Multi-environment field trials for wheat yield, stability and breeding progress in Germany

Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015 - 2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits. Beside grain yield, ten agronomic traits, four baking quality traits, plant height, heading date, maturity date and six fungal disease infection indices are included. Additionally, we provide management records, including fertilizer use, plant protection measures, irrigation, and weather data. We demonstrate how this dataset can address four agronomic questions related to GxExM interactions. Further potential applications of the dataset include empirical analyses, genomic and enviromic analyses for breeding targets, or development of decision-supporting models for agricultural management and policy decisions.

具有时空变异的多环境试验（Multi-environmental trials, MET）是解析作物基因型-环境-管理（genotype-environment-management, GxExM）互作机制的关键手段。本研究公开了一套针对德国冬小麦的多环境试验数据集。该数据集涵盖2015至2020年共6年、6个试验地点的多环境试验，包含9种作物管理方案（由3种处理组合构成，各地点与年份的处理分布并不均衡），共测试了1963年至2016年间审定的228个小麦品种，总计包含526751条数据点，覆盖24个性状。除籽粒产量外，数据集涵盖10个农艺性状、4个烘焙品质性状、株高、抽穗期、成熟期以及6种真菌病害侵染指数。此外，本数据集还附带提供了肥料施用、植保措施、灌溉情况及气象数据等管理记录。本研究展示了该数据集可用于解答4项与GxExM互作相关的农艺学问题。该数据集的其他潜在应用方向包括：实证分析、面向育种目标的基因组与环境组分析，以及面向农业管理与政策制定的决策支持模型开发。