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Updated: May 10, 2025

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
A global dataset on mungbean for managing seed yield and quality
Natalia da Silva Volpato1, Federico M Gomez2, Víctor D Giménez2
1Department of Agronomy, Kansas State University, Manhattan, Kansas, US. volpato@ksu.edu.
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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