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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...
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| 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 |