to rely on seed saved from the previous harvest (Gastel et al., 2001)In Kenya, there has been low adoption of new technologies due to several constraints , key among them being: weak research-extension-farmer linkages, low funding ;and inadequate field staffing levels ;and inadequate promotion and marketing of new varieties and complementary technologies by the private sector,(GOK,2010). The establishment of KSC in Kitale in 1956 was the initial mark of the formal seed system in Kenya. The company was established to produce pasture seed for the immigrant farmers (Sikinyi, 2010). Today, the formal system comprises a number of specialized organizations in the public and private sector involved directly or indirectly (regulatory agency) in breeding, multiplication, quality control, processing, storage, marketing, and distribution of seed. The formal seed system supplies strictly regulated certified seeds of improved varieties and accounts for 20% of the seeds sown in Kenya (Sikinyi, 2010). The informal seed system is still the major seed source in Kenya. It provides seeds without quality control and supplies 80% of the seeds for planting purposes in the country (Sikinyi, 2010). According to MOA, the informal seed sources include road-side nurseries, farm-saved seed, farmer-to-farmer exchange, local markets, NGOs and CBOs. Seed provided by relief agencies are sometimes obtained from non-registered seed dealers with unknown quality (Sikinyi, 2010). A number of NGOs are establishing private companies to supply small scale farmers with certified seed.Gamba et al, 2003 found out in their study that 56% percent of small-scale farmers and corresponding 49% percent of large scale farmers obtained wheat seeds from other farmers. They also found that seeds from various harvest and from Kenya Farmers' Association (KFA) were both 9% and the Kenya Seed Company (KSC) and KFA both constituted 5% for large scale farmers. Most small scale farmers, they observed, (50%) obtained seeds in the same village although about 35% travelled more than 10 Km to get the seed. About 59% of large scale farmers travelled more than 10 Km to get seed, while 28% obtained seed from the same village. According to ISF.2007, modern seed treatment products offer control of target pests and diseases and ensure the establishment of healthy and vigorous plants. Their formulation and industrial application also contribute to improvement in growers and workers safety and stewardship of the environment. Todays modern seed treatment products have to meet not only efficacy standards but also safety and environment standards. The newest active substances and formulations provide long-lasting, broad spectrum, control of pests and diseases (depending on the specific active ingredient). Modern formulated seed treatment products are precisely blended products consisting of several active ingredients, special wetting agents, colorants and sometimes bird repellents which are rigorously tested for their safety to the seed, the users and the environment.1.2 Statement of the Problem According to Hassan et al, 1993, in their research, all farmers use improved wheat varieties. However, farmers sources of wheat seed, seeding rate, and sowing vary greatly. Fifty per cent of the farmers use their own seed, and only 15% of those who bought seed for cash (5% of all farmers) acquired it directly from Kenya Seed Company. They went further to observe that the rest purchased seed from merchants and other farmers. It will be interesting therefore to find behavioural pattern of these farmers, who acquire their seeds from informal sources and how they improve their seeds with an aim of improving farm productivity. One aspect of this is through chemical seed treatment of the seeds. Today, the formal system comprises a number of specialized organizations in the public and private sector involved directly or indirectly (regulatory agency) in breeding, multiplication, quality control, processing, storage, marketing, and distribution of seed. The formal seed system supplies strictly regulated certified seeds of improved varieties and accounts for 20% of the seeds sown in Kenya. To be sure, most farmers still rely primarily on farmer-to-farmer exchanges or saved seed (Delay 2004). However, surveys such as these are often unable to provide real insights into the improved seed adoption due to problems in their design. The question that should be asked is what type of variety is a farmer cultivating and when did he or she purchase the seed. For improved open-pollinated varieties such as wheat and teff, farmers do not necessarily need to purchase seed each season as they would hybrid maize. Rather, they might purchase seed every 4-5 years to replace their stocks of saved seed with seed that has a higher level of purity, and thus better performance when cultivated (Doss et al. 2003).The costs of wheat production are also influenced by the quality of seeds available to farmers. The quality of wheat seeds has raised some concerns among wheat producers. Some certified wheat varieties available are contaminated with other seeds. This has led majority of farmers to prefer to use retained or non-certified seeds, and selected and treated seeds from neighbours. Most of these seeds may not be treated. Some farmers are now forced to invest in seed drying and treating plants, thus, developing the market further for uncertified treated seeds, (Nyoro et al., 2001). Gamba et al, 2003, captured this phenomenon when they found that of 63% of small scale farmers and 66% of large scale farmers attached importance to cleaning their wheat seeds before planting. They also found that only 59% of small scale farmers dressed their seeds, with only 52% of their respective large scale farmers doing so. It would therefore be of economic importance to understand dynamics of seed chemical treatment by the farmers so as to ensure increased productivity at farm level.1.3Objectives of the study 1.3.1Broad Objective The general objective of the study will be to assessment of factors influencing treatment of home saved wheat seeds among farmers in Uasin Gishu County. 1.3.2Specific objective 1. To investigate the socio factors (education, gender, age, land size, experience, off-farm income, number of children) that affect treatment of home saved wheat seeds in Uasin Gishu County2. To assess the role of market institutions, infrastructure and household assets in determining treatment of home saved wheat seed by farmers. 3. To identify determinants of market participation for home saved wheat seed4. To assess the effect of treated home saved wheat seeds on integration of farmers into rural output markets.1.4Research hypothesis 1. Socio factors (education, gender, age, land size, experience, off-farm income, number of children) do not have significant effect on treatment of home saved wheat seeds in Uasin Gishu County2. Market institutions, infrastructure and household assets do not have significant roles in determination of home saved wheat seeds3. There are no determinants of market participation for home saved wheat seeds4. Treatment of home saved wheat seeds does not have effect on integration of farmers into rural output markets1.5Significance of the study Quality seed is vital to the success of our countrys agricultural development. In the existing condition, one of the main sources of this quality seed is farmers treatment of home saved seeds. So, this study along with the analysis of the situation of seed supply has policy implication for the regional policy makers with regard to creating conducive environment for farmers treatment of home saved seeds and in general formulating policies and strategies for the development of the seed sector. Besides, it would be a useful reference for researchers and others interested in the area of study.1.6 Scope and Limitation of the StudyThis study mainly emphasizes on farmers treatment of home saved seeds. Based on this idea wheat seed will be referenced as used in Uasin Gishu County.

