Multiple linear regression models based on principal component scores to predict slaughter weight of broiler

Mendes M.

ARCHIV FUR GEFLUGELKUNDE, cilt.73, sa.2, ss.139-144, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 73 Sayı: 2
  • Basım Tarihi: 2009
  • Dergi Adı: ARCHIV FUR GEFLUGELKUNDE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.139-144
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

The aim of this study was to predict slaughter weight of male chickens by using principal component scores in multiple regression analysis. Chickens were raised under two different stocking densities. Four weeks age of body measurements were used as predictor variables. Two different approaches were used for those aims. In the first approach, only one selected score value obtained by principal component analysis was used for the prediction of slaughter weight. In the second approach, all six score values obtained from principal component analysis were used as independent variables.