Intelligent pesticide recommendation system for cocoa plant using computer vision and deep learning techniques

Abstract

Abstract Agriculture in India is a vital sector that contains a major portion of the population and impacts substantially the country’s economy. Cocoa is a crop that has commercial importance and is used for the production of chocolates. It is one of the main crops cultivated in south India due to the humid tropical climate. However, the cocoa plant is susceptible to various diseases caused by bacteria, viruses, and pests resulting in yield losses. Visual analysis is a subjective and time-consuming process. Further, farmers use improper pesticides to prevent diseases, and this will degrade the plant and soil quality. To overcome these problems, this paper proposes an automatic cocoa plant disease detection and pesticide recommendation system using computer vision and deep learning techniques. The proposed system was evaluated on several cocoa plant images, and an accuracy of 97.36% was obtained in disease classification. The proposed system can help cocoa farmers in the detection of cocoa plant diseases in the early stage and reduce the use of excessive pesticides, thus promoting sustainable agriculture practices.

Plant phenotyping relevance

ココア植物画像から病害状態を推定する画像・深層学習手法が研究の中心であり、病害分類性能も評価しているため、植物フェノタイピング手法として収録する。

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