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Determination of the effect of the dam age, birth type, and sex on growth curve traits of hair goat kids

Tropical Animal Health and Production · Aralık 2023

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YÖKSİS Kayıtları
Determination of the effect of the dam age, birth type, and sex on growth curve traits of hair goat kids
Tropical Animal Health and Production · 2023 SCI-Expanded
DOKTOR ÖĞRETİM ÜYESİ MUSTAFA ÇAM →

Makale Bilgileri

DergiTropical Animal Health and Production
Yayın TarihiAralık 2023
Cilt / Sayfa55
Özet This study was conducted to investigate the best-fit growth curve and dam age, sex, and birth type effect on growth curve traits of hair goat kids. Monthly 3858 test day body weight (BW) records of 643 hair goat kids from birth to 150 days of age were used to determine the best-fit growth curve and estimate growth curve parameters with Gompertz and Von Bertalanffy models. The BW records were assigned to three groups: dam age (3, 4, 5, 6, 7 years), sex (female, male), and birth type (single, twin). The Gompertz model gave more consistent results than the Von Bertalanffy model according to the goodness of fit criteria. Dam age had no significant effect on any of the growth curve traits. Sex of kids showed a significant effect on maturity index (parameter K) (P < 0.001), estimated mature body weight (parameter A), and weight at point of inflection (IPW) (P < 0.01). Also, birth type had a significant effect on initial/birth weight (parameter B) and parameter K (P < 0.001). Age at point of inflection (IPT) was not affected by any of the factors. Twin kids had a higher maturity index than singles while females higher than males. In conclusion, the Gompertz model was the most suitable model for hair goat kids for selection strategies. For proper selection, the effect of sex and birth type on growth curve traits should be considered by hair goat breeders.

Yazarlar (3)

1
Serdar Güler
ORCID: 0000-0003-2499-9237
2
Mustafa Çam
ORCID: 0000-0002-1821-191X
3
Ali Atik
ORCID: 0000-0001-5722-8012

Anahtar Kelimeler

Growth Growth curve Hair goat Non-linear regression Parameter estimation

Kurumlar

Bahri Dagdas International Agricultural Research Institute
Konya Turkey
Selçuk Üniversitesi
Selçuklu Turkey

Metrikler

1
Atıf
3
Yazar
5
Anahtar Kelime