Assessing the quantities of legume-based products: A dataset of conversion coefficients into a comparable dry-legume equivalent unit
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Abstract
Measuring the consumption of processed foods made from a common raw agricultural ingredient requires to make quantities comparable, by converting them in raw product equivalent. This conversion also allows to compute total quantities. In the case of legumes, the challenge is to take into account a wide diversity of final products including packaged dry legumes, processed legumes and products cooked from legumes and other ingredients. While the total quantity of the final product purchased or consumed is easily available, the corresponding quantity of dry legumes used to make the final product is not. We create a dataset of technical coefficients to convert quantities of final legume-based products into dry-legume equivalent unit. For this purpose, we first list all legume-based products purchased in French retail stores from 2002 to 2019. Those products were identified in our primary data source, the Kantar Worldpanel data. Then, for each final legume-based product, we rely on information from existing food databases, literature and products labels to build a coefficient based on three intermediary technical sub-coefficients. The first sub-coefficient measures the proportion of cooked legumes used in each product. The second sub-coefficient adjusts the quantities for products that lose water during processing (such as dehydrated or baked products). Finally, the third sub-coefficient is a conversion coefficient, used to express the quantities of legumes purchased in dry-legume equivalent. This dataset centralizes technical conversion coefficients that are useful to analyze global French legume markets, regardless of the type of product purchased (dried legumes, canned legumes, meals...). These coefficients also allow to infer quantities at the upstream agricultural production level.
Keywords: Legumes; Proportion; Consumption; Food products; Dry; Processed; Recipe; Technical coefficient
Acknowledgements
This work received funding from the European Union's Horizon research under grant agreement No. 101060075 as part of the Brightspace project; the French National Research Agency (ANR) under the Investments for the Future (Investissements d'Avenir) program, grant ANR-17-EURE-0010; and the metaprogram SYALSA financed by INRAE, as part of the Durqual project.
Cite this article
Marine Spiteri, Lola Pedrini, Agathe Thierry, Valérie Orozco, Olivier de Mouzon, Zohra Bouamra-Mechemache (2024) Assessing the quantities of legume-based products: A dataset of conversion coefficients into a comparable dry-legume equivalent unit, Data in Brief,
Volume 58, 2025, 111222, https://doi.org/10.1016/j.dib.2024.111222
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Open Access This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.You are not required to obtain permission to reuse this article. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.
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BrightSpace Project information
BrightSpace Horizon Europe project Grant Agreement No. 101060075
https://cordis.europa.eu/project/id/101060075
CALL: Innovative governance, environmental observations and digital solutions in support of the Green Deal
WORK PROGRAMME Topic ID: HORIZON-CL6-2021-GOVERNANCE-01-12 EU agriculture within a safe and just operating space and planetary boundaries
BrightSpace Project coordination: Wageningen Economic Research, The Hague, NL
Contact: brightspace.wecr@wur.nl | Website: www.brightspace-project.eu
Project duration: 1 November 2022 – 31 October 2027
Funding acknowledgement
BrightSpace is funded by the European Union. Grant Agreement No. 101060075. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.
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- Has part
- Dataset: 10.57745/QZDIUT (DOI)