Problems with multiple-trait analysis in animal breeding and solutions


Firat M. Z.

TURKISH JOURNAL OF VETERINARY & ANIMAL SCIENCES, cilt.21, sa.3, ss.227-231, 1997 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 3
  • Basım Tarihi: 1997
  • Dergi Adı: TURKISH JOURNAL OF VETERINARY & ANIMAL SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.227-231
  • Anahtar Kelimeler: multiple-trait analysis, animal breeding, variance matrix, MAXIMUM-LIKELIHOOD, MATRICES
  • Akdeniz Üniversitesi Adresli: Hayır

Özet

in animal breeding applications, more than one traits are measured on each individual, for example, beside milk production the amount of fat and protein in milk are also measured. Since these traits are strongly correlated, instead of analysing each one separately, it is much more appropriate to evaluate them simultaneously. Thus estimates of genetic and phenotypic correlations and heritability are easily obtained. The obvious problem of multiple-trait analysis is the additional computational requirements due to the increased number of equations to be solved. The other problem is that the more traits are analysed, the greater the probability of estimates outside the parameter space.

In animal breeding applications, more than one traits are measured on each individual, for example, beside milk production the amount of fat and protein in milk are also measured. Since these traits are strongly correlated, instead of analysing each one separately, it is much more appropriate to evaluate them simultaneously. Thus estimates of genetic and phenotypic correlations and heritability are easily obtained. The obvious problem of multiple-trait analysis is the additional computational requirements due to the increased number of equations to be solved. The other problem is that the more traits are analysed, the greater the probability of estimates outside the parameter space. 

The objective of this study is to suggest some solutions after discussing the problems imposed by the use of multiple-trait analysis together with its advantages. Simulation study has been carried out and the results are presented in table format.