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

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 to the ne...

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Detalles Bibliográficos
Autores principales: Chung, Teresa, Tam, Issan Yee San, Lam, Nelly Yan Yan, Yang, Yanni, Liu, Boyang, He, Billy, Li, Wengen, Xu, Jie, Yang, Zhigang, Zhang, Lei, Cao, Jian Nong, Lau, Lok-Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9722920/
https://www.ncbi.nlm.nih.gov/pubmed/36470940
http://dx.doi.org/10.1038/s41598-022-25452-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9722920/
https://www.ncbi.nlm.nih.gov/pubmed/36470940
http://dx.doi.org/10.1038/s41598-022-25452-3

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