Typologies, choice of products to process and profit efficiency of baobab processing in Kenya

Abstract

Baobab (Adansonia digitata L.) is one of the underutilized fruit trees which have continued to provide more non-timber benefits to the people. These trees are mostly used traditionally for their oil, food and medicinal properties. Baobab is an iconic tree that is commonly utilized as a source of food and income generation due to its nutritive properties. Despite its importance, baobab processing in Kenya remains low and it is characterized by an undeveloped market system with few processed products being available in the market. Thus, the main questions that remains unanswered are, is baobab processing profitable? What are the factors that determine baobab processing in Kenya? Further, what are the factors that determine the choice of baobab product to process in Kenya? The above concerns remain undocumented and not well known. Thus, this study sought to characterize the baobab processors, determine the factors that influenced the choice of baobab product to process, and estimate the profit efficiency of baobab processing in Kenya. The study was conducted in Kitui, Mombasa, Nairobi, Kilifi, and Makueni Counties. The research used purposive and snowball sampling techniques to select a sample of 304 baobab respondents. The study used a structured questionnaire to collect information from the respondents. Principal components analysis and cluster analysis were adopted to characterize the baobab processors. The logit regression model was used to determine the processor’s choice of product to process, while stochastic frontier analysis was adopted to estimate the profit efficiency of the baobab processors and its determinants. The socio-economic characteristics results revealed that 92.5% of the respondents were female while the males were 7.5%. Baobab candy was the most processed product by over 90 % of the respondents, followed by ice cream at 4.6%, juice at 3.6%, and powder at 1%. Majority (76.2%) of the respondents had access to land while the level of credit access was low (35.7%) among the processors. The main (50.4%) target market was rural market and most (54.8%) processors reported varied processing patterns throughout the year. The processors depicted different education levels, experience, income from others sources, profit levels, baobab revenue processing cost and efficiency levels among the study counties. The cluster analysis findings indicated that the baobab processors in the study area would generally be grouped into three types namely: type 1 which is characterized by high quantity processors; type 2 which consists of average quantity processors and type 3 which is made up of low quantity processors. The Principal Component Analysis (PCA) results revealed that variations in baobab processing were due to income, output, input, and socio-demographic factors of the baobab processors. Baobab processors’ clusters were shaped by training, experience, quantity of baobab processed, baobab processing cost, income from other sources, access to land, and baobab profit levels. The logit model results indicated that education level (P<0.05), number of baobab trees owned (P<0.01), and credit access (P<0.05) favored processing of other products (juice, ice cream, and powder) while marital status (P<0.05) and land size (P<0.05) positively influenced candy as the choice of baobab product to process. The stochastic frontier analysis results revealed that on average the profit efficiency of baobab was 60% which implies that the baobab processors would generally increase their profit efficiency by a further 40% keeping all the other factors constant. The model indicated that the coefficient of sugar costs positively correlated with the normalized profit of baobab processing. The results of the inefficiency model showed that the level of non-processing income, marital status (P<0.05), gender (P<0.1), and number of baobab trees owned (P<0.01) influenced profit efficiency positively, while non-baobab processing occupation (P < 0.1) negatively influenced profit efficiency. The study concludes that, the processors in the study area were heterogeneous in nature. The baobab processors were moderately profit efficient with the women processors being generally less profit efficient compared to their male counterparts. The determinants of profit efficiency were incomes from other sources, number of trees owned, gender, marital status, and non-processing occupation. The study recommended that policy makers should put in place policies that will help increase processors’ efficiency through training and adopting better processing technologies. Similarly, there was need to address the gender gap in baobab profit efficiency between male and the female processors. Further, investment in human capital, particularly informal education on baobab processing activities and encouraging harvesting and conservation of baobab trees will help spur baobab value addition. Lastly, there is need to streamline laws governing land access and ownership among the baobab processors so as to allow access to baobab and harvesting especially those that are in restricted areas such game reserves and parks. Providing processors with land ownership documents will enable them to access credit to use in baobab processing.