Agribusiness

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    ANALYSIS OF FACTORS INFLUENCING MICROFINANCE CREDIT UPTAKE AMONG SMALLHOLDER DAIRY CATTLE FARMERS IN MAARA SUB-COUNTY, THARAKA NITHI COUNTY, KENYA
    (Chuka University, 2023-10) KAVIKU AGNES MUTINDA
    Microfinance institutions are essential in improving smallholder farmers’ production and productivity by providing financial resources. Despite the benefits of microfinance credit on production, its uptake in the Maara sub-county remains low compared to potential output. Several factors have been shown to contribute to low microfinance credit uptake, including inadequate financial literacy, lack of collateral, high transaction costs, and inadequate infrastructure. However, these factors may vary from region to region. Therefore, there is a need to continuously study the factors that affect microfinance credit uptake to develop dynamic policies for sustainable agricultural productivity. The study aimed to analyse the effect of institutional factors, farmer and farm characteristics, the influence of perceptions and attitudes, and the effect of milk yield on microfinance credit uptake among smallholder dairy farmers in the Maara Sub-County. The study employed a descriptive research design and utilized a sample of 315 smallholder dairy cattle farmers, selected through cluster sampling from a target population of 1,500. The study applied the theory of diffusion of innovation. A semi-structured questionnaire was used to collect data on institutional factors, farm and farmers’ characteristics, milk yield, and farmers’ perceptions and attitudes. The analysis of the data was conducted utilizing Stata version 17. A probit model was used to determine how farm and farmers’ characteristics, institutional factors, and milk yield affect microfinance credit uptake. A Principal Component Analysis was used to analyse the effects of farmers’ perceptions and attitudes on microfinance credit uptake. Group membership, collateral availability, and the number of dairy cattle all had a positive and significant (p = 0.000) effect on microfinance credit uptake. Collateral availability had the highest effect implying that one unit increase in the smallholder dairy cattle farmers' collateral increases the uptake of microfinance credit by 45.23%. The positive effect may imply that the collateral can be liquidated in case of default. At the same time, the number of dairy cattle had the lowest effect implying that an increase in the number of dairy cattle by one unit increases the uptake of microfinance credit by 11.19%. The results of this study also showed that years of schooling had a negative and significant (p =0.000) effect on credit uptake. The negative effect implies that an increase in one unit of schooling years decreases the uptake of microfinance credit by 1.57%. This implies that more educated smallholder dairy cattle farmers have a higher level of awareness regarding the costs associated with credit uptake such as interest rates, thus lowering their borrowing. However, the gender of the decision maker, age, land size, household size, the area under dairy cattle, and the milk yield per cow per day did not significantly (p > 0.05) affect the uptake of microfinance credit by smallholder dairy cattle farmers. The Principal Component Analysis model results showed that smallholder dairy cattle farmers negative experience had the highest factor loading (38.88%), while farmers' mistrust of the microfinance credit provider had (17.07%) loading factor on the uptake of microfinance credit. Therefore, the study concluded that group membership, collateral availability, and the number of dairy cattle play a vital role in positively influencing credit uptake. On the other hand, the negative effect of years of schooling underscores the importance of implementing targeted financial literacy programs to empower farmers with the necessary knowledge and bridge the credit uptake gap. The study further recommended that formulating policies geared toward enhancing the educational attainment of farmers would be vital in enhancing credit uptake to farmers in the study area. To promote sustainable agricultural productivity, targeted financial literacy programs must address farmers' challenges. Encouraging participation in farmer groups will enhance credit access.