CHAPTER TWO2.1Concepts and the Theoretical Framework2.1.1. SeedThe importance of seed as the carrier of most important characteristics for crop production has been recognized since the early days of agriculture. Starting from 10000 years ago, harvesting seed from preferred, plants has been the basis of crop domestication and consequently of present day agriculture (Louwaars and Gam, 1999).Seed is the most important agricultural input; it is the basic unit for distribution and maintenance of plant population. It carries the genetic potential of the crop plant. It thus dictate the ultimate productivity of other input such as fertilizer, pesticide irrigation water etc., which build the environments that enable the plant to perform (Mugonozza, 2001).Seed and other planting materials are the farmers' most precious resources, especially for smallholders in Sub-Saharan Africa, where agriculture is characterized by much risk and uncertainty (WBG, 1999). Seed is generally considered to be the most affordable external input for farmers, and many of its benefits are assumed to be scale-neutral. So investments in crop improvement potentially can reach a wide range of farmers. While many other areas are also important for agricultural development such as markets, credit supply, support institutions, and policies access to appropriate seed is clearly the first step (McGuire, 2005).The use of good quality seed of adopted and improved varieties is widely recognized as fundamental to ensure increased crop production and productivity. This is even more important in Sub-Saharan Africa (SSA) in the view of increasingly available land, declining soil fertility and ever growing population; those facts increase the importance of promotion and use of good quality seed as a means to intensify food production (FAO, 1999).The potential benefits from the distribution of good quality seed of improved varieties are enormous, and the availability of quality seed of wide range of varieties and crops to the farmers is the key to achieve food security in SSA. Enhanced productivity, higher harvest index, reduced risks from pest and disease pressure, and higher incomes are some of the direct benefits potentially accrued to the farmers (FAO, 1999).2.1.2.Seed systemSeed systems are composed of set of dynamic interaction between seed supply and demand, resulting in farm level utilization of seed and thus plant genetic resource. The seed system is essentially the economic and social mechanism by which farmers demand for seed and various traits they provide met by various possible sources of supply (FAO, 2004).The term seed system represents the entire complex organization, individual and institution associated with the development, multiplication, processing, storage, distribution and marketing of seed in any country. The seed system includes traditional (or informal) system and the non- traditional (or formal or commercial) systems. Legal institutions such as variety release procedures, intellectual property rights, certification programs, seed standards, contract laws, and law enforcement are also an important component of the seed system of any country. They help determine the quantity, quality, and cost of seeds passing through the seed system (Maredia, et al., 1999).Seed system participants may be relatively few or many, predominantly public or private depending upon the farmers that the system serves. In local systems of seed exchange, farmers often undertake most of the activities that define a seed system. As systems expand to national, regional, and international scales, participants will include the following: farmers, international agricultural research centers, private and public domestic seed enterprises, retailers and distributors, multinational seed companies, private research institutions, farmers associations and cooperatives, banks and credit institutions, trade associations, local governing bodies, donor agencies, national agencies and ministries, community groups (social, religious, etc.), agricultural universities, national agricultural research institutes and NGOs/PVOs. These participants may assume multiple roles in the process of seed provision, performing one or several activities (WBG,1999).Seed systems, formal or informal, fulfill a series of functions that are basic prerequisites for expecting the best possible productivity from a crop in a specific situation. Healthy, viable seed of the preferred variety needs to be available at the right time, under reasonable conditions, so that farmers can use their land and labor resources with the best yield expectations. The wrong variety, sown at the wrong time with infected seed of poor germination potential, will seriously limit a farmers expectation of production and productivity. Thus, any seed system has multiple functions to fulfillfor a range of farmers, farming conditions, and crops in a village, region, or country. A seed system can be assessed at any time according to how well it fulfills these functions. Conditions, situations, groups of farmers, or crops can be identified under which the specific system works well (Welfzien et al., 2001).Activities undertaken to supply seeds to farmers include research and development, multiplication, processing, distribution, and uptake. Other activities that may occur in conjunction with these include transport and storage, as well as quality control (such as seed certification). Seed provision to farmers also includes activities undertaken to influence the process, such as: pricing, financial and technical support, provision of inputs, communication and coordination, as well as market research and promotion. Finally, policy formulation underpins seed systems, defining the boundaries and opportunities for the conduct of all seed system activities (WBG, 1999)2.1.3. Formal seed systemAccording to FAO (1999), formal seed system as a sector comprises all seed program components, namely; plant breeding, seed production, processing, marketing, extension, quality control and certification, that interact among themselves and usually regulated by law. The formal seed sector was set up and organized with the principal goal of diffusing quality seed of improved varieties developed by formal breeding programs. The principal sources of materials for formal breeding programs are the ex situ collections of gene banks. Gene banks contain materials that were originally collected from farmers systems, that isin the case of cultivated plantsmaterials that were developed and maintained by farmers.The formal system has been relatively successful for well-endowed, high-potential areas, but much less successful in more variable, marginal areas. This is partly explained by the fact that improved varieties tend to be poorly adapted to farmers preferences and production environments. In general, plant breeders have lacked understanding about what farmers in these areas need, developing only few, genetically uniform products for on-farm testing. Evaluation and selection of new materials was on-station, where conditions are different from those in the target environment (Almekinders, 2000).The formal seed system can be characterized by a clear chain of activities. It usually starts with plant breeding and promotes materials for formal variety release and maintenance. Regulations exist in this system to maintain variety identity and purity as well as to guarantee physical, physiological and sanitary quality. Seed marketing takes place through officially recognized seed outlets, and by way of national agricultural research systems. In formal seed production, seed multiplication occurs through several generations rather than continually recycling the seed of one generation, to avoid building up physical or genetic contamination over time in the same lot of seed (Louwaars et al., 1999)A major challenge for formal seed supply is to produce sufficient seed of all varieties needed, and deliver it to farmers in a timely manner. This requires considerable organization, time, and space, and incurs risks due to costs and production. To start with, significant area and effort is involved in seed production, though this varies by crop according to its multiplication rate (i.e. how much usable seed is produced per seed sown (McGuire, 2005).The study made by Baniya et al (2003) signify that, the formal system focuses more on the interests of the seed company, and has more access to biotechnology and plant breeding techniques, so this seed system generally neglects the indigenous knowledge. The market is dominated by a few suppliers with potentially serious implications for technology choice and price fixing.2.1.4. Informal seed systemInformal or on-farm seed system, vary among country, region and crops. They rely on seed- saving practices, that is, keeping parts of the harvest for planting in the next season. The system usually plants local varieties of seed kept from the previous years harvest, obtained from neighbors and/or the local market.This is the predominant system for food crops in subsistence agriculture. It is estimated that in developing countries, the informal seed system is responsible for more than 80% of the total area planted with subsistence crops. It is a resilient system, which is very active even without the support of public or private institutions. On farm seed system are essential for improving food security for developing countries. They will likely continue to be the main source of seed for subsistence crops in the world. This system is not market oriented; seeds are usually produced for consumption. Some surplus can be bartered with neighbors or sold to local grain dealers (FAO, 2004).GTZ ,(2000) , in a study clearly states that (for small-scale farmers in developing countries) management of seed is of crucial importance and forms an integral part of crop production systems. This study further notes that for many centuries, farmers have developed and maintained their own plant genetic resources, based on local means of seed production, selection and exchange. Introgressions, mutations and introductions from elsewhere are the common sources of new genetic material in a community. Newly introduced varieties are subject to farmers experimentation, and when adopted they become part of the local gene pool. In many cases, this integration involves physical mixing of seeds and