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dc.contributor.authorMurage, Francis M.
dc.date.accessioned2019-09-26T13:07:00Z
dc.date.available2019-09-26T13:07:00Z
dc.date.issued2019-08
dc.identifier.citationMasters Thesis 2019en_US
dc.identifier.urihttp://repository.embuni.ac.ke/handle/embuni/2195
dc.descriptionA Thesis Submitted in Partial Fulfillment for the Award of the Degree of Master of Science in Agricultural Resource Management in the University Of Embuen_US
dc.description.abstractCurrent demand for soybean in Kenya is higher than production. The deficit which is over 95% is filled through importation from neighboring countries. Despite the high demand, adoption and production is low (0.56 to 1.1 t ha-1) against potential yield of 3.0 – 3.6 t ha-1. The low production is associated with low use of fertilizers. Farmers are using mineral fertilizers below recommended rates and they are not using organic fertilizers despite them being readily available. The objectives of the study was therefore to determine the effect of applying organic and inorganic fertilizers singly or in combination on grain yield of soybean, compare economics of soybean under organic and inorganic fertilizers and to determine factors influencing adoption of soybean by smallholder farmers in the central Highlands of Kenya. To achieve these objectives, on-farm experiments were set in Embu County and a survey was carried out in Embu, Meru and Tharaka Nithi Counties. The experiments had six treatments; (tithonia, tithonia plus fertilizer, fertilizer plus manure, fertilizer, manure and a control) arranged in Randomized Complete Block Design (RCBD). The plot sizes measured 6 m × 4.5 m and the main data collected was yield and labour. In the survey, the sample size was 210 farmers. Net benefits, benefit cost ratio and return to labor were used as the economic tools in data analysis. All biophysical data was subjected to analysis of variance (ANOVA). To determine factors influencing adoption of soybean, data was subjected to Cross-tabulation for categorical variables to test for association using Pearson chi-square statistic, the data was also subjected to a binary logistic regression model to predict the factors affecting adoption of soybean in the central highlands of Kenya. Results showed that there was a significant difference in soybean yield among treatments in LR 2016 and SR 2016, (P= <0.0001) and (P= <0.0033) respectively. A combination of manure plus fertilizer and tithonia plus fertilizer recorded a significant higher soybean yield than the control in both seasons. Manure plus fertilizer recorded a significantly higher net benefit and return to labour than the control in both seasons and it is the only treatment that recorded a return to labour of greater than 2.0, which is the minimum acceptable for smallholder farming activities. Out of 210 households interviewed, 41% were adopters while 59% were non-adopters. Total farm size, membership of a farmer group and attendance of training on soybean positively influenced adoption of soybean while age of household head negatively influenced adoption of soybean. The implication of these results is that farmers should be integrating organic and inorganic fertilizer in soybean farming in Embu County. Integration of manure and fertilizer should be advocated for in order to realize maximum economic benefits from soybean farming. Further, the adoption of soybean in the central Highlands of Kenya can be enhanced by targeting young household heads, household heads with bigger farm sizes, encouraging farmers to join farmer groups and increasing trainings on soybean. These findings provide a guide to the extension agents in the Ministry of Agriculture, Livestock and Fisheries (MoALF) in Embu, Meru and Tharaka Nithi Counties. This will help them in designing training manuals for farmers in regard to soybean production and increasing adoption of the crop in these Counties.en_US
dc.language.isoenen_US
dc.publisherUniversity of Embuen_US
dc.titleEnhancing Soybean Production, Economics and adoption among Smallholder Farmers in the Central Highlands of Kenyaen_US
dc.typeThesisen_US


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