Abstract
This study investigates how genetic and climatic factors affect parameters of breadmaking quality of wheat kernel and flour starch component. Nine wheat cultivars with different combinations of HMW-GS were grown in three production years. Various rheological devices such as Falling Number (FN), Farinograph, Amylograph, Mixolab and SDmatic were used for characterization of milled wheat samples. The most results showed that climatic factors affected parameters of breadmaking quality of wheat kernel and flour starch component more than HMW-GS composition. However, some results of the bread making quality parameters that are considered to be very reliable indicators of changes in starch component of wheat in wet years, such as FN and maximum peak of viscosity by Amylograph, were dependent of HMW-GS composition.
Highlights
The first factor was the production year, whereas the second factor was the group of wheat cultivars with different combinations of high molecular weight (HMW)-glutenin subunits (GS) followed by the comparison of mean values based on Tukey’s multiple means comparison tests, correlation matrix (Pearson), linear regression analysis and principal component analysis (PCA)
Significant effect of the production year (Y) was found for the sprouted kernels content (SPC), falling number (FN), maximum peak of viscosity by Amylograph (AMS), water absorption by Farinograph (WA), degree of softening by Farinograph (DS), rate of starch enzymatic degradation (γ) by Mixolab, C3-C4 by Mixolab, C5-C4 by Mixolab, and level of damage starch by Sdmatic (UCD KSDAM) (p
Based on the results of two-factorial analysis of variance (ANOVA), it could be concluded that climatic factors that prevailed in 2008, 2009, and 2010 affected parameters of breadmaking quality of wheat kernel and flour starch component more than HMW-GS composition of the examined wheat cultivars
Summary
The aim of this study was to examine how genetic and climatic factors cause changes of breadmaking quality parameters of wheat kernel and flour starch component. The first factor was the production year, whereas the second factor was the group of wheat cultivars with different combinations of HMW-GS followed by the comparison of mean values based on Tukey’s multiple means comparison tests, correlation matrix (Pearson), linear regression analysis and principal component analysis (PCA).
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