spontaneous crossing with other materials. The informal seed sector has strong local character, without necessarily being confined to a small geographical area.2.4Adoption of New TechnologiesAdoption was defined as the degree of use of a new technology in long-run equilibrium when a farmer has all the information about the new technology and its potential. Adoption refers to the decision to use a new technology, method, practice, etc. by a firm, farmer or consumer. Adoption of the farm level (individual adoption) reflects the farmers decisions to incorporate a new technology into the production process. On the other hand, aggregate adoption is the process of spread or diffusion of a new technology within a region or population. Therefore, a distinction exists between adoption at the individual farm level and aggregate adoption, within a targeted region or within a given geographical area (Feder et al., 1985 as cited in Dereje, 2005)Adoption of technological innovations in agriculture has attracted considerable attention among development economists because the majority of the population of less developed countries derives their livelihood from agricultural production and a new technology, which apparently offers opportunities to increase production and productivity (Feder et al., 1985 as cited in Girmachew,2005).Agriculture progresses technologically as farmers adopt innovations. The extent to which farmers adopt available innovations and the speed by which they do so dete mines the impact of innovations in terms of productivity growth (Diederen et al., 2003).2.3 treated home saved seedsWeir et al., (2000) emphasized that although farming methods in Ethiopia are still rather traditional, farmers in many areas do have the option of using new, higher-yielding crop varieties and some modern inputs, primarily chemical fertilizers. Rates of adoption of such innovations vary widely from one part of the country to another, allowing us to compare sites at different stages in the adoption and diffusion process.According to Sunding et al.(2000), measures of adoption may indicate both the timing and extent of new technology utilization by individuals. Adoption behavior may be depicted by more than one variable. It may be depicted by a discrete choice, whether or not to utilize an innovation, or by a continuous variable that indicates to what extent a divisible innovation is used.Adoption at the farm level describes the realization of a farmers decision to implement a new technology. On the other hand, aggregate adoption is the process by which a new technology spreads or diffuses through a region. Therefore a distinction exists between adoption at the individual farm level and within a targeted region. If an innovation is modified periodically, however, the equilibrium level of adoption will not be achieved. This situation requires the use of econometric procedures that can capture both the rate and the process of adoption (Getahun et al., 2000).Determinants of technology adoption encompass characteristics of the home saved seeds encompass technology, features of the farming system, market and policy environment as well as the socioeconomic characteristics of the decision making unit (Ehui et al., 2003). Several parameters have been identified as influencing the adoption behavior of farmers from qualitative and quantitative models for the exploration of the subject. Social scientists investigating farmers adoption behavior have accumulated considerable evidence showing that demographic variables, technology characteristics, information sources, knowledge, awareness, attitude, and group influence affect adoption behavior (Oladele, 2005).Also according to Alemu et al. (1998), many variables can influence farmers' awareness and adoption of new varieties: human capital variables such as literacy; farm size; information sources such as agricultural extension or the research station; and distance from seed sources. Farmers with more land had a higher probability of adoption, probably because they are wealthier and have more land to experiment with improved wheat varieties. Extension visits also resulted in a higher probability of adoption by raising farmers' awareness of new wheat varieties and providing information about agricultural practices to accompany them. Oxen ownership increased the probability that farmers would adopt improved wheat varieties. Oxen owners usually participate more frequently in a demonstration, which gives them access to information on new technologies.Distance is a major obstacle for adoption of technologies in developing countries. The impediment posed by distance is likely to decline with the spread of wireless communication technologies. It is a greater challenge to adopt technologies across different latitudes and varying ecological conditions (Sunding et al., 2000). Farmers with some education attainment are also less likely to go without adopting one or more of the technology choices: the marginal effect of the education variable is significantly negative for the probability of no adoption. More educated households are commonly well informed and receptive, which translates to a higher likelihood of engaging in new technologies. This finding is in line with several previous studies which point out innovation is positively related to farmers abilities to decipher and analyze information (Ersado et al., 2003).The rate of adoption is defined as the percentage of farmers who have adopted a given technology. The intensity of adoption is defined as the level of adoption of a given technology. The number of hectares planted with improved seed (also tested as the percentage of each farm planted to improved seed) or the amount of input applied per hectare will be referred to as the intensity of adoption of the respective technologies (Nkonya et al.,1997as cited in Mesfin,2005).2.5 Nature of seed marketingSeed marketing is the most important as well as a challenging aspect of seed industry because of the nature of the product. Seed being a living organism, means that it's quality deteriorates faster. Thus, it's shelf life is limited and it must be marketed within one season. Another peculiar feature of seed is that it requires two to three years lead time to meet the specific requirements; that is to meet the demand for particular seed, its production has to be organized at least two years in advance. The changes in the weather, price of crop, and price of competing crop, may change the prospects of demand for seed of particular variety at the commencement of sowing season (Singh, 2004).The nature of seed demanded by farmers differs. Large- and medium-scale farmers use markets to purchase uniform genetic materials that are highly responsive to chemical inputs and embody specific characteristics (e.g., color, uniformity of grain size) rewarded by the market. By contrast, more subsistence-oriented smallholders may value characteristics such as drought tolerance, early maturity or good storage more than fertilizer responsiveness. Because of the small size of their land holdings, mixed cropping practices, and strategy of minimizing production risks by diversifying the variety base, smallholders also demand relatively small quantities of seed but for a number of varieties of the same crop and recycled seed over more seasons than larger commercial farmers (Maredia et al., 1999).Seed demand from different users can be met by promoting a range of seed organizations with comparative cost advantages in supplying seeds of distinct commodities to different groups. For example, multinational seed companies can meet the seed needs of large-scale commercial farmers whose quality requirements and willingness to pay are higher than smallholder farmers. The seed needs of the latter group can be met more effectively by small-scale firms or Community-based Seed Multiplication and Distribution Schemes such as farmers seed groups and Cooperatives (Maredia et al., 1999).The largest problem faced by seed multiplication program elsewhere in Africa is difficulty of building a sustainable seed market. Small quantities of seed are profitably sold within the village community. Sales are strongest for newly introduced varieties. But most small-scale farmers are unwilling to pay premium price to their neighbors for seed they can obtain from their own harvests (Rohrbach et al., 2002).According to Tsigedingle (2002), from the total seed produced by farmers in 1998/99 in the SNNPR only 10.7% was purchased by as a seed WTC, 6.8% exchanged through informal system as seed to neighbors and relatives, 26.6% was used for home consumption and 55.9% sold as grain similarly from 1999/2000 produced wheat seed, 40.6%was purchased by WTC the rest used as own seed and sold as grain to the market.To increase the sales of seed produced by farmers, promotion activities should be conducted to raise awareness of all farmers in villages under smallholder seed production programs (Kibiby et al., 2001). Promotional activities should focus on the advantage of improved seed and the quality of seed produced in their own villages by small holder seed producers. A primary objective of these promotional activities would be to increase the willingness of farmers to purchase seed from small producers.The study made by Abdisa et al. (2001) stressed on that if farmers could not find sustainable and dependable market for their improved seed produce they would feel restrained from production activities. This will lead farmers to be suspicious and reluctant to adopt any technology offered to them. Hence market information; on where and when to sell is quit essential, if informal seed production is to be sustainable.One important factor that influence farmers' seed multiplication is the performance of the existing market channel. The choice of the marketing channel depends on a number of aspects. These include availability of markets, prices offered in the market, distance to the market and the potential of the market to absorb the stock on sale (Montshwe, 2006).A commonly used measure of market performance is the marketing margin or price spread. A marketing margin is the percentage of the final weighted average selling price taken by each stage of the marketing chain. A wide margin means usually high prices to consumers and low prices to producers (Getachew, 2002 as cited in Rehima, 2007).

