Journal list menu

Volume 60, Issue 3 p. 1373-1385
ORIGINAL RESEARCH ARTICLE

Genomic selection helps accelerate popcorn population breeding

Ismael Albino Schwantes

Ismael Albino Schwantes

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
Antônio Teixeira do Amaral Júnior

Corresponding Author

Antônio Teixeira do Amaral Júnior

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Correspondence

Antônio Teixeira do Amaral Júnior, Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias (CCTA), Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brasil.

Email: [email protected]

Search for more papers by this author
Janeo Eustáquio de Almeida Filho

Janeo Eustáquio de Almeida Filho

Bayer Crop Science, Coxilha, RS, Brazil

Search for more papers by this author
Marcelo Vivas

Marcelo Vivas

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
Pablo Diego Silva Cabral

Pablo Diego Silva Cabral

Instituto Federal Goiano, Campus Rio Verde, Rio Verde, GO, Brazil

Search for more papers by this author
Amanda Gonçalves Guimarães

Amanda Gonçalves Guimarães

Univ. Federal dos Vales do Jequitinhonha e Mucuri – Campus JK Diamantina, MG, Brazil

Search for more papers by this author
Fernando Higino de Lima e Silva

Fernando Higino de Lima e Silva

Instituto Federal Goiano, Campus Rio Verde, Rio Verde, GO, Brazil

Search for more papers by this author
Pedro Henrique Araújo Diniz Santos

Pedro Henrique Araújo Diniz Santos

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
Messias Gonzaga Pereira

Messias Gonzaga Pereira

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
Alexandre Pio Viana

Alexandre Pio Viana

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
Guilherme Ferreira Pena

Guilherme Ferreira Pena

Univ. Estadual de Mato Grosso, Campus Alta Floresta, MT, Brazil

Search for more papers by this author
Fernando Rafael Alves Ferreira

Fernando Rafael Alves Ferreira

Laboratório de Melhoramento Genético Vegetal, Centro de Ciências e Tecnologias Agropecuárias, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil

Search for more papers by this author
First published: 04 February 2020
Citations: 6

Assigned to Associate Editor Jode Edwards.

Abstract

Recurrent selection is a method for developing new popcorn (Zea mays L.) cultivars. We aimed to determine the selection accuracy and genetic gains for different selection strategies: estimates based exclusively on phenotypic data (PhEN), estimates based on phenotypic and genotypic data (PhEN + GEN), and estimates based exclusively on single nucleotide polymorphism (SNP) marker genotyping (GEN). For the GEN strategy, we tested, via simulation, the possibility of reducing the number of SNPs and increasing the training population. The traits evaluated were 100-grain weight, ear height, grain yield, popping expansion, plant height, and popping volume. Field trials were undertaken with 98 S1 progenies at two locations in an incomplete block design with three replications. The progenies’ parents were genotyped with a panel of ∼10,507 SNPs. As predicted by the GEN strategy at different selection intensities, the average annual genetic gain for the different traits were 29.1 and 25.2% higher than those of PhEN and GEN + PhEN for 98 candidates; 148.3 and 140.9% higher for 500; and 187.9 and 179.4% higher for 1,000 selection candidates, respectively. Recurrent genomic selection may result in high genetic gain, provided that: (a) phenotyping is accurate; (b) selection intensity is explored by genotyping several progenies and increasing the number of candidates; (c) genomic selection is used for early selection; and (d) the model is adjusted for a few more cycles of phenotyping. The simulation suggests that desirable values of genetic gain may be obtained by reducing the number of SNPs and increasing the training population size.

CONFLICT OF INTEREST STATEMENT

The authors declare that there is no conflict of interest