Soil fertility decline continues to be a major challenge limiting agricultural productivity globally. Despite the novelty of organic-based technologies in enhancing agricultural production in Kenya's central highlands, adoption is low. Therefore, we carried out a cross-sectional household survey of 300 randomly selected smallholder farmers to determine the specific organic-based practices by farmers; and the socioeconomic factors that influence the adoption intensity of selected organic-based technologies. We used descriptive statistics to summarize the data and the Tobit regression model to evaluate the socioeconomic determinants of adoption intensity of selected organic-based technologies. We identified nine organic-based technologies that had different adoption rates among the farmers. The majority of the farmers had adopted manure (97%) and manure combined with fertilizer (92%) in Murang'a and Tharaka-Nithi, respectively. Manure was applied to the largest land in Murang'a with 31% of the cultivated land. In comparison, manure combined with fertilizer had the highest adoption intensity in Tharaka-Nithi applied to about 25% of the cultivated land. Gender, age of the household head, level of education, household size, access to external labor, training, Tropical Livestock Unit, agriculture group membership, access to credit, land cultivated, and farming experience influenced the adoption intensity of organic-based technologies among smallholder farmers. Based on the smallholder farmers' adoption behavior, this study can be used to disaggregate the farming households better in order to tailor specific organic-based soil fertility technologies solutions that meet their unique needs. One group would be those households that face specific constraints, as reflected in their low adoption rates, women-headed households and older farmers, and thus require more targeted / intensive efforts to overcome these barriers. The other group would be those households that require less focus because, when confronted with the technologies, they are more likely to adopt them easily, for example, the male-headed households. Hence, the smallholder farmers' adoption behavior, can enable policymakers to form a base for designing appropriate policies that encourage the adoption of organic-based soil fertility technology by smallholder farmers.

Majority of the rural households in Kenya depend on agriculture as a source of food and livelihood. Agricultural productivity has been declining due to many factors resulting in increased food insecurity in the country. Consequently, there is a renewed interest in promoting drought-tolerant crops such as sorghum which thrives in the arid and semiarid lands of the developing world. However, performance of sorghum production among the smallholder farmers has still remained low. This study was thus carried out to identify factors that influence technical efficiency of sorghum production among smallholder farmers in Machakos and Makindu districts of the lower eastern Kenya. Collected data on farm and farmer characteristics were analysed by use of descriptive statistics and Tobit model. Result highlights show that technical efficiency was influenced positively by formal education level of the household, experience in sorghum farming, membership in farmers associations, use of hired labour, production advice, and use of manure. Surprisingly household size, meant to enhance labour, had a negative influence. To increase technical efficiency, efforts should focus on improving information flows on agronomic practices. Farmers should also be encouraged to form and actively participate in various farmers associations, which enhance learning and pooling of labour resources, hence improving technical efficiency.

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Indigenous chicken (IC) production is a source of food security and income among smallholder farmers within high potential areas and semi-arid lands (ASAL). The demand for IC eggs and meat is anticipated to increase threefold by the year 2020 by health conscious consumers. However, potential of IC to contribute to household incomes and poverty alleviation in ASAL is constrained by slow maturity of IC and low productivity. Hence, to address these constraints improved indigenous chicken (IIC) technologies have been developed and introduced to smallholders in high potential area and ASAL. However, only a few smallholder farmers have adopted the IIC technologies. Therefore the objective of this study was to determine the effect of farmer socioeconomic characteristics on adoption and intensity of adoption the IIC technology in Makueni and Kakamega counties. A total of 384 households were sampled using multi-stage sampling to collect data through interviews. The collected data was analyzed using a double hurdle model. The results suggest that sex of the household head, farm size, group membership, which had not been previously identified in IIC studies as a significant variable, distance to training centre, off-farm activities and IIC awareness significantly affected adoption decision of improved IC. On the other hand education of the household head, household size, farm size, source of information on IIC and awareness on IIC had significant effects on the level of adoption. The recommendations from this study have an implication on extension policy, land use policy, food policy, collective action and pricing policy in the context of technology adoption in Kenya.

Indigenous chickens are important in Kenya for food security, income generation, employment and improved livelihoods. However, despite these benefits producers are constrained from participating in the high value markets. A purposive multi-stage sampling was used to sample 130 households from Makueni County. The data were collected using a structured questionnaire, key informant interviews and focus group discussions. These data were then analysed using descriptive statistics and a probit econometric model. The decision to participate in the indigenous chicken high value market was influenced by the education level of the household head, processing, the age of the household head, group membership, the flock size and region. Therefore, it is recommended to form farmer groups for increased productivity, collective marketing and enhanced value addition.

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This paper discusses the economic potential in terms of income changes that may result from conversion to low-external-input agriculture (LEIA) organic farming in a Kenya's catchment area. A spreadsheet model applying the gross margin and net present value analysis was developed to estimate economic returns to labour and land of alternative smallholder cropping systems in the East Mau Catchment. The income and costs over a 10-year horizon associated with current cropping practices of a typical farm household cultivating 1.12 hectares of maize-bean intercrop, Irish potato, carrots, tomatoes, cabbages and kales mix were characterized based on field work conducted in 2008-2010. An ''average'' smallholder LEIA organic farm was simulated based on the conventional one, and its income discounted. A comparison was then made of the two farm types. Results indicate annual net present value returns to cropped land average Ksh 21,878/ha ($ 267/ha) and Kshs 22,561/ha (€ 275/ha) in 2010 values for conventional and prototype LEIA organic farming systems, respectively. Net returns are particularly sensitive to crop yields and price and cost of fertilizers and seeds. Further efforts should be made to provide an economic analysis of other LEIA organic farming practices such as composting, double digging and agroforestry in terms of additional labour costs resultant. The model can be extended to build more scenarios on the role of price premiums. Additionally, further research should be done to exploit the socio-demographic factors affecting the adoption of low-external-input systems.

This paper assesses the impact of access to agricultural credit on the agricultural productivity of 422 smallholder farmers that cultivate maize or rice in the Western and Eastern province of Rwanda. Stratified, simple random and convenience sampling techniques were used to sample districts, sectors, cells and households. Data were collected using structured interviews and analyzed using propensity score matching techniques. Results indicated that productivity was higher by 44% among the farmers who accessed credit implying that they harvested on average an extra 440 kilograms of maize or rice. According to a crop-specific analysis, agricultural credit access had a more significant impact on maize productivity, with a difference in proportion of 68% (p = 0.000) but had no impact on rice productivity (p = 0.149). The study concludes that agricultural credit was important for Rwanda’s agricultural productivity. Thus policy measures should aim at improving smallholder farmers’ access to agricultural credit and promoting the use of modern agricultural inputs, particularly among rice farmers in Rwanda