IntroductionKenyan economy largely depends on the agricultural sectors, which accounts for an average of 25 percent of gross domestic product (GDP). About 75 percent of Kenyans owe their livelihoods to agriculture (EPZA, 2005 as cited by Bett, 2012). This just acts to illustrate the importance of agricultural sector in Kenyas economy. Wheat as a crop is the second most important cereal grain in Kenya. The crop is grown largely for commercial purposes on large scale farms. Wheat growing areas in Kenya include scenic Rift Valley regions of Uasin-Gishu, Narok, Marakwet, Elkeiyo, Londiani, Molo, Nakuru and Timau. These areas have altitude ranging from 1200m and 1500m above sea level, with annual rainfall ranging from between 800mm and 2000mm with up to 2500mm in high grounds. The area under wheat production in Kenya increased from 144000ha in 2002 to 150000 ha in 2003 (EPZA, 2005 as cited by Bett 2012). 2.6 Literature ReviewThis deals with past studies closely related to this study. It will deal with solutions or lack of solutions from these studies, mainly aiming at importance of various findings from different studies and variances with this study.Rahman et al, (2013), in their stuy of adoption of different wheat farming technologies in Bangladesh found that 96% of respondents in Thakurgaon and 91% of Dinajpur wheat farmers did not treat their seeds. They correctly stated that this will have assisted in protection from primary diseases and augmentation of wheat productivity. The scope of their study was however very wide in the sense that many wheat growing technologies like fertilizer application were also considered in their study. It will be very interesting to understand outcomes from specific studies targeting only wheat seed treatment so as to enhance the overall wheat yield, specifically from Kenyan farms.In 2002, most of the farmers of Participatory Variety Selection (PVS) villages did not preserve any wheat seeds due to lack of proper knowledge of preservation technique,(Pandit et al.,2007).They further continued to explain that Bangladesh Agricultural Development Corporation (BADC) was the major source (60%) of their wheat seeds followed by local market (36%) and relatives (4%). In 2005, seed source was completely changed. Farmers were trained several times about seed production and preservation techniques through PVS, and they learned those very efficiently. They also understood the importance of good quality seeds. Therefore, in 2004-05, farmers of the village used 100% seeds from their own source. In that season, 60% seeds were used from their own preservation, 30% from neighbours and only 10% from their relatives. This was a tremendous achievement of PVS activity. Many of these farmers were also trained many times before starting PVS in traditional ways but that could not bring any impact. Successful storing of seeds also benefited them financially. Many farmers earned good amount of money by selling seeds. This shows that farmers in Uasin Gishu can also be attuned to same technologies. This study aims to understand the different parameters influencing farmers decisions in Uasin Gishu County, with an aim of improving wheat seeds in all aspects, with a particular emphasis on seed treatment.According to Bishaw 2004, in Syria, chemical seed treatment is applied regularly by the formal sector and informal sector (except for barley seed from the informal sector). He further says that on the other hand, in Ethiopia large-scale seed treatment is restricted to seed production and for certified seed sold to the state farms only whereas seed for the peasant sector is not treated. Moreover, there is limited information on economic benefits of seed treatment under different crop production and management practices. He adds that, in light of results from recent studies, it is important to conduct systematic seed treatment studies and appraise its current status and provide alternative options to introduce on-farm seed treatment. In both cases designing simple application techniques and provision of information through an extension programme is important to emphasize the safety measures associated with chemical seed treatment, he emphasises. This study therefore aims to fulfil this advice with concentration on Uasin Gishu wheat farmers, in Kenya.2.7Theoretical FrameworkAdoption is seen as the first or minimal level of behavioural utilization and innovation. It is an idea, practice, or object; perceived as new by an individual or other units of adoption (Rogers 2003 as cited by Bett 2012). According to Feder et al, (1993 as cited by Bett 2012) an innovation is defined as a technological factor that changes the production function regarding which there exists some uncertainty, whether perceived or objective (or both). The uncertainty diminishes over time through the acquisition of experience and information, and the production function itself may change as adopters become more efficient in the application of the technology. They continue to argue that technology adoption may also be viewed from two perspectives. At the micro level, each decision unit must choose whether to adopt the innovation and its intensity of use if adopted. Many adoption studies, they further noted, therefore, examine the factors influencing the firms or households adoption decision and may be viewed from a static or dynamic (if learning and experience are incorporated in the decision model) perspective. At the macro level, they noted, the adoption pattern of the whole firm or household population is examined over time to identify the specific trends in the diffusion cycle. Diffusion studies do not consider the innovation process, but begin at a point in time when the innovation is already in use.Determinants of adoption are outlined clearly by (Rogers 2003 as cited by Bett, 2012). He outlined them as being dependent on perceived attributes, of which comparative advantage or the degree to which an innovation is perceived better than the idea it supersedes is first taken into account. Other issues of attributes that he outlined are: complexity (the degree to which a practice is perceived as relatively difficult to understand and to adopt, negatively related to its rate of adoption), trialability (degree to which an innovation may be experimented at a limited basis) and compatibility (degree to which sustainable practice is perceived as consistent with the existing values, past experience and needs of potential adopters. Rogers further described innovation process as a process through which an individual passes from; knowledge to attitude and finally to adopting (indivual or collective, optional or authority). He further pointed out the importance of communication channels in innovation process defining them as interpersonal or mass media, originating from specific or diverse sources. He also defined Social system as norms, network interconnectedness pointing out that these socio-cultural practices and norms can inhibit or drive adoption. He stated that efforts of promotion agent in the past and present are important.The current study drew similarity with this theory to study factors influencing use of pre-emergence herbicides among wheat farmers in Uasin Gishu County.Rogers categorizes adopters into: 1) innovators who are educated and venturesome; 2) early adopters who are popular educated and are normally social leaders; 3) early majority who are deliberate and have many social contacts; 4) late majority who are very skeptical; 5) laggards who are traditional and normally of lower social economic class. These may end up not adopting the technology. The distribution of these groups follows the familiar bell-shaped curve, when plotted to indicate their features in the relevant population.

