MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202521022944 A) filed by Mokhtar Ahmed Sallam Al-Awadhi; and Ratnadeep R. Deshmukh on March 14, 2025, for System And Method For Detecting Honey Adulteration And Classifying Honey Botanical Origins Using Hyperspectral Non-Imaging And Machine Learning.
Inventors include Mokhtar Ahmed Sallam Al-Awadhi; and Ratnadeep R. Deshmukh.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The invention presents a non-destructive system for detecting honey adulteration and classifying botanical origins using hyperspectral non-imaging technology combined with advanced machine learning algorithms. It employs a novel wavelength selection method to reduce data dimensionality by 98.8%, identifying critical wavelengths for analysis. The system achieves 100% accuracy in classifying 10 botanical origins and detects adulteration with 96.67% accuracy. It also quantifies adulteration levels using Partial Least Squares Regression (PLSR). A user-friendly interface provides real-time results, including botanical origin, adulteration status, and concentration. This rapid, cost-effective solution outperforms traditional methods, ensuring food safety and quality control across diverse honey types and adulterants.
Disclaimer: Curated by HT Syndication.
