India: Researchers develop system recognizing tomato leaf diseases

Indian scientists developed a system to recognize tomato leaf diseases, which achieves 94.9% accuracy for classification and validation. "In the future, this model will be implemented by increasing the number of diseased classes as well as other plant diseases," they say. 
"Plants are the key source of human energy generation and have nutritional, therapeutic, and other benefits. Plant diseases cause a significant loss in crop productivity, and manually inspecting for plant diseases is a labour-intensive and ineffective approach", the team shared with the presentation of their research.

 To overcome this problem, automated plant disease detection systems have been developed using many approaches that rely on machine learning and image processing to address the indicated issue. "The ability of plant illnesses to alter the color and texture of leaves is exploited to build techniques for detecting plant diseases. In this discipline, deep learning models like VGG (Visual Geometry Group) and ResNET (Residual Network) are often applied. However, because they are primarily focused on disease classification on a specific crop or dataset, the majority of these models are not scalable."

The purpose of this newly done research is to present an enhanced approach for detecting leaf diseases. The suggested system is built with Alexnet and trained and tested on a variety of tomato leaf diseases. This model achieves 94.9% accuracy for classification and validation. "The objective of this research was to demonstrate a scalable and generalized model for utilizing deep learning to identify leaf illness. A dataset of 16,000 images was prepared by tomato leaves which are publicly available datasets. ALexNet architecture is used to decrease training time and show superior performance over previous approaches", the team says. 

In the future, the author would like to implement this approach by increasing the number of classes and detecting types of diseases.

Reference: Jangir, Sarla & Shukla, Praveen & Jain, Mayank & Jajoo, Palika. (2023). Identification of Diseases for Tomato Leaves Using AlexNet.
DOI:10.1109/IATMSI56455.2022.10119326
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Sources: researchgate.net, ieeexplore.ieee.org, hortidaily.com