Faculty of Agriculture

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Demand analysis of fresh fruits consumption among urban households in Nakuru City
(Egerton University, 2025-10) Lenah Waithira Mwangi
Fresh fruits are a vital source of essential micro and macro nutrients and play critical role in improved nutrition, disease prevention and dietary balance however, urban Kenyan households consume far below the World Health Organization (WHO) and the United Nations-Food and Agriculture Organization (FAO) recommendations (400g/day. The general objective of this study was to contribute towards improved household nutrition through enhanced fresh fruit consumption among low- and high-income households in Nakuru City, Kenya. Specific objectives were to determine consumption patterns of fresh fruits among low- and high-income households; to estimate the demand of selected fresh fruits among low- and high-income households; and to determine the factors that influence the willingness to pay for selected fresh fruits attributes among the low- and high-income households in Nakuru City. Nakuru City was purposively selected and systemic random sampling proportionate to ward sizes was used to select respondents from each ward and cross-sectional data from 237 households was obtained. Descriptive and inferential statistics, Linearized Approximation Almost Ideal Demand System (LA/AIDS) model and the Hedonic Pricing Model were used for data analysis. The study revealed that low-income households exhibited higher fruit expenditure responsiveness (53.42%) to income changes than high-income households (46.57%). Bananas, oranges and melons displayed elastic demand among low-income households, while avocado and pineapple were inelastic. Own-price elasticities were negative for all fruits implying normal goods. Cross price elasticities indicated substitutability for bananas and avocados and complementarity for bananas and melons. High-income households spent 41% more on fresh fruits monthly than their low-income counterparts. Hedonic results indicated positive income effect and significant preference for quality attributes. Fresh fruit attributes that influenced willingness to pay significantly included absence of defects, texture, size, fruit color, and freshness for both low and high-income households. Perceived nutrition, income, gender of the household head and education level of the household head were the socio-economic characteristics that influenced willingness to pay for fresh fruits. The results underscore income, and not price, as the primary driver of fruit consumption disparities. Fruit vouchers, price control measures and public awareness campaign could be used to assist vulnerable to improve fruit consumption. Attribute-based pricing strategies and income consideration should be applied to enhance fresh fruits consumption.
Determinants of market participation and effects on household income among small-scale indigenous chicken farmers in Kweneng East District, Botswana
(Egerton University, 2025-09) Lerato Pheko
Poultry farming is pivotal to rural livelihoods and smallholder farming. Indigenous chickens, within poultry farming, are essential for boosting household income and food security even though farmers of these chickens remain impoverished. One possible reason for this is their limited participation in profitable markets. The aim of the study was to improve household income of small-scale indigenous chicken farmers by promoting their participation in profitable markets in Kweneng East District, Botswana. Specifically, this study aimed at identifying preferred indigenous chicken market outlets and their price differentials. It also determined the factors influencing market participation and the intensity of participation among small-scale indigenous chicken farmers, and the factors influencing the choice of market outlets among small-scale indigenous chicken farmers. Additionally, it examined the effects of market participation on household income among small-scale indigenous chicken farmers. A multi-stage sampling approach was applied to obtain a sample of 276 indigenous chicken farmers and the data was collected through a semi-structured questionnaire. Descriptive statistics was used to identify the preferred market outlets and their price differentials. Majority, about 30% indigenous chicken farmers, prefer a farm gate as a market outlet. Restaurants offer higher prices, BWP 103.24 (USD 7.39) and BWP 143.33 (USD 10.26) for hens and cocks, respectively, than other market outlets. The double hurdle model revealed that access to market information significantly influences the decision to participate by 1.062 at 1% and the intensity to participate. Multivariate Probit results revealed that off-farm income positively influenced the choice of farm gate market at 1% and market bargaining power had a positive statistical influence on the choice of all market outlets at a 1% significance level. The Average Treatment effect on the treated results of the endogenous switching regression model revealed that market participants would earn less (23 472 BWP) if they did not participate in the market and non-participants would earn 22 274 BWP if they had decided to participate and this shows the effect of market participation on the household income of farmers. The study recommends farmer collaboration to enhance collective marketing and access to diverse market outlets by indigenous chicken farmers. The study also suggests the improvement of access to public extension offices and road and transport networks to high value markets for upgrading the indigenous chicken farming industry.
