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Rising Kashmir > Blog > Anchor > SKUAST-K Prof develops cutting-edge App to detect saffron adulteration
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SKUAST-K Prof develops cutting-edge App to detect saffron adulteration

Javid Sofi
Last updated: March 15, 2024 12:27 pm
Javid Sofi
Published: March 15, 2024
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3 Min Read
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Amjad M. Hussaini, an Associate Professor of Plant Biotechnology at Sher-e-Kashmir University of Science and Technology Kashmir (SKUAST-K), has launched a groundbreaking mobile application fueled by artificial intelligence designed to detect adulteration in saffron.
Dubbed ‘Saffron Rapid Test,’ this intuitive app aims to tackle the persistent issue of saffron adulteration, which has long plagued both consumers and the saffron industry. Professor Hussaini highlighted the importance of combatting saffron adulteration, citing its detrimental impact on consumers and the economy during an interview with Rising Kashmir.
Traditional methods of saffron authentication, reliant on complex laboratory equipment, presented challenges, particularly for small-scale consumers in saffron-growing regions. To address this challenge, Professor Hussaini and his team devised a comprehensive strategy, integrating artificial intelligence, mechanical engineering, and saffron expertise.
Utilizing innovative visual markers and state-of-the-art technology, they developed a method to authenticate saffron samples effectively. Overcoming initial skepticism, the team successfully standardized the use of Foldscope, a low-cost device initially intended for children’s scientific inquiry, for detecting saffron adulteration.
The ‘Saffron Rapid Test’ app employs unique visual markers, such as papillose protuberances along the top margins, to differentiate between genuine and counterfeit saffron samples. Additionally, the app utilizes Convolutional Neural Networks (CNN) for automated detection, achieving an impressive accuracy rate of 99.5%.
Described as a customer-centric frugal science-based approach, this innovative method represents a significant advancement in saffron authentication. Collaboration with an overseas Indian student specializing in machine learning technology played a crucial role in overcoming challenges in developing the artificial intelligence detection system.
Professor Hussaini emphasized that the ‘Saffron Rapid Test’ app empowers consumers by providing them with a simple tool to detect fake saffron samples. With just an Android phone equipped with a Foldscope, users can capture a photo of a saffron sample and upload it to the app. Powered by artificial intelligence, the app swiftly determines the authenticity of the sample, enhancing consumer confidence and safeguarding the integrity of the saffron industry.
The ‘Saffron Rapid Test’ app is readily available for download on the Google Play Store, offering accessibility to consumers seeking to ensure the quality of their saffron purchases.
 
 
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