Agricultural Pest and Disease Detection in Banana Plant

Abstract

Agriculture is the primary source in providing food for the entire nation. Consequently, agriculture is the fundamental origin of food supply. The contributions of agriculture include increase in employment opportunity and economy of the nation. According to IBEF, in India 58% of entire population depends on agriculture as their main occupation. Currently 81.1% of the total agricultural production is produced by livestock farmers. There will be 50% of loss in yield because of pest and disease. The disease in the plant excitants farmers to use unsuitable pesticide which causes unfavorable consequences. This may lead to the reduction in soil and food quality. Besides it has an adverse impact on human life. Nevertheless, farmers are heedless of these effects. The diseases which are naturally created will cause a serious impact on yields also it will bring down the quality of the food and soil. The symptoms which can cause the less yield are infinitesimal and because of the less human vision potentiality it is difficult to recognize the disease. Plant diseases will require genuine identification and proper categorization of the crops. The developed advanced methodology will identify the diseases, percentage of spread area, pesticide name with the quantity of the pesticide require to heal particular disease using image processing technique.

Plant phenotyping relevance

画像処理によりバナナ葉の病害を識別し、病害の広がり面積という植物の病徴・重症度を推定する方法が研究の中心であるため、農薬助言を含むが植物病害フェノタイピングとして採用する。

Code and data availability

The paper describes a banana leaf disease detection model (100 leaf images, TensorFlow Lite on Raspberry Pi) but provides no public dataset, code, model checkpoint, or any availability statement or URL for its images or analysis. Figures are embedded in the article itself, and no supplement is mentioned.

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