Determinants of utilization of recommended forages and concentrates among smallholder dairy farmers in Nakuru County, Kenya
(Egerton University, 2025-10) Flora Gash Kambabazi
The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed The dairy industry was an important part of the Kenyan agro economy. It contributed about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million about 4 per cent to the national GDP and it supports more than 1.5 million smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru smallholder farmers. This is because milk production among dairy farmers in Nakuru County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high County was low as a result of the quality scarce pasture and also their high prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, prices, which were unaffordable in the dry season. This led to unstable production, reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming reduced economical returns and the difficulty in sustainability of dairy farming in the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to the long run. Through these obstacles, research made a broad contribution to no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in no poverty and zero hunger through enhancing profitability milk output in smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish smallholder dairy farmers. The objectives of the particular study were i) to establish the facto the factothe factothe facto the facto the factors that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and rs that influence the decision to use recommended forages and concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using concentrates, ii) to establish the degree of technical efficiency using recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of recommended forages and concentrates iii) to establish the profitability of use of recommended forages and concuse of recommended forages and conc use of recommended forages and concuse of recommended forages and concuse of recommended forages and conc use of recommended forages and conc use of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and conc use of recommended forages and conc use of recommended forages and concuse of recommended forages and conc use of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and concuse of recommended forages and conc use of recommended forages and concuse of recommended forages and concentrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in entrates by the smallholder dairy farmers in Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that Nakuru County in Kenya. The research was anchored on the information that gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub gathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Subgathered in a sample of 225 small holder dairy farmers Njoro and Molo Sub-Counties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were sCounties in Nakuru County, Kenya. The respondents were s Counties in Nakuru County, Kenya. The respondents were selected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage elected by a multistage sampling method and semi sampling method and semisampling method and semisampling method and semi sampling method and semisampling method and semisampling method and semisampling method and semisampling method and semisampling method and semi sampling method and semisampling method and semisampling method and semisampling method and semisampling method and semisampling method and semisampling method and semisampling method and semi sampling method and semisampling method and semi-structured questionnaires were used to collect the cross structured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross structured questionnaires were used to collect the cross structured questionnaires were used to collect the crossstructured questionnaires were used to collect the crossstructured questionnaires were used to collect the cross -sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type sectional data. The results of the Probit model revealed that female gender, type breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, memb breed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membbreed, land tenure, live weight of cows, credit utilization, membership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, ership of a group, production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension production system, herd size and contacts with the concerned extension agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on agent, education and experience had a significant (P < 0.05 0.1) influence on decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder decision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholderdecision to use the recommended forage and concentrates by smallholder dairy dairy dairy dairy dairy farmers. The farmers. The farmers. The farmers. The farmers. The farmers. The farmers. The farmers. The St ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy ochastic frontier model findings demonstrated that smallholder dairy farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) farmers that used both forages and concentrates were more efficient (0.636) compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency compared to those who used only forages (0.364). The average technical efficiency was 34.was 34.was 34. was 34.was 34.was 34.85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among 85 percent amongst the ones using both feeds, 24.07 among ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated ones using forages only. This showed that farmers who fed on both feeds generated milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, milk yield increased by 75.93 percent and farmers who fed on forages only, increased by 65.15 percent. G increased by 65.15 percent. Gincreased by 65.15 percent. G increased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. Gincreased by 65.15 percent. G increased by 65.15 percent. G increased by 65.15 percent. Gincreased by 65.15 percent. Gross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of ross margin analysis showed that a combination of forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins forages and concentrates (P<0.1) was very beneficial in raising gross margins among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used among the smallholder dairy farmers (KES 89,745.77) than when forages were used only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin oonly (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin o only (KES 57,619.25). The average gross margin of all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was f all feed levels of quality was 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43. The averages of changes in the level feed quality were statistically 78,037.43.
Influence of students’ participation in young farmers’ clubs on performance in and attitude towards agriculture in secondary schools in Suba Sub-County, Kenya
(Egerton University, 2025) Opere, James Muok
Kenya’s economic growth is primarily driven by agriculture. Setting up Young Farmers’ Clubs (YFCs) in secondary schools is one way of attracting young people in agriculture as well as developing their production skills. The level of participation in YFCs is likely to inﬂuence the students’ performance as well as their attitude towards agriculture. The purpose of this research was to ascertain how students’ involvement in Young Famqers’ Clubs inﬂuence their performance in agriculture and attitude towards the subject in secondary schools in Suba Sub-County. The research employed cross-sectional survey design targeting 628 Form Three students taking agriculture in public secondary schools in Suba Sub-County. The data was collected from an accessible population of 286 Fonn Three agriculture students who are also members of Young Fanners’ Clubs in 37 public secondary schools in Suba. A sample size of 126 respondents was obtained through stratiﬁed random sampling. Nassiuma, (2000) formula was applied to obtain the sample size. Respondents were allocated across the strata according to school categories i.e.; one national school, two extra county schools, two county schools and three sub- county schools giving a total of eight schools. Data was collected using semi-structured questionnaires. The instrurnent’s validity was assessed by specialists in agricultural education and extension from Egerton University. Reliability was established through a pilot testing involving 30 agriculture students in ﬁve secondary schools in neighbouring Nyatike Sub-County. Cronbach alpha coefﬁcient was used to assess the instrument’s reliability where a coefﬁcient of 0.817 was computed and taken as satisfactory. SPSS version 25 was used for data cleaning, coding and analysis. The hypotheses were examined at 5% signiﬁcance level using ordered logistic regression analysis. This study found that Young Farmers’ Clubs are accorded with key school facilities such as farm and access to the library. Young Farmers’ Clubs perform a variety of activities, ranging from crop production (e.g. vegetable growing and tree planting) to livestock keeping (e.g. rearing of cattle and sheep).The study ﬁndings revealed that students’ perfonnance and attitude towards agriculture are positively inﬂuenced by participation in Young Farmers’ Clubs. This study recommends that students’ participation in Young Fanners’ Clubs activities could be encouraged in all secondary schools as a way of augmenting students’ perfonnance in agriculture and improving their attitude towards the subject. This can be done by providing adequate time for YFC’s activities. In addition, the necessary facilities should be made available so that their involvement is worthwhile.
Household willingness to pay or participate in the control of The invasive ipomoea plant species in Kajiado Central Sub-County, Kajiado County, Kenya
(Egerton University, 2025) Kidist Abebe mersha
Communal grazing lands are crucial for the livelihoods and food security of pastoralist communi- ties in Kajiado County, Kenya, who depend mainly on livestock. Over the past decade, changes in land use have allowed the invasive Ipomoea species to spread, shrinking available grazing areas and putting the long-term resilience of these communities at risk. Guided by Random utility theory and theory of Common Pool Resources, this research was needed to contribute empirical evidence to support policy formation on sustainable rangeland management. This study focused on estimat- ing the household willingness to participate in control efforts and identify factors inﬂuencing their willingness. The speciﬁc objectives of this study were; to characterize households’ willingness to pay or participate in the control of the invasive lpomoea species; to estimate the mean level of willingness to pay or participate, and determine the factors inﬂuencing household willingness to pay. Primary data were collected from 267 households through a semi-structured questionnaire between April and May 2025 using a multistage sampling procedure across three wards in Kajiado Central Sub-County: Purko, Dalalekutuk, and Illdamat that were later cleaned and analyzed using SPSS version 27 and STATA version 17 respectively. The data were analysed using descriptive statistics for the ﬁrst objective, while a double-bounded dichotomous choice CVM approach with a seemingly unrelated bivariate probit model was employed to estimate mean WTP/WTPa and identify its determinants. Out of 260 responses, 81.2% (21 1 households) expressed willingness to pay in cash, while 81.92% (213 households) were willing to participate through labour. The SUBP model results showed that the mean willingness to pay was KES 9,541.44 KES per year and 14.13 Labour days. key detenninants of WTP/Pa included positive signiﬁcance from extension access (18.4%), land tenure security (5.1%), and livestock ownership (1%), while age (-1.4%), Bid amounts and labor requirements (-6%) showed negative signiﬁcance. The study concludes that pastoral households are largely willing to participate in efforts to control invasive Ipomoea and recommends that policymakers take these key factors into account when designing community- based strategies to manage the spread of invasive plants and strengthen the resilience of pastoral systems.
