Great Innovation! IIT Mandi Develops A Special App, Photos To Reveal Potato Disease
This research has been completed under the guidance of Dr. Srikant Srinivasan, Associate Professor, School of Computing and Electrical Engineering, IIT Mandi.
Researchers at IIT Mandi, Himachal Pradesh, have developed the best and working technique for the potato cultivators, now they can detect crop failure through photos. Researchers have prepared a computer app with a complex computational model, which will be able to detect blight disease using photographs of the potato leaves. This will detect The feat has been carried out in association with Central Potato Research Institute (CPRI) Shimla under the guidance of Dr. Srikant Srinivasan, Associate Professor, School of Computing and Electrical Engineering, IIT Mandi. In this research, Artificial Intelligence (AI) technology has succeeded in detecting diseased parts of leaves.
Will know in time
Potatoes usually have blight disease and if not stopped in time, the entire crop is damaged in just a week. To check this, experts have to go to the fields. Its disease is detected after careful examination. But now after this new technology, just the photos of the leave will help detect whether the crop is diseased or not. Once examined, if it's known that the crop is going to be damaged, then the crop can be saved by using insecticides in time.
How this works
By taking a photo of diseased-looking leaves with this app, this app will confirm in real-time whether the leaf is getting damaged or not. The farmer will know in time when to spray the field to prevent the disease so that the yield does not get damaged. Also, it prevents wastage of money due to fungicide.
'98 percent results came positive'
Dr. Srikant Srinivasan, who was involved in this research, said that so far 98 percent of its results have come positive. Special emphasis has been given to make this model work across the country. After the success of this model, the IIT Mandi team is miniaturizing it to about 10 MB to make it easily available as an application on a smartphone.
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