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

Han F, Aheto JH, Rashed MMA, Zhang X

DOI: 10.1016/j.fochx.2022.100280
Published: 2022 Jun 30
Container: Food chemistry: X
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.fochx.2022.100280,
  title = {Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food.},
  author = {Han F and Aheto JH and Rashed MMA and Zhang X},
  year = {2022},
  journal = {Food chemistry: X},
  doi = {10.1016/j.fochx.2022.100280},
  url = {https://doi.org/10.1016/j.fochx.2022.100280}
}

RIS

TY  - JOUR
TI  - Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food.
AU  - Han F
AU  - Aheto JH
AU  - Rashed MMA
AU  - Zhang X
PY  - 2022
JO  - Food chemistry: X
DO  - 10.1016/j.fochx.2022.100280
UR  - https://doi.org/10.1016/j.fochx.2022.100280
ER  -

APA

F, H., JH, A., MMA, R., & X, Z. (2022). Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food.. Food chemistry: X. https://doi.org/10.1016/j.fochx.2022.100280

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pubmed · retrieved 2026-11-10T10:28:34.973Z