Related Experiment Video
Updated: Mar 14, 2026
15:30
A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
Published on: August 5, 2020
12.7K
A global experimental dataset for assessing grain legume production
Charles Cernay1, Elise Pelzer1, David Makowski1
1UMR Agronomie, INRA, AgroParisTech, Université Paris-Saclay, 78850 Thiverval-Grignon, France.
Scientific Data
|September 28, 2016
Summary
This study compiles global grain legume performance data from 173 articles, covering 39 species across five continents. The accessible dataset aids in identifying high-yielding legume varieties for improved agriculture and food security.
Area of Science:
- Agricultural Science
- Agronomy
- Environmental Science
Background:
- Global grain legume diversity is underutilized, despite their importance in human diets, animal feed, and environmental sustainability.
- There is a need for experimental data to assess and identify high-performing grain legume species.
- Existing data on legume performance is fragmented, hindering global assessments.
Purpose of the Study:
- To create a comprehensive, reusable dataset of grain legume field experiment results.
- To facilitate the identification of superior grain legume species for enhanced agricultural productivity.
- To support global assessments of grain legume production potential and environmental benefits.
Main Methods:
- Compiled data from 173 published articles on field experiments.
- Included 39 grain legume species across five continents.
- Structured data into a relational database with 198 standardized attributes, recording yield, biomass, nitrogen content, water use, and management practices for 8,581 crop-site-season-treatment combinations.
Main Results:
- Developed a relational database with 9 tables and 198 attributes from 8,581 experimental units.
- Data encompasses grain yield, biomass, nitrogen content, soil nitrogen, and water use for 39 grain legume species.
- Included post-legume crop yields (cereals, oilseeds) where available, alongside detailed management information (tillage, fertilization, irrigation, pest control).
Conclusions:
- The created dataset is freely reusable, easily updatable, and provides valuable, standardized information.
- This resource will aid in evaluating grain legume production globally and identifying promising species.
- Facilitates research into optimizing legume cultivation for food, feed, and environmental services.