Effect of cassava (manihot esculenta crantz) fermentation and cricket (acheta domesticus) enrichment on protein quality, sensory properties, and shelf life of cassava-cricket biscuits
(Egerton University, 2025-08) Kevine Odhiambo Otieno
Climate change and population growth, which have led to the subdivision of agricultural land, are threats to food security. Cassava (Manihot esculenta Crantz) and cricket (Acheta domesticus) are potential solutions to this threat. This study aimed to develop biscuits from fermented cassava enriched with cricket flour that meet the protein requirements of 5-13-year-olds. Cassava flour was fermented spontaneously and with Aspergillus oryzae, and mixed with cricket flour at three levels: 12%, 24%, and 36%. The blended flours were kneaded and baked at 180°C/7 minutes into biscuits then analysed for nutritional, microbial, shelf life, and sensory properties. Cricket flour was also analysed for amino acids and fatty acids. The results showed that cricket protein had significantly higher levels of all amino acids except threonine than the reference protein. It was richest in tyrosine, glutamic acid and histidine, with concentrations of 5.01, 4.76, and 4.01 g/100g, respectively. Cricket flour is a good source of retinol, with a concentration of 1.46 mg/100 g. The fat in cricket flour is richest in elaidic, palmitic, and stearic fatty acids, with concentrations of 43.13%, 21.83%, and 11.02%, respectively. Both method of fermentation and substitution level of cricket flour significantly improved the protein quality, sensory, microbial and shelf-life properties of the resultant biscuits. Biscuits made from spontaneous and Aspergillus oryzae fermented cassava flour had higher protein and ash content, and lower moisture and carbohydrate content than unfermented biscuits (p<0.05). Consumers rated the sensory attributes of biscuits lower as the cricket substitution level increased, regardless of the fermentation method used. Increasing the amount of cricket flour in biscuits significantly increased the intensity of colour, crumbliness, and bitterness, while significantly decreasing the intensity of consistency, density, baked aroma, sugary taste, and buttery flavour, irrespective of the fermentation method. Initial peroxide values of cassava-cricket biscuits were 2.9- 3.7 mEq of O2/kg. During storage the activation energy for oxidative rancidity in cassava-cricket biscuits was from -8.84 to 10.07 1.07 J/K/Mol, enthalpy change was from -2462.71 to -2443.80 kJ/Mol, entropy change from -49.51 to -46.37 J/K/Mol and Gibbs free energy was from 11.242.18 to 12,160.12 kJ/Mol. The thermodynamic properties of the biscuits showed that the environment was anaerobic and had low water activity hindering oxidative rancidity during storage, so peroxide value could not be solely relied on to predict shelf life. These findings show that cassava and cricket utilization can open up a new frontier in the incorporation of insects in baked foods as protein sources, and address food security challenges in Sub-Saharan Africa.
Effect of choice of market outlets on profitability among vanilla smallholder farmers in Antalaha District, Madagascar
(Egerton University, 2025-09) Georgia, Rahelison
Madagascar's agricultural sector is dominated by smallholder farmers, who contribute significantly to the nation's economy, employment, food security, and income. Besides that, Madagascar is the world's leading vanilla producer, primarily in the north-east, precisely in the SAVA region of Sambava, Antalaha, Vohémar and Andapa, where 87.2% of the smallholder farmers engage in the production of vanilla. However, smallholder vanilla farmers in this region still face food insecurity, lower incomes and high levels of poverty. The market outlet choices by vanilla smallholder farmers affect their profitability. This research seeks to contribute to improved livelihoods of smallholder vanilla farmers in Antalaha district of Madagascar through an understanding of the market outlet choices for enhanced profitability. The specific objectives of this research are to examine vanilla market constraints among smallholder farmers, to determine factors influencing choice of different market outlets of vanilla among smallholder farmers, to determine the profitability of participation in different vanilla market outlets among smallholder farmers and to assess the effect of market outlet choices on profitability among smallholder vanilla farmers. The study used data collected from a sample of 384 smallholder vanilla farmers from two municipalities, Ampohibe and Ambalabe, in the Antalaha districts of Madagascar. A multistage sampling technique was employed to select the respondents and cross-sectional data was collected using semi-structured questionnaires. The software Statistical Package for Social Sciences (SPSS) and STATA were employed to analyse the data. Principal component analysis (PCA) was used to group vanilla market constraints into clusters. The results revealed that smallholder farmers in both municipalities faced 14 vanilla market constraints, which were grouped into 4 principal components. Multivariate probit (MVP) results show that factors including sex, education level, off-farm income, land ownership, group membership, vanilla yield, dry vanilla, and green vanilla significantly affect the of market outlet choices among smallholder vanilla farmers. Gross margin analysis and Endogenous Switching Regression indicate that cooperatives and urban markets (6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) 6089.68 Ariary per kg) offer higher gross margins per kilogram for farmers than those who use local markets (4340.65 Ariary p 4340.65 Ariary p 4340.65 Ariary p 4340.65 Ariary p4340.65 Ariary p4340.65 Ariary per kg)er kg) er kg)er kg)er kg). The research recommends that vanilla small-scale farmers should be encouraged to join cooperatives, with government support for cooperative programs, alongside improvements in education, market access, agricultural training and infrastructure. The results should help smallholder vanilla farmers to select the most profitable outlets
Effect of corporate governance practices mediated by risk management on sustainability of agricultural cooperatives in Ngozi Province, Burundi
(Egerton University, 2025-09) Bernice Nasangwe
