Scopus Eşleşmesi Bulundu
22
Cilt
453-462
Sayfa
🔓
Açık Erişim
Scopus Yazarları: S. Prabowo, Mustafa Garip
Özet
Depth dimensions are a fundamental linear type trait in the animal body included in dairy cattle science. Unfortunately, the prominent body depth dimension to milk yield is unspecified in lucidity. Thus, the objective of the current research was to identify the excellent body depth dimension of dairy cattle for milk yield as a selection precedence trait. The experiment employed 121 lactation Holstein cows aged specify as 2–6, raised on an Indonesian smallholder commercial dairy farm. R version 4.2.1 with RStudio software simultaneously worked as a statistical analysis tool. The principal component analysis (PCA), correlation, and regression analyses were executed sequentially. The product of the PCA revealed that the chest depth (CHD), body depth (BDD), and udder depth (UDD) traits are the essential body depth dimensions in dairy cattle. A crowning envoy associated with the milk yield capacity was delegated to the UDD trait. However, the UDD is the finest trait for the lactation cow selection program. Presumably, the BDD trait is the prime characteristic for calves and heifer selection schemes.
Anahtar Kelimeler (Scopus)
body measurement
Holstein cows
principal component
correlation
depth dimension
Anahtar Kelimeler
body measurement
correlation
depth dimension
Holstein cows
principal component.
principal component
mavi = YÖKSİS
yeşil = Scopus
Makale Bilgileri
Dergi
Universidade do Estado de Santa Catarina
ISSN
2238-1171
Yıl
2023
/ 8. ay
Cilt / Sayı
22
/ 3
Sayfalar
453 – 462
Makale Türü
Özgün Makale
Hakemlik
Hakemli
Endeks
Scopus (Elsevier)
TEŞV Puanı
48,00
Yayın Dili
İngilizce
Kapsam
Uluslararası
Toplam Yazar
2 kişi
Erişim Türü
Basılı+Elektronik
Erişim Linki
Makaleye Git
Alan
Sağlık Bilimleri Temel Alanı
Veteriner Zootekni
body measurement; correlation; depth dimension; Holstein cows; principal component.
YÖKSİS Yazar Kaydı
Yazar Adı
PRABOWO SİGİD, GARİP MUSTAFA
YÖKSİS ID
7759521
Hızlı Erişim
Metrikler
TEŞV Puanı
48,00
Yazar Sayısı
2