Feasibility of utilizing color imaging and machine learning for adulteration detection in minced meat

Rady, A.M., Adedeji, A. and Watson, N.J. orcid.org/0000-0001-5216-4873 (2021) Feasibility of utilizing color imaging and machine learning for adulteration detection in minced meat. Journal of Agriculture and Food Research, 6. 100251. ISSN 2666-1543

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Item Type: Article
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© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords: Machine learning; RGB; Meat adulteration; Industry 4.0; Digital manufacturing; Non-invasive sensing
Dates:
  • Published: December 2021
  • Published (online): 5 December 2021
  • Accepted: 3 December 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) > FSN Nutrition and Public Health (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Jul 2024 09:08
Last Modified: 12 Jul 2024 09:08
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.jafr.2021.100251
Open Archives Initiative ID (OAI ID):

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