Asia, India, China, Middle East, Cultivation/Production, Equipment/Technology, Pests and Diseases, Smart Farming, Trends

Indian scientists developed smartphone app to help potato farmers detect late blight disease

Scientists from the Indian Institute of Technology (IIT) in Mandi have reportedly developed a smartphone app for automated disease detection in potato crops using photographs of its leaves. The research led by Dr. Srikant Srinivasan, Associate Professor, School of Computing and Electrical Engineering, IIT Mandi, in collaboration with the Central Potato Research Institute, Shimla, uses artificial intelligence (AI) techniques to highlight the diseased portions of the leaves of potatoes infected by the late blight pathogen, Phytophthora infestans.

“In India, as with most developing countries, the detection and identification of blight are performed manually by trained personnel who scout the field and visually inspect potato foliage,” explained Dr. Srinivasan. This process, as expected, is tedious and often impractical, especially for remote areas, because it requires the expertise of a horticultural specialist who may not be physically accessible.

“Automated disease detection can help in this regard and given the extensive proliferation of the mobile phones across the country, the smartphone could be a useful tool for potato farmers in this regard,” said Mr. Joe Johnson, Research Scholar, IIT Mandi, while highlighting the practical usage of his research. The advanced HD cameras, better computing power and communication avenues offered by smartphones offer a promising platform for automated disease detection in crops, which can save time and help in the timely management of diseases, in cases of outbreaks.

The computational tool developed by the IIT Mandi scientists can detect blight in potato leaf images. The model is built using an AI tool called “mask region-based convolutional neural network architecture” and can accurately highlight the diseased portions of the leaf amid a complex background of plant and soil matter.

In order to develop a robust model, healthy and diseased leaf data were collected from fields across Punjab, U.P and Himachal Pradesh. It was important that the model developed should have portability across the nation. “The model is being refined as more states are covered,” added Dr. Srinivasan and highlighted that it would be deployed as part of the FarmerZone app that will be available to potato farmers for free.

Source: India Education Diary. Read the full story here

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