Abstract
Groundnut is a major oilseed crop and food crop. In groundnut plant major diseases are occuring on the leaf part. The diseases of the leaf will greatly impact the quality and the production of the groundnut is also reduced. In order to reduce the diseases occurring and the problem happens due to the diseases, this paper uses Artificial Intelligence to identify the disease of groundnut leaves. This proposed model identifies the leaf diseases such as leaf spot, rust, groundnut bud necrosis, root rot and web blotch. In this model image processing and CNN are used along with the Artificial Intelligence. This proposed model was trained with large number of leaf diseased data sets collected from farms. The collected datasets are tested using CNN and the results of the dataset were evaluated. In this experiment than the traditional method Artificial Intelligence had a higher efficiency and accuracy. The accuracy of this model was as high as 96.50%. This research study can come up with an instance for the leaf disease identification of groundnut. The provided solution is a anecdote, scalable and accessible tool for the identification of disease and the management of diverse agricultural plants.
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Maheswaran, S., Indhumathi, N., Dhanalakshmi, S., Nandita, S., Mohammed Shafiq, I., Rithka, P. (2022). Identification and Classification of Groundnut Leaf Disease Using Convolutional Neural Network. In: Kalinathan, L., R., P., Kanmani, M., S., M. (eds) Computational Intelligence in Data Science. ICCIDS 2022. IFIP Advances in Information and Communication Technology, vol 654. Springer, Cham. https://doi.org/10.1007/978-3-031-16364-7_19
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