The Revista Brasileira de Zootecnia (RBZ) is a publication dedicated to the broad field of Animal Science. We publish high-quality, original scientific research that spans across diverse areas within the discipline. The scope of RBZ encompasses a wide range of topics, including aquaculture, biometeorology and animal welfare, forage crops and grasslands, animal and forage plants breeding and genetics, animal reproduction, ruminant and non-ruminant nutrition, meat science and muscle biology, precision livestock, and animal production systems and agribusiness.
The Revista Brasileira de Zootecnia (RBZ) is a publication dedicated to the broad field of Animal Science. We publish high-quality, original scientific research that spans across diverse areas within the discipline. The scope of RBZ encompasses a wide range of topics, including aquaculture, biometeorology and animal welfare, forage crops and grasslands, animal and forage plants breeding and genetics, animal reproduction, ruminant and non-ruminant nutrition, meat science and muscle biology, precision livestock, and animal production systems and agribusiness.
The Revista Brasileira de Zootecnia (RBZ) is a publication dedicated to the broad field of Animal Science. We publish high-quality, original scientific research that spans across diverse areas within the discipline. The scope of RBZ encompasses a wide range of topics, including aquaculture, biometeorology and animal welfare, forage crops and grasslands, animal and forage plants breeding and genetics, animal reproduction, ruminant and non-ruminant nutrition, meat science and muscle biology, precision livestock, and animal production systems and agribusiness.
01/Jul/2016
Hikmet Orhan, Ecevit Eyduran, Adile Tatliyer, Hasan Saygici
DOI: 10.1590/S1806-92902016000700004
This study was conducted on 2049 eggs, collected from commercial white layer hybrids, with the purpose of predicting egg weight (EW) from egg quality characteristics such as shell weight (SW), albumen weight (AW), and yolk weight (YW). In the prediction of EW, ridge regression (RR), multiple linear regression (MLR), and regression tree analysis (RTM) methods were used. Predictive performance of RR and MLR methods was evaluated using the determination coefficient (R2) and variance inflation factor (VIF). R2 (%) coefficients for […]
Keywords: chaid algorithm; data mining; decision tree; multiple regression