Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food

Elemental fingerprint coupled with machine learning modelling was proposed for species authentication of the edible animal blood gel (EABG). A total of 25 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectroscopy (AAS) in 150 EABG samples pr...

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Detalles Bibliográficos
Autores principales: Han, Fangkai, Aheto, Joshua H., Rashed, Marwan M.A., Zhang, Xingtao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Short Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914555/
https://www.ncbi.nlm.nih.gov/pubmed/35284814
http://dx.doi.org/10.1016/j.fochx.2022.100280

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914555/
https://www.ncbi.nlm.nih.gov/pubmed/35284814
http://dx.doi.org/10.1016/j.fochx.2022.100280

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