Improvement of quality-related traits of grains is a constant concern in white oat breeding programs, which challenges breeders to understand their dynamics. The performance of different genetic combinations must be thoroughly evaluated to make high nutritional quality cultivars available. This study aimed to estimate the heterosis on F 1 and F 2 generations, vigor loss, due to inbreeding, and correlation between the grain chemical components to understand the dynamics of these traits, considering two segregating oat progenies. The populations Albasul × UPF 15 (population 1) and IAC 7 × UFRGS 19 (population 2) were developed. Both populations showed transgressive segregant individuals. The combination Albasul × UPF 15 provided significant heterosis for traits β-glucan total and soluble fiber contents, while the population obtained by crossing IAC 7 × UFRGS 19 generated significant gain by heterosis for total fiber, insoluble fibers and non-structural carbohydrate contents. Considering the F 2 average for each population, one can observe that population 1 presents higher β-glucan and lipid contents than population 2. On the other hand, population 2 has higher protein content than population 1. In both populations, the non-structural carbohydrate content is strongly and negatively correlated whith protein, total and insoluble fibers. Correlations between total fibers and lipids and between total fibers and insoluble fibers were both positive and high in both populations.
The objective of this work was to compare uni- and multivariate biometric methods to evaluate the adaptability and stability of an important group of white oat (Avena sativa) cultivars grown in Southern Brazil. The used experimental design was a randomized complete block, in a factorial arrangement of 12 environments x 7 cultivars, with three replicates. The analysis of variance and the methods of Eberhart & Russel, Annicchiarico, and the harmonic mean of the relative performance of predicted genetic values (MHPRVG) were assessed. In the general comparison of the methods, the 'UPFA Gaudéria' and 'URS Guapa' genotypes were more stable regarding grain yield. The 'UPFA Gaudéria' and 'URS-21' genotypes stood out for hectoliter weight, presenting the best performances by the methods of Annicchiarico and the MHPRVG. For thousand-grain weight, all methods showed similar results, indicating that the 'UPFA Gaudéria' genotype presented the best results. The 'URS Guapa' genotype was superior when using the methods of Eberhart & Russel, Annicchiarico, and the MHPRVG. The uni- and multivariate methods evaluated are suitable to estimate with high confidence the adaptability and stability of cultivars for each targeted grain production, yield, and quality.
Oat is an important winter cereal used for food and feed. The industrial crop yield is an important parameter to characterize the quality of the grain and the conversion of this in processed products. Thus, this study aimed to identify the phenotypic interrelations of cause and effect between traits associated with the industrial yield of oat. The experiment was conducted in the growing seasons of 2013 and 2014. The experimental design was a randomized block, arranged in a factorial design: two (harvests) x 20 (genotypes), with six replicates. The oat genotypes formed different phenotypic classes for the measured traits. The industrial yield is directly associated with the test weight, grain yield and grain index. Phenotypic associations can be efficiently used in breeding programs aiming at oat indirect selection to improve industrial performance. Highlighted Conclusions 1. Different phenotypic classes are observed for the measured traits. 2. Milling yield is associated with the hectoliter weight, grain yield and grain index. 3. The milling yield can be improved by indirect selection.
Wheat is the main source of carbohydrate for humanity, being the second most-produced cereal in the world. Brazil is not self-sufficient in this crop, and the Country needs to import wheat to supply the national demand. The objective of this study was to analyze the performance of agronomic traits in wheat segregating populations in the F2 generation, and to estimate the genetic distance between the parents and the segregating populations , number of grains per ear (NGE), grain mass per ear (GME), grain yield per plant (GYP) and ear harvest index (EHI) were measured. The population 5 showed the greatest stature and population 4 showed less variability for the trait. All populations showed averages of NFT and GYP higher than the parents, indicating the presence of transgressive segregants, or presence of dominance in these traits. The grain mass per ear is the trait that contributes most to the distance between the genotypes. There was the formation of four groups by Tocher's grouping method and the population 3 is the most different to the parents, when considering all traits. Highlighted ConclusionThere is genetic variability for traits within wheat segregating populations.
Oat is an important winter cereal used for food and feed. The industrial crop yield is an important parameter to characterize the quality of the grain and the conversion of this in processed products. Thus, this study aimed to identify the phenotypic inter-relations of cause and effect between traits associated with the industrial yield of oat. The experiment was conducted in the growing seasons of 2013 and 2014. The experimental design was a randomized block, arranged in a factorial design: two (harvests) x 20 (genotypes), with six replicates. The oat genotypes formed different phenotypic classes for the measured traits. The industrial yield is directly associated with the test weight, grain yield and grain index. Phenotypic associations can be efficiently used in breeding programs aiming at oat indirect selection to improve industrial performance. Highlighted Conclusions1. Different phenotypic classes are observed for the measured traits. 2. Milling yield is associated with the hectoliter weight, grain yield and grain index. 3. The milling yield can be improved by indirect selection.
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