Classification of food waste in a limited set of Maltese households

Abstract

This study investigates the classification and quantification of food waste within Maltese households to understand its composition, seasonal variation, and the factors influencing its generation. The research adopts a mixed method approach, integrating both quantitative and qualitative data collection techniques. Quantitative data was collected by directly measuring food waste in 30 participating households across five districts in Malta over four seasons. The food waste was categorised into avoidable, potentially avoidable, and unavoidable waste. The data was analysed using permutational ANOVA to identify significant differences in food waste generation rates across districts and seasons. Qualitative data was gathered through semi-structured interviews and focus group discussions to explore household behaviours and attitudes towards food waste. The study found significant district-based variations in avoidable food waste generation, with the Northern Harbour District exhibiting lower rates due to specific waste-reducing practices like composting and feeding leftovers to animals. Seasonal variations indicated higher food waste in autumn and lower rates in winter. The thematic analysis of the interviews revealed key drivers of food waste, such as inadequate meal planning, improper food storage, and a lack of awareness about food waste reduction strategies. Participants expressed emotional responses like guilt and frustration when discarding food, highlighting the moral and ethical dimensions of food waste. Meanwhile, the focus group highlighted practical challenges in incorporating potentially avoidable food items into daily meals, despite recognising their value in reducing waste. Based on these findings, the study recommends comprehensive education and awareness programmes to enhance consumer knowledge on food waste management. Promoting practical tools such as meal planning applications and community-based foodsharing initiatives can further mitigate food waste. Future research should expand the sample size and explore long-term changes in food waste behaviours to inform more effective policy interventions.