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  • Author or Editor: D. Novoselović x
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Ten winter wheat ( Triticum aestivum L.) cultivars were tested in randomized complete block design (RCBD) trials at one location (Osijek) for several agronomic and quality traits through six growing seasons (1996/97–2001/02). Data were employed to develop modeling strategy for exploring genotype by environment interaction (GEI) by using models based on information on genotypic and environmental variables. The relative size, hence importance of the GEI compared to main effects of genotypes and environments was estimated for all effects from simple additive model (genotypes, environments and residuals, last including both GEI and experimental error) while the AMMI2 model was used as a basis for comparison of the GEI patterns. The final step in modeling strategy was fitting factorial regression models to all analyzed traits using available genotypic and environmental covariates, until the best fit solution was found for each analyzed trait.Comparing the relative sizes of genotypic and GEI effects, the last one was sizeable smaller, for all traits except grain yield (GY), thousand-kernel weight (TKW), and Hagberg falling number (HFN). Fitting of genotypic and environmental covariates resulted in various solutions for different traits, most frequently employing single genotypic covariate — Glu-A1.Regardless of their relatively small size, the GEI effects in wheat quality traits can offer a better insight into fluctuations of varietal quality over a range of environmental conditions, as they can be successfully modeled using various genotypic and environmental covariates. The advantage of described approach is attainable in virtually any breeding program, because during the implementation of the program breeders routinely score for a number of genotypic and environmental variables.

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The objective of this paper was to evaluate the adequacy of different methods of planting in small plots and compared with the grain yield rank of wheat genotypes in large plots under different planting densities. Significant differences were found among cultivars, same cultivars under different planting densities, years of testing and planting densities. The estimated values of heritability in narrow sense for grain yield were high and varied from 68 to 99%, depending on the method of planting and planting density. Comparison of correlation among cultivar’s rank between Method 1 (planting with drilling machine) and other Methods (manual planting) revealed that these relationships were dependant upon the year of testing and varied from low to high, positive or negative and from significant to non-significant. The highest correlation was found between Method 1 and Method 3 (20 kernels/hill) in both years of testing. If we wish to test a larger number of genotypes from gene bank collections or advanced lines in early phase of breeding program for grain yield on small plots we can recommend the use of hill plots with planting density as close as possible to those in large plots.

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The gluten proteins of 15 winter wheat cultivars grown in eastern Croatia were studied for their contribution to the bread-making quality. Composition of high-molecular-weight glutenin subunits (HMW-GS) was analyzed by SDS-PAGE, while the quantity of gluten proteins was determined by combined extraction/RP-HPLC procedure. The results of the linear correlation analysis carried out on the particular gluten proteins and technological properties showed that the amount of total gluten content highly correlates with protein content. Among gluten proteins, the glutenins showed higher correlation with protein content, with pronounced influence of HMW-GS, than gliadins. Wet gluten content was significantly correlated to total gliadin quantity. Gluten index as gluten quality parameter was positively influenced by total glutenins and low-molecular-weight glutenin subunits (LMW-GS), and negatively, by the ratios of gliadin to glutenin (Gli/Glu), whereas the amount of gliadins was not important. Dough development time was strongly correlated with total gluten content, total glutenins and the Gli/Glu ratio. Dough mixing resistance was strongly affected by total glutenin content with pronounced influence of HMW-GS. Degree of dough softening is mainly negative influenced by total glutenins and ratio of Gli/Glu. Farinograph quality number as flour quality index was highly positively correlated with total glutenins, with emphasized influence of HMW-GS. The Gli/Glu ratio had the highest influence on dough maximum resistance. Dough extensibility showed moderate correlation with total gliadins. The results of the linear correlation indicated that loaves volumes were significantly influenced by total gluten proteins, HMW-GS and LMW-GS.

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