ArticleNPJ science of food2025
Mapping the global origins of soybean: a study using ICP-MS and chemometrics.
Article in NPJ science of food, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To enhance transparency in the soybean supply chain and help prevent misrepresentation of geographic origin, an analytical method combining ICP-MS with chemometrics was developed. A total of 422 soybean samples were collected from Brazil, the United States, Argentina, China, India, Paraguay and Canada, representing over 95% of global production. The OPLS-DA multivariate analysis model used for classification achieved 98.5% accuracy, with Ni, Na, Mo, Ba, Co, Cr, Cd, Sr, Se, K and Ca identified as key elements for origin differentiation. This approach provides a practical tool for companies and regulators to verify geographic origin, supporting compliance with trade and sustainability requirements and tariff-related controls. Additionally, the ability to differentiate soybean samples from various regions within Brazil and the United States was investigated and preliminary comparisons of meal samples from deforested and non-deforested areas in Brazil revealed elemental differences, suggesting potential environmental influences and highlighting the need for further investigation.
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