Abstract
Agricultural products are prone to diseases as they come into the attack of fungi, bacteria, and affected by bad environmental conditions. The symptoms are first visible on leaves and stems. This paper proposed methodology to detect diseases in leaves and suggestion for selection of pesticides using artificial neural network (ANN). Different types of diseased leaf images are used as dataset for training the ANN. Proposed method segments diseased portion and healthy portion of pre-processed leaf image using K-mean clustering. Texture feature is extracted as an input to the ANN. Using ANN, type of diseases is identified and pesticide is suggested. Proposed method worked better than other methods and is verified by parameters like precision and recall.
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Salunkhe, S.S., Phadke, G., Kadam, S., Kadu, A. (2020). Strawberry Leaf Diseases Detection and Suggestion for Pesticides Using Artificial Neural Network. In: Reddy, V., Prasad, V., Wang, J., Reddy, K. (eds) Soft Computing and Signal Processing. ICSCSP 2019. Advances in Intelligent Systems and Computing, vol 1118. Springer, Singapore. https://doi.org/10.1007/978-981-15-2475-2_42
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DOI: https://doi.org/10.1007/978-981-15-2475-2_42
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