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- Title
Selection index based on random regression model in 'Tahiti' acid lime.
- Authors
Malikouski, Renan Garcia; Alves, Rodrigo Silva; Peixoto, Marco Antônio; Ferreira, Filipe Manoel; do Nascimento, Emanuel Ferrari; de Morais, Andréia Lopes; Zucoloto, Moises; das Graças Dias, Kaio Olimpio; Bhering, Leonardo Lopes
- Abstract
An accurate and efficient statistical method for repeated measures analysis and selection of scion/rootstock combinations (SRC) is a fundamental prerequisite for genetic progress in 'Tahiti' acid lime breeding. Thus, this work aimed: (i) to evaluate the applicability and efficiency of random regression models in the analysis of repeated measures and (ii) to apply a selection index to recommend SRC of 'Tahiti' acid lime, associating vegetative and productive traits. Between July 2017 and January 2019, 24 SRC of 'Tahiti' acid lime were evaluated for vegetative and productive traits over eight measurements. The random regression model (RRM) was compared with a repeatability model (REP). The variance components were estimated via residual maximum likelihood. The predicted genotypic values were predicted via the best linear unbiased prediction. The genotypic values (for REP) and the areas below the genotypic trajectories (for RRM) were used as input for the additive index aiming for simultaneous selection. The three best-performing genotypes were selected, considering a selection percentage equal to 12.5%. Models based on random regression and repeatability showed the same selected genotypes, even though, there were changes in the ranking. The random regression model allows the prediction of genotypic values for genotypes that were not evaluated in the field being advantageous for genetic evaluation of 'Tahiti' acid lime. The selection index based on the REP and RRM models indicated that the recommended SRC for propagation and planting are Iconha/'Riverside' citrandarin, CNPMF5059/'Riverside' citrandarin and Itarana/Swingle citrumelo.
- Subjects
RIVERSIDE (Calif.); REGRESSION analysis; ROOTSTOCKS; PLANT propagation; GENOTYPES; STATISTICAL reliability; ACIDS
- Publication
Euphytica, 2022, Vol 218, Issue 11, p1
- ISSN
0014-2336
- Publication type
Article
- DOI
10.1007/s10681-022-03105-w