A multivariate heterogeneous variance components model for multi-environment studies with locational genetic effects

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KARADAĞ ÇAMAN Ö.

SOFT COMPUTING, vol.25, no.21, pp.13195-13200, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 21
  • Publication Date: 2021
  • Doi Number: 10.1007/s00500-021-06132-2
  • Journal Name: SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Page Numbers: pp.13195-13200
  • Keywords: Multivariate variance components, Mixed modelling, Genetic variance components, Location effect, Heritability, AVERAGE INFORMATION REML, PRINCIPAL COMPONENT, EFFICIENT ALGORITHM
  • Hacettepe University Affiliated: Yes

Abstract

In this paper, a multivariate heterogeneous variance components model was developed which allows for determination of location specific variance components in the analysis of multiple related traits. In addition to spatial heterogeneity, genetic similarities are also considered by assigning genetic variance components. The performance of the developed model was evaluated through an extensive simulation study and comparison of models was conducted by heritability estimations. The simulation study reveals that the developed method can control the locational heterogeneity well and the heritability estimations are close to desired proportions for the developed model. A real plant breeding data set was used for illustration.