International Journal of Drug Delivery Technology
Volume 16, Issue 6s, 2026

Agro-Vision: Intelligent Detection of Potato Leaf Diseases Using Deep Learning

Pavan Mitragotri1, Hrishikesh Mogare2, Vinod Kokitkar3, Dr. Pavan Kunchur4

1Department of MCA, KLS GIT, Belagavi, India. Email: pvmitragotri@git.edu

2Department of MCA, KLS GIT, Belagavi, India. Email: hrishikeshmogare@gmail.com

3KLS GIT, Belagavi, India. Email: vpkokitkar@gmail.com

4Department of CSE, KLS GIT, Belagavi, India. Email: pnkunchur@git.edu


ABSTRACT

Background: Plant diseases are a huge problem for farmers and our food supply. Finding them early is key to protecting crops and getting better harvests. Potatoes are especially vulnerable to diseases example early blight and late blight. If these aren't caught quickly, they can wipe out entire fields and cost farmers higher amount of money. That's why we created Agro-Vision. It's a smart system that uses artificial intelligence to spot potato leaf diseases. The system looks at pictures of potato leaves and tells you if they have early blight, late blight, or if they're healthy.

Methodology: We built Agro-Vision using a special type of AI called MobileNetV2. We trained it on lots of leaf images and used techniques to make sure it works well even when conditions change. The best part? It's really accurate. In our tests, Agro-Vision got things right 90 percentage of the time. When it makes a correct diagnosis, it's usually between 83 percentage and 100 percentage confident about its answer. We made Agro-Vision easy to use by putting it in a simple web app. You can upload a picture of a potato leaf, and it gives you an instant diagnosis along with how confident it is about each possible disease. This makes it a practical tool that farmers can actually use in their fields.

Conclusion: What this means is that Agro-Vision offers a reliable, affordable way to catch plant diseases early. It could be a game-changer for modern farming, helping growers protect their crops without needing expensive equipment or expert knowledge.

Keywords: Plant disease detection, Convolutional Neural Networks, Transfer learning, MobileNetV2, Computer vision, Precision agriculture.

How to cite this article: Mitragotri P, Mogare H, Kokitkar V, Kunchur P, Agro-Vision: Intelligent Detection of Potato Leaf Diseases Using Deep Learning...Int J Drug Deliv Technol. 2026;16 (6s): 343-347; DOI: 10.25258/ijddt.16.6s.37

Source of support: None

Conflict of interest: None