Abstract
Food waste is a global challenge. Detailed information on quantities and drivers is needed to provide tailored recommendations for prevention measures. Current studies on meat waste in the Hospitality and Food Service business (HaFS) sector are rare, often based on small sample sizes, and seldom use comparable reference units. The present study reports meat and meat product waste in the German HaFS business sector based on structured telephone interviews. Purchased fresh meat and meat product quantities, as well as waste during storage, due to preparation and leftovers, are captured for four different market segments. Waste ratios referring to weekly meat purchases are analysed and compared between these segments, as well as on the business-type level. In this context, the authors distinguish total and avoidable meat waste. Absolute meat waste volumes are extrapolated on a weighted base for the entire German HaFS sector. Factors influencing meat waste are identified through regression analysis in order to derive possible food waste prevention measures. The results are discussed to provide recommendations for future national monitoring, policy instruments and research.
Highlights
The limits of planetary resources, combined with a growing world population and a correspondingly increasing demand for food, make more sustainable production and consumption behaviours imperative
A fractional logistic regression analysis was carried out to identify influencing factors related to the indicated waste ratios and to verify Hypothesis 1 (H1)
This indicates that an increase in the weekly meat purchases by 1 t potentially leads to an increased meat waste ratio of 6.8 percentage points
Summary
The limits of planetary resources, combined with a growing world population and a correspondingly increasing demand for food, make more sustainable production and consumption behaviours imperative. Institute and other leading scientific organisations [2,4], detailed information regarding the emergence of food waste is a fundamental requirement to implement prevention measures and assess their efficiency in a second step. In this context, a comprehensive database would allow for a comparison between product groups, value chains, regions and countries in order to identify influencing factors [5] and derive efficient preventive actions [6,7].
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