The impact of agricultural technologies on crop yield is influenced by the environment type (ENVT) as determined by weather and soil. Understanding the correlation between the ENVT of the testing site in relation to the ENVT of the target production region is important for the evaluation and scaling out of agricultural technologies. Here we propose and apply the first explicit method to characterize ENVTs for major rainfed maize, soybean, and wheat producing regions in the United States. We combined a tested spatial framework, Technology Extrapolation Domain (TED), with crop modeling, long-term (30-y) daily weather records, and soil and management databases to calculate the frequency of ENVTs per crop for major harvested areas. Each ENVT was determined based on the intensity of drought and heat stress during key crop stages for yield determination. The ENVT repeatability was calculated based on the frequency of the most dominant ENVT in each TED. We found that inter-annual variation in drought and heat stress was larger than spatial variation. Our ENVTs explained 2x to 7x larger portion of the variance in actual yield compared to the existing TED framework that is based on long-term annual climate means and soil water storage. For maize and soybean, ca. 30% of their harvested area was located in TEDs with highly repeatable ENVTs (>66% of years). In contrast, only 15% of the wheat harvested area was located in TEDs with high ENVT repeatability. In comparison to the TED framework, the ENVTs defined here can help better capture G×E×M interactions and determine the environmental correlation between testing sites and target production environments.

农业技术对作物产量的影响受由天气和土壤决定的环境类型 (ENVT) 的影响。了解测试地点的 ENVT 与目标生产区域的 ENVT 之间的相关性对于农业技术的评估和扩展很重要。在这里，我们提出并应用第一个明确的方法来表征美国主要雨养玉米、大豆和小麦产区的 ENVT。我们将经过测试的空间框架、技术外推域 (TED) 与作物建模、长期（30 年）每日天气记录以及土壤和管理数据库相结合，以计算主要收获地区每种作物的 ENVT 频率。每个 ENVT 都是根据关键作物阶段的干旱和热应激强度确定的，以确定产量。ENVT 可重复性是根据每个 TED 中最主要的 ENVT 的频率计算的。我们发现干旱和热应激的年际变化大于空间变化。与基于长期年度气候平均值和土壤蓄水量的现有 TED 框架相比，我们的 ENVT 解释了实际产量差异的 2 到 7 倍. 对于玉米和大豆，约。他们 30% 的收获面积位于具有高度可重复 ENVT 的 TED（>66% 的年份）。相比之下，只有 15% 的小麦收获面积位于具有高 ENVT 可重复性的 TED。与 TED 框架相比，这里定义的 ENVT 可以帮助更好地捕获 G×E×M 交互并确定测试站点和目标生产环境之间的环境相关性。