2.8 CONCEPTUAL FRAMEWORKSeed dressing of Home Saved Seeds

Economic Factors Farm Size Nature of Landholding House Hold Income Credit Availability Availability of Commercialy treated Seeds

Social Factors Age of Farmers Literacy Level Household Size Friends/Other Farmers

Promotional factors Extension services Trainings Wheat market information

Figure 2.1: Conceptual FrameworkSource: Author, 2013

CHAPTER THREE3.0IntroductionThis chapter presents the research methodology to be used to achieve the study objectives. It consists of conceptual framework, sampling procedures, study area, methods of data collection and data analysis.3.1 Study AreaThe study will be conducted in Uasin Gishu County, which is a cosmopolitan area. Uasin Gishu County is one of the 47 counties of Kenya. It measures 3,328 km. It borders Nandi, Kericho, Baringo, Elgeyo Marakwet, Trans Nzoia, and Kakamega counties. Eldoret is its capital city as well as its commercial centre. The County has five constituencies; Moiben, Kesses, Kapseret, Turbo and Soy. It has three administrative districts Eldoret East, Eldoret West and Eldoret South. According to the 2010 census, Uasin Gishu has a population of 894,179 with 202,291 households and a population density of 269 people per square km. The age distribution is 0-14 years 41.5 %, 15-64 years 55.7%, and above 65 years 2.9%. A young population signifies a high level of dependence, especially to cater for such needs as education and health (Uasin Gichu County website). Estimated 90 percent of the entire land area in the county is arable and can be classified as high potential. There are four major soil types in the area, all of which are suited for agricultural production. These include red loam, red clay, brown clay and brown loam. A total of 29,801.92 hectares is gazetted forest. Out of this, 13,183.54 hectares (44 percent) is under plantation, while, 16,618.38 hectares (56 percent) is under indigenous forest cover. Through the rural afforestation programme, there are woodlots scattered across the constituency. Poverty level in the county stands at 49% (KNBS, 2007). Forty percent (40%) of this is rural based while 54% is urban. Food poverty stands at about 41%. The major causes of poverty are unemployment, lack of markets for the farm produce, high cost of inputs and poor food storage facilities. A high rate of population growth has contributed to increasing poverty, since social facilities such as health, education, and transport have been exhaustively used. According to various statistics unemployment, both formal or informal or self-employment levels is at 30%. Data available in Uasin Gishu District Youth Office indicate that the percentage of unemployed youth is at 61%.Figure 3.1 Map of Uasin Gishu

Table 3.1: Population distribution in the Uasin Gishu CountyPopulation by Administrative districtsArea (Km2) Population Density Location

Eldoret East

Eldoret West

Eldoret South

District Survey Office, a, Population year 3.2 Research design The study will adopt a descriptive and an explanatory research designs since it seeks to describe and explain the factors that influence treatment of home saved wheat seeds ; and further explain how home saved seed impacts on farmers wheat yield, farm income and efficiency in wheat production by treated home saved wheat seed and non-treated home saved wheat seed. 3.3Target Population The population for the study will be based on the 2006 District agriculture Annual Report that showed that 395 farmers practiced wheat farming,. 3.4Sample FrameIn this study, the household with wheat seed will be the primary unit of analysis. This is because socio-economists, agronomists and policy makers need to understand the basic characteristics of the decision-making unit to better design appropriate research and policy initiatives using sample statistics. The sample frame will be the set of wheat farmers in Uasin Gishu County. The sample for key informants shall include the following service providers involved in wheat projects: wheat extension workers, trainers, and community workers, wheat market players and other informal market players. 3.5Sample Size To determine the sample size, the following equation will be used with 5% significance level and 95% confidence interval (Yavuz, 2009).

