A global dataset on mungbean for managing seed yield and quality

Area of Science:

• Agricultural Science
• Agronomy
• Plant Science

Background:

• Mungbean is a protein-rich legume with expanding global cultivation.
• Optimizing mungbean yield and nutritional quality is crucial for food systems and sustainable agriculture.
• Current management practices for mungbean remain underexplored globally.

Purpose of the Study:

• To compile a comprehensive global open dataset on mungbean crop management practices.
• To analyze the impact of key agronomic factors on mungbean seed yield and quality.
• To facilitate research and optimization of mungbean cultivation worldwide.

Main Methods:

• A meta-analysis of 2,154 observations from 227 studies published between 1984 and 2023.
• Inclusion of data on fertilization, irrigation, row spacing, seeding rate, and planting date.
• Development of an open-access dataset for agricultural research.

Main Results:

• The dataset provides insights into the effects of various management practices on mungbean seed yield and quality.
• Identified key agronomic variables influencing crop performance and nutritional content.
• Established a foundation for data-driven optimization of mungbean cultivation.

Conclusions:

• The developed open dataset is a valuable tool for researchers and agronomists.
• Enables optimization of mungbean management for enhanced seed yield and nutritional value.
• Supports the advancement of food security and sustainable agricultural practices through improved mungbean production.