The growth of agricultural cooperatives in Burundi is very crucial for the rural development. This is due to its critical role in improving the welfare and livelihood of smallholder farmers. With this acknowledgement, the sustainability of cooperatives in Burundi is key. However, in the past decade, performance of cooperatives in Burundi has been declining with majority being inactive. Corporate governance and risk management practices have been viewed as catalysts for improvement of cooperatives longevity. Therefore, this study seeks to determine the effect of corporate governance practices mediated by risk management on sustainability of agricultural cooperatives. Specifically, the objectives of this study were firstly, to determine the factors influencing adoption of corporate governance practices, secondly to determine the effect of corporate governance practices on sustainability of agricultural cooperatives, and lastly to determine the effect of corporate governance mediated by risk management on sustainability of agricultural cooperatives in Ngozi province. A multistage sampling method was used to select an initial sample of 293 members of the agricultural cooperatives. An additional 14 respondents were later included, bringing the total sample size to 307. The data collected will be analysed using statistical software (STATA) and Smart PLS version 3. Through a cross-sectional survey, data were collected using a standardized questionnaire. Factors that significantly influenced the implementation of corporate governance practices were gender, education level, years of membership, level of position, number of meetings, information dissemination, credit facilities, and participation in trainings, understanding tasks assigned to leaders, involvement of members in decision making, understanding of principles by members, leadership style and organizational culture. Secondly, the findings indicated that there was a positive and significant relationship between responsibility CGP and economic, social, environment sustainability. The results also revealed a positive and significant relationship between participation CGP and social, environmental sustainability; rule by law CGP and social, environmental sustainability; transparency CGP and economic, environmental sustainability. However, fairness was found to have a negative relationship with environmental sustainability. As recommendations, in order for cooperatives to sustain economically, socially, and environmentally in the long term; the study recommended to develop a cooperative governance capacity-building program, to set up a support system for agricultural cooperatives, and to promote stakeholder involvement in the risk management process.
Effect of credit access on income among small scale youth tomato farmers in Mvomero District Tanzania
(Egerton University, 2025-11) Chelangat ,Huldah Too
Despite the potential that the agriculture sector holds to contribute to reducing the high unemployment levels among the youth, the sector remains largely untapped. Youth farmers struggle to get access to credit for agricultural activities, which is critical for the purchase of inputs and setting up of agricultural investments. This study looked into the effect of access to credit on income among small-scale youth tomato farmers in Mvomero district, Tanzania. Tanzania is largely endowed with arable land and favourable weather conditions for agricultural production. The first objective sought to determine the perceptions of youth on the process of accessing credit from lending institutions. The second objective reviewed the determinants of credit access and the third objective analysed the impact of credit on income. A sample of 562 youth were interviewed for the study and the data analysed using STATA software. For the first objective the exploratory factor analysis (EFA) was used and the findings show that youth perceive the process of seeking and applying for credit as cumbersome and the procedures complex. The second objective was analysed using the binary logit regression model and the results found that level of education, years of farming experience, land size, gender, group membership, and distance to lending institutions were significant in determining access to credit. The third objective was analysed using the propensity score matching technique (PSM). The PSM results show that access to credit increases farm income as it allows the purchase of quality inputs and investment in farm activities. Additionally, income from farmers borrowing from formal institutions was higher than those acquiring loans from informal channels. In conclusion, uptake of agricultural credit among youth farmers can be increased through financial literacy, youth-friendly packages, and simplified and inclusive loan application and requirements. Further research is proposed to explore other factors that can enhance youth engagement in agriculture and the impact of access to credit across various value chains.
Effect of supplementary diets on the performance of honeybees (apis mellifera) during dearth period in Baringo County
(Egerton University, 2025-09) Haron, Juma Masai
The dry periods in arid and semi-arid lands in Kenya (ASALs) affect honeybees due to a shortage of pollen and nectar, jeopardizing colony health, honeybee industry viability, ecosystem balance, human nutrition, and income for the ASAL communities. To address this challenge, a study was conducted in April, 2023 to July, 2023 at the Dryland Research Training and Ecotourism Centre (DRTEC) in Chemeron, Baringo County. The aim was to investigate the effect of supplementary diets on honeybee performance. There were four dietary treatments: T1 (control), no supplementary feed; T2, soybean flour, T3, chickpea flour, and T4, ground Prosopis juliflora pods. All diets included milled sorghum, brewer's yeast, skimmed milk, and honey as additional supplements at varying ratios. Twelve wooden Langstroth beehives with similar colony strengths were randomly selected and labelled for the experiment. Proximate analysis of the diets was done before the feeding trial which was conducted. Each hive received 250g of their assigned dietary supplement weekly for thirteen consecutive weeks using the top bar feeding technique. The data that was collected involved population density, honey yield, sealed brood area (cm³), and diet acceptance. During the thirteen-week period, the amount of the population density and sealed brood area was measured on a weekly, bi-weekly, and monthly basis, respectively. Honey was harvested at the end of the research. Regarding the results, the feed intake of the diets T2 (soybean) at 105.18g +2.53g/week and T3 (chickpea) at 106.57g +2.50g/week were not significantly different. Both diets had significantly higher intake than T4 (Prosopis pods) with an average intake of 78.13g ± 2.53g per week. Colonies fed on diets T2 (soybean) and T3 (chickpea) had the largest sealed brood areas (1720.00cm²±86.69cm² and 1586.75cm²±60.58cm², respectively) compared to T4 (Prosopis pod meal) with 1101.88cm²±52.41cm². The control group (T1) had the lowest sealed brood area at 908.38 cm²±32.25cm². The highest bee population density (8 frames/colony) was observed in colonies fed T2 and T3 diets. Diet T4 followed in population density while the control group (T1) exhibited the lowest population density (5 frames/colony). Honey production had similar trends to density. Colonies in the control group (T1) yielded 3.53kg±0.46kg, while those fed T2, T3, and T4 yielded 9.50kg±0.68kg, 8.13kg±0.58kg, and 5.37kg±0.35kg, respectively. Colonies fed soybean and chickpea (T2 and T3) supplements made significantly more honey as compared to the other treatments. The result of the study showed that soybean and chickpea flour supplements enhanced the performance of honeybees, resulting in higher honey yield and higher income.
