AI CROP DISEASE DETECTION

Abstract

The rapid growth of technology in agriculture has created new opportunities to improve crop productivity and reduce losses caused by diseases. Crop diseases are one of the major challenges faced by farmers, leading to significant reduction in yield and quality. Early detection and proper diagnosis of these diseases are essential for effective treatment and prevention. This project, titled “AI Crop Disease Detection System”, aims to develop a web-based application that uses Artificial Intelligence to identify crop diseases from images. The system allows users to upload images of infected crop leaves through a simple and user-friendly interface. The uploaded image is processed using an AIbased model, which analyzes the image and predicts the type of disease. The backend of the system is developed using Python Flask, which handles image processing, model prediction, and server-side operations. The frontend is designed using HTML, CSS, and JavaScript to provide an interactive user experience. The system uses MySQL database to store user information, uploaded images, and prediction results.

Plant phenotyping relevance

感染葉画像から作物病害を推定するAI画像解析システムの開発が中心であり、植物の病害状態を直接評価するため、植物フェノタイピング手法として収録する。

Code and data availability

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