L.B. Sousa
Cotton genotypes selection through artificial neural networks
Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar’s development. Differently from these analyses, the computational intelligence approach has been little explored in genetic improvement of cotton. Thus, this study was carried out with the objective of presenting the use of.. Read More»
Genet. Mol. Res. 16(3): gmr16039798
DOI: 10.4238/gmr16039798
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.. Read More»
Genet. Mol. Res. 15(1): gmr.15017843
DOI: 10.4238/gmr.15017843
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 met.. Read More»
Genet. Mol. Res. 14(3): 2015.August.14.26
DOI: 10.4238/2015.August.14.26
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 obta.. Read More»
Genet. Mol. Res. 15(4): gmr.15048836
DOI: 10.4238/gmr.15048836
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 an.. Read More»
Genet. Mol. Res. 14(4): 2015.October.19.10
DOI: 10.4238/2015.October.19.10
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 selec.. Read More»
Genet. Mol. Res. 16(2): gmr16029661
DOI: 10.4238/gmr16029661
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