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.

Genetic parameters and selection of soybean lines based on selection indexes

Defining selection criteria is important to obtain promising genotypes in a breeding program. The objective of this study was to estimate genetic parameters for agronomic traits and to perform soybean line selection using selection indices. The experiment was conducted at an experimental area located at Capim Branco farm, belonging to the Federal University of Uberlândia. A total of 37 soybean genotypes were evaluated in randomized complete block design with three replicates, in which twelve agronomic traits were evaluated. Analysis of variance, the Scott-Knott test at the 1 and 5% level of probability, and selection index analyses were performed. There was genetic variability for all agronomic traits, with medium to high levels of genotype determination coefficient. Twelve lines with a total cycle up to 110 days were observed and grouped with the cultivars MSOY 6101 and UFUS 7910. Three lines, UFUS FG 03, UFUS FG 20, and UFUS FG 31, were highlighted regarding grain yield with higher values than the national average of 3072 kg/ha. The direct selection enabled the highest trait individual gains. The Williams (1962) index and the Smith (1936) and Hazel (1943) index presented the highest selection gain for the grain yield character. The genotype-ideotype distance index and the index of the sum of ranks of Mulamba and Mock (1978) presented higher values of total selection gain. The lines UFUS FG 12, UFUS FG 14, UFUS FG 18, UFUS FG 25, and UFUS FG 31 were distinguished as superior genotypes by direct selection methods and selection indexes.

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.

Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis

The genetic diversity study has paramount importance in breeding programs; hence, it allows selection and choice of the parental genetic divergence, which have the agronomic traits desired by the breeder. This study aimed to characterize the genetic divergence between 24 soybean genotypes through their agronomic traits, using multivariate clustering methods to select the potential genitors for the promising hybrid combinations. Six agronomic traits evaluated were number of days to flowering and maturity, plant height at flowering and maturity, insertion height of the first pod, and yield. The genetic divergence evaluated by multivariate analysis that esteemed first the Mahalanobis' generalized distance (D2), then the clustering using Tocher's optimization methods, and then the unweighted pair group method with arithmetic average (UPGMA). Tocher's optimization method and the UPGMA agreed with the groups' constitution between each other, the formation of eight distinct groups according Tocher's method and seven distinct groups using UPGMA. The trait number of days for flowering (45.66%) was the most efficient to explain dissimilarity between genotypes, and must be one of the main traits considered by the breeder in the moment of genitors choice in soybean-breeding programs. The genetic variability allowed the identification of dissimilar genotypes and with superior performances. The hybridizations UFU 18 x UFUS CARAJÁS, UFU 15 x UFU 13, and UFU 13 x UFUS CARAJÁS are promising to obtain superior segregating populations, which enable the development of more productive 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.

Selection for wide adaptability and high phenotypic stability of Brazilian soybean genotypes

Advances in genetic enhancement techniques have led to an increase in soybean production. Thus, soybean is currently one the most economically important cultured species worldwide. The objectives of the present study were to study the interaction of soybean genotypes per environment in terms of grain productivity and to evaluate their phenotypic adaptability and stability, with the final aim of selecting lineages with high productivity, wide adaptability, and high stability. Seven soybean genotypes, consisting of five lineages developed by the soybean genetic enhancement program of the Universidade Federal de Uberlândia (Brazil) and two controls, were evaluated during several annual cycles in seven different environments. A randomized complete block design (RCBD) with three replicates was adopted in each site. This study followed the methodology proposed by Eberhart and Russel and Lin and Binns, with modifications by Carneiro, and the AMMI (additive main effects and multiplicative interaction model) analysis. The average productivity of soybean cultivars in the trials was 2739.26 kg/ha. The L01V13 genotype and the UFUS Guarani cultivar had wide adaptation according to the methodology proposed by Eberhart and Russel and Lin and Binns, with modifications by Carneiro. When analyzed with the AMMI model, the UFUS Guarani cultivar showed high stability. In general, the methodologies studied are complementary and, when used together, increase the reliability of the classification, providing support for the use of specific soybean cultivars in different environments.

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.

Correlations between traits in soybean (Glycine max L.) naturally infected with Asian rust (Phakopsora pachyrhizi)

Soybean (Glycine max L.)-breeding programs aim to develop cultivars with high grain yields and high tolerance to Asian soybean rust (Phakopsora pachyrhizi). Considering that the traits targeted for breeding are mainly quantitative in nature, knowledge of associations between traits allows the breeder to formulate indirect selection strategies. In this study, we investigated phenotypic, genotypic, and environmental correlations between the agronomic traits of soybean plants naturally infected with P. pachyrhizi, and identified agronomic traits that would be useful in indirectly selecting soybean genotypes for high yields. The study was conducted on the Capim Branco Farm, Uberlândia, Brazil, with 15 soybean genotypes, which were cultivated in a completely randomized block design with four replications. Fourteen phenotypic traits were evaluated using the GENES software. The phenotypic and genotypic correlations were positive and of a high magnitude between the total number of pods and the number of pods with two or three grains, indicating that the total number of pods is a useful trait for the indirect selection of soybean genotypes for high grain yields. Strong environmental correlations were found between plant height at blooming and maturity and grain yield and yield components.

Evaluation of soybean lines and environmental stratification using the AMMI, GGE biplot, and factor analysis methods

In the final phases of new soybean cultivar development, lines are cultivated in several locations across multiple seasons with the intention of identifying and selecting superior genotypes for quantitative traits. In this context, this study aimed to study the genotype-by-environment interaction for the trait grain yield (kg/ha), and to evaluate the adaptability and stability of early-cycle soybean genotypes using the additive main effects and multiplicative interaction (AMMI) analysis, genotype main effects and genotype x environment interaction (GGE) biplot, and factor analysis methods. Additionally, the efficiency of these methods was compared. The experiments were carried out in five cities in the State of Mato Grosso: Alto Taquari, Lucas do Rio Verde, Sinop, Querência, and Rondonópolis, in the 2011/2012 and 2012/2013 seasons. Twenty-seven early-cycle soybean genotypes were evaluated, consisting of 22 lines developed by Universidade Federal de Uberlândia (UFU) soybean breeding program, and five controls: UFUS Carajás, MSOY 6101, MSOY 7211, UFUS Guarani, and Riqueza. Significant and complex genotype-by-environment interactions were observed. The AMMI model presented greater efficiency by retaining most of the variation in the first two main components (61.46%), followed by the GGE biplot model (57.90%), and factor analysis (54.12%). Environmental clustering among the methodologies was similar, and was composed of one environmental group from one location but from different seasons. Genotype G5 presented an elevated grain yield, and high adaptability and stability as determined by the AMMI, factor analysis, and GGE biplot methodologies.

Adaptability and stability of soybean genotypes in off-season cultivation

The oil and protein contents of soybean grains are important quantitative traits for use in breeding. However, few breeding programs perform selection based on these traits in different environments. This study assessed the adaptability and stability of 14 elite early soybean breeding lines in off-season cultivation with respect to yield, and oil and protein contents. A range of statistical methods was applied and these analyses indicated that for off-season cultivation, the lines UFUS 5 and UFUS 10 could be recommended due to their superior performance in grain yield, oil content, and specific adaptability to unfavorable environments along with high stability in these characteristics. Also recommended were UFUS 06, which demonstrated superior performance in all three tested characteristics and showed adaptation to favorable environments, and UFUS 13, which showed high adaptability and stability and a superior performance for protein content.