Reducing postharvest losses in fresh produce chains in transition countries

Food losses in fresh produce chains are a serious problem worldwide and the problem is most prevalent in developing countries. Up to 70% of fruit and vegetables produced in these countries, especially in Africa, is lost along the supply chain. High food losses are a major obstacle in achieving sustainable food supply chains. It has repercussions on food security and economic growth, especially in Africa where most of the countries rely on agriculture. Furthermore, food losses result in wastage of scarce resources such as water and land used for production. Therefore, there is an urgent need for effective interventions that reduce food losses and thereby improve the sustainability of fresh produce chains and reduce the food insecurity in developing countries. Recent studies indicated that a considerable amount of PHLs in fresh produce chains is avoidable. Several solutions to reduce PHLs in fresh produce chains have been put forward in literature. However, the proposed solutions fall short in that they are either from a logistics control or from a quality control perspective, and solutions are not taking into account the constraints inherent to the typical context characteristics (e.g. tropical climate, restricted resources, and limited competences). Moreover, the solutions seldom consider concurrent improvement of both quality control and logistics control along stages in the supply chain.

Aim
The overall aim of this project is to get insight in how the performance of quality control and logistics control activities affect the risk on post-harvest losses, and how characteristics of the African context affect the performance of quality control and logistics control activities. 

Approach
The first step in the research is to develop an analytical framework showing major quality control and logistics control activities that can affect post-harvest losses (PHLs), and the technological and managerial (organisational) context factors that can affect their performance.

Next, the analytical framework will be operationalized into a diagnostics system analysis tool to analyse the current performance of quality and logistics control activities, and to assess the vulnerability of the context in view of the risk on post-harvest losses. The instrument will be validated by structured expert interviews (Delphi study). Moreover, a systematic sampling scheme to monitor product quality parameters will be developed.

Case studies in Zimbabwe will be selected to concurrently analyse the performance of quality control and logistic control, the Zimbabwean context characteristics, and the variability in quality parameters at critical post-harvest stages.
Simulation modelling will be used to generate alternative solutions to reduce PHLs given the typical Zimbabwean context characteristics
Finally, based on above projects roadmaps will be developed to advance towards more advanced quality control and logistics control activities to reduce PHLs.