ArticleData in brief2024
Updating "machine learning imagery dataset for maize crop: A case of Tanzania" with expanded data to cover the new farming season.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Lightweight vision transformer and ResNet-9 models for real-time plant disease detection and pest classification with SHAP explainability.BMC plant biology · 2026Article
- Towards precision agriculture: A dataset for early detection of corn leaf pests.Data in brief · 2025Article
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Authors and funding
2 authors.
Funding
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Abstract
Maize Lethal Necrosis (MLN) and Maize Streak Virus (MSV) are among maize diseases which affect productivity in Tanzania and Africa at large. These diseases can be detected early for timely interventions and minimal losses. Machine learning (ML) has emerged as a powerful tool for automated diseases detection, offering several advantages over traditional methods. This article presents the updated dataset of 9356 imagery maize leaves to assist researchers in developing technological solutions for addressing crop diseases. The high-resolution imagery data presented in this dataset were captured using smartphone cameras in farm fields which were not selected in the previously published dataset. Also, data collection was taken in the range of three months from November 2022 to January 2023 to incorporate farming season not covered in the previously published dataset. The presented dataset can be used by researchers in the field of Artificial Intelligence (AI) to develop ML solutions and eliminate the need of manual inspection and reduce human bias. Developing ML solutions require large amount of data therefore, the updated and previously published datasets can be combined to accommodate diverse and wider applicability.
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