Genotype x environment interaction and stability of soybean cultivars for vegetative-stage characters.

In order to obtain the certificate of cultivar protection, it is necessary to prove its distinctiveness, homogeneity, and stability. Currently, there are 37 descriptors for differentiating soybeans cultivars. However, they are still not enough and, as a result, it is necessary to create, identify, and evaluate new descriptors. This study was aimed at evaluating the genotypic and environment interaction (GxE) and determining the stability of eight soybean cultivars for five vegetative-stage descriptors. The research was done in a greenhouse of the Soybean Breeding and Genetic Studies Program of Universidade Federal de Uberlândia. The treatments were composed of eight soybean cultivars, sown in two different growing seasons (January 25, 2014 and November 27, 2014). The experiments were carried out in randomized complete blocks with three replications and each experimental plot consisted of one pot with four soybean plants. The characters evaluated were: length of hypocotyl (LH), length of epicotyl (LE), length of unifoliolate leaf petiole (LUP), length of first trifoliate leaf petiole (LTLP), and rachis length of terminal leaflet of the first trifoliate leaf (RL). The data achieved from the trials were undergone genetic-statistical analyses by the GENES software. For all analyzed characters, the existence of genetic variability was observed emphasizing the vegetative-stage descriptors' utility to differentiate soybean cultivars. The occurrence of GxE interaction was detected for all characters assessed, mainly of complex nature, except by RL, which was of simple nature. The most stable cultivars for the vegetative-stage descriptors analysed were UFUS 7415 and UFUS Impacta.

Phenotypic and genotypic correlations between soybean agronomic traits and path analysis.

The goals of this research were to evaluate the phenotypic and genotypic correlations between agronomic traits, to perform path analysis, having as main character grain yield, and to identify indirect selection criteria for grain yield. The experiment was carried out in an experimental area located at Capim Branco farm, which belongs to Federal University of Uberlândia, during the growing season of 2015/2016.Twenty-four soybean genotypes were evaluated under randomized complete block design with three repetitions, of which agronomic traits and grain yield were measured. There was genetic variability for all traits at 5% probability level through the F-test. Thirty significant phenotypic correlations were also observed with values oscillating from 0.42 to 0.87, which indicated a high level of association between some evaluated traits. Additionally, we verified that phenotypic and genotypic correlations were essential of the same direction, being the genotypic ones of superior magnitudes. Plants with superior vegetative cycle had longer life cycles; this fact could be explained by the significant phenotypic correlations between the number of days to the blooming and number of days to maturity (0.76). Significantly positive phenotypic and genotypic correlations for the total number of pods per plant and grain yield per plant (0.84) were observed. Through the path analysis, the trait that contributed the most over grain yield was the number of pods with three seeds as it showed the highest direct effect on grain yield per plant, as well as a strong indirect effect on the total number of pods. Therefore, the phenotypic and genotypic correlations suggested high correlations between grain yield and number of branched nodes, the number of pods with two and three seeds, and the total number of pods. Also, the path analysis determined the number of pods with three seeds as having the highest favorable effect on grain yield, and thus, being useful for indirect selection toward productive soybean genotypes.

Analysis of the genetic divergence of soybean lines through hierarchical and Tocher optimization methods.

This study aimed to evaluate the clustering pattern consistency of soybean (Glycine max) lines, using seven different clustering methods. Our aim was to evaluate the best method for the identification of promising genotypes to obtain segregating populations. We used 51 generations F5 and F6 soybean lines originating from different hybridizations and backcrosses obtained from the soybean breeding program of Universidade Federal de Uberlândia in addition to three controls (Emgopa 302, BRSGO Luziânia, and MG/BR46 Conquista). We evaluated the following agronomic traits: number of days to flowering, number of days to maturity, height of the plant at maturity, insertion height of the first pod, grain yield, and weight of 100 seeds. The data was submitted to analyses of variance followed by average Euclidean distance matrix estimation used as measure of dissimilarity. Subsequently, clusters were formed using the Tocher method and dendrograms were constructed using the hierarchical methods simple connection (nearest neighbor), complete connection (most distant neighbor), Ward, median, average within cluster connection. The nearest neighbor method presented the largest number of genotypes in group I and showed the greatest similarity with the Tocher optimization method. The joint use of these two methodologies allows for differentiation of the most genetically distant genotypes that may constitute the optimal parents in a breeding program.

Selecting soybean resistant to the cyst nematode Heterodera glycines using simple sequence repeat (microssatellite) markers.

The soybean cyst nematode (SCN) is a major cause of soybean yield reduction. The objective of this study was to evaluate the efficiency of marker-assisted selection to identify genotypes resistant to SCN race 3 infection, using Sat_168 and Sat-141 resistance quantitative trait loci. The experiment was carried out under greenhouse conditions, using soybean populations originated from crosses between susceptible and resistant parent stock: CD-201 (susceptible) and Foster IAC (resistant), Conquista (susceptible) and S83-30 (resistant), La-Suprema (susceptible) and S57-11 (resistant), and Parecis (susceptible) and S65-50 (resistant). Plants were inoculated with SCN and evaluated according to the female index (FI), those with FI < 10% were classified as resistant to nematode infection. Plants were genotyped for SCN resistance using microsatellite markers Sat-141 and Sat_168. Marker selection efficiency was analyzed by a contingency table, taking into account genotypic versus phenotypic evaluations for each line. These markers were shown to be useful tool for selection of SCN race 3.