Dynamic Shelf-Life Prediction System to Improve Sustainability in Food Banks

摘要

Because food banks receive primarily surplus foods with limited shelf-life, inaccurate quality monitoring can lead to increased food safety risk and waste. A lack of information about the quality and condition of donated food, dependence on volunteer workers, and inadequate inspection equipment can limit a food bank's ability to safely distribute food to people in need. In lieu of expensive lab equipment and technicians, historical data and visual inspections provide a reasonable estimate of the initial quality of donated food, and bacterial growth models can be used to project spoilage rates during storage. Since spoilage rates are highly dependent on food temperature, this paper considers the effect of temperature in a kinetic model to estimate the number of specific spoilage organisms and to predict the remaining shelf-life of perishable foods in food banks. This method can be integrated with warehouse management systems to develop a sustainable inventory management system that reduces food waste and improves food safety, thereby enabling food banks to serve more people in need.