Image dataset of ten durian diseases captured in real-field conditions from a
family orchard in Vinh Long, Vietnam
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Nguyen T
Data Brief
2025[Dec]; 63
(?): 112244
PMID41342007
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This dataset comprises 5452 images of durian plant parts-including leaves,
flowers, branches, stems, and roots-affected by ten common disease classes. The
images were captured from one family-owned durian orchard and four nearby
orchards in Vinh Long Province, Vietnam. Each class contains approximately
405-427 raw images, photographed using an iPhone 14 under natural field
conditions. These conditions simulate typical farmer photography practices,
featuring varied angles, inconsistent lighting, and complex environmental
backgrounds, resulting in significant visual noise. All raw JPEG images were
manually reviewed and cropped on macOS systems using MacBook devices equipped
with Apple M4 chips to focus on disease-affected regions, reduce file size, and
minimize background noise. The processed, cropped images are provided in PNG
format with variable dimensions. Images were resized to 224×224 pixels only
during model training for machine learning experiments. Disease symptoms were
verified in collaboration with plant pathologists to ensure accurate
classification. This dataset is publicly available on Mendeley Data and is
suitable for developing and evaluating machine learning models in plant disease
classification. It is particularly valuable for testing model performance under
real-world, noisy conditions and for supporting the creation of mobile or
edge-based diagnostic tools in agriculture.
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