ArticleScientific data2025
A global dataset on mungbean for managing seed yield and quality.
Article in Scientific data, 2025. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- From Model to Crop: Roles of Macroautophagy inGenes · 2025Review
- A global dataset on mungbean for managing seed yield and quality.Scientific data · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mungbean, a protein- and nutrient-rich legume widely grown in Asian countries, is now expanding to other regions. With increasing global demand for nutritious foods and more sustainable agricultural practices, mungbean represents a valuable opportunity to diversify food systems and improve global nutrition. However, management practices to optimize seed yield and quality (including seed oil and protein concentration) remain largely unexplored due to the recent introduction of this crop in many parts of the world. This study aims to create a global open dataset of key crop management practices and their impact on seed yield parameters and quality. This dataset included 227 studies published between 1984 and 2023, comprising 2,154 observations. It focuses on key agronomic practices, including fertilization, irrigation, row spacing, seeding rate, and planting date. By providing comprehensive insights into mungbean cultivation, this open-access dataset enables researchers and agronomists to optimize management practices, identify research gaps, and enhance seed yield and nutritional quality. It serves as a valuable tool for improving food security and sustainable agriculture.
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Registered trials
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