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    Analysis of Technical Efficiency on Orange Fleshed Sweet Potatoes Production Among the Smallholder Farmers in Migori County Kenya
    (science pc, 2024-02-09) Lawrence Otieno Jabuya1, * , Shelmith Wanja Munyiri2 , Martin Kagiki Njogu2
    Sweet potatoes (Ipomea batatas L.), particularly the orange fleshed variety, have become increasingly popular due to their ability to thrive in various environmental conditions with minimal inputs. Orange fleshed sweet potatoes (OFSPs) show potential for productivity, yet smallholder farmers in Kenya still struggle to maximize their yields. The factors influencing OFSP production efficiency among these farmers in Western Kenya have not been thoroughly examined. This study evaluated the technical efficiency of OFSP production among smallholder farmers in Migori County. Using a descriptive research design, a sample of 225 OFSP farmers was randomly selected by a cluster sampling technique. Data was collected through a structured questionnaire on inputs and selected socio-economic factors. The data was analyzed using the frontier stochastic model in STATA. Smallholder farmers estimated mean technical efficiency was 77.82% significant variables were; size of the land, availability of planting vines, access to hired labour, gender of the household decision maker, farming experience, household size, land ownership status, participation in training programs and extension services, and proximity to markets, indicating a need to improve OFSP production by 22.18%. These findings suggest that to reduce inefficiencies among smallholder OFSP farmers, targeted training programs are needed to enhance farmers' agronomic knowledge specific to OFSP production. Further, policy interventions should prioritize the provision of extension services to support and improve the performance of OFSP smallholder farmers.
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    Ensemble approach for potential habitat mapping of invasive Prosopispp.inTurkana,Kenya
    (Wiley, 2018-03-03) TimNg,Wai,Cândidode ,Alexsandro ,Silva ,Oliveira , Rima,Purity,Atzberge, Clement , Immitzer,Markus
    Aim:Prosopisspp.areaninvasivealienplantspeciesnativetotheAmericasandwell adapted to thrive in arid environments. In Kenya, several remote‐sensing studies conclude that the genus is well established throughout the country and is rapidly in‐ vadingnewareas.ThisresearchaimstomodelthepotentialhabitatofProsopisspp. by using an ensemble model consisting of four species distribution models. Furthermore, environmental and expert knowledge‐based variables are assessed. Location:TurkanaCounty,Kenya.Methods:Wecollectedandassessedalargenumberofenvironmentalandexpertknowl‐ edge‐based variables through variable correlation, collinearity, and bias tests. The varia‐ bleswereusedforanensemblemodelconsistingoffourspeciesdistributionmodels:(a) logisticregression,(b)maximumentropy,(c)randomforest,and(d)Bayesiannetworks.The modelswereevaluatedthroughablockcross‐validationprovidingstatisticalmeasures. Results: The best predictors for Prosopis spp. habitat are distance from water and built‐upareas,soiltype,elevation,lithology,andtemperatureseasonality.Allspecies distributionmodelsachievedhighaccuracieswhiletheensemblemodelachievedthe highest scores. Highly and moderately suitable Prosopis spp. habitat covers 6% and 9% of the study area, respectively. Main conclusions: Both ensemble and individual models predict a high risk of continued invasion,confirminglocalobservationsandconceptions.Findingsarevaluabletostake‐ holdersformanaginginvadedarea,protectingareasatrisk,andtoraiseawareness.
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    Effect of Borrower's Socio-Economic Profile on Agribusiness Loans Default Rate in Agricultural Finance Corporation, Mount Kenya Region
    (Journal of Economics, Management and Trade, 2023-05-24) M’Muruku Salesio Miriti a* , Gathungu Geofrey Kingori b and Rael Nkatha Mwirigi c
    Background: Agribusiness loans advanced by Agricultural Finance Corporation (AFC) in Mount Kenya Region have high default rate of 20.33% which compares unfavourably with 10% benchmark for all types of loans in Kenya. This is a challenge, given the strategic importance of agribusiness credit in mainstreaming livelihoods to alleviate poverty by offering occupational and professional opportunities. This study aimed at analysing effect of borrower’s socio-economic profile on AFC loan default rate in agricultural finance corporation, Mount Kenya Region. Methods: According to AFC records Mount Kenya region represents a branch network of 11 branches and a population of 3,002 agribusiness borrowers. Using a descriptive research design a sample of 300 borrowers was drawn from a combined list through systematic random sampling technique with an interval of ten. Primary data on borrower’s socio-economic profile was collected using a structured questionnaire. The data was analysed using Statistical Packages for Social Sciences (SPSS V.27) and Stata version. Using regression analysis, the effect of independent and dependent variable to predict default rate was estimated. ANOVA was performed to get the Fstatistic so as to test for the adequacy of the regression model. The logit econometric model was used to specify the statistical relationship between the independent variable and AFC loan default. Results: Results of the study revealed that multiple borrowing and borrower-lender distance were significant at 5%. Farming experience, borrowing experience and off-farm income were significant at 10%, 5% and 1% levels of significance. Multiple borrowing and borrower-lender distance were found to have 5.5% and 0.8% associations with default rate, respectively. Conclusion: The findings show that to mitigate default, the borrower should avoid multiple borrowing and manage the friction of distance. The study is significant since it enlightens the credit stakeholders on collective efforts that are effective in addressing the problem of default. The study recommends government interventionist policy by facilitating uptake of agricultural insurance and subsidizing input costs. Borrowers are encouraged to embrace technology, team up as farming communities to look for markets and affordable inputs, adopt agricultural insurances and adhere to lending directives.
