A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf life of fresh horticultural product, namely lettuce, onion, carrot, and cabbage based on its microbial growth status, governed by extrinsic and intrinsic parameters (temperature, water activity and pH, respectively). The remaining shelf life of the studied horticultural products is determined by using the online predictive food microbiology tool— the Combined Database for Predictive Microbiology (Combase). The time to reach the infectious doses of bacteria considered in the study for each of the four horticultural products are predicted; (2) the calculation of the dynamic price of the produce that should be set each day, depending on the predicted end of the marketing period to increase the demand and potential for sale to the final consumer. The proposed dynamic pricing model assumes a linear relation with the remaining shelf life of the analyzed vegetable to set the selling price. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety. The automatic dynamic pricing gives new opportunities to small retailers to manage their business, fostering profit and simultaneously contributing to reduce food waste. Thus, this decision support system can contribute to the sustainable value of reducing food waste by providing information to small grocers and retailers on the safety of their perishable status depending on storage conditions and allowing them to suggest a fair price depending on that quality.
A complete decision-support infrastructure for food waste valorisation
