Browsing by Author "Siele Joseah"

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    Influence of innovation platform-based capacity building on farm-level milk losses among smallholder dairy farmers in Mogotio Sub-County, Baringo County, Kenya
    (Egerton University, 2025) Siele Joseah
    Smallholder farmers constitute 80 percent of dairy producers and 56 percent of the milk production in Kenya. The income generated from milk for many smallholder farmers is their only income. Furthermore, many farmers experience significant farin-level losses of milk, which negatively impacts their income. Decreasing farm-level milk loss through the use of an interactive innovation platform is important in increasing the income of smallholder dairy farmers and actors along the dairy milk value chain. This study aimed to help decrease fann- level milk loss through an innovation capacity development and platforin-based approach of smallholder dairy farmers in the Mogotio Sub-County of Baringo County. A mixed-methods research design was employed. The target population was 2500 smallholder dairy farmers, and the accessible population was 840 members of the Mogotio Dairy Cooling Plan. A sample of 120 fanners was selected from a baseline survey, and probability sampling was employed to select the sample of farmers. Capacity building was rendered to dairy fanners by the researcher and KALRO staff in 8 weeks. At the end of the project, 120 farmers were sampled in an end-of-project survey to measure the effect of the capacity-building intervention. Thirty of the farmers selected were purposefully sampled for focus group discussions. Data were collected from smallholder dairy farmers via a questionnaire and focus group discussion guides. Stakeholder data were collected via a key infonnant study guide. To maintain reliability, instruments were piloted at Marigat Ward. The Cronbach’s alpha coefficient was used to measure the reliability of the data; a reliability of 0.781 was found, which is above the acceptable limit of 0.7. SPSS and NVivo were used for data analysis. For study hypothesis testing, bivariate statistics were used; Pearson chi-square and t- test Were conducted at the ct = 0.05 level of significance. Descriptive statistics used measures of central tendency, dispersion, and proportions analysis. The study surfaced high levels of farm-level loss of milk, low levels of milk production, and high spillage, spoilage, and contamination of milk for smallholder dairy fanners in Mogotio Sub-County. The capacity- building intervention positively affected the reduction in farm-level loss of milk for smallholder dairy farmers in Mogotio Sub-County. The use of the platform provided farm- level handling practice innovation for smallholder dairy farmers. The intervention also added to the traditional government extension service with changes in their agricultural extension services. Based on this study, I recommend that the Ministry of Agriculture and Livestock Development help with the advocacy to integrate innovation platforms, digital platforms, smallholder dairy farmers, and dairy value chain actors into the traditional extension
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    Influence of innovation platform-based capacity building on farm-level milk losses among smallholder dairy farmers in Mogotio Sub-county, baringo county, kenya
    (Egerton University, 2025-08) Siele Joseah
    Smallholder farmers constitute 80 percent of dairy producers and 56 percent of the milk production in Kenya. The income generated from milk for many smallholder farmers is their only income. Furthermore, many farmers experience significant farm-level losses of milk, which negatively impacts their income. Decreasing farm-level milk loss through the use of an interactive innovation platform is important in increasing the income of smallholder dairy farmers and actors along the dairy milk value chain. This study aimed to help decrease farm-level milk loss through an innovation capacity development and platform-based approach of smallholder dairy farmers in the Mogotio Sub-County of Baringo County. A mixed-methods research design was employed. The target population was 2500 smallholder dairy farmers, and the accessible population was 840 members of the Mogotio Dairy Cooling Plan. A sample of 120 farmers was selected from a baseline survey, and probability sampling was employed to select the sample of farmers. Capacity building was rendered to dairy farmers by the researcher and KALRO staff in 8 weeks. At the end of the project, 120 farmers were sampled in an end-of-project survey to measure the effect of the capacity-building intervention. Thirty of the farmers selected were purposefully sampled for focus group discussions. Data were collected from smallholder dairy farmers via a questionnaire and focus group discussion guides. Stakeholder data were collected via a key informant study guide. To maintain reliability, instruments were piloted at Marigat Ward. The Cronbach‘s alpha coefficient was used to measure the reliability of the data; a reliability of 0.781 was found, which is above the acceptable limit of 0.7. SPSS and NVivo were used for data analysis. For study hypothesis testing, bivariate statistics were used; Pearson chi-square and t-test were conducted at the α = 0.05 level of significance. Descriptive statistics used measures of central tendency, dispersion, and proportions analysis. The study surfaced high levels of farm-level loss of milk, low levels of milk production, and high spillage, spoilage, and contamination of milk for smallholder dairy farmers in Mogotio Sub-County. The capacity-building intervention positively affected the reduction in farm-level loss of milk for smallholder dairy farmers in Mogotio Sub-County. The use of the platform provided farm-level handling practice innovation for smallholder dairy farmers. The intervention also added to the traditional government extension service with changes in their agricultural extension services. Based on this study, I recommend that the Ministry of Agriculture and Livestock Development help with the advocacy to integrate innovation platforms, digital platforms, smallholder dairy farmers, and dairy value chain actors into the traditional extension.