Effects of aflatoxin-inhibiting technologies on productivity of groundnuts in Elgeyo Marakwet and Baringo Counties, Kenya
(Egerton University, 2025-09) Buba Daffeh
Aflatoxin contamination is a major constraint to Kenya's food safety and market access, causing losses estimated at US$17.28 million annually. Groundnuts are highly susceptible to aflatoxin contamination. Both pre-and post-harvest contaminations are due to favourable conditions for aflatoxin-producing fungi. This leads to low-quality produce, low prices, health risks, and reduced income for smallholder farmers. Although several aflatoxin-inhibiting technologies have been promoted to improve groundnut productivity and quality, existing studies have not adequately documented their use, adoption levels, and impact on productivity, particularly in Elgeyo Marakwet and Baringo counties. The study specifically intended to map pre- and post- harvest aflatoxin-inhibiting technologies, identify factors influencing their adoption, assess the extent of these technologies' adoption, and determine their effects on groundnut productivity and quality. A multistage sampling technique was used to select 384 smallholder farmers across the two counties. Primary data were collected using a validated semi-structured questionnaire. Data analysis was conducted using SPSS and STATA 18. Descriptive statistics were used to examine current practices, while multivariate probit and ordered probit models assessed adoption factors and extent. An ordered probit endogenous switching regression model was applied to estimate the effects on productivity. The results posited that access to education, gender, farming experience, group membership, price of groundnuts, fertiliser use, use of improved varieties, off-farm income, and distance to market significantly influenced the uptake of a majority of aflatoxin-inhibiting technologies. Regarding adoption intensity, the findings revealed a high propensity for adoption among medium adopters as opposed to low and high adopters. Finally, the results denoted increased productivity among the medium (ATT=100kg/acre) and high (ATT=42kg/acre) adopters of aflatoxin-inhibiting technologies. The possible reason may be the selectiveness of the medium adopters when using technologies effectively. Adoption alone is enough, but selecting the most effective and timely application of the technologies is vital. For that reason, medium adopters outperform high adopters, seeing greater yield gains. Prioritise integrated approaches (e.g., resistant seeds + Aflasafe GAPs proper drying) to achieve >95% control, with subsidies for smallholder groundnut farmers. Low adopters were worse off, emphasising the need for optimal uptake to improve outcomes. The study recommends that target extension services delivery, strengthening cooperative groups, reducing the cost of the technologies, and social network programs should be prioritised. This will guide interventions aimed at improving groundnut production and boosting smallholder livelihood in Elgeyo Marakwet and Baringo counties, Kenya.
Evaluation of quality properties of eggless mayonnaise analogue prepared from chia mucilage (salvia hispanica ˆ l.) with added gum arabic from acacia senegal var. kerensis
(Egerton University, 2025-09) Odep, Apondi Lydia
Eggless low fat mayonnaise was prepared by substituting portion of the oil with gum Arabic and chia mucilage and the result of their inclusion on the physico-chemical, sensory and shelf life properties was evaluated and equated to control with 75% oil and egg yolk. Physico-chemical properties were analyzes using AOAC methods, both consumer acceptability test and quantitative descriptive analysis were done for sensory evaluation. Peroxide value was used as a spoilage indicator for shelf-life evaluation. Gum Arabic (GA) from Acacia Senegal var kerensis has been approved as an emulsifier and stabilizer in food processing industry associated with higher lipoprotein content and high-water solubility. Chia mucilage on the other hand has been approved to be incorporated as an egg yolk and fat mimetics as it is dense in polysaccharides. In this study, eggless fat reduced mayonnaise analogue was innovatively prepared using chia seeds mucilage and gum Arabic from Acacia senegal var. kerensis. Chia mucilage was used at 15, 30, 45, and 60% levels to partially replace sunflower oil and substitute the egg yolk in the mayonnaise. The findings showed that all fat-reduced eggless mayonnaises had a greater water content of 0.74 but a much lower calorie content of 493 kcal/100g and 20% fat content. The control had 0.39 moisture, 77% fat, and 784 kcal/100g of calories. These variations grew as the amount of chia mucilage substituted increased, affecting protein, pH, and carbohydrates. The amount of ash in RFM and the control did not differ significantly. The results of the sensory evaluation showed that using gum Arabic and chia seed mucilage in place of mayonnaise was acceptable. Overall acceptability showed a positive link with all the measures, with flavor showing the largest correlation (r=0.78). Principal component analysis (PCA) loadings of 16 mayonnaise sensory qualities revealed that the first six principal components accounted for almost 66% of the variances in sensory characteristics. With regards to texture, RFM had desirable texture in terms of firmness, adhesiveness and viscosity. The microbial counts of all samples tested were in the acceptable limits for example the total viable count<50, yeast and molds <15 while salmonella and coliforms were not detected thus rendered safe before organoleptic evaluation. The shelf life (SL) of the samples reduced with increasing temperatures and time ranging 45 to 52 days. The formulated mayonnaise analogue had lower peroxide value (PV) ranging 0.2-11.8 than control with PV 0.5-12.6 thus longer SL. This is the first time an eggless fat-reduced mayonnaise analogue prepared using chia seed and gum Arabic from Acacia senegal var. kerensis has been informed.
