چکیده مقاله
The one size fits all approach to functional foods is proving insufficient, leading to variable efficacy among consumers This paper proposes a paradigm shift toward Personalized Nutrition PN , utilizing Artificial Intelligence AI to integrate and analyze complex Multi Omics data Genomics, Metabolomics, and Microbiomics to develop highly targeted and efficacious functional food products The research gap lies in translating vast 'omics data into actionable, industrial scale food formulations This extended abstract explores the architecture of a PN platform that predicts an individual's metabolic response to specific bioactive ingredients e g , prebiotics, polyphenols and guides the development of personalized functional food prototypes designed to optimize specific health markers e g , blood sugar control, gut health modulation This approach moves beyond simple dietary advice to the creation of bespoke food matrices
کلیدواژهها
نویسندگان
Amir Salar Montazerfarj
Department of Food Science and Technology, Varamin Pishva Branch, Islamic Azad University, Varamin, Iran
Leila Nateghi
Department of Food Science and Technology, Varamin Pishva Branch, Islamic Azad University, Varamin, Iran
Reyhaneh Sadat Mostafavi
Master's Student, Food Science and Technology, Research Sciences, Islamic Azad University, Iran
شیوه ارجاع
Montazerfarj, Amir Salar and Nateghi, Leila and Mostafavi, Reyhaneh Sadat,1404,Personalized Nutrition Platforms Driven by Multi-Omics Data and AI for Functional Food Development,The first national conference environment, smart agriculture, food security,Varamin
ارائهشده در
مجموعه مقالات اولین همایش ملی محیط زیست، کشاورزی هوشمند، امنیت غذایی28 آبان 1404 · ورامین