Reducing post-harvest losses improves local food security, contributes to the increasing global food demand and increases recourse use efficiency. Reported information on actual post-harvest losses (PHL) is difficult to compare because of the use of different system boundaries, loss concepts and estimation methods. There has been little effort to systematically organize and analyse PHL according to food groups, (segments of) supply chains, and prevailing agro-environmental and socio-technical conditions.
This project develops a generic method to map PHL using sub-Saharan Africa as a case study. Based on the available literature a spatial database will be developed for different food groups with point data information on current PHL in different segments of the supply chain and associated agro-environmental and socio-technical characteristics.This database combined with other spatial databases (e.g. land use, climate and harvesting periods) is used to scale up and extrapolate point data with quantitative PHL information to other areas with similar characteristics. By combining and overlaying different maps relationships between observed PHL and agro-environmental and socio-technical factors are determined and relatively homogenous zones identified with consistent PHL for a given food group and segment of the value chain. Based on the same PHL database key agro-environmental and socio-technical factors that are associated with PHL will be analysed using statistical methods enabling the identification of options to reduce PHL. In dedicated field studies in Ethiopia, post-harvest management will eb described and PHL quantified for selected food groups to collect information missing in the literature and to further identify and asses options aimed at reducing PHL.