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Indian scientists develop AI technology for 20 second soil testing and crop health assessment

Indian scientists develop AI technology for 20 second soil testing and crop health assessment
Sustainable Farming

IIT Indore has once again made significant strides, this time in the field of sustainable farming. Following their recent research on Alzheimer's disease, the institute has now shared advanced technology insights with farmers from Simrol village to enhance sustainable farming practices and soil quality. This initiative aims to reduce losses and increase crop productivity, benefiting over 100 farmers from the villages of Ghosikhurd and Simrol.

What is Sustainable Farming:

Sustainable farming is a powerful approach to agriculture that focuses on meeting current needs without compromising the ability of future generations to meet their own. Farmers and livestock keepers who prioritize sustainability adopt three common goals: long-term profitability, care for the land, air, and water resources, and improving the quality of life for farmers, livestock keepers, agricultural workers, and communities.

Soil Testing in 20 Seconds with Machine Learning and AI:

Dr. Chandrabhan Patel, Co-Founder and CEO of Quantic L2M, discussed new sustainable farming methods involving the use of fertilizers. He highlighted that under the guidance of professors from IIT Indore, Quantic L2M has developed technology capable of testing soil in just 20 seconds. By leveraging machine learning and artificial intelligence, this technology can significantly improve the productivity and quality of crops.

Identifying Crop Diseases with Advanced Technology: Professor Mukherjee, Director of Quantic L2M and a professor at IIT Indore, mentioned that their technology can promptly identify crop diseases. Chief Technical Officer Vikas Verma explained that this machine can provide farmers with immediate information about soil parameters. This allows farmers to determine which fertilizers and pesticides are needed for their fields, ultimately enhancing crop production.

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