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    ANALYSIS OF SOCIO-ECONOMIC, PRODUCTION AND MARKETING FACTORS INFLUECING COMMON BEAN COMMERCIALIZATION AMONG SMALLHOLDER FARMERS IN CHEPALUNGU SUB-COUNTY, BOMET COUNTY, KENYA
    (Chuka University, 2023-10) LANGAT SHEILA CHEPKOECH
    Common beans (Phaseolus vulgaris L.) are important pulses for human nutrition for its edible seeds. Currently, the level of common bean production in Kenya is 0.67 t/ha. Common bean commercialization provides a pathway for improving productivity and food security. The current level of common bean commercialization is at 40% which is regarded low as farmers grow common beans as a subsistence crop which may not be economically sustainable. Subsistence farming is considered inefficient and may not be viable in ensuring food and income sufficiency in the long run. This study aimed at determining socio-economic, production and marketing factors influencing common bean commercialization in Chepalungu sub-county, Bomet County. The study adopted utility maximization theory and a descriptive research design. A cluster random sampling procedure was used to obtain a sample of 313 smallholder common bean farmers from a population of 1,440 common bean farmers. A semi-structured questionnaire was used to collect primary information on socio-economic characteristics (age, family size, level of education, gender and off-farm income), production factors (land, labor, inputs, capital), and marketing factors (marketing channels, distance to the market, market price, market information and marketing experience) influencing common bean commercialization among smallholder farmers. The collected data was analyzed using SPSS version 29 and STATA version 15 and econometric analysis was done using Stochastic frontier model, multiple regression model and Tobit model. Common bean productivity was measured using technical efficiency and the results from Stochastic frontier model indicated that the technical efficiency was 93.36%. These findings suggest that smallholder common bean farmers can increase current production by 6.64% by increasing their efficiency. Land under common beans, seeds and agrochemicals were significant at 1% and had a positive influence on the level of common bean productivity while family man days had a negative influence on the level of common bean production. The findings further show that distance to the market and farming experience increased technical inefficiencies by 0.68 and 0.24 units respectively. The level of common bean commercialization was 43.46 %. Multiple regression model shows that certified seeds and manure were significant at 1% while second generation seeds, planting fertilizer and hired labor were significant at 5% and positively influenced the level to common bean commercialization. Cropping systems negatively influenced common bean commercialization and was significant at 1% level. Tobit model shows that the quantity of common beans produced, marketing experience, distance to the market, farm gate marketing channel, land size and extension services positively affected common bean commercialization implying that a unit increase in these variables will lead to an increase in common bean commercialization while age and access to market information had significant negative effect at 1% and 5% respectively on commercialization implying that a unit increase in both variables will decrease level of common bean commercialization. The level of productivity was high (93.36%) showing that farmers are more efficient but the level of commercialization was low (43.46%), showing that majority of farmers do not participate in the market. Smallholder common bean farmers in Bomet County are advised to increase the land allotted to common beans, use certified seed and agrochemicals to increase productivity and commercialization. Policy makers are also encouraged to provide farmers with inputs and affordable farming credit so that farmers can afford improved seeds so as to increase common bean productivity which would in turn increase the level of commercialization.