Fresh fruits and vegetables are invaluable for human health, but their quality deteriorates before reaching consumers during distribution due to ongoing biochemical processes and compositional changes. The current lack of any objective indices for defining “freshness” of fruits or vegetables limits our capacity to control product quality and leads to food loss and waste. In this work, we undertook interdisciplinary research to address plant science challenges related to food security and human health. This work has leveraged machine learning technologies and multi-omics tools to understand post-harvest senescence and microbial spoilage of fresh produce for the purpose of developing a simple imaging “FreshID” device to evaluate fruit and vegetable quality. In essence, we are proposing a comprehensive research program to identify proteins and compounds as “freshness-indicators” and to aid development of an innovative and easy-to-use accessibility tool to accurately estimate the freshness and/or contamination of produce. The goal of the proposed research will be advances in both basic research and applied science. Such a tool would allow a new level of post-harvest logistics, supporting availability of high-quality, nutritious, fresh produce.