Where,n : Sample size.N : Number of wheat farmers in the population. : Population variance. d : Type I error (0.05).z : Table value of Z Standard Normal distribution.D : d/z value.However, just in case that some of the questionnaires may not represent the population or may be incomplete, the number of questionnaires will be increased by 5%. Total number of questionnaires 147+ (147*0.05) = 154. Therefore the study sample size will be 154 wheat farmers. Where, Neyman allocation formula was used to distribute the sample size among the strata. The purpose of the method was to maximize survey precision, given a fixed sample size. With Neyman allocation, the "best" sample size for stratum h would be:

Where, nh is the sample size for stratum h, n is total sample size, Nh is the population size for stratum h, N is the total population Hence, Table 3.3 Sample sizePopulation CategoryTarget PopulationSample Size

Eldoret East

Eldoret West

Wareng,

Total

Source: Survey Data (2012)3.6Sampling ProceduresThe central paradox of sampling is that it is impossible to know from examining a sample, whether or not it is a good sample in the sense of being free from selection bias (E.K.Langat, 2010). A chance selection is an assurance of freedom from selection bias, and as such is an essential item in the credentials of a sample (Stuart and Ord, 1994). A sample selected by chance mechanism with calculable chances of selection is called a random sample (Ibid). Therefore, to draw a fairly representative sample, a list will be made of all wheat farmers. Stratified random sampling technique will be used in the study to categorize farmers into the five zones management systems. A multistage sampling technique will be used to select sites and draw sample of farmers for the study. First three districts will be selected purposively from the region considering their agro-ecology, experience in farmers treatment of home saved seeds, and the production potential for respective crops in the region demonstrated by the consideration of the Uasin Gishu as model demonstration area for farmers based seed and seedling treatment. Sampling of households will be carried out considering two sampling frames of farmers: adopter of respective seed treatment and non-adopters. A farmer engaged in seed treatement for two or more years will be considered as adopter. This is because of the intention not to consider opportunistic farmers that just try for a year and abandon the next year. Farmers will be randomly selected from each of the categories. Stratification will produce the precision in the estimates of the characteristics of the whole population. By stratifying into sub-groups, the required number of farmers can then be sampled (Dillon and Hardaker, 1993 3.7Data Collection ToolsA structured questionnaire will be used to elicit information from respondents identified. This tool is useful as it tends to collect standard responses that can facilitate analysis and comparison of parameters. Primary data collection always involves the tradeoff between undertaking an intensive study in small geographical areas versus a broader examination of a larger area (Fidzani, 1993). In attempting to balance the requirement for capturing important details and unlimited applicability, a questionnaire will be designed as a tool for data collection. Similarly, key informant interviews will be carried out to help verify the respondents responses and to provide a detailed understanding of significant issues in home saved wheat seed treatment and its adoption. Scheduled interviews will be mainly used to elicit information from farmers.Fifteen enumerators to aid in data collection will be identified from each of the divisions and trained. The training will culminate in the pre-testing of the questionnaire. The pre-testing will be done in Narok County to ensure that all the enumerators interpret the questionnaire in the same way.Observation is also an important method of data collection and so it shall be used in the study. This involves observing the natural behaviour of individuals to obtain information relevant to the goals of the study. Observation method will be used in this study for behaviour analysis rather than attitude or opinion analysis.According to Fraenkel and Wallen (2000), the questionnaire is ideal for survey research because it is typically more economical, efficient and applicable when handling large samples. The questionnaire will be structured to capture information on factors that influence treatment of home saved wheat seed. 3.7.1 Validity Fraenkel and Wallen (2000), define validity as the degree to which results obtained from the analysis of collected data actually represents the phenomena under study. To improve on the appropriateness, meaningfulness and usefulness of the findings and inferences of the study, the validity of the questionnaire will be assessed by ensuring it captures meaningful information as intended by the researcher. The content, construction and face validity of the questionnaire will be assessed by experts and peers from the department of Agricultural Economics who will validate the questionnaire developed by the researcher.3.7.2 Reliability.Reliability of the questionnaire will be estimated using the Cronbachs reliability coefficient, which is a measure of internal consistency (Fraenkel and Wallen, 2000). A reliability coefficient of 0.7 or higher is recommended and will be used as the threshold for accepting reliability. In case of a low coefficient being obtained, item-by-item analysis will be done in order to improve weak points in the questionnaire. Kerlinger, (1978), describes reliability as the accuracy or precision of a measuring instrument. The questionnaires will be designed carefully to ensure no ambiguity and that all respondents understand and respond to all issues in exactly the same way as expected by the researcher. 3.8Primary DataThe study will be based on primary data which will be obtained from the farm survey using a structured questionnaire. 3.8.1Secondary DataSecondary data will be sourced from various sources such as journals, conference reviews, books, magazines, official government reports such as statistical abstracts, national and district development plans, Ministry of Agriculture, and that of Social Services annual reports. Desktop literature and the internet will be useful in accessing information from available and accessible documents, journals, published and unpublished reports, agricultural journals and books. Any farm records from keen farmers who keep records will also be used.3.8.2Type of Data CollectedThe data to be collected from the farm survey will consist of the respondents household sizes, land sizes, land tenure system, level of education of household head, occupation of household heads, agricultural activities (crop and livestock), output levels, income levels, source of incomes, savings, credit and government/ non-governmental support, willingness of farmers to treat home saved wheat seeds, annual consumption estimates and overall contribution to family budgets. Additionally, the following information will be sought; farm and farmer characteristics such as age and gender of the respondents, years of experience in dairy farming, size of labour used, and extension services provided to wheat farmers.

