Metabolomics for origin traceability of lamb: An ensemble learning approach based on random forest recursive feature elimination

Metabolomics for origin traceability of lamb: An ensemble learning approach based on random forest recursive feature elimination

The origin traceability of lamb is a longstanding concern for consumers. Despite the widespread application of untargeted metabolomics in meat origin traceability, challenges remain in achieving rapid and accurate identification of biomarkers. This study utilized untargeted metabolomics to analyse f...

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Bibliographic Details
Main Authors: Chongxin Liu, Simona Grasso, Nigel Patrick Brunton, Qi Yang, Shaobo Li, Li Chen, Dequan Zhang
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:Food Chemistry: X
Subjects:
Lamb
Machine learning
Metabolomics
Origin traceability
Random forests
Recursive feature elimination
Online Access:http://www.sciencedirect.com/science/article/pii/S2590157525007035
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http://www.sciencedirect.com/science/article/pii/S2590157525007035

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