Traceable and Scalable Food Balance Sheets from Agricultural Commodity Supply and Utilization Accounts (2010-2022)

Area of Science:

• Agricultural Economics
• Food Systems Analysis
• Data Science

Background:

• The Food Balance Sheets (FBS) from the Food and Agriculture Organization (FAO) are crucial for food system research but lack transparency and scalability.
• Limited data accessibility hinders empirical analysis and complex modeling of agricultural development, food security, and dietary health.

Purpose of the Study:

• To introduce a novel traceable Food Balance Sheets (T-FBS) dataset.
• To enhance the transparency, traceability, and scalability of food system data for improved empirical analysis.

Main Methods:

• Developed T-FBS from detailed Supply Utilization Accounts (SUA) data.
• Utilized a Primary Commodity equivalent (PCe) aggregation approach for commodity flow analysis.
• Ensured consistency and balance across multiple dimensions in the aggregated dataset.

Main Results:

• The T-FBS dataset covers 57 PCe commodities across 195 regions (2010-2022), derived from over 500 SUA products.
• T-FBS shows close alignment with FAO-FBS for dietary energy and macronutrients.
• Identified key uncertainties in elements like feed, trade, and stocks compared to FAO-FBS.

Conclusions:

• The T-FBS dataset offers enhanced methodological transparency and traceability for food system studies.
• Improved scalability and robustness of food data support future research and open-source collaboration.
• T-FBS provides a more reliable foundation for analyzing agricultural development and food security.