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使用康奈尔净碳水化合物和蛋白质系统进行全群优化。I. 用线性规划预测饲料生物学价值以优化日粮

Whole-herd optimization with the Cornell Net Carbohydrate and Protein System. I. Predicting feed biological values for diet optimization with linear programming.

作者信息

Tedeschi L O, Fox D G, Chase L E, Wang S J

机构信息

Department of Animal Science, Cornell University, Ithaca, NY 14853, USA.

出版信息

J Dairy Sci. 2000 Sep;83(9):2139-48. doi: 10.3168/jds.S0022-0302(00)75097-1.

Abstract

We developed a diet optimizer for least-cost diet formulation with the Cornell Net Carbohydrate and Protein System (CNCPS) using linear programming. The CNCPS model is intrinsically nonlinear, and feed biological values vary with animal and feed characteristics. To allow linear diet optimization, we first used the CNCPS model to generate biological values to characterize the energy and protein content of each feed for the specific group for which the diet was being formulated. The biological values used were metabolizable energy (Mcal/kg), metabolizable protein [(% dry matter (DM)], passage rate (%/h), bacteria yield efficiencies (g/g), and degradation rate of the carbohydrate B2 fraction (%/h). In addition, the ruminal balances for nitrogen and peptides were included in the optimizer to optimize ruminal degradation of fiber. The objective function was to minimize diet cost subject to animal requirement and feed availability constraints. The animal constraints were set by requirements for DM intake (kg/d), metabolizable energy (Mcal/kg), metabolizable protein (%DM), and effective neutral detergent fiber (%DM) for a given level of production. Data from a dairy farm were used to evaluate this linear diet optimizer. Across all classes of dairy cattle, the CNCPS 4.0 model typically obtained a solution in less than six iterations that met the requirements with nearly 100% accuracy. We conclude this linear optimizer can be used to accurately formulate least-cost diets with the CNCPS model.

摘要

我们使用线性规划开发了一种基于康奈尔净碳水化合物和蛋白质系统(CNCPS)的最低成本日粮配方优化器。CNCPS模型本质上是非线性的,饲料的生物学价值会因动物和饲料特性而有所不同。为了实现线性日粮优化,我们首先使用CNCPS模型生成生物学价值,以表征为特定组动物配制日粮时每种饲料的能量和蛋白质含量。所使用的生物学价值包括代谢能(兆卡/千克)、代谢蛋白质[(%干物质(DM)]、通过率(%/小时)、细菌产生效率(克/克)以及碳水化合物B2部分的降解率(%/小时)。此外,优化器中纳入了瘤胃氮和肽的平衡,以优化纤维的瘤胃降解。目标函数是在满足动物需求和饲料可用性约束的条件下使日粮成本最小化。动物约束条件是根据给定生产水平下对干物质摄入量(千克/天)、代谢能(兆卡/千克)、代谢蛋白质(%DM)和有效中性洗涤纤维(%DM)的要求来设定的。来自一个奶牛场的数据被用于评估这种线性日粮优化器。在所有奶牛类别中,CNCPS 4.0模型通常在不到六次迭代中就能获得一个几乎100%准确满足要求的解决方案。我们得出结论,这种线性优化器可用于使用CNCPS模型准确配制最低成本日粮。

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