The Transformative Role of Artificial Intelligence in Modern Food Science

  • سال انتشار: 1404
  • محل انتشار: نهمین کنگره بین المللی علوم و صنایع غذایی، کشاورزی و امنیت غذایی
  • کد COI اختصاصی: FOODCONG09_107
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 46
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نویسندگان

Nazanin Talebi

Babol Noshirvani University of Technology, Babol, Iran.

Mohammadreza Azimi

Royal College of Surgeons in Ireland, Dublin, Ireland.

چکیده

The integration of Artificial Intelligence (AI) into food science represents a paradigm shift, moving the field from reactive practices to a proactive, predictive, and highly efficient discipline. This paper comprehensively reviews the multifaceted applications of AI across the entire food value chain, from sustainable agricultural production to personalized consumer nutrition. We examine how machine learning, computer vision, and natural language processing are revolutionizing key areas including product development, quality control, food safety, and supply chain optimization. In product development, AI accelerates the discovery of novel formulations and plant-based alternatives by analyzing complex datasets beyond human capability. Computer vision systems enhance quality assurance through automated, real-time defect detection with superior accuracy. Predictive analytics bolster food safety by enabling rapid pathogen identification and precise traceability for targeted recalls. Furthermore, AI is the cornerstone of personalized nutrition, tailoring dietary recommendations to individual genetic and metabolic profiles. Despite its promise, challenges such as data quality, model transparency, and high implementation costs remain. This review concludes that AI is not merely a tool but a transformative force, augmenting the capabilities of food scientists and paving the way for a more sustainable, safe, and consumer-centric food system. Ongoing collaboration between AI experts and food scientists is crucial to address existing hurdles and fully realize this potential.

کلیدواژه ها

Artificial Intelligence, Food Science, Machine Learning, Precision Nutrition, Predictive Analytics, Food Safety, Quality Control, Sustainable Production

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