International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 2
March-April 2026

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A Cross-sectional Review on Competitive Study between Conventional and Unconventional Techniques used in Detection of Food Adulteration

Author(s) Ms. Divija Pareek, Ms. Ruchika Dwivedi, Dr. Bhawana Jangir, Dr. Geetika Saxena
Country India
Abstract Abstract
Food adulteration affects public health and erodes confidence in the food supply chain. This article gathers information from studies that have been published so far between 2014 and 2025. It emphasizes detection of adulterants in frequently used foodstuffs such as milk, paneer, ghee, pulses, spices, honey, jaggery, and edible oils. The research categorizes detection techniques into one of three main groups: traditional detection methods, instrumental detection methods, and AI-enabled computational models. Conventional approaches utilize qualitative spot tests according to AAU and FSSAI recommended protocols. Instrumental methods include chromatography, spectroscopy, and electrophoresis. These recent methods employ machine learning algorithms, convolutional neural networks, and hyperspectral imaging. It reviews those techniques in terms of sensitivity, accuracy, cost-effectiveness, speed, and compatibility with different foods. Traditional methods are cheap and accessible, but the results reveal a general lack of precision. Instrumental procedures are considered sensitive and reliable, but they need to be conducted in the laboratory. Models powered by AI show a promising capability to achieve accuracy and speed, but they rely on very large datasets and substantial computational power. The review concludes with identification of gaps in standardization and validation and suggestions for future research focusing on design of portable, scalable, and user friendly detection.
Keywords FSSAI, AAU, Food adulteration, chromatography, spectroscopy, electrophoresis, CNN
Field Biology > Bio + Chemistry
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-17
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E-ISSN 2582-2160
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