3.9 Data Collection ProceduresThe researcher will obtain an introductory letter from Egerton to facilitate acquisition of a research permit from the Ministry of Agriculture and Livestock Development . The researcher will visit the farmers and administer the questionnaires, conduct the interviews and involve himself in participatory observation.The identified (15) enumerators having been trained on the administration of the questionnaire and observation techniques will do a pilot survey whose results will be checked before embarking with the proper survey. A list of the farmers will be prepared and randomly selected as earlier discussed. Interviews will be scheduled with relevant respondents including focused group discussions. 3.10 Variables description Dependent variables: The logistic model uses dichotomous values as dependent variable. Independent variables: It is hypothesized that farmers decisions to adopt or reject new technologies at any time are influenced by the combined effect of a number of factors. This includes both discreet and continuous variables such as: household characteristics, socio- economic characteristics and institutional characteristics in which farmers operate.1. Education level of the respondent, normally the household head (EEDUCATION): In almost all of studies on agriculture, education has been taken as an important explanatory factor that positively affects the decision of households to adopt new agricultural technologies (Abay and Assefa, 2002). Farmers with more education should be aware of more sources of information, and be more efficient in evaluating and interpreting information about innovations than those with less education. Thus it is hypothesized that producers with more education are more likely to be adopters than farmers with less education (Teklewold et al., 2006). It is will be measured as a categorical variable in grades or number of years in school.2. Family size (FSIZE): It is a continuous variable which indicate the number of persons living in the house of each respective farmer. It is expected that as the size of the house hold increase the adoption of new technologies will improve .This indicates that larger families are more likely to be involved in wheat seed treatment of home saved seeds because availability of enough manpower.3. Land size (SLAND): It represents the total owned and cultivated land by household. It is expected to be positively associated with the decision to adopt seed production technologies. This means that farmers who have relatively large farm size will be more initiated to involve in seed production, and the reverse is true for small size farm land. It is continuous variable measured in hectares. The positively significant coefficient of farm land size indicates its positive influence on technology adoption. Subsistence oriented small farmers are highly risk averse to apply innovation due to limited holding and uncertain outcome of technology (Bahadur, 2004).4. Off-farm income (OFFINC): Off-farm income represents the amount of income the farmers earn in the year out of on-farm activity. It is the amount of income (in Kshs) generated from activities other than wheat production. The households engaged in off-farm activities are better endowed with additional income to purchase essential farm inputs, like seed dressing chemicals and even essential machinery for use in seed treatment5. Farming experiences (YEXPER): Is measured in the categorized number of years since a respondent started farming on his own. Experience of the farmers is likely to have a range of influences on adoption. Experience expected to improve farmers involvement in seed production. A more experienced grower may have a lower level of uncertainty about the technologys performance (Chilot et al, 1996). Farmers with higher experience appear to have often full information and better knowledge and are able to evaluate the advantage of technology. 6. Total Maize acreage (TMA): This refers to the total number acreage under maize per household (TMA). Maize and wheat both compete for resources such as land among farmers. It is therefore expected that increased maize acreage will lead to reduced planting of wheat with subsequent effect on seed dressing of wheat seeds.7. Access to credit facility (CACCESS): It is a dummy variable, which takes a value of 1 if the farm household had access to credit and 0 otherwise. Adoption of new technology with complementary inputs require considerable amount of capital for purchase of inputs (seed, fertilizer).Farmers who have access to formal credit are more probable to adopt improved technology than those who have no access to formal credit (Yishak, 2005). On the other hand the availability of farm credit especially from formal sources is vital components of the modernization of agriculture and to increase productivity. Those farmers who have access to agricultural credit are believed to adopt technology more than those who have no access to credit. This indicates smallholder farmers cannot finance these inputs for seed production unless they get alternative means. 8. Extension service (ESERVICE): Extension visits will help to reinforce the message and enhance the accuracy of implementation of the technology packages (Oladele, 2005). More frequent extension visits, using different extension teaching methods like attending demonstrations and field day can help the farmers to adopt a new technology. If the farmers get better extension services, they are expected to adopt seed production technologies than others. In this study this variable was treated as a dummy variable. That is if the farmers gets extension service it is coded as 1 and 0, otherwise.9. Availability of training (ATRAIN): Farmers may obtain information from different source and may learn also from extensqion agents through extension programs. However unless they can obtain required skill through training they may face difficulty to understand and apply new technologies. So those farmers who get training on wheat seed treatment are more willing than those who didnt get training to treat their home saved seeds. It is dummy variable measured as 1 if farmers got specific training on seed multiplication and 0 otherwise.10. Distance from a seed treater (DISTREAT): It is a continuous variable measured in kilometers. The nearer a seed dressing machine is nearer to the farmer, the higher would be the probability that a farmer will trest his home saved seeds.Their are farms with their own seed treatment machines. Therefore, in this study, it is hypothesized that this variable is negatively related to willingness to treat home saved seeds.11. Market distance (DISMARKET): As a farm household is nearer to market places, it is expected to be more likely participate in intensive farming activities that demands adoption of new agricultural technologies. Therefore, it is expected that as a given farm household gets far away from such areas the likelihood of getting involved in home saved wheat treatment practice decreases. It is continuous variable measured in km.

