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A Comprehensive Genotype and Environment Assessment of Wheat Grain Ash Content in Oregon and Washington: Analysis of Variation

May 2009 Volume 86 Number 3
Pages 307 — 312
Craig F. Morris,1,2 Shuobi Li,3 G. E. King,4 Doug A. Engle,1 John W. Burns,5 and Andrew S. Ross6

USDA-ARS Western Wheat Quality Laboratory, Washington State University, Pullman Washington, 99164-6394. Names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by the USDA implies no approval of the product to the exclusion of others that may also be suitable. Corresponding author. Phone: +1.509.335.4062. Fax: +1.509.335.8573. E-mail: morrisc@wsu.edu Northwest A&F University, Yangling, Shaanxi 712100, China; on sabbatical at the Western Wheat Quality Laboratory. Department of Food Science & Human Nutrition, Washington State University, Pullman, WA 99164-6394; assigned to the Western Wheat Quality Laboratory. Department of Crop and Soil Sciences (retired), Washington State University, Pullman, WA 99164-6420. Department of Crop and Soil Science, Oregon State University, Corvallis, OR 97331-3002.


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Accepted March 17, 2009.
ABSTRACT

A comprehensive analysis of the variation in wheat grain ash content has not been previously conducted. This study assessed the relative contribution of genotype and environment to variation in ash content, with a particular aim of ascertaining the potential for manipulating the trait using contemporary adapted germplasm. A total of 2,240 samples were drawn from four years of multilocation field plots grown in the wheat production areas of Oregon and Washington states. Genotypes included commercial cultivars and advanced breeding lines of soft and hard winter, and soft and hard spring wheats with red and white kernel color, several soft white club wheats, and one soft white spring waxy wheat cultivar. In addition to ash, protein content, test weight, and Single Kernel Characterization System kernel hardness, weight and size were also measured. In total, 20 separate fully balanced ANOVA results were conducted. Whole model R2 values were highly significant, 0.62–0.91. Nineteen of the 20 ANOVA results indicated significant genotype effects, but the effects were not large. In contrast, environment effects were always highly significant with F values often one to two orders of magnitude larger than the genotype F values. The grand mean for all samples was 1.368% ash. For individual data sets, genotype means across environments varied ≈0.1–0.3% ash. The genotypes judged noteworthy because they had the highest least squares mean ash content were OR9900553 and ClearFirst soft white winter, NuHills hard red winter, Waxy-Pen and Cataldo soft white spring, and WA8010 and Lochsa hard spring wheats. Genotypes with lowest least squares mean ash were Edwin (club) soft white winter, OR2040073H hard red winter, WA7952 soft white spring, and WA8038 hard spring wheats. In conclusion, wheat grain ash is more greatly influenced by crop year and location than by genotype. However, sufficient genotype variation is present to plausibly manipulate this grain trait through traditional plant breeding.



This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. AACC International, Inc., 2009.