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The success of breeding programs depends on selection procedures and on the breeding methods adopted for selecting segregating populations. The objective of this study was to evaluate the efficiency of the Bulk method with selection in the F3 generation (BulkF3) compared to that of Bulk method as well as determine the most effective selection strategy in terms of genetic gain. Twenty segregating populations were selected by two methods. The 60 best families of each method were selected according to their average agronomic performance. An augmented block design was used. The following agronomic traits were evaluated: insertion height of first pod, plant height at maturity, number of branches and of pods per plant, 100-seed weight, and grain yield. For comparison of the methods, genetic component estimates, genetic gain and predicted breeding values were calculated using mixed models (REML and BLUP). The results showed the families obtained with the BulkF3 method were more productive, showed suitable plant height, a larger number of branches and pods, and higher 100-seed weight. The BulkF3 method was found to be an effective selection strategy for soybean improvement.

The objective of this study was to evaluate the relationship between agronomic traits and physiological traits of seeds in segregating soybean populations by canonical correlation analysis. Seven populations and two commercial cultivars in three generations were used: F plants and F seeds; F plants and F seeds, and F seeds and plants. The following agronomic traits (group I) were evaluated: number of days to maturity, plant height at maturity, insertion height of first pod, number of pods, grain yield, and oil content. The physiological quality of seeds (group II) was evaluated using germination, accelerated aging, emergence, and emergence rate index tests. The results showed that agronomic traits and physiological traits of seeds are not independent. Intergroup associations were established by the first canonical pair for the generation of F plants and F seeds, especially between more productive plants with a larger pod number and high oil content and seeds with a high germination percentage and emergence rate. For the generation of F plants and F seeds, the first canonical pair indicated an association between reduced maturity cycle, seeds with a high emergence percentage and a high percentage of normal seedlings after accelerated aging. According to the second canonical pair, more productive and taller plants were associated with seed vigor. For the generation of F seeds and plants, the associations established by the first canonical pair occurred between seed vigor and more productive plants with high oil content and reduced maturity cycle, and those established by the second canonical pair between seeds of high physiological quality and tall plants.

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In addition to the agronomic traits of interest, soybean cultivars destined for human consumption must have specific attributes that meet the demands of the consumer market. To meet this demand, this study aimed to select progenies with agronomic and commercial traits of interest from soybean populations obtained from crosses between different food and grain genotypes and to estimate the genetic parameters of these populations. The F3:4 and F4:5 progenies that originated from the two crosses were evaluated in the 2015/16 and 2016/17 agricultural years, respectively, using the pedigree method. The experimental design utilized augmented blocks, while statistical analyses were performed by using the REML/BLUP methodology. The evaluated traits were plant height at maturity (APM), insertion height of first pod (AIV), lodging (AC), agronomic value (VA), number of pods per plant (NV), number of days to maturity (NDM), number of branches (NR), number of nodes (NN), 100-seed weight (PCS), and grain yield per plant (PG). The best progenies were selected, and the following genetic parameters were estimated: genetic variance, phenotypic variance, heritability, and selective accuracy. The estimates of the genetic parameters indicate the presence of high genetic variance in these populations. Heritability was high for most of the traits, indicating good potential for the selection of superior genotypes.

The aim of this study was to compare the agronomic performance of RR soybean genotypes with conventional soybean genotypes derived from two-way crosses and evaluate through path analysis the influence of important traits for culture on the grain yield (GY) in the Northwestern of São Paulo, Brazil. It was used the randomized block design with three replications. Among the analyzed RR genotypes, three genotypes has high GY, with average values over 4575.5 kg ha-1 , while among the conventional, ten genotypes, and the check Conquista showed superiority for GY, with average values over 3511.4 Kg ha-1. In general, the most productive RR soybean genotypes showed higher values when compared with conventional genotypes with higher yield. However, conventional soybean showed a higher number of superior genotypes with similar behavior when compared to the RR soybean. For the group of RR soybean genotypes, all agronomic traits, except one hundred seed weight (HSW), correlated positively with GY. For the group of conventional soybean genotypes, there was no significant correlation between GY and all agronomic traits analyzed. The genotypic correlation and path analysis indicate the plant height at flowering (PHF) and plant height at maturity (PHM) as the most favorable and direct effect on GY.

Soybean has a recognized narrow genetic base that often makes it difficult to visualize available genetic and phenotypic variability and identify superior genotypes during the selection process. However, the phenotypic expression of soybean plants is highly affected by photoperiod and the cultivation of a given variety is performed in the latitude range that presents ideal conditions for its development based on its relative maturity group (RMG) for the optimization of the phenotypic expression of its genotype. Based on the above, this study aimed to evaluate the efficiency of artificial neural networks (ANNs) as a tool for the correct discrimination and classification of tropical soybean genotypes according to their relative maturity group during the population selection process with the aim of optimizing the phenotypic performance of these selected genotypes. For this purpose, three biparental populations were synthesized, one with a wide genetic variability for the RMG character obtained from the hybridization between genitors of maturity groups RMG 5 (Sub-tropical 23° LS) × RMG 9.4 (Tropical 0° LS) and two populations with a narrow variability obtained between genitors RMG 7.3 (Tropical 20° LS) × RMG 9.4 and RMG 5.3 × RMG 6.7, respectively. Criteria for comparing the developed ANN architecture with Fisher’s linear and Anderson’s quadratic parametric discriminant methodologies were applied to the data for the discrimination and classification of the genotypes. ANN showed an apparent error rate of less than 8.16% as well as a low influence of environmental factors, correctly classifying the genotypes in the populations even in cases of reduced genetic variability such as in the RMG 5 × RMG 6 population. In contrast, the discriminant functions were inefficient in correctly classifying the genotypes in the populations with genealogical similarity (RMG 5 × RMG 6) and wide genetic variability, with an error rate of more than 50%. Based on the results of this study, ANN can be used for the discrimination of genotypes in the initial generations of selection in breeding programs for the development of high performance cultivars for wide and reduced photoperiod amplitudes, even with fewer selection environments, more efficiently, and with fewer time and resources applied. As a result of similarity between the parents, ANN can correctly classify genotypes from populations with a narrow genetic base, in addition to pure lines and genotypes with a high degree of inbreeding.

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