Effect of high and low molecular weight glutenin subunits, and subunits of gliadin on physicochemical parameters of different wheat genotypes

Identification of functional properties of wheat flour by specific tests allows genotypes with appropriate characteristics to be selected for specific industrial uses. The objective of wheat breeding programs is to improve the quality of germplasm bank in order to be able to develop wheat with suitable gluten strength and extensibility for bread making. The aim of this study was to evaluate 16 wheat genotypes by correlating both glutenin subunits of high and low molecular weight and gliadin subunits with the physicochemical characteristics of the grain. Protein content, sedimentation volume, sedimentation index, and falling number values were analyzed after the grains were milled. Hectoliter weight and mass of 1000 seeds were also determined. The glutenin and gliadin subunits were separated using polyacrylamide gel in the presence of sodium dodecyl sulfate. The data were evaluated using variance analysis, Pearson's correlation, principal component analysis, and cluster analysis. The IPR 85, IPR Catuara TM, T 091015, and T 091069 genotypes stood out from the others, which indicate their possibly superior grain quality with higher sedimentation volume, higher sedimentation index, and higher mass of 1000 seeds; these genotypes possessed the subunits 1 (Glu-A1), 5 + 10 (Glu-D1), c (Glu-A3), and b (Glu-B3), with exception of T 091069 genotype that possessed the g allele instead of b in the Glu-B3.

Non-parametric stability analyses of dough properties in wheat

AbstractLiterature has unveiled that a paper has not been published yet on using non-parametric stability statistics (NPSSs) for evaluating genotypic stability in dough properties of wheat. Accordingly, the effects of genotype (G), environment (E) and GE interaction (GEI) on alveograph parameters, i.e. dough baking strength (W) and its tenacity (P)/extensibility (L), of 18 wheat (T. aestivum L.) genotypes were studied under irrigated field conditions in an 8-year trial (2006-2014) in central Turkey. Furthermore, genotypic stability for W and P/L was determined using 8 NPSSs viz. RM-Rank mean, RSD-Rank’s standard deviation, RS-Rank Sum, TOP-Ranking, Si(1), Si(2), Si(3) and Si(6) rank statistics. The ANOVA revealed that W and P/L were primarily controlled by E, although G and GEI also had significant effects. Among the 8 NPSSs, only RM, RS and TOP statistics were suitable for detecting the genotypes with high stable and bread making quality (e.g. G1 and G17). In conclusion, using RM, RS and TOP statistics is advisable to select for dough quality in wheat under multi-environment trials (METs).