MST-Department of Agribusiness Management and Trade (AMT)

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Adoption Intensity, Perception and Profitability of Organic Based Soil Fertility Management Technologies in Murang’a and Tharaka-Nithi Counties, Kenya
(Kenyatta University, 2021) Mwaura, George Gacheru; Erick K. Bett; Jayne N. Mugwe; Felix K. Ngetich
There have been major efforts to introduce and promote organic based technologies among the smallholder farmers to address low and declining soil fertility. Despite these efforts, adoption of these organic based technologies has been dismal. This study aimed to; (1) determine the socio-economic factors that influence adoption intensity of organic based technologies for soil fertility management, (2) determine perceived benefits by farmers of using organic based technologies, and (3) determine the profitability of using organic based technologies for managing soil fertility. The study was carried out in two subcounties; Meru-South and Gatanga where these organic based technologies have been introduced and promoted previously. The study adopted a survey research design. A sample of 150 households selected randomly from each study area were interviewed. Tobit regression model was used to analyse the adoption intensity of organic based technologies. Nine organic based technologies were adopted. Socio-economic factors that influenced the adoption intensity in Murang’a were gender of the household (+), age (-), level of education (+), household size (+), access to external labour (+), training (+), total livestock unit (+), total land under cultivation (+), title deed ownership (+), agricultural group membership (+), household access to credit (+). In Tharaka-Nithi, the following were determinants of adoption intensity gender of the household (+), education level (+), size of the household (+), access to external labour (+), years of experience (+), training (+), total livestock unit (+), land under cultivation (+), title deed ownership (+), agricultural group membership (+), access to credit (+). The study further examined farmer perception. The perceptions were based on four variables; potential to improve soil fertility, potential to improve yields, profitability and labour requirements of organic based inputs. To analyse farmers’ perceptions, an ordered logit regression model was fitted into the data. Farmers’ perception results showed that majority of the respondents in Murang’a (115, 76.7%) and Tharaka-Nithi (104, 69.3%) strongly agreed that organic based technologies can improve yields. Factors that influenced perception were gender (-), household size (+), external labour (+), total livestock unit (+), group membership (+), training (+), land under cultivation (-), and credit access (+). Financial analysis of the maize enterprise was carried out using the gross margin analysis. Manure and manure+fertilizer was considered, while sole inorganic fertilizer was included in the analysis for comparison purposes. Gross margins showed that in Murang’a manure+fertilizer yielded 1962 Kgha-1, manure yielded 1820Kgha-1, and inorganic fertilizer recorded 1483 Kgha-1. In Tharaka-Nithi, manure +fertilizer yielded 1940 Kgha-1, manure yielded 1723 Kgha-1, inorganic fertilizer 1689 Kgha-1. Manure reported higher gross margins (44074) in Murang’a while manure+fertilizer showed higher gross margins (45625) in Tharaka-Nithi. This study recommends using organic-based inputs because they have been perceived to have the potential to increase crop yields and improve soil fertility. Also, the gross margins of sole manure and manure+fertilizer were higher than the gross margins of sole fertilizer.
Analysis of Cooking Fuel Demand Patterns among Rural Farm Households in Kiambu County, Kenya
(kenyatta University, 2020) Kago, Elizabeth Wangui; Kago Elizabeth Wangui; Gabriel Mwenjeri
Cooking fuel energy is an important element in the daily livelihood of households where majority depend on fuel wood which’s readily available for energy sources. However, these natural resources experience degradation occasioned by the growing population causing an imbalance in the demand and supply. Therefore, it has decreased fuel wood availability and accessibility thus fuel scarcity making it expensive to acquire which has led households to use alternative sources of fuel. For this reason, there’s a dilemma between meeting the growing demand for fuel energy and the sustainable utilization of the limited stock of natural resources. Due to a significance disruption of bio-diversity, it has led to many households depending on the market (prices) as their main source of fuel. More so, there’s use of multiple fuel which is influenced by income and other factors. Price volatility as well as income vulnerability significantly affect household consumption patterns. Hence, this study aimed at investigating the influence of household characteristics on energy demand, determining the impact of income changes on household energy demand patterns and identifying the energy demand patterns for fuel used by households to address the persistent problem of fuel insecurity. Guided by neoclassical demand of consumer behavior, Quadratic Almost Ideal Demand System (QUAIDS) was used for analysis. Data was collected from 200 respondents using systematic random sampling. Analysis was done using STATA version 13 to obtain descriptive statistics and the empirical results. The results indicated that firewood, charcoal and kerosene are necessary goods while LPG was a luxury. Expenditure elasticity for the fuels were positive implying that the fuels were normal goods and an increase in income will lead to higher consumption. The main determinants of energy demand were gender, education level and occupation of the household head as well as age and household size. It is recommended that government and other stakeholders formulate income oriented policies to augment household earnings which will increase their purchasing power. Furthermore, the government should enact policies to ensure LPG is affordable with a view to mitigate against environmental degradation. Additionally, capacity building by educating both the old and young by giving information on the negative impacts of using such fuel and the benefits derived when the public switch to modern fuels. Besides, strategies are needed to identify affordable, scalable and accessible efficient fuel-saving cooking practices to the local context.
