Assessment of passion fruit orchard management and farmers’ technical efficiency in Central-Eastern and North-Rift Highlands, Kenya

Abstract

In Kenya, passion fruit (Passiflora edulis L.) has emerged as an important high market value horticultural crop over the last decade following the establishment and expansion of large scale processors of fruit juice and increasing population of health conscious consumers.  This has led to increasing interest in the enterprise among farmers. However, many farmers have also withdrawn from passion fruit farming, citing low productivity of orchards.  The objective of this study was to compare management and technical efficiency (TE) of orchards in Central-Eastern (Embu and Meru Counties) and North-Rift (Uasin Gishu County) Highlands of Kenya in order to determine opportunities for increasing and sustaining productivity. Cross-sectional data from 123 randomly selected farmers was collected using a personally administered structured questionnaire and subjected to managerial and stochastic frontier analysis. Management was assessed considering five practices; training of vines and pruning, weeding, watering, disease management and manure/fertilizer application. Meru County had the highest mean TE (65%) followed by Uasin Gishu (57%) while Embu was the least efficient (47%). Mean scores for the five management practices evaluated also followed a similar trend across the three Counties. The five management practices assessed significantly influenced TE. Therefore, the study established a relationship between orchard management practices and TE of farmers. The study recommends promotion of county cross-border farmer linkages as a platform for sharing ideas and success experiences. Further, increased emphasis on frequent farmer update on farming trends through participatory methods (lead farmer approach, training, farm visits and demonstrations) are recommended to increase farmer awareness on appropriate orchard management practices, which would eventually contribute to improved technical efficiencies and productivity.

Keywords: Technical efficiency, managerial analysis, stochastic frontier analysis