Banana Crop Disease Detection Using Deep Learning Approach

Abstract

Abstract: India is primarily an agricultural country where a significant portion of the population depends on agriculture for their livelihood. However, plant diseases are a major issue for farmers, hindering their efforts to cultivate crops. Delayed detection of diseases can result in a significant loss of yield and income for farmers. To mitigate these negative impacts, we have created a project that utilizes machine learning and deep learning techniques such as image processing and Convolutional Neural Networks to detect various diseases in banana plants. Our machine learning model enables early detection of diseases, which can help minimize the loss of yield and enable farmers to take necessary preventive measures to halt the spread of diseases in their crops

Plant phenotyping relevance

バナナ植物の病害状態を画像処理と深層学習で推定する手法が研究の中心であり、植物病害フェノタイピングに該当する。

Code and data availability

The paper describes a CNN for banana disease detection but provides no public dataset, code, model, or supplement with availability language or URLs. The dataset is described only as assembled from the internet, Kaggle, and manual captures, with no repository or access details.

No evidence-backed public reproduction asset is currently recorded.