Abstract
ABSTRACT Runner peanuts are known for their high pod yields, but are late to flowering and pod maturation, and the optimal combination of these traits with pod yield is widely desired for peanut improvement. Selection indexes are useful tools for crop breeding. In this study, seven selection indexes combined with economic weights were used in a peanut population to estimate the superior and balanced genetic gains. Eleven runner genotypes were grown in three environments in the Northeast region of Brazil under a randomized block design with five replicates. The following indices were used: Smith and Hazel, Pesek and Baker, Williams, Elston, Subandi, Cruz, and Mulamba & Mock, in combination with the following economic weights: weight 1 for all evaluated traits, primary and secondary traits, genetic variation coefficient, genetic standard deviation, and b coefficient, obtained via multivariate regression. Although the population is genetically uniform, statistical differences were found, indicating sufficient genetic variability to generate selection progress. The combinations involving earliness traits were not satisfactory for production gains. The index based on the Mulamba & Mock rankings combined with weight 1 for all traits proved the optimal combination, as indicated by the most balanced gains. The cultivars Florunner, Cavalo, LGoPE-06, and LViPE-06 are promising germplasm for ensuring satisfactory selection gains based on production means and high heritability of the most evaluated traits.
Highlights
Selection indices are valuable genetic tools to assist in routine breeding procedures, especially for estimating genetic progress to predict the success of modified populations.The selection indexes available in the literature are divided into parametric and nonparametric categories
These coefficients, which maximize the correlation between the index and genotype aggregate, are estimated using the following equations: H = a1g1 + a2g2 + + angn = ni = 1aigi = a 'g where: H - genotype aggregate; I - selection index; g - vector (1 × n) of genetic values of n traits; y - vector (1 × n) of phenotypic means; a’ - vector (n × 1) of economic weights of different traits established by breeder; n - number of traits adopted to estimate the index; and b’ - vector (n × 1) of weighting coefficients of the index estimated by Eq 7: b= P −1Ga
Significant statistical effects were found for genotypes in all traits (Table 2), indicating variability between germplasm and the contribution of selection techniques to assist in the identification of genotypes with favorable alleles
Summary
Selection indices are valuable genetic tools to assist in routine breeding procedures, especially for estimating genetic progress to predict the success of modified populations. Seven selection indexes were tested in combination with economic weights to estimate maximum genetic gains in a runner peanut population. For selection based on the classical index (Smith, 1936; Hazel, 1943), the indexes were estimated through a linear combination of traits weighted by the respective b coefficients These coefficients, which maximize the correlation between the index and genotype aggregate, are estimated using the following equations:. Where: H - genotype aggregate; I - selection index; g - vector (1 × n) of genetic values of n traits; y - vector (1 × n) of phenotypic means; a’ - vector (n × 1) of economic weights of different traits established by breeder; n - number of traits adopted to estimate the index; and b’ - vector (n × 1) of weighting coefficients of the index estimated by Eq 7: b= P −1Ga (7). The order of selection, from the first to the last individual, was considered as a category and evaluated in terms of agreement and disagreement, as described in Eq 14: dii=' D + D (14)
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