IIT Mandi develops AI-based model for detecting disease in potato crops

Scientists from the Indian Institute of Technology (IIT) Mandi have developed a computational model 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 at IIT Mandi, in collaboration with the Central Potato Research Institute, Shimla, uses Artificial Intelligence (AI) techniques to highlight the diseased portions of the leaf.

Funded by the Department of Biotechnology, Govt of India, the results of this research have recently been published in the journal Plant Phenomics, in a paper co-authored by Dr Srikant Srinivasan and Dr Shyam K. Masakapalli, along with research scholars, Joe Johnson, and Geetanjali Sharma, from IIT Mandi, and Dr Vijay Kumar Dua, Dr Sanjeev Sharma, and Dr Jagdev Sharma, from Central Potato Research Institute, Shimla, according to a press statement.

Potatoes, in the history of the world, have been the 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.

The reason? Potato Blight.

The Blight is a common disease of the potato plant, 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.

“Automated disease detection can help in this regard and given the extensive proliferation of mobile phones across the country, the smartphone could be a useful tool in this regard,” said 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.

In order to develop a robust model, healthy and diseased leaf data were collected from fields across Punjab, UP and Himachal Pradesh. It was important that the model developed should have portability across the nation.

Even though potato is not a staple food in most regions of the world, it is a cash crop, and failure in it can have disastrous consequences, particularly to farmers with marginal landholding. Thus, early detection of blight is important to prevent financial catastrophe to the farmer and the country’s economy.