Statistical Modeling of Seafood Fraud Highlights Uncertainties in Products From Metro Vancouver, British Columbia, Canada: Revisiting Hu et al. (2018). [PDF]
J Food SciPhillips JD, De Vuono-Fraser FA.
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Can Citizen Science Be a Key Factor in the Fight Against Mislabeling? Discovering What Squid Is on the Plate. [PDF]
FoodsMuñoz-Colmenero M +7 more
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Artificial Intelligence in Religious Certification: A Comprehensive Review of Halal Digitalization, Compliance Integrity, and Future Directions. [PDF]
Int J Food SciRiaz MN, Irshad F, Haider MB.
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Research note: A machine learning approach for authentication of laying hen housing systems based on egg quality parameters. [PDF]
Poult SciVan Nerom S +4 more
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Digital PCR for the Authentication of KAMUT<sup>®</sup> Brand Wheat in Grain and Flour Mixtures. [PDF]
FoodsMorcia C +8 more
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Meat Adulteration in the MENA and GCC Regions: A Scoping Review of Risks, Detection Technologies, and Regulatory Challenges. [PDF]
FoodsDaher Z +5 more
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Confronting the inevitable: Harnessing technology to contain systemic scientific fraud. [PDF]
Proc Natl Acad Sci U S ASinger P.
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Emerging risk identification in the food chain using text mining-supported monitoring of food safety news: insights from 2022 to 2023. [PDF]
Sci RepFarkas Z +9 more
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