1Departamento de Ciencia Animal, Universidad Politécnica de Valencia, Valencia, Spain.
2Departamento Producción Animal, Universidad CEU Cardenal Herrera, Moncada, Valencia, Spain.
*Corresponding author: Tel. +34-963877007; E-mail: cjfernandez@dca.upv.es
To predict milk production in dairy goats using multiple component systems models, a homogenous group of 34 dairy goats within a commercial farm (Excamur, S.L.) was used. During 5 months lactation period body weight and dry matter intake were recorded and a multiple component system model was developed. The training models are characterized by an expanding set of management options such as feed intake, energy digestibility, locomotion energy expenditure and maintenance. Total milk yield during lactation by goat was simulated. Milk yield (MY) from a group of 10 goats (from literature) and the MY obtained at the present trial were used to validate the multiple component simulation models. An r of 0.93 was obtained between MY observed and predicted with the multiple component system. Therefore, the multiple component simulation models at the present work are useful to predict MY in Murciano-Granadina goat during lactation when total mixed ratio was used to feed the animals.
Multiple component model, dairy goat, milk yield prediction