Indian Instituted of Technology Mandi and Central Potato Research Institute Shimlahave jointly developed a computational model to detect the diseases of potato crop by using photograph of its leaves. The computer application developed by the researchers using a complex computational model can detect blight in potato leaf images, according the IIT, Mandi sources.
The team is working on converting the developed tool to a smartphone application for a more practical usage which work upon a computational model for automated disease detection in potato crops using photographs of its leaves using Artificial Intelligence (AI) technique to highlight the diseased portions of the leaf. The study was funded by the Department of Biotechnology of union Govt, also published in the journal Plant Phenomics, in a paper co-authored by Dr Srikant Srinivasan, and Dr Shyam K Masakapalli along with research scholars, Mr Joe Johnson, and Ms Geetanjali Sharma, from IIT Mandi and Dr Vijay Kumar Dua, Dr Sanjeev Sharma, and Dr Jagdev Sharma, from Central Potato Research Institute, Shimla. Potatoes Blight had been cause of the world’s great famine of the mid-nineteenth century that killed over a million people in Ireland and rang the death knell for the Irish language.
Potato Blight is a common disease that starts as uneven light green lesions near the tip and the margins of the leaf and then spreads into large brown to purplish-black necrotic patches that eventually leads to rotting of the plant. If left undetected and unchecked, blight could destroy the entire crop within a week under conducive conditions. 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.
”The new research and application would help in this regard and given the extensive proliferation of the mobile phones across the country, the smartphone could be a useful tool in this regard,” said Mr Joe Johnson, Research Scholar, IIT Mandi, With advancement of 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 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, UP and Himachal Pradesh.
It is said that the model is being further refined as more states are on the coverage mode. As a part of the Farmer Zone App it will be available for free to the potato farmers.