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Impact of grain morphology and the genotype by environment interactions on test weight of spring and winter wheat (Triticum aestivum L.)

Yabwalo, Dalitso N., Berzonsky, William A., Brabec, Daniel, Pearson, Thomas, Glover, Karl D., Kleinjan, Jonathan L.
Euphytica 2018 v.214 no.7 pp. 125
Triticum aestivum, algorithms, cultivars, flour, genetic improvement, genotype, genotype-environment interaction, phenotypic variation, plant breeding, prices, regression analysis, spring, spring wheat, statistical models, variance, wheat classes, winter, winter wheat, South Dakota
Wheat (Triticum aestivum L.) market grades and prices are determined in part by test weight (TW). Millers value high TW because it is typically associated with higher flour extraction rates and better end-use quality. Test weight is expected to be influenced by other directly quantifiable grain attributes such as grain length (GL), grain width (GW), shape, single-grain-density (SGD), thousand-grain-weight (TGW), and packing efficiency (PE). The objectives of this study were to: (1) determine the primary morphological grain attributes that comprise TW measurements for winter and spring wheat classes; and (2) determine TW stability and genotype and genotype × environment interactions (GEIs) of the attributes that comprise TW. A market class representative group of 32 hard spring and 24 hard winter wheat cultivars was grown at several locations in South Dakota in 2011 and 2012. A regularized multiple regression algorithm was used to develop a TW model and determine what grain attribute reliably predicts TW. A GGE biplot was used for stability and GEI analyses whereas a linear mixed model was used for variance analyses. Data were collected on eight grain traits: TW, SGD, TGW, protein concentration, GW, GL, shape, size, and PE. Observations showed that in both spring and winter wheat, SGD accounted for over 90% of the phenotypic variation of TW. Cultivars with stable and high TW were identified in both wheat classes. Apart from TW; significant (p < 0.0001) genotype, environment, and GEI variances were observed for GW and SGD, a more direct measure of which could help improve genetic gain for TW.