12. Access to input supply (INACCESS): Farmers involved in wheat production require various types of farm input. Sunding et al (2000) indicate that the introduction of new technologies may increase demand for complementary inputs and when the supply of these inputs is restricted, adoption will be constrained. This perception of farmers measured as dummy variable and 1 if he perceive that there is sufficient availability of input important for seed multiplication 0 otherwise13. Availability of cleaning srvices(SCLEAN): Farmers will readily seed dress their wheat seeds if cleaning services of the seeds are available. Impurities such as seeds from weeds, dirt and other seed-crops will reduce the productivity of the farms. It will also imply an increased cost of production further complicated by the resultant inefficient dressing. This will be a dummy variable with a value of 1 if farmers perceive that a seed cleaner will be available along with seed dressing services and 0 if otherwise.14. Expected wheat price at end of season (EPRICE): Farmers asses thecprofitability of each farm enterprise every season. If the expected revenue at the end of wheat planting season is perceived to be favourable, farmers will choose to grow wheat and vice versa for perceived-expected low price. This means that a farmer will be more inclined to seed dress his home saved wheat seeds, if price expectation will be favourable.3.10.1 Data Analysis TechniquesThe collected data will be analyzed using descriptive. Data will also be analyzed statistically using parametric procedures. This (parametric) approach uses EXCEL and the Statistical Package for Social Scientists (SPSS) software to analyze quantitative data. Correlation and regression analyses will also be performed by use of SPSS. The correlation analysis will be used to establish the degree of relationship between factors of production (Xis). A regression analysis will be used to estimate the influence of various factors ontreatment of home saved wheat seeds. Regression analysis will generate statistical parameters which will then be used to test for statistical significance using t- test. 3.10.2Descriptive StatisticsDescriptive statistics will be used to describe the socio-economic characteristics of the respondents. Cross tabulation, frequencies, percentages and means will be computed in order to understand the data collected. This will test the hypothesis of the study which states that socio- cultural factors do not affect adoption of treatment of home saved wheat seeds.3.11Empirical Model 3.11.1Theoretical Model and Empirical SpecificationGiven that the focus of this study is to identify the determinants of the adoption of improved treatment of home saved wheat seeds and how such adoption may affect wheat production from farming, the study will state basic relationship of the impact of the new innovation adoption on farm income, measured by farmers farm income as a linear function of vector of explanatory variables ( X i ) and an adoption dummy variable (Wi ). The linear regression can be specified as..13.12Data Sources and TypesWhere Yi is the mean farmer income from farming wheat, is a normal random distribution term, andZi is a dummy variable for use of new technology; Zi = 1 if the treatment of home saved seed is adopted andZi = 0 otherwise. The vectorX i represents household and farm characteristics. Whether farmers adopt improved varieties or not is dependent on the characteristics of farmer farm and technology. By deciding to adopt an improved home treatment seed variety the farmer has self-selected to participate instead of a random assignment. Following Becerril and Abdulai (2009), we assume that the farmer is riskneutral. The index function used to estimate the adoption of home saved seed can be expressed as:Z* = X ' + ...................................................................................................................2Where Z * is a latent variable denoting the difference between utility from adopting improved varieties U iA and the utility from not adopting the innovation UiN . The farmer will adopt the new innovation if Z * = UiA -UiN > 0. The term X ' will provides an estimate of the difference in utility from adopting the innovation (UiA -UiN), using the household and farm-level characteristics, Xi, as explanatory variables, while i is an error term. In estimating equations (1) and (2), it needs to be noted that the relationship between the new innovation and an outcome such as income could be interdependent. Specifically, the selection bias occurs if unobservable factors influence both error terms of the income equation () and the innovation choice equation (), thus resulting in the correlation of error terms of the outcome and technology choice specifications. Thus, estimating equation 1 using the ordinary least squares (OLS) will lead to biased estimates. To address this problem, a two-step Heckmans procedure will be used to analyze factors affecting the probability of adopting home saved seed treament. The model is appropriate because it addresses simultaneity problems.3.13The Heckman Two-Step Method The Heckman (1976) two stage procedure has been used to address selection bias when the correlation between the two error terms is greater than zero (Hoffman and Kassouf, 2005; Adeoti, 2009; Johannes et al., 2010; Siziba et al., 2010). The approach depends on the restrictive assumption of normally distributed errors (Wooldridge, 2002). The procedure involves, first, the estimation of the selection equation using a probit model (adoption equation 2) and second, the estimation of the income equation 1. The adoption equation (equation 2) is estimated asZ* = X ' + Z* is a latent variable representing the propensity of a farmer to adopt home treated wheat seeds.is the vector of farmers assets endowment, household characteristics, technology characteristics and location variable that influence adoption decision. The probit model will predicts the probability of adoption and also obtains the inverse Mills ratio (IMR) as shown below:.3Where and are, respectively the standard normal density function and standard normal distribution functions. i is the calculated IMR term to provide OLS selection corrected estimates (Greene, 2003)The choice to adopt or not to adopt a home treated seed will be considered in the first step and if a household has treated home saved wheat , the impact of home treated wheat seeds on wheat yield, household income and farming efficiency are determined in the second stage. ..4Where Yi = home wheat saved seed (Y=1, if treated; Y = 0, otherwise) ..53.14Propensity score matching (PSM)PSM estimates the difference in wheat yield per hectare and household welfare of trated home saved seeds and non=treated home saved seed. Household welfare will be measured using the level of farm income. The effect can be stated as;Effect ..6Where y1i is household with treated home saved wheat seeds income and y0j is household without treated home saved seeds income. Determining the effect of home saved seeds on farm income and wheat yield of wheat farmer using PSM is a two stage procedure where in the first stage, the propensity score will be estimated. This will be done by running a logistic regression where on the left side is whether a farmer has treated home saved seeds or not (Dependent variable: Y=1, if treated ; Y = 0, otherwise) and the variables that affect probability of adopting treated home saved seeds.Yi= f (Xi) 7aY1 = log (Pi /1-Pi) = i+ i Xi+ i 7(b) WherePi = probability of treating home saved wheat seeds1- Pi = probability of not treating home saved wheat seeds Yi = treatment of home saved seeds (Y=1, if treated ; Y = 0, otherwise)Xi = factors that influence whether farmers treat home saved wheat seeds = Error termThe propensity score is the predicted value obtained from the above regression and this is predicted probability (p) or log [p/ (1-p)]. In the second stage, each farmer with treated wheat seeds is matched to one or more farmers without home saved seeds on the propensity score and this will be done using nearest neighbor matching, kernel, local linear matching and stratification matching. These methods enable a procedure where the best match (non-member) for each member is identified and a weight is allocated, NN allocate a weight of 1 for the nearest match and zero for all others. Sum of the weights equal to one () and 01..8(a)Thus Effect ...8(b)Average effect of treated home saved seeds (AETHSS) AETHSS = ....3.7(a)AETHSS = E[ Y1t-Y0t/Di=1]= E[E{Y1i/Di=1, p (Xi)}-E{Y0i/Di=0, p(Xi)}/Di=1]. 3.7(b)

Where Y1i and Y0i are the potential outcomes for the two counterfactual situations of treated home saved wheat seeds and non- home saved wheat seeds, p (Xi) is the propensity score, D is the membership variable, where D=1, if member and 0 otherwise.Caliper, local linear matching, stratification and DD matching approaches will be used and their results compared. This is because comparing results across different matching methods can show if the estimates of the effect arrived at are robust (Khandker, Koolwal and Samad, 2010)The same data instrument will be used to collect data from farmer with treated wheat seeds is matched to one or more farmers without home saved seeds and also use of a representative sample will be selected by ensuring randomness and sufficient sample to reduce the bias with use of PSM, as suggested by Heckman, Ichimura, and Todd (1997, 1998). T-test will be used to determine if there is significant difference between farm income of farmer with treated wheat seeds is matched to one or more farmers without home saved seeds. 3.15Estimating the Production Function The study uses Cobb- Douglas production function generally given as Y =0 Xi i e..............3.8(a)Yi = 0X1 1X22X33X44X55e ..............3.8(b)Yi = Total output by respondent i A = Total factor productivity coefficient Xi = Factors affecting wheat output i = Are the elasticities of independent variables = The stochastic error term

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