category Regional, patiala, , tags Regional, patiala, , DW BUREAU PATIALA Under the joint Supervision and strong initiative of Dr. Ganesh Kumar Sethi and Dr. Rajesh Kumar Bawa, Ph.D. researcher, Komal Sharma of the Department of Computer Science, Punjabi University, Patiala has developed a web-based tool named ARVIS, (Automatic Rice Variety Identification System), that is capable of identifying and classifying the varieties of rice through digital imaging of rice seeds or grains of which are being grown in Punjab using the Machine Learning approach. Highlighting the importance of the research work, Dr. Ganesh Kumar Sethi, Assistant Professor, Multani Mal Modi College, Patiala stated that by using machine learning to identify the visual characteristics of different rice varieties, it is possible to verify the authenticity of rice products. This can help to prevent fraud and ensure that consumers are getting what they paid for. In future, the tool can be helpful in Breeding Programs also which means it can help to develop new varieties of rice that are more resistant to diseases, pests, and climate change. It has been reported that they have also filed a patent for this research work in the Indian Patent Office and published research papers in the reputed journals. For the research carried out the Research Scholar has also got Best Paper Award in International Conference on innovative and Research in Marine Electrical and Electronics Engineering held in 2021 in Chennai. Further, Dr. Rajesh Kumar Bawa, Professor, Punjabi University, Patiala and Co-Supervisor said that the identification of rice varieties is a challenging task that requires precise image analysis techniques. The research scholar has been able to overcome this challenge by developing an innovative approach that uses machine learning algorithms to identify and classify different rice varieties based on their morphological, texture and color characteristics. Highlighting the importance of this research, Research scholar, Komal Sharma, stated that the identification of rice varieties is critical for ensuring the authenticity of rice products in the market. The major challenge faced for the development of ARVIS was the non-availability of a public benchmark image dataset of rice varieties of Punjab. (editor dailyworld.in)