From narratives to numbers: Quantifying Euro2040 farm profiles using FADN data.

Abstract

Background: European agriculture is becoming more diverse. However, policy and statistical systems still rely on a legacy of simplified farm classifications. These do not reflect newly emerging farming models or their heterogeneity. The Euro2040 profiles address this gap by offering a richer, narrative-based segmentation. They capture differences in motivations, business models and future pathways. However, Euro2040 profiles remain difficult to apply empirically and are not directly observable in standard datasets.

Results: This study translates Euro2040 profiles into measurable variables. A structured expert elicitation was applied to define relevant indicators. An indicator-profile matrix was developed using FADN (i.e. Farm Accountancy Data Network)-based data. Key dimensions include economic size, land use, labour structure, diversification and dependence on subsidies. These dimensions enable systematic differentiation between farm types. The framework also allows linking qualitative narratives with observable standard European farm-level data. However, several profiles remain poorly captured. Urban, controlled-environment, social-care and cellular farms are often partially or fully 'invisible' in current datasets. This reflects limitations in existing statistical systems rather than conceptual weaknesses of the profiles.

Conclusion: The framework links qualitative profiles with quantitative data. It enables more detailed empirical analysis and supports more targeted policy design. The results highlight a mismatch between farm diversity and existing monitoring systems. This suggests a need to extend current indicators to better capture emerging farming models and improve policy targeting. © 2026 Society of Chemical Industry.