Department of Dairy Science, University of Wisconsin-Madison, Madison 53705.
Department of Dairy Science, University of Wisconsin-Madison, Madison 53705.
J Dairy Sci. 2020 Apr;103(4):3774-3785. doi: 10.3168/jds.2019-17608. Epub 2020 Feb 13.
The objective of this study was to develop a model application to systematize nutritional grouping (NG) management in commercial dairy farms. The model has 4 sub-sections: (1) real-time data stream integration, (2) calculation of nutritional parameters, (3) grouping algorithm, and (4) output reports. A simulation study on a commercial Wisconsin dairy farm was used to evaluate our NG model. On this dairy farm, lactating cows (n = 2,374 ± 185) are regrouped weekly in 14 pens according to their parity and lactation stage, for which 9 diets are provided. Diets are seldom reformulated and nutritional requirements are not factored to allocate cows to pens. The same 14 pens were used to simulate the implementation of NG using our model, closely following the current farm criteria but also including predicted nutritional requirements (net energy for lactation and metabolizable protein; NE and MP) and milk yield in an attempt to generate more homogeneous groups of cows for improved diet accuracy. The goal of the simulation study was to implement a continuous weekly system for cows' pen allocation and diet formulation. The predicted MP and NE requirements from the NG were used to formulate the diets using commercial diet formulation software and the same feed ingredients, feed prices, and other criteria as the current farm diets. Diet MP and NE densities were adjusted to the nutritional group requirements. Results from the simulation study indicated that the NG model facilitates the implementation of an NG strategy and improves diet accuracy. The theoretical diet cost and predicted nitrogen supply with NG decreased for low-nutritional-requirement groups and increased for high-nutritional-requirement groups compared with current farm groups. The overall average N supply in diets for NG management was 15.14 g/cow per day less than the current farm grouping management. The average diet cost was $3,250/cow per year for current farm management and $3,219/cow per year for NG, which resulted in a theoretical $31/cow per year diet cost savings.
本研究旨在开发一种模型应用程序，以实现商业奶牛场的营养分组（NG）管理。该模型有 4 个部分：（1）实时数据流集成，（2）营养参数计算，（3）分组算法，（4）输出报告。利用威斯康星州一家商业奶牛场的模拟研究来评估我们的 NG 模型。在该奶牛场，泌乳奶牛（n=2374±185）每周根据胎次和泌乳阶段重新分组到 14 个畜栏中，为此提供了 9 种日粮。日粮很少重新配方，也不考虑营养需求来为畜栏分配奶牛。使用我们的模型模拟 NG 的相同 14 个畜栏，紧密遵循当前农场标准，但也包括预测的营养需求（泌乳净能和可代谢蛋白；NE 和 MP）和产奶量，以尝试为提高日粮准确性生成更均匀的奶牛组。模拟研究的目标是实施奶牛畜栏分配和日粮配方的连续每周系统。NG 的预测 MP 和 NE 需求用于使用商业日粮配方软件和与当前农场日粮相同的饲料成分、饲料价格和其他标准来配方日粮。日粮 MP 和 NE 密度根据营养组要求进行调整。模拟研究的结果表明，NG 模型有助于实施 NG 策略并提高日粮准确性。与当前农场分组相比，NG 理论日粮成本和预测氮供应减少了低营养需求组，增加了高营养需求组。NG 管理的日粮中氮总供应量比当前农场分组管理少 15.14 克/头/天。当前农场分组管理的日粮成本为 3250 美元/头/年，NG 管理的日粮成本为 3219 美元/头/年，这导致日粮成本每年节约 31 美元/头。
