Recent advances on artificial intelligence-based approaches for food adulteration and fraud detection in the food industry: Challenges and opportunities.

Journal: Food chemistry
PMID: 39675268

Abstract

Food adulteration is the deceitful practice of misleading consumers about food to profit from it. The threat to public health and food quality or nutritional valuable make it a major issue. Food origin and adulteration should be considered to safeguard customers against fraud. It has been established that artificial intelligence is a cutting-edge technology in food science and engineering. In this study, it has been explained how AI detects food tampering. Applications of AI such as machine learning tools in food quality have been studied. This review covered several food quality detection web-based information sources. The methods used to detect food adulteration and food quality standards have been highlighted. Various comparisons between state-of-the-art techniques, datasets, and outcomes have been conducted. The outcomes of this investigation will assist researchers choose the best food quality method. It will help them identify of foods that have been explored by researchers and potential research avenues.

Authors

  • Puja Das
    Department of Food Engineering & Technology, Central Institute of Technology, Deemed to be University, Kokrajhar, Assam, India.
  • Ammar B Altemimi
    Food Science Department, College of Agriculture, University of Basrah, Basrah 61004, Iraq.. Electronic address: ammar.ramddan@uobasrah.edu.iq.
  • Pinku Chandra Nath
    Bioproducts Processing Research Laboratory (BPRL), Department of Bio Engineering, National Institute of Technology, Agartala 799046, India; Department of Applied Biology, University of Science and Technology Meghalaya, Baridua 793101, India.
  • Mehak Katyal
    Department of Nutrition and Dietetics, School of Allied Health Sciences, Manav Rachna International Institute of Research and Studies, Faridabad 121004, Haryana, India.
  • Radha Krishnan Kesavan
    Department of Food Engineering & Technology, Central Institute of Technology, Deemed to be University, Kokrajhar, Assam, India.
  • Sarvesh Rustagi
    Sarvesh Rustagi, School of Applied and Life Sciences, Dehradun, Uttarakhand.
  • Jibanjyoti Panda
    Nano-biotechnology and Translational Knowledge Laboratory, Department of Applied Biology, School of Biological Sciences, University of Science and Technology Meghalaya, Techno City, 9(th) Mile, Baridua, 793101, India.
  • Satya Kumar Avula
    Natural and Medical Sciences Research Centre, University of Nizwa, Nizwa 616, Oman. Electronic address: chemisatya@unizwa.edu.om.
  • Prakash Kumar Nayak
    Department of Food Engineering and Technology, Central Institute of Technology Kokrajhar, Kokrajhar 783370, India.
  • Yugal Kishore Mohanta
    Department of Applied Biology, University of Science and Technology Meghalaya, Baridua 793101, India; Centre for Herbal Pharmacology and Environmental Sustainability, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam 603103, India. Electronic address: ykmohanta@gmail.com.

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