Factors influencing use and extent of use of storage systems among smallholder rice farmers” in Kyela District, Tanzania
(Egerton University, 2025-08) Ikupa ,Partson Mwanjabala
Rice is the second staple food and cash crop produced in Tanzania after maize, it contributed to national economic growth, food security and source of employment for millions of populations. However, smallholder farmers lack knowledge of the proper postharvest management; thus, they become unaware and unknowledgeable decisions on the storage technique to use and as a result a lot of their produce are wasted. Therefore, assessment of factors influencing use and extent of use of crop storage system in Kyela district is needed. The specific objectives of this study are: to characterise the smallholder rice farmers based on the storage systems they use, to determine the factors that influence the use of storage systems in Kyela district, and to determine the factors that influence the extent of storage of rice among the smallholder rice farmers in the Kyela district. A survey of a sample of 267 smallholder rice farmer in Kyela district from three wards of Katumba songwe, Makwale, and Mwaya was conducted using semi-structured questionnaire. Descriptive and inferential statistics analysis (i.e., the double hurdle model and Logit model) were conducted using STATA software. Descriptive statistics indicated that users of the storage system had higher on-farm income, more education, participate more in group membership, had more access to extension service, training and credit than non-users. The Double Hurdle Model (DHM) revealed that the male household head, household size, access to training, access to agricultural extension services, and on-farm income were found to have a positive and significant effect on smallholder farmers’ use of a storage system. In addition, the extent of smallholder farmers' use of storage systems was positively influenced by male household head, access to training, access to agricultural extension services and on-farm income, while negatively influenced by farm size. Finally, the Logit model revealed that the choice of storage system type was significantly and positively influenced by age, marital status (married), access to training, and quantity of rice harvested, while household size, total storage cost, and on-farm income had a negative influence. This study recommends that smallholder farmers need training on how to use storage systems effectively because rice farming predominates in the research area. Also, more effort should be directed to promoting post-harvest storage systems at various levels (home, community, and national), through agricultural extension services by private/international institutions, and government
Effects of Agroecological Vegetable Cropping Systems on Smallholder Farmers’ Performance in Kiambu and Murang’a Counties, Kenya
(Egerton University, 2025) Essy Chemutai Kirui
Brassica and Traditional African Vegetable (TAV) farming is a source of employment opportunities and income for smallholder farmers in Kenya. However, the production of these vegetables is hindered by various challenges which lead to lower incomes for the smallholder farmers. Agroecological cropping systems present solutions to these production problems, but there is insufficient evidence of their economic advantages. This study, therefore, sought to determine the effect of agroecological vegetable cropping systems on the performance (net income and technical efficiency) of smallholder farmers in Kiambu and Murang’a counties. The specific objectives were to characterize smallholder farmers implementing agroecological vegetable cropping systems; to determine the factors that influence the adoption of agroecological vegetable cropping systems; and to assess the effect of agroecological vegetable cropping systems on the performance of smallholder farmers in Kiambu and Murang’a counties. Multistage purposive sampling was carried out to collect data from 546 households using standardized, semi-structured questionnaires. Descriptive statistics were used to characterize the smallholder farmers. Multivariate probit model was used to assess the factors that influence adoption of agroecological cropping systems. The multinomial endogenous switching regression model was used to assess the effect of adoption on smallholder farmers’ performance. Study results indicated that most of the smallholder farmers (78%) had adopted crop rotation but the rate of adoption for other cropping systems was low. The findings indicated that the gender and occupation of the household head, gender of the plot owner and manager, gross income from vegetable production, number of trainings attended, availability of market information, income from non-vegetable farming activities, distance to input and output markets, access to extension services and the location of the farm were the major factors influencing adoption. Additionally, adopting crop rotation alone significantly (p<0.05) led to a decrease in smallholder farmers' net incomes, whereas adopting multiple cropping alone led to a significant (p<0.05) increase in the farmers’ net incomes. Regarding technical efficiencies crop rotation alone was associated with a negative and significant (p<0.01) effect, whereas adopting both multiple cropping alone and the combination of multiple cropping and crop rotation contribute significantly and positively to farmers' technical efficiencies at (p<0.01) and (p<0.1) respectively. The study recommended that policies and programs aimed at promoting the adoption of agroecological cropping systems that boost farmers’ net incomes and technical efficiencies should be developed.
Effects of Climate Variability Adaptation Strategies on Kenyan Agro-Pastoralists’ Resilience and Food Security: a Case of Laikipia West Sub-County
(Egerton University, 2025) Cyrille Samson Awuonda
Climate variability is a global phenomenon that negatively affects agricultural production. Kenya is one of the countries with livelihoods, particularly in arid and semi-arid areas, that depend on natural resources sensitive to climate variability. ASAL agro-pastoralists are constantly engaging in adaptation strategies whose effectiveness relies on the extent of adoption to mitigate the negative impacts of climate variability. Generally, the study aimed to contribute towards improved livelihood through enhancing agro-pastoralism adaptation strategies to climate variability in Laikipia West sub-county, Kenya. Specifically, identifying and characterizing dominant adaptation strategies used by agro-pastoralists, analyzing socio-economic and institutional factors influencing the number and choice of adaptation strategies adopted, examining the effects of adaptation strategy packages on resilience to climate variability, and lastly, determining the effects of adaptation strategy combinations on food security. Data from 308 households were analyzed through Factor Analysis, Poisson Regression, Multivariate Probit, Principal Component Analysis, Instrumental Variable Regression, and a generalized ordered probit model using Stata and the R program. Exploratory factor analysis results indicated that seven packages explained 57.4 of % variation in the data. Household dependency ratio, education level, gender of the household head, group memberships, and household wealth positively influenced the intensity of the package used. In contrast, age, interaction between gender and farming experience, years of education, and unmet credit needs negatively affected package use. The marginal effect of Multivariate probit revealed mixed effects of the dependency ratio, education, and distance to extension agents. Group memberships, lack of credit demand, and wealth index for households positively influenced the choice. In contrast, age, gender, farm size, and livestock holdings had negative impacts. Farm risk reduction practices, diversification practices, adult equivalent household size, years of education of the household head, and access to agro weather information were associated with higher resilience. Consumption equivalent household size, farming experience of household head, household education stock, tropical livestock unit, access to agroweather information, and a combination of risk reduction, cultural farm, and sustainable agricultural practices were associated with a higher food security score. The study recommends that interventions intended to manage agroweather shocks in ASAL should account for improved resilience and food security. There is a need for future studies to analyze the role of quality education when integrated with indigenous knowledge on adaptation.
