Abstract: India, one of the top ten producers and consumers of rice worldwide, heavily relies on rice production and consumption to suit its dietary and economic needs. The early detection of any disease and the administration of the necessary remedies to the affected plants are essential for the health and the development of rice plants. It makes logical to create an automated system because manually diagnosing diseases requires a lot of time and effort. A machine learning-based technique for diagnosing rice leaf disease is presented in this study. The three most prevalent diseases affecting rice plants, according to this article, are leaf smut, bacterial leaf blight, and brown spot. Clear images of damaged rice leaves over a white background made up the input. Following the required pre-processing, the dataset was trained using a range of different machine learning approaches.

PDF | DOI: 10.17148/IJARCCE.2022.11772

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