New Approaches to Determination of the Best Nonlinear Function Describing Growth at Early Phases of Kivircik and Morkaraman Breeds

Eyduran E., Kuecuek M., Karakus K., Ozdemir T.

JOURNAL OF ANIMAL AND VETERINARY ADVANCES, cilt.7, sa.7, ss.799-804, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 7
  • Basım Tarihi: 2008
  • Dergi Adı: JOURNAL OF ANIMAL AND VETERINARY ADVANCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.799-804
  • Anahtar Kelimeler: Body weight, growth model, morkaraman breed, kivircik breed, Absolute Reduction Ratio, Absolute Reduction Ratio for Cut-off value, CURVE CHARACTERISTICS, FEMALE KIDS, MODELS, LAMBS, SHEEP
  • Gazi Üniversitesi Adresli: Hayır

Özet

The present study was to determine the most suitable nonlinear growth model explaining growth at early stage of lambs of Morkaraman and Kivircik breeds from birth to 180th days of age. For this aim, Monomolecular, Gompertz, Logistic with 3 parameter, Richards, logistic with 4 parameter growth models were used for explaining the body weight-time relationship on 4 breed-sex groups; namely, Morkaraman-Male, Morkaraman-Female, Kivircik-Male and Kivircik-Female. These growth models were fitted to weight-age data on basis of averages of all groups at each period. Body weights of these lambs were recorded fortnightly from birth to 180th days of age. Criteria such as R(2) and Root Mean Square Error (RMSE) and Asymptotic Correlation Coefficients (ACC) between growth parameters in all models were used to determine the best growth model explaining growth at early stage of weight-age of these lambs, Apart from these criteria, we developed two new approaches derived from Asymptotic Correlation Coefficients (ACC), namely, Absolute Reduction Ratio (%) (ARR) and Absolute Reduction Ratio for Cut-off value (%) (ARRC). It was concluded that the most appropriate growth model explaining body weight-time relationship at early phase of four groups was found to be Gompertz growth model and new approaches gave more effective results about testing effectiveness of growth models.