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Selection of winter wheat (Triticum aestivum L.) genotypes requires testing programs with complementary locations that sample environments of interest with minimal duplication. The goal of the current study was to improve prediction of genotype performance in the highly variable environments of the central Great Plains in the United States by estimating the contributions of genotype, location, and year to wheat yield variability and identifying subgroups of test locations that minimize crossover genotype-by-environment interaction. Variance components were estimated from Kansas wheat performance data from 17 locations from 1982 to 2002. Annual data sets balanced for genotypes and environments were used to generate genotype, genotype-by-environment biplots that could objectively separate locations into groups with the same top-yielding genotype. Location, year, and their interaction introduced the greatest proportion of the variability in wheat performance test yields. Frequency of common grouping during the 21-year period was used to construct six groups of test locations representing unique target environments. Evaluation of the six groups using results from two subsequent years revealed that they generally agreed with location groups observed in the previous 21 years. Smaller regional genotype-by-environment variance component estimates compared with statewide estimates further confirmed the effectiveness of the pro posed six regions for reducing genotype-by-environment interaction.