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Image dataset of Taro Leaf Blight disease collected from the West African Sub-Region.

Data in brief · 10 Jul 2025 · 10.1016/j.dib.2025.111869

Abstract

This dataset encompasses an extensive collection of 18,248 high-resolution JPEG images, documenting various stages of Taro Leaf Blight (TLB) infection in Taro plants across West Africa. TLB, primarily caused by the pathogen Phytophthora colocasiae, manifests through necrotic leaf spots, white sporangia bands, and orange droplets, severely impacting the agricultural output and economic stability of smallholder farmers in the region. The images represent a range of infection stages-early, mid, late, and healthy conditions-captured during the dry and early rainy seasons in Nigeria and Ghana using smartphones equipped with high-resolution cameras. This dataset was carefully curated to help in the development and training of machine learning models for early and accurate detection of TLB, a crucial step towards effective disease management. By enabling the application of advanced diagnostics through technologies such as smartphone apps and AI-based analysis tools, this dataset not only aims to enhance the technological capabilities within agricultural sectors but also serves as a vital educational resource. Researchers and developers can utilize this dataset to create and refine models that diagnose plant diseases promptly, thereby allowing for timely interventions that can prevent widespread crop damage and subsequent economic losses. Additionally, the dataset supports ongoing efforts to integrate artificial intelligence with traditional farming practices, offering a bridge between advanced technological solutions and accessible applications for resource-limited settings. The potential reuse of this dataset extends beyond disease identification; it encompasses agricultural research, educational purposes, and further development of automated systems for plant health monitoring, making it a cornerstone for future innovations in agricultural technology and management strategies.

Plant phenotyping relevance

タロイモ葉の病害症状を画像で記録した大規模データセットであり、植物の病害状態を推定する画像ベース表現型解析の基盤として、データセット自体が中心的成果である。

abstractThis dataset encompasses an extensive collection of 18,248 high-resolution JPEG images, documenting various stages of Taro Leaf Blight (TLB) infection in Taro plants across West Africa.
abstractThis dataset was carefully curated to help in the development and training of machine learning models for early and accurate detection of TLB

Code and data availability

The paper is a Data in Brief describing a public plant-phenotyping image dataset (18,248 taro leaf blight images) deposited on Mendeley Data with an explicit direct URL and DOI, matching an allowed URL exactly.

Datasetpublic

tion • Institution : University of Lagos, Akoka. Kwame Nkrumah University of Science and Technology • City/Town/Region: Abakaliki, Ebonyi, Izzi, Ezza North, Agbani, Ngwo, Ashanti. • Country : Nigeria and Ghana Data accessibility Repository name: Mendeley Data Data identification number: 10.17632/3knm93dkc5.1 Direct URL to data: https://data.mendeley.com/datasets/3knm93dkc5/1 Related research article Nwaneto, C., Yiinka-Banjo, C., Ugot, O. A., Annor, T., & Umeugochukwu, O. (2024). EARLY DETECTION OF THE TARO LEAF BLIGHT DISEASE IN THE WEST AFRICAN SUB-REGION USING DEEP IMAGE CLASSIFICATION MODELS. Smart Agricultural Technology , 100,636. 1 Value of the Data • This dataset is important for dev

Open resource ↗Mendeley Data · 10.17632/3knm93dkc5.1 · lines:1-60

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