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Genetic parameters in Stylosanthes using different statistical methods
Author(s) -
Sim atilde o de Oliveira Ronaldo,
Ab iacute lio de Queir oacute z Manoel,
Lisboa Rom atilde o Roberto,
Augusto de Souza Almeida Bruno,
Mistura Cl aacute udio,
Paganucci de Queir oacute z Luciano
Publication year - 2015
Publication title -
african journal of agricultural research
Language(s) - English
Resource type - Journals
ISSN - 1991-637X
DOI - 10.5897/ajar2015.10329
Subject(s) - best linear unbiased prediction , restricted maximum likelihood , selection (genetic algorithm) , stylosanthes , statistics , genetic variability , biology , plant breeding , mathematics , agronomy , microbiology and biotechnology , maximum likelihood , genotype , machine learning , computer science , genetics , gene
Genetic parameters in Stylosanthes accessions were estimated through (ANOVA) and REML/BLUP (Restricted Maximum Likelihood /Best Linear Unbiased Prediction), to compare them for the genetic values in order to select superior accessions. Twenty five genotypes were evaluated in two environments in a randomized blocks experimental design with four replications. The genetic parameters were estimated for 12 descriptors by the two methods. Both methods indicating that the accessions presented genetic variability for the descriptors, but, the ANOVA and the REML/BLUP presented divergent values for the unbalanced data and for descriptors with high environmental influence, as it happens with mass descriptors, what, in turn, indicates that the method REML/BLUP leads to a more accurate predictions and allows for the selection of Stylosanthes accessions. It allows the inclusion of characters, even if they present heterogeneity of the residual variance. The indirect selection may be used, because the primary stem length descriptor revealed itself as a good option due to the correlation with the total dry mass. The accessions BGF-016 and BGF-015 are the most promising ones to be taken up by a Stylosanthes plant breeding program for fodder in the Brazilian Semiarid region.   Key words: Semiarid, forages, breeding

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