Evaluation of a dynamic simulation model for milk production systems

Revista Brasileira de Zootecnia

Daniel De Noronha Figueiredo Vieira Da Cunha²  José Carlos Pereira²  Oriel Fajardo De Campos¹  José Luis Braga¹  Fabyano Fonseca E Silva¹  Janaina Azevedo Martuscello² 

[1] ,UFV Departamento de Zootecnia

关键词: dairy cattle;    modeling;    gado de leite;    modelagem;   

DOI  :  10.1590/S1516-35982010000400027

来源: SciELO

【 摘 要 】

The objective of this study was to develop and to evaluate a dynamic simulation model, with stochastic components in order to assess milk production systems. The simulation model was developed by using STELLA 9.0, ZooCalc 1.0 and electronic data sheets. The physical structure of the herd was divided into 15 interlinked modules that represented categories or subdivisions of categories. Mathematical models obtained from the literature were used to simulate the body weight of growing and lactating animals and milk production and milk composition. Electronic data sheets were used to calculate the nutritional requirements and dietary balance. After cost minimization, each feed was evaluated by using ZooCalc 1.0. Some average responses of farm size, zootechnical and economic index, the change in the area used for com silage production, the calving interval and age at first insemination were obtained to evaluate whether the simulation model was working consistently with the expected. To assess the capacity of the model to gene rate simulated values that approach reality, the degree of linear association was measured between the values generated by the model and the values observed in practice. Sensitivity analyses showed that the values produced by the simulation model were in agreement with the expected results, in response to changes in the area of com crop used for com silage production, the calving interval and the age at first insemination. There was correlation between the values generated by the simulation model and the values observed in practice and the degree of linear association for the variables could be considered high.

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