Assessment of the Performance of Small-Scale Dairy Farming in Meru County, Kenya
(Kenyatta University, 2019-06) Kainda, Seberah
Despite the apparent importance of the dairy sub-sector to Kenya’s economy, the sector is plagued with low milk production. The general objective of the study was to assess dairy performance among the small-scale farmers in Meru County. The specific objectives were (i) to characterize small-scale dairy farmers; (ii) to assess the profitability of small-scale dairy enterprises; and (iii) to determine the factors influencing profitability among small-scale dairy farmers in Meru County. The research used cross-sectional design where 150 small-scale dairy farmers were selected from the subgroups using simple random sampling technique. Gross margin analysis was used to analyse profitability while multiple linear regression analysis using ordinary least square method was used to determine the factors influencing dairy profitability. The mean age of dairy farmers in Meru County was 45.7 years with 92% being men who are the household heads. 92% of the farmers had formal education and 68% had experience of more than 10 years. The average household size was 5 members. Only 29.3% of farmers had applied for a dairy enterprise development loan. Most of the farmers were members of groups and had attended dairy farming trainings. Dairy in Meru County was characterised by intensive farming technologies for instance zero grazing system. The average land size under dairy was 0.7 acres and the average herd size was 3 cows. Results also show that there is potential for increased small-scale dairy performance in Meru County. Dairy farming was profitable with farmers receiving an average gross margin of Ksh. 5,299 per cow per month. The model shows that herd size, education level and credit access have significant influence on dairy profitability. In view of the study findings the study recommends that the policy makers should take initiative in enacting laws aimed at lowering the cost of inputs thus reducing production costs. Secondly the study recommends that the government should prioritize investing in farming as a way of promoting employment to the population. The study also recommends use of alternative improved feed such as homemade dairy ration to reduce feed cost as one way of maximizing profits from small-scale dairy farming. Finally, the study recommends that policy intervention should be aimed at establishing breeding centers for dairy cows in order to enable farmers increase herd size, formulation of laws which can help farmers get access to loans in order to invest in dairy farming and transfer of knowledge through provision of extension services to educate farmers on dairy management.
Determinants and Profitability of Coffee Market Outlet Choice among Farmers in Murang’a County, Kenya
(Kenyatta University, 2021) Keru, Zacharia Ndungu; Bernard Njehia; Lucy Ngare
The coffee industry is a significantly important contributor to the Kenyan economy. Relatively, this is as a result of coffee farmers’ productivity which trickles down to their individual decisions at the farm and marketing level. When there are different outlets in the coffee market, farmers are expected to utilize the opportunities provided by selling through the most beneficial market outlet. Murang’a County has cooperatives, licensed millers, direct sale and informal traders as the existing marketing outlets. This study aimed at investigating the determinants that lead farmers to the choice of selling coffee through the different marketing outlets and the profits generated through their decisions. The specific objectives were: determining the marketing characteristics of the coffee farmers; analyzing the determinants of coffee market outlet preference and analyzing the farm profitability obtained from the choice of different market outlets. This study was based on the rational choice theory where the farmer weighs in on profit margins and factors that come into play during marketing before choosing an outlet based on the degree of happiness and satisfaction. Purposive sampling method was used in selecting 150 farmers from a sample population of 70,000 farmers. Sample sizes of 68(Kandara), 42(Gatanga) and 40(Kangema) were generated through proportional distribution of respondents. Descriptive statistics techniques such as pie-chart, tables, bar graphs, means and percentages were used in analyzing coffee marketing characteristics of farmers; The Multinomial Logistic Regression model using Stata v13 was used in analyzing the determinants of coffee market outlet choice; and Gross Margin was used in analyzing profitability of outlets. The study findings on marketing characteristics of coffee farmers shows that: Majority of farmers sold coffee in fresh cherry form, followed by dried beans, pulped beans and then clean beans; Sixty percent of farmers had more than twenty years of experience in coffee marketing; More than half of farmers sold quantities below 1 tonne; Sixty one percent of farmers sold coffee below the price of ksh.50 before the survey period; 23% of farmers owned coffee transportation equipment, 29% acquired credit from outlet, 52% were updated with coffee marketing information; Cooperative societies were the most