Fusarium head blight (FHB) is a serious threat for the quality of wheat products. In order to breed wheat lines with improved FHB resistance we investigated several FHB resistance components in Croatian and international wheat lines. We tested for Type I resistance (resistance against initial infection), Type II resistance (resistance against spreading), Type III resistance (DON resistance) and general FHB resistance. This information allows us to select proper parents used in future crosses to improve FHB resistance by combining and improving the level of individual resistance components. The genotypes Divana and SirbanProlifik showed the highest resistance levels against initial infection. The genotypes Libellula and Srpanjka had the highest resistance level against FHB spreading. The genotype Renan was the most DON resistant line.
Authors:D. Novoselović, G. Drezner, A. Lalić, S. Grljušić, and J. Gunjača
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.
Authors:Ž. Kurtanjek, D. Horvat, G. Drezner, and D. Magdić
Gluten proteins composed of gliadins and glutenins are important contributors to the wheat quality properties. Twenty-eight winter wheat cultivars differing in bread processing quality were collected at the experimental fields of the Agricultural Institute Osijek, Croatia, in growing season 2006/2007.The HMW-GS composition and gliadin contents were determined by SDS-PAGE and RP-HPLC, respectively, with the aim to determine their relationship with wheat quality properties. Based on gliadins and HMW-GS data for 28 wheat cultivars PLS models were developed for the prediction of 15 baking quality parameters.NIPALS algorithm was applied for the evaluation of the latent variables and regression coefficient parameters. The obtained 4-th order models have average coefficients of determination R2=0.80.Determined variable importance in projections (VIP) coefficients revealed that HMW-GS data have the dominant influence on the baking quality parameters. For extensographic and farinographic properties the Glu-D1 locus has the main VIP coefficient while Glu-B1 locus is the most important for the indirect quality parameters. The derived PLS models and VIP coefficients could be used in molecular based wheat selection and breeding program.
Authors:G. Drezner, J. Gunjača, D. Novoselović, and D. Horvat
Ten winter wheat (
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.
Authors:D. Horvat, Z. Jurković, G. Drezner, G. Šimić, D. Novoselović, and K. Dvojković
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.
Authors:V. Guberac, S. Maric, M. Bede, J. Kovacevic, G. Drezner, A. Lalic, M. Josipovic, M. Krizmanic, T. Juric, and D. Kis
The aim of this research was to examine influence of sowing rate on grain yield of four new winter wheat cultivars, taking in account their genetic characters. Statistical analysis of the obtained results showed that the sowing rate influence on the grain yield was not statistically significant. On the other hand, various sowing rates had highly significant influence on the ear number per a unit area. The largest number of ears was achieved by the sowing rate of 700 germinable seeds/m
).Difference in grain yield between examined cultivars was highly significant (P<0.01) while the difference in number of ears per a unit area was significant (P<0.05). The highest average yield and highest number of ears in the two-year period were achieved by the cultivar AG 5.12 (8.56 t/ha and 770 ears/m
).Since a satisfactory and statistically significant grain yield was achieved, even with a lower sowing rate, both during and in the average of the two year research, the author’s advice wheat producers to apply the above mentioned. In this way total production costs would be decreased to a lower rate.