Effectiveness of Selected Quasi-Public Extension Services and Field Practices in Reducing Post-harvest Sugarcane Loss among Small holder Farmers in Awendo Sub-County, Kenya
(Egerton University, 2025) Collince Otieno Sagege
Farmers globally experience post-harvest sugarcane losses that reduces their income. Sony Sugar Company in Kenya instituted field practices in 2011 to reduce this post-harvest loss. Such practices included trailer loading limit and proper gleaning. Farmers are trained on gleaning and sensitised to supervise sugarcane loading. However, a gap exists on effectiveness of these selected field practices and quasi-public extension services. As a result, this study sought to examine effectiveness of the selected quasi-public extension services and field practices in reducing post-harvest sugarcane loss among smallholder farmers in Awendo Sub-County. This study employed a descriptive survey design, guided by the Theory of Change. Target and accessible populations were 3,123 and 2,403 contracted smallholder farmers respectively distributed proportionately across the four wards, namely; North-East, Central, South and West Sakwa. Additionally, all other 67 accessible stakeholders responsible for sugarcane harvesting and transport were purposively included. Supervisors checked the questionnaires for face and content validity. The questionnaire was pilot tested using 30 smallholder farmers from Suna East Sub-County. Data was collected using valid and reliable questionnaires. Cronbach’s Alpha reliability coefficients of 0.749 and 0.711 for smallholder farmers’ and other stakeholders’ questionnaires were established. Only 132 smallholder farmers’ questionnaires were valid giving 89.8% response rate. Descriptive statistics and spearman’s correlation were used to analyse data using SPSS version 21. Post-harvest sugarcane loss had positive relationships with training farmers on sugarcane gleaning (r (130) = .142, p > .05.), sugarcane gleaning during loading (r (130) = .199, p < .05.) and trailer loading limit (r (130) = .129, p > .05.) Sensitisation of farmers on supervision of cane loading had statistically insignificant relationship, r (130) = -.027, p > .05. with post-harvest sugarcane loss. Thus, while training farmers on sugarcane gleaning did not effectively reduce post-harvest sugarcane loss, sensitisation of farmers on supervision of sugarcane loading, gleaning during loading and trailer loading limit effectively reduced post-harvest loss. This study recommends that Sony Sugar Company should enhance its quasi-public extension service of training of farmers on sugarcane gleaning during loading to prevent spillage. Farmers or their agents should be present during loading, glean the sugarcane being scattered by grabbers despite the myriad challenges as benefits outweigh the challenges. Sony Sugar Company through her field staff should ensure trailer load limit is maintained to reduce post-harvest sugarcane loss.
Factors influencing the rise in insecurity in gudele payam in juba, south sudan
(Egerton University, 2015-08) Manut John ,Wol Deng
This study investigated the factors influencing the rise of insecurity in Gudele Payam Juba City, South Sudan. Gudele Payam has experienced increasing crime levels, threatening residents’ safety and social stability, yet prior research on South Sudan’s security lacks specific analysis of localized drivers, particularly economic and socio-cultural factors in this post-conflict, peri-urban context. This study sought to identify and map insecurity incidents, examine the economic and socio-cultural factors driving their increase, and evaluate residents’ coping mechanisms in Gudele Payam amid rising threats. The study was Conducted in Gudele Payam’s quarter councils selected for their size, mix of formal and informal structures, and high insecurity rates. The research was guided by the broken windows theory, viewing the environment as key to social cohesion and control. Stratified random and purposive sampling selected articipants, with data collected via interviews due to low literacy levels. Quantitative data were processed using the Statistical Package for Social Sciences (SPSS) software to generate descriptive statistics, including frequency tables illustrating factors driving insecurity. Findings showed Gudele Payam faced high incidents of theft (55%), robbery (52%), assault (43%), and drug-related insecurities (38%), with hotspots mapped in dense, poorly lit areas. Economic factors like unemployment (72%), poverty (68%), and informal markets (61%) significantly contributed to insecurity. Socio-cultural factors, including breakdown of traditional values (59%), influx of non-natives (53%), and weak community cohesion (47%), also fueled the rise. Coping mechanisms included vigilante groups (41%) and eligious/traditional authorities (32%), though 27% felt helpless. Conclusions are: (1) varied insecurity types and hotspots demand targeted policing; (2) economic hardship drives crime, needing job creation; (3) socio-cultural fragmentation worsens insecurity, requiring cohesion efforts; and (4) limited coping strategies highlight the need for enhanced security support. The study provided a comprehensive understanding of insecurity factors in Gudele Payam, informing targeted strategies to reduce it and enhance safety. Recommendations included community-based prevention programs, economic opportunities, strengthened social cohesion, and improved local security capacity, contributing to residents’ well-being
Uptake and Effects of Climate Smart Aquacultural Practices in Productivity among Smallholder Fish Farmers in Kakamega County, Kenya
(Egerton University, 2025) Boke Christopher Magesi
Climate change and its negative impacts on livelihoods and ecosystems are a major global concern. The aquaculture segment has also been disfranchised due to climatic variabilities, posing a risk to its sustainability in light of increasing population demands. To tackle this, climate smart aquaculture strategies have been escalated for acceptance and implementation by aquafarmers. Nevertheless, it is unknown whether fish farmers prefer these practices, and little is known about their contribution to productivity. This study aimed to determine fish farmers' preferences for climate smart aquaculture practices, determine the socio-economic and institutional drivers of choice of climate smart aquacultural practices, and determine how these practices affect productivity among farmers in Kakamega county, Kenya. Through multistage sampling approach, 220 fish farmers were selected with data collected applying semi-structured questionnaires. A best worst scaling technique served to identify preferences for CSA interventions. In relation to the factors influencing the choice of CSA practices, the study adopted a multivariate probit model, and the effects of climate smart aquaculture practices on productivity were determined using a multinomial endogenous switching regression. The results posited that most fish farmers highly preferred the use of solar power, water reuse, and water harvesting climate smart aquaculture goals, while the use of wind power, dam liners, and improved feeds were the least preferred. On the second objective age of the respondent, level of education, gender, farmers' experience, household size, land size, extension services, and training pointedly influenced the uptake of climate smart aquaculture practices. Finally, the results demonstrated high productivity among farmers who used CSA practices in combinations (Da_Ta_St at 3665.96 Kgs/Ha) as compared to the single application of these practices (Adjusted stocking 489.99 and Dam lines at 196.63). In conclusion, the uptake of climate smart aquaculture strategies by fish farmers significantly contributed to an upsurge in productivity. The study recommends policies that prioritize the preferences of aqua farmers in the development of climate smart aquaculture interventions, the revitalization of the aquaculture sector through enhanced access to extension and knowledge diffusion aimed at promoting the uptake of these innovations. The findings of this study contribute to the current body of literature on climate-smart aquaculture and will inform policy formulation and the development of strategies intended to promote aquatic farming.