selected followed by Millers, multiple outlets, informal traders and direct sale; Cooperative societies were selected by 72% of members and 20% of non-members, millers by 4% of members and 50% of non-members, informal traders by 6% of members and 13% of non-members, multiple outlets by 17% of members and 12% of non-members, direct sale by 4% of non-members and 0% of members. The regression outcomes on the determinants of coffee market outlet choice showed that the statistically significant estimates at 5% level of significance are quantity offered for sale, distance to market outlet, coffee outlet price, farmer’s experience, credit, ownership of transport, lack of up-to date market information and lack of off-farm income. These findings suggest that an adjustment in each one of the significant estimates significantly influences the probability of selling coffee to/through either of the four market outlets. The profits acquired between farmers selling to different outlets was statistically different (p=0.02) implying that direct sale is shown significantly as the most profitable (GM=415) followed by millers, cooperatives and then informal traders. In view of the research findings, several recommendations are suggested: Coffee cooperative societies should invest in milling plants and offer credit to farmers; Farmers should avoid selling coffee to informal traders and instead dry coffee and sell to millers as dried beans.
Impact of Collective Marketing Participation on Smallholder Avocado Farmers’ Income in Murang’a County, Kenya
(Kenyatta University, 2023-09) Kwizerimana, Samuel; Nigat Bekele; Jayne Mugwe
Abstract
Profitability and Technical Efficiency Analysis of Pigeon Pea Production in Machakos County, Kenya
(Kenyatta University, 2023) Ngiri, Stephanina Makena; Gabriel Mwenjeri; Lucy Ngare
Pigeon pea is a drought-tolerant crop mainly grown by small-scale growers in arid and semi-arid regions mostly for income generation and enhancing food security. Pigeon pea is a very essential crop, particularly in destinations accustomed to drought. Nevertheless, its production remains low. As is with other small holder farmers, pigeon pea producers are often faced with resource-use inefficiency and high costs of inputs in production implying that the proper and efficient allocation of resources is vital to guarantee pigeon pea farmers attainment of additional benefits from their input. Hence, this study aimed at estimating the profit and technical efficiency, assessing profitability and examining factors influencing profit and technical efficiency of pigeon pea production in Machakos County, Kenya. The sample size was 346 respondents targeting pigeon pea farming households’ population. This study relied on primary data collected using structured questionnaire administered to the farmers. Machakos County was purposively selected for the study. The inefficiency effect model and a Cobb-Douglas stochastic frontier production analysis method were utilized to estimate profit and technical efficiency and determine the factors that determine pigeon pea farmers' efficiency. Furthermore, thorough evaluation of profit level was made possible by gross margin analysis. According to the pigeon pea gross margin analysis, pigeon pea farmers in Machakos County had a gross margin of Kshs 3470.60 per acre. The sample pigeon pea farms had profit efficiency levels ranging from 0.11 to 0.9, while their technical efficiency levels ranged from 0.09 to 0.86, according to the findings. The estimated mean level of technical efficiency of the sample farmers, which was approximately 59%, demonstrates the likelihood of increasing the quantity of pigeon pea yield by 41%. Farmers can only achieve this by effectively utilizing the resources at their disposal. On the other hand, mean profit efficiency was 44% implying that there exists an opportunity to increase profit levels by 56% when farmers’ allocative and technical efficiencies are improved. Land size, seeds and labour significantly influenced profits whereas farm size, quantity of seeds, manure and labor significantly determined pigeon pea output. The inefficiency parameter and the stochastic production frontier model were used to calculate the factors that influence efficiency where; farming experience, education, off-farm income, and access to credit all had a positive influence on technical efficiency. Contrarily, the technical efficiency of pigeon pea production was negatively influenced by sex, age, the occupation of the household head, and household size. Profit efficiency was positively influenced by education, proximity to the market, and marketing information, whereas age, occupation, and group membership had a significant and negative impact. In order to assist farmers in making sound decisions regarding the marketing of their produce, strategies that make use of current market information are recommended. It was also recommended to devise strategies for making certified planting seeds available, not only to boost productivity but also production efficiency. Lastly, effective extension services and programs should be developed by the appropriate organizations to improve farmers' capacity to increase pigeon pea productivity.

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