Food waste (FW) is a key challenge on the sustainable development agenda of countries worldwide. The lack of FW data and insights from its analysis about quantities, causes, and characteristics is a significant obstacle in implementing adequate reduction and prevention interventions for different sectors. The primary purpose of the case studies was to review FW prevention, reduction, and management initiatives. Lessons and best practices that enable and facilitate solutions were identified.

Nine case studies were conducted targeting five sectors: food services (one restaurant and one hotel), wholesale markets (one fruits and vegetables wholesale market), retailers (one retail market, one retail shop, and one supermarket), caterers (one hospital), and households (five middle- and five high-income households). The case studies consisted of a FW audit that measured the amounts generated from various processes and identified drivers/causes and current best practices. Quantification involved physical separation, weighing, and categorizing the different food components. The separation classified quantities into edible and inedible portions. The study also focused on assessing the environmental and socio impacts, based on assessed and categorized FW quantities.

FW is a complex phenomenon where the amount, causes and consequences are contextually different. It is not easy to compare and contrast country-level data and the individual actors in the same country. Therefore, the case study approach has been used in many FW-related studies. Multiple case studies can be expensive and time-consuming to implement. Under this study, we analyzed nine case studies targeting five sectors: food services (four restaurants, a dessert shop and one hotel), wholesale markets (one fruit and vegetable market ), retail markets (one supermarket, one fruit and vegetable retailer, one Dedicated Economic Center), caterers/institutional canteens (one hospital) and households (five middle-income households and five low-income households). Entities were selected based on willingness to participate and an actual FW reduction need.