African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6140

Full Length Research Paper

Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn

Maicon Nardino
  • Maicon Nardino
  • Department of Mathematics and Statistics, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Diego Baretta
  • Diego Baretta
  • Plant Genomics and Breeding Center, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Ivan Ricardo Carvalho
  • Ivan Ricardo Carvalho
  • Plant Genomics and Breeding Center, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Tiago Olivoto
  • Tiago Olivoto
  • Department of Agronomic and Environmental Sciences, Federal University of Santa Maria Frederico Westphalen, Rio Grande do Sul, Brazil.
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Diego Nicolau Follmann
  • Diego Nicolau Follmann
  • Agronomy Department, Federal University of Santa Maria, Santa Maria, Rio Grande do Sul, Brazil.
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Vinícius Jardel Szareski
  • Vinícius Jardel Szareski
  • Department of Crop Science, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Mauricio Ferrari
  • Mauricio Ferrari
  • Plant Genomics and Breeding Center, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Alan Junior de Pelegrin
  • Alan Junior de Pelegrin
  • Plant Genomics and Breeding Center, Federal University of Pelotas, Capão do Leão, Rio Grande do Sul, Brazil.
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Valmor Antonio Konflanz
  • Valmor Antonio Konflanz
  • Breeder Company Plants KSP Seeds Ltda, Pato Branco, Brazil.
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Velci Queiróz de Souza
  • Velci Queiróz de Souza
  • Federal University of Pampa, Dom Pedrito, Rio Grande do Sul, Brazil.
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  •  Received: 09 September 2016
  •  Accepted: 05 October 2016
  •  Published: 01 December 2016

Abstract

Adoption of accurate and simplistic biometric models that estimate variance components, predicting genotypic effects are desired in plant breeding. The aim of this study was to estimate the variance components and predict genotypic values by REML/BLUP for combinations of maize inbred lines derived from two heterotic groups with F1's evaluation in four locations. The crosses originated 25 hybrids that were evaluated in four trials. Genotype x environment interaction provided oscillations regarding the best combinations in the environments and must be individually analyzed in each environment, the superior crosses for grain yield, except 15x3’ combination, which achieved good performance in all the trials. The combination of 5x4' is promising for obtaining high grain yield in Itapiranga and Pato Branco. The 5x3’ combination have a higher overall average, being higher than the other combinations in Clevelândia and Ampere environments for plot yield, providing hybrids with fewer branches in the tassel.

 

Key words: Best linear unbiased predictor, restricted maximum likelihood, Zea mays L.

Abbreviation

BLUP, Best linear unbiased prediction; DLN, distance from the last node of the stem to the first branch of the tassel; EH, ear height; GY, plot grain yield; NTB, number of tassel branch; REML, restricted maximum likelihood; TKW, thousand-kernel weight.