African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6401

Full Length Research Paper

Genetic divergence of corn cultivars in relation to grain productivity, crude protein content and amino acid profile

Bruna Mendonca Alves
  • Bruna Mendonca Alves
  • Department of Plant Science, Federal University of Santa Maria (UFSM), Santa Maria, RS, Brazil.
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Alberto Cargnelutti Filho
  • Alberto Cargnelutti Filho
  • Department of Plant Science, Federal University of Santa Maria (UFSM), Santa Maria, RS, Brazil.
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Leila Picolli da Silva
  • Leila Picolli da Silva
  • Department of Animal Sciences, Federal University of Santa Maria (UFSM), Santa Maria, RS, Brazil.
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Marcos Toebe
  • Marcos Toebe
  • Foundation Federal University of Pampa (UNIPAMPA), Itaqui, RS, Brazil.
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Claudia Burin
  • Claudia Burin
  • Department of Plant Science, Federal University of Santa Maria (UFSM), Santa Maria, RS, Brazil.
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Alexandra Pretto
  • Alexandra Pretto
  • Foundation Federal University of Pampa (UNIPAMPA), Dom Pedrito, RS, Brazil.
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  •  Received: 06 March 2015
  •  Accepted: 16 July 2015
  •  Published: 06 August 2015

Abstract

The aim of this study was to investigate the genetic variability among early-maturing and extremely early-maturing corn cultivars in relation to grain productivity, crude protein content and amino acid profile to obtain future crosses of cultivars with improved nutritional characteristics. Data from two experiments, which were both conducted in randomized block design and three replicates. Thirty-six early-maturing and 22 extremely early-maturing cultivars were evaluated of the experiments. Grain productivity, crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine and arginine were evaluated. Analysis of variance was performed for each variable and means were compared by Scott-Knott test. Mahalanobis generalized distance matrix was calculated, and the cultivars were grouped using the unweighted pair group method with arithmetic mean (UPGMA). A dendrogram was then constructed, and the cophenetic correlation coefficient was calculated. The group means were compared using the t-test for independent samples. Genetic variability was detected in 13 variables for both maturity groups. For the early-maturing and extremely early-maturing cultivars, five and four groupings were obtained, respectively, based on grain productivity, crude protein content and amino acid profile, indicating that the crossbreeding of these cultivars may be used to improve the grain protein content and amino acid profile.

 

Key words: Zea mays L., genetic variability, nutritional variability, clustering analysis, near-infrared reflectance spectroscopy.