Gilbert Catherine, Martin Nicolas
University of Illinois at Urbana-Champaign, Department of Crop Sciences, Urbana, IL, United States.
Front Plant Sci. 2024 Mar 25;15:1310461. doi: 10.3389/fpls.2024.1310461. eCollection 2024.
This research introduces a novel framework for enhancing soybean cultivation in North America by categorizing growing environments into distinct ecological and maturity-based zones. Using an integrated analysis of long-term climatic data and records of soybean varietal trials, this research generates a zonal environmental characterization which captures major components of the growing environment which affect the range of adaptation of soybean varieties. These findings have immediate applications for optimizing multi-environment soybean trials. This characterization allows breeders to assess the environmental representation of a multi-environmental trial of soybean varieties, and to strategize the distribution of testing and the placement of test sites accordingly. This application is demonstrated with a historical scenario of a soybean multi-environment trial, using two resource allocation models: one targeted towards improving the general adaptation of soybean varieties, which focuses on widely cultivated areas, and one targeted towards specific adaptation, which captures diverse environmental conditions. Ultimately, the study aims to improve the efficiency and impact of soybean breeding programs, leading to the development of cultivars resilient to variable and changing climates.
本研究引入了一种新颖的框架,通过将种植环境划分为不同的生态和基于成熟度的区域,来提高北美的大豆种植水平。通过对长期气候数据和大豆品种试验记录进行综合分析,本研究生成了一个区域环境特征描述,该描述涵盖了影响大豆品种适应范围的生长环境的主要组成部分。这些发现对优化多环境大豆试验具有直接应用价值。这种特征描述使育种者能够评估大豆品种多环境试验的环境代表性,并据此制定测试分布策略和试验地点布局。通过大豆多环境试验的历史场景,使用两种资源分配模型展示了这一应用:一种旨在提高大豆品种的总体适应性,侧重于广泛种植区域;另一种旨在实现特定适应性,涵盖多样的环境条件。最终,该研究旨在提高大豆育种计划的效率和影响力,从而培育出能适应多变气候的品种。