New methodology for facilitating food wastage quantification. Identifying gaps and data inconsistencies

Area of Science:

• Environmental Science
• Agricultural Economics
• Food Science

Background:

• Global food loss and waste is a significant issue, with 1.3 billion tons wasted annually.
• Quantifying food waste is essential for resource optimization and cost reduction, but current methods face challenges.
• Identifying and classifying food waste generators is a labor-intensive bottleneck in waste quantification.

Purpose of the Study:

• To develop a novel methodology for automatically identifying and classifying potential food waste generators.
• To provide baseline information for the initial stages of food waste inventory scope establishment.
• To create a visual tool for localizing food waste hotspots and assessing economic activity impacts.

Main Methods:

• Utilized the Statistical Classification of Economic Activities in the European Community (NACE) at the 'class' level.
• Integrated NACE data with municipal trading income tax data using Geographic Information Systems (GIS).
• Developed a methodology to map potential food waste generators and their significance within the agrifood chain.

Main Results:

• Successfully implemented the methodology in Zamudio, Spain, identifying entities, their food waste potential, and geographical locations.
• The approach allowed for the comparison of food waste generating activities in different municipalities (Karrantza, Spain) and regions (Basque Country, Spain).
• Generated a visual tool that localizes potential food waste generation points and quantifies the impact of economic activities.

Conclusions:

• The proposed methodology effectively facilitates the identification and classification of food waste generators.
• This approach streamlines the initial steps of food waste quantification by providing crucial baseline data.
• The GIS-based tool offers a valuable resource for targeted waste reduction strategies within the agrifood sector.