Postharvest Quality Prediction of Oranges

Omri Jovani, M.Sc. student at the Department of Industrial Engineering

12 May 2022, 14:30 PM, Room 206& via zoom

Abstract:
Studies conducted in recent years have shown that 33%-50% of total food production in the world is lost at different stages of the supply chain. For fruits and vegetables produce, this annual loss reaches as much as 45%-55%. The leading distribution method used in fresh produce is based on the First In First Out (FIFO) principal. In FIFO, the produce is marketed according to its storage time regardless of any other parameter. A more efficient alternative to FIFO is the First Expired First Out (FEFO) approach which has the potential to reduce food loss significantly. By conducting an extensive data collection effort, we show how machine learning models can be used to predict postharvest produce quality based on storage conditions and preharvest features.

Bio:
Omri Jovani, M.Sc. student at the department of Industrial Engineering in Tel Aviv University, specializing in Data Science. Omri holds a B.Sc. degree in Industrial Engineering from Tel Aviv University, and works as a data scientist at the ad-tech industry. The research is being supervised by Dr. Noam Koenigshtein and Dr. Yael Salzer.