Non-targeted detection of food adulteration using an ensemble machine-learning model

Non-targeted detection of food adulteration using an ensemble machine-learning model

Abstract Recurrent incidents of economically motivated adulteration have long-lasting and devastating effects on public health, economy, and society. With the current food authentication methods being target-oriented, the lack of an effective methodology to detect unencountered adulterants can lead...

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Bibliographic Details
Main Authors: Teresa Chung, Issan Yee San Tam, Nelly Yan Yan Lam, Yanni Yang, Boyang Liu, Billy He, Wengen Li, Jie Xu, Zhigang Yang, Lei Zhang, Jian Nong Cao, Lok-Ting Lau
Format: Article
Language:English
Published: Nature Portfolio 2022-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-25452-3

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https://doi.org/10.1038/s41598-022-25452-3

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