Herdabilidade como peso econômico na aplicação de índices de seleção no melhoramento de arroz

Cazassa, Reinaldo Soares; Tomé, Laís Moretti; Lima, Isabela Pereira de; Botelho, Flávia Barbosa Silva; Moura, A. M. de; Reis, Miria Hespanhol Miranda; Silva, Gilberto Alves de Miranda; Oliveira, Tulio Vecchi Sousa de

doi:10.34117/bjdv5n9-069

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“…The great difficulty in using this and other methodologies is the definition of economic weights to maximize the correlation of genetic values, which lacks a standard procedure [14]. Some procedures, such as the use of genetic variation coefficients [42], heritability [43], or random weights [14], especially where weights are subject to estimation bias and impact the selection result, have already been tested. In the method proposed in the present study, there is no need to assign weights, which standardizes the selection procedure and makes it more accurate.…”

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confidence: 99%

Multiple Traits Selection Strategies: A Proposal for Coffee Plant Breeding

Piza,

Luz,

Andrade

et al. 2023

Agronomy

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Experiments with progenies of perennial species such as coffee are generally affected by the heterogeneity of residual variances between information repeatedly collected in space and time on the same individual. In this study, we propose an index that considers the individual heritability of multiple traits for progeny selection and evaluate the applicability of this index in comparison with other indices in a real dataset. Data from 30 coffee genotypes in the F4:5 generation were used to obtain the individual heritability values (hi2) of progenies that were subjected to factorial analysis to obtain the scores and construct a scatter plot, where graphical analysis (GA) was applied. Genetic gains were obtained for productivity and resistance to Cercospora leaf spot using GA. The best performance among the strategies (−12.11%) was obtained using GA for resistance to Cercospora leaf spot, which has low heritability—contrary to the result obtained using the commonly used index based on the sum of Mulamba and Mock ranks. The GA approach allows an assertive selection to minimize the effects of heterogeneity between seasons, and greater genetic gains are obtained. Its use as a tool for the selection of perennial plant progenies based on multiple characters is promising.

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