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The advent of artificial technologies like electronic noses, electronic eyes, and electronic tongues has fundamentally reshaped our approach to evaluating food samples, as underscored by their ability to capture intricate sensory attributes. The symbiotic relationship between artificial instruments and machine learning underscores their potential to reshape the food industry, ensuring that the food we relish is not only delectable but also safe and of the highest quality.
The use of artificial intelligence (AI) tools like big data and machine learning for antimicrobial resistance (AMR) surveillance in livestock production shows promise for informing AMR mitigation efforts, according to a recent study led by University of Nottingham researchers.
A variety of actions, spanning from simply changing a nozzle to implementing AI technology, can contribute to making sanitizing procedures more sustainable. The authors dive into some of these actions and look at the effectiveness, implementation challenges, and consequences for the end products.
Artificial Intelligence (AI) with optical imaging may be a promising solution for detecting pathogens in foods, and would save the food industry time and resources, according to a recent study.
The Food and Agriculture Organization of the United Nations (FAO) and Wageningen University recently held a workshop about early warning tools and systems that can be used to manage imminent and emerging food safety issues.
Key Technology has announced its new, AI-driven Sort-to-Grade®
software for Key digital sorters, which recognizes and categorizes the surface defects and length of individual potato strips.
The U.S. Food and Drug Administration (FDA) has launched the third phase of the Artificial Intelligence (AI) Imported Seafood Pilot program, which uses AI and machine learning to strengthen the screening process for seafood imports entering the U.S.
Key Technology recently introduced the new artificial intelligence (AI)-driven FM Alert software for its digital sorting systems, which captures and saves digital images of critical foreign material (FM) contaminants.
A recent project report published by the UK Food Standards Agency reflects the potential of advanced technologies and data analytics—such as artificial intelligence (AI) and imaging methods—for improving meat inspection processes.