CHARACTERIZATION AND DETERMINANTS OF BAOBAB PROCESSING IN KENYA

Abstract

Baobab is an iconic tree that is utilized as a source of food and income generation. While extant literature on baobab has focused on its morphological attributes and nutrient composition, there is a gap in literature in understanding the characteristics of processors and the factors that determine baobab processing. Using cross section data of 304 baobab processors in Kenya, we employ Principal Component Analysis and Cluster Analysis to characterize baobab processors and identify determinants of baobab processing. Results of processed volumes show that baobab processors are grouped in three clusters of high, average and low categories. Clusters of processors are shaped by number of years in processing, access to training, quantity processed, processing cost, income from other sources, access to land, and profit levels. The study suggests the need to train processors on baobab processing to increase their efficiency and returns. Through training, processors will be able to make informed decisions on input use, packaging and presentation of their products to the customers. Also, investment in baobab conservation, harvesting more trees and reducing the maturity rate of the baobab trees will increase baobab inputs thus lowering processing cost.

Keywords

• baobab processing
• processor characteristics
• kenya
• cluster analysis
• principal component analysis