AI-Driven Nondestructive Measurement Technologies for Meat Quality and Safety: A Review. [PDF]
FoodsAlal LB +5 more
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Liver Injury Associated With Irregular Herbal Products: A Translational Case Series With Chemical Authentication and Causality Assessment Using the Updated RUCAM. [PDF]
Case Reports HepatolGóis FL +5 more
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Machine learning-based prediction and quality control of meat and meat products: applications for intelligent quality management in the meat industry. [PDF]
Food Sci Anim ResourKim YJ +7 more
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Evaluating Honey Adulteration Through Physicochemical Characterization and Liquid Chromatography-Mass Spectrometry-Based Sugar Profiling. [PDF]
FoodsAl-Hetlani E +4 more
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A confirmation test for the presence of Quillaja saponin and adulteration with Madhuca saponin in poultry feed using high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry. [PDF]
Poult SciThalhamer B +3 more
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Immature Honey as a Quality Challenge in Global Apicultural Production. [PDF]
FoodsGajda A +5 more
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Food Defense Risk Assessment of an Edible-Coating Processing Line: A Comparative Case Study Using TACCP and CARVER+SHOCK. [PDF]
FoodsSegovia-Bravo KA +2 more
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A Validation-Driven Explainable Deep Ensemble Framework for Image-Based Saffron Adulteration Detection. [PDF]
FoodsBukhari SNH, Ogudo KA.
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A Fluorescence-Based Sensor Combined with Chemometric and Deep Learning Approaches for Detecting and Quantifying Coconut Milk Fraud in Bovine Milk. [PDF]
Sensors (Basel)Cahyarani SMD, Lee H.
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