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Updated: May 21, 2026

Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Harmonised dataset for decomposing and matching food items in dietary data for high-resolution modelling
Anita Frehner1, Zaray Rojas Conzuelo2,3, Sebastian Richter2,4
1Department of Food System Sciences, Research Institute of Organic Agriculture (FiBL), Frick, Switzerland. anita.frehner@fibl.org.
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Modelling environmental, social and nutritional impacts of food consumption requires detailed, disaggregated data linking consumption-level food items to agricultural commodities. Here, we present a harmonised dataset for the decomposition of composite foods - such as mixed dishes, processed products, and multi-ingredient items - recorded in European dietary surveys (classified using European Food Safety Authority (EFSA)'s FoodEx2 system) and their association with life cycle inventory data. The dataset includes a decomposition table as well as matching tables linking FoodEx2 items to food item labels of three commonly used environmental impact databases (Poore and Nemecek dataset, Agribalyse v3.2, Ecoinvent v3.10). Yield conversion factors and consumer food waste coefficients are incorporated to support full food supply chain impact modelling. The dataset is complemented by an R script that supports semi-automatic matching, which can easily be applied to other datasets. Together, these open-access resources support high-resolution modelling of food systems in nutrition, sustainability, and food policy research by transparently connecting reported food consumption to underlying ingredient and commodity data.
