The FOod Commodity composition for Waste qUantification and valorization opportunitieS (FOWCUS) Dataset

Area of Science:

• Food Science and Technology
• Sustainability Studies
• Agricultural Economics

Background:

• Existing food composition databases primarily focus on chemical analysis, neglecting the quantification of waste streams.
• Understanding the full composition of food commodities is essential for addressing food waste challenges.
• The food supply chain generates avoidable, potentially avoidable, and unavoidable waste, impacting economic and environmental sustainability.

Purpose of the Study:

• To introduce FOWCUS, a novel dataset providing detailed composition of approximately 280 food commodities.
• To quantitatively capture food products and by-products contributing to various food waste categories.
• To facilitate the identification of revalorization pathways for unavoidable food waste and support food waste quantification.

Main Methods:

• Development of a comprehensive dataset (FOWCUS) covering diverse food commodity groups.
• Quantitative analysis of food product components and their potential waste generation.
• Indexing the dataset according to the FAOSTAT commodity typology for standardized use.

Main Results:

• FOWCUS dataset includes detailed composition for ~280 food commodities across multiple categories.
• The dataset quantifies potential food waste generation across the supply chain.
• Identifies opportunities for valorizing unavoidable food waste into feedstocks for biochemical, biomaterial, and bioenergy applications.

Conclusions:

• FOWCUS is a valuable resource for food waste research and policy.
• The dataset supports monitoring food waste reduction targets at national and international levels.
• Enables better management of food waste and valorization of by-products.