Improvement of end‐use quality in wheat (Triticum aestivum L.) depends on thorough understanding of the influences of environment, genotype, and their interaction. Our objectives were to determine relative contributions of genotype, environment, and G × E interaction to variation in quality characteristics of hard red winter wheat. Eighteen winter wheat genotypes were grown in replicated trials at six locations in Nebraska and one site in Arizona in 1988 and 1989. Harvested grain was micromilled to produce flour samples for evaluation of protein concentration, mixing characteristics, and sodium dodecylsulfate (SDS) sedimentation. Kernel hardness was determined by microscopic evaluation of individual kernels. Genotype, environment, and interaction effects were found to significantly influence variation in all quality parameters. Variances of quality characteristics associated with environmental effects were generally larger than those for genetic factors. The magnitude of G × E effects were found to be of similar magnitude to genetic factors for mixing tolerance and kernel hardness, but were smaller for flour protein concentration, mixing time, and SDS sedimentation value. Significant differences among genotype responses (b‐values) were observed in the regressions of genotype mean on location means for each quality parameter. There were few instances of significant deviations from regression. Positive correlations between genotype grand mean and genotype b‐values for flour protein, mixing time, and mixing tolerance suggest that simultaneous improvement in both mean and stability for these traits may be difficult. Based on these results, environmental influences on enduse quality attributes should be an important consideration in cultivar improvement efforts toward enhancing marketing quality of hard red winter wheat.

Data from USDA‐coordinated winter wheat (Triticum aestivum L.) regional performance nurseries collected over the time period 1959 to 2008 were used to estimate genetic gain (loss) in grain yield, grain volume weight, days to heading, and plant height in winter wheats adapted to the Great Plains of North America. In both the Southern Regional (SRPN) and Northern Regional Performance Nurseries (NRPN), linear regression revealed significant positive relationships between relative grain yields of advanced breeding lines and calendar year of the nursery trial. The estimated genetic gain in grain yield potential since 1959 was approximately 1.1% (of the control cultivar Kharkof) yr−1 for all entries in the SRPN, and 1.3% yr−1 if only the most productive entry was considered. For the NRPN, the estimates of genetic gain in grain yield were 0.79% yr−1 for all entries, and also 0.79% yr−1 for the most productive entry. Linear regressions of relative grain yields vs. year over the time period 1984 to 2008, however, showed no statistically significant trend in the SRPN. For the same time period in the NRPN, a statistically significant positive slope of 0.83 was observed, though the coefficient of determination (R2) was only 0.28. Relative grain yields of Great Plains hard winter wheats may have peaked in the early to mid‐1990s, and further improvement in the genetic potential for grain yield awaits some new technological or biological advance.

Genetic diversity is the basis for successful crop improvement and can be estimated by different methods. The objectives of this study were to estimate the genetic diversity of 30 ancestral to modern hard red winter wheat (Triticum aestivum L.) cultivars adapted to the Northern Great Plains using pedigree information, morphological traits (agronomic measurements from six environments), end-use quality traits (micro-quality assays on 50 g grain or milled flour samples for the six environments), and molecular markers (seed storage proteins separated using SDS-PAGE, 51 SSRs, and 23 SRAP DNA markers), and to determine the relationships of genetic distance estimates obtained from these methods. Relationships among diversity estimates were determined using simple (Pearson) and rank (Spearman) correlation coefficients between distance estimates and by clustering cultivars using geneticdistances for different traits. All methods found a wide range in genetic diversity. The genetic distance estimates based on pedigree had the highest values due to possible over-estimation arising from model assumptions. The genetic diversity estimates based on seed storage protein were lowest because they were the major determinants of end-use quality, which is a highly selected trait. In general, the diversity estimates from each of the methods were positively correlated at a low level with the exceptions of SRAP diversity estimates being independent of morphologic traits (simple correlation), SDS-PAGE, and SSR diversity estimates (rank correlation). However, SSR markers, thought to be among the most efficient markers for estimating genetic diversity, were most highly correlated with seed storage proteins. The procedures used to accurately estimate genetic diversity will depend largely upon the tools available to the researcher and their application to the breeding scheme.

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