An open science framework and tools to create reproducible food composition data for use in nutrition

Segovia de la Revilla, Lucia; Codd, Thomas; Joy, Edward J.M.; Mlambo, Liberty; Grande, Fernanda; Rittenschober, Doris; Moltedo, Ana; Holmes, Bridget A.; Ander, E. Louise. 2025 An open science framework and tools to create reproducible food composition data for use in nutrition. Journal of Food Composition and Analysis, 137, 106894. 10.1016/j.jfca.2024.106894

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Official URL: https://doi.org/10.1016/j.jfca.2024.106894

Abstract/Summary

Food composition tables and databases (FCTs) and Nutrient Conversion Tables (NCTs) are essential for nutrition research. Compiling a new NCT requires multiple FCTs, usually with incompatible formats. FCT cleaning and standardisation is rarely reproducible and requires significant resources. Our aim was to develop a framework and tools for compilation and reporting of reproducible FCTs/NCTs, through expanding the fish and other aquatic products in the global NCT for the Food and Agriculture Organization of the United Nations (FAO) Supply and Utilization Accounts. FAO/ International Network of Food Data Systems (INFOODS) guidelines, and open science tools were used for processing. New R functions and scripts were developed to: import and standardise 12 FCTs; re-calculate food components; perform quality checks; and format outputs (e.g., spreadsheets). This resulted in the expansion of the global NCT, providing information on 32 food components for 95 fish and other aquatic products. The workflow takes 160 seconds to run. The scripts are publicly available in GitHub, with a manual, and can be used or adapted. These open science tools provide a novel resource to create, update and expand FCTs/NCTs in a reproducible, reusable, efficient, and transparent manner, for use in nutrition research.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.jfca.2024.106894
ISSN:	08891575
Date made live:	13 Jan 2025 14:51 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/538717

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1016/j.jfca.2024.106894

ISSN:

08891575

Date made live:

13 Jan 2025 14:51 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/538717