Extensive Repository of Jackfruit Leaf Images Capturing Health States and Developmental Stage Patterns in Natural Environments

Published: 3 September 2025| Version 1 | DOI: 10.17632/4yvym5m8n8.1
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Description

This dataset contains raw images of jackfruit (Artocarpus heterophyllus) leaves categorized into five classes: Dried, Healthy, Leaf_Miner, Senescence, and Young. The images were collected using smartphone devices from Savar and Rajbari districts, Bangladesh under natural field conditions. Each image represents different health conditions and growth stages of jackfruit leaves. The dataset is unprocessed, making it suitable for developing models on leaf health and growth stage detection, as well as general agricultural image analysis. Dataset Classes and Image Counts: Dried:500 images Healthy:500 images Leaf_Miner:500 images Senescence:500 images Young:500 images Image Details: Original image resolution:3072 x 4096 Resized image resolution:480 x 560 Image formate:JPG Color mode:RGB Collection device: Smartphone camera Location: Savar and Rajbari districts, Bangladesh

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Institutions

  • Daffodil International University

Categories

Computer Vision, Machine Learning, Supervised Learning, Agricultural Development, Convolutional Neural Network, Deep Learning, Agricultural Biotechnology, Agriculture

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