A durian leaf image dataset of common diseases in Vietnam for agricultural diagnosis

Abstract

Agriculture plays a vital role in Vietnam’s economy, with durian being a key high-value crop that supports millions of farmers. However, durian leaves are highly susceptible to pests, diseases, and environmental stressors, negatively impacting yield and quality. This study introduces a dataset of 2595 durian leaf images, categorized into six classes: 484 healthy leaves and 2111 diseased leaves spanning Blight (440), Colletotrichum (400), Algal (462), Phomopsis (411), and Rhizoctonia (398). The images were collected from durian orchards across Vietnam under diverse conditions, then background-removed, resized to 400 × 400 pixels, and manually annotated with expert guidance. This dataset provides a valuable resource for advancing research in automated plant disease detection, enabling the development of computer vision models for early diagnosis and precision farming, thereby supporting sustainable durian production and improved crop productivity.

Plant phenotyping relevance

植物葉の病徴を画像として収集・注釈したデータセットが研究の中心であり、植物病害状態の画像ベース表現型解析に利用できる。

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