Factors Influencing Adoption of Hermetic Storage Technology in Green Grams and Its Impact on Farmer’s Household Income in Kitui County, Kenya

Abstract

Inadequate and poor post-harvest grain storage is a major constraint to green gram farmers in Kitui County. It has been identified as the key challenge for smallholder green gram growers because it has significantly reduced the quality and quantity of green grams after harvest, resulting in the shortage of food supply and or price manipulation for millions of households in the study area. Resultant food losses have affected green gram trade and have adverse implications on the economy. Hermetically sealed post-harvest storage systems, such as the Purdue Improved Crop Storage (PICS) bags, initially developed by Purdue University for the storage of cowpeas in West Africa, can contribute dramatically to reducing such food losses. In recognition of this, USAID’s Kenya Agricultural Value Chains Enterprises (KAVES) project has been a driving force behind the introduction and promotion of Hermetic Storage Technology (HST) that involves the use of the hermetic bags in Kenya since 2013. Hermetic Storage Technology (HST) is intended to reduce post-harvest storage losses and boost household welfare through increased incomes. However, the extent to which the adoption of the HST in Kenya has contributed to reduction of post-harvest storage losses and consequently increased income has not been comprehensively documented. The specific objectives that this study addressed were to: assess the factors that influence the adoption of HST, determine the extent of HST utilization by smallholder green grams farmers, and evaluate the impact of HST utilization on green grams farmers’ household income in Mwingi Central and Mwingi West, Kitui county. Primary data were collected from 271 randomly selected farm-households. Descriptive statistics was used for characteristics and basic analyses. Double-hurdle model was used to analyze the factors that influence adoption and the extent of utilization of HST while Endogenous Switching Regression Model (ESRM) was used to analyze the effect of HST adoption and utilization on household income. The results show that the age of the household head,........................................................................