Crop cultivar performance is a result of combined effects of genotype, environment and genotype × environment (G × E) interaction. To effectively generate reliable estimates of crop yield the magnitude and patterns of G × E in regional yield trials should be specified. This research aimed to (1) investigate existing possible mega-environments (ME) and suitability of test locations for winter wheat zoning, and (2) determine the role of climatic factors in clustering patterns of G × E. Winter wheat yield data from a three-year nationwide yield trial consisting of 24 genotypes grown in 24 test environments supplemented with 37 climatic factors were subjected to empirical and analytical analyses. Standard deviation-scaled genotype main effect and G × E interaction (SD-GGE) biplot methodology, factorial regression and partial least square regression were applied to both analyses. The combined ANOVA showed that the environmental effect was the main source of variation (83%), and the magnitude of G × E interaction was sixfold greater than genotype alone. The SD-GGE biplot confirmed non-repeatable patterns for grouping of test locations across years, indicating significant (P < 0.01) rank-change location-by-year interactions and existence of strong "crossover" G × E interactions. This led to the conclusion that the winter wheat growing region in Iran consists of a single but complex ME for grain yield, suggesting that high-yielding-and stable winter wheat genotypes should be developed for the entire region rather than genotypes adapted to specific agro-ecological regions. Precipitation (monthly and total) and temperature (minimum, maximum and average) accounted for 25.4% and 56.8% of total G × E.

作物品种性能是基因型、环境和基因型×环境（G×E）相互作用综合效应的结果。为了有效地产生作物产量的可靠估计，应指定区域产量试验中 G × E 的大小和模式。本研究旨在 (1) 调查现有可能的大环境 (ME) 和冬小麦分区试验地点的适用性，以及 (2) 确定气候因素在 G × E 聚类模式中的作用。为期三年的全国产量试验由在 24 个测试环境中生长的 24 个基因型组成，并辅以 37 个气候因素，进行了实证和分析分析。标准偏差标度的基因型主效应和 G × E 相互作用 (SD-GGE) 双标法，因子回归和偏最小二乘回归应用于这两种分析。组合方差分析表明，环境影响是变异的主要来源（83%），G × E 相互作用的幅度比单独的基因型大六倍。SD-GGE 双标图证实了跨年测试位置分组的不可重复模式，表明显着（P  < 0.01) 逐年排名变化位置的相互作用和强“交叉”G × E 相互作用的存在。由此得出的结论是，伊朗的冬小麦种植区由一个单一但复杂的粮食产量 ME 组成，这表明应该为整个地区开发高产且稳定的冬小麦基因型，而不是适应特定农业的基因型。生态区。降水量（月和总量）和温度（最小值、最大值和平均值）分别占总 G×E 的 25.4% 和 56.8%。