Factors Influencing Nutritional Awareness, Perceptions and Consumption of Rabbit Meat among Households in Njoro Sub County, Kenya
(Egerton University, 2025) Muchira Anthony Munene
Globally, the livestock sector is undergoing a transformation driven by rapid urbanization, population growth and increasing incomes. This has led to the rising demand for sustainable and healthy protein sources. Rabbit meat has been highlighted as a nutritious food option. Its high protein, low cholesterol, and rich mineral content, makes it a potential alternative to conventional meats such as beef, pork, and poultry. Despite its advantages, consumption remains low in Kenya due to limited nutritional awareness, negative consumer perceptions and other socioeconomic and demographic factors. The specific objectives of this study were to identify factors influencing nutritional awareness, perceptions of rabbit meat and determine factors influencing consumption of rabbit meat among households in Njoro Sub-County, Kenya. Data from 186 households in three wards (Njoro, Kihingo, and Mauche) were collected using face-to-face interviews. A multistage approach consisting of purposive, simple and systematic random sampling methods was used to select households. Multivariate probit regression, ordered probit regression analysis and the double hurdle model were employed for analysis using SPSS 16 and STATA 27 software. The results of the study indicated that education, marital status, occupation, and age significantly influence households’ nutritional awareness of rabbit meat. Households perceived rabbit meat favorably regarding taste, smell, nutrition, and preparation time, but noted concerns about its affordability and accessibility. Age, education, awareness, income, and location significantly influenced overall perceptions of rabbit meat. Factors that influenced initial decision by households for rabbit meat consumption were awareness on nutritional value, age, education level, knowing a rabbit keeper, distance to market and taste. Age, household size, distance to market, affordability and location significantly influenced the consumption per capita of rabbit meat by households. The study concluded that rabbit meat was perceived positively for its taste, nutrition and ease of preparation while its consumption was constrained mainly by affordability and accessibility. To boost rabbit meat consumption, the study recommends awareness campaigns with a focus on younger individuals. Regional disparities on rabbit meat perception call for location-specific outreach, while improved distribution networks and pricing incentives can enhance accessibility and affordability. Further research should explore how sensory attributes and preparation methods influence acceptance across demographic groups.
Economic valuation of the environmental management of prosopis juliflora (mathenge) in Baringo South Sub-County, Kenya
(Egerton University, 2025) Loveness Gloria Phiri
Prosopisj uliflora is an invasive tree species that has caused signiﬁcant impacts across arid and semi-arid regions across Kenya, including Baringo South Sub-County. Initially introduced as a measure to combat desertiﬁcation, the tree has spread profoundly, contributing to biodiversity loss and undermining agro-pastoral livelihoods. As a result, utilization-based management interventions have emerged as a means to mitigate its adverse effects while simultaneously offering income-generating opportunities to the affected con-rmimities. This study sought to assess the economic value of its management in Baringo South Sub-County. Speciﬁcally, it aimed to characterize management interventions, identify socio-economic and institutional factors inﬂuencing adoption intensity, and assess their net economic beneﬁts. A cross-sectional research design was used, combining data from 270 randomly selected households, 10 key informants, and 2 focus group discussions. Quantitative data was analysed using descriptive statistics, a generalized Poisson regression model, and probabilistic cost-beneﬁt analysis through Monte Carlo simulations with 10,000 iterations. Qualitative data underwent thematic analysis. From the results, charcoal (84.85%) and ﬁrewood (47.73%) production were the most widely implemented strategies of managing Prosopis juliflora. Adoption intensity was signiﬁcantly associated with factors such as landholding size and proximity to markets (both positively correlated at p < 0.01). All interventions demonstrated a beneﬁt-cost ratio (BCR) greater than 1, indicating proﬁtability under uncertainty. Livestock feed processing (BCR = 7.49), charcoal production (BCR = 4.97), land reclamation (BCR = 4.55), and biochar production (BCR = 3.37) emerged as the most economically viable options. In conclusion, utilization-based management of P|'OSOpiS juliflora enhances rural livelihoods while contributing to ecological restoration. These findings offer policy-relevant insights for developing integrated strategies that balance economic use with sustainable environmental management of Prosopi sj ulifl ora in Kenya’s dryland regions. They also align with the Baringo County Integrated Development Plan (2023-2027), Kenya’s Vision 2030, and the Sustainable Development Goals

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