Kalantari A S, Armentano L E, Shaver R D, Cabrera V E
Department of Dairy Science, University of Wisconsin-Madison, Madison 53706.
Department of Dairy Science, University of Wisconsin-Madison, Madison 53706.
J Dairy Sci. 2016 Feb;99(2):1672-1692. doi: 10.3168/jds.2015-9810. Epub 2015 Dec 10.
This article evaluates the estimated economic impact of nutritional grouping in commercial dairy herds using a stochastic Monte Carlo simulation model. The model was initialized by separate data sets obtained from 5 commercial dairy herds. These herds were selected to explore the effect of herd size, structure, and characteristics on the economics and efficiency of nutrient usage according to nutritional grouping strategies. Simulated status of each cow was updated daily together with the nutrient requirements of net energy for lactation (NEL) and metabolizable protein (MP). The amount of energy consumed directly affected body weight (BW) and body condition score (BCS) changes. Moreover, to control the range of observed BCS in the model, constraints on lower (2.0) and upper (4.5) bounds of BCS were set. Each month, the clustering method was used to homogeneously regroup the cows according to their nutrient concentration requirements. The average NEL concentration of the group and a level of MP (average MP, average MP+0.5SD, or average MP+1SD) were considered to formulate the group diet. The calculated income over feed costs gain (IOFC, $/cow per yr) of having >1 nutritional group among the herds ranged from $33 to $58, with an average of $39 for 2 groups and $46 for 3 groups, when group was fed at average NEL concentration and average MP+1SD concentration. The improved IOFC was explained by increased milk sales and lower feed costs. Higher milk sales were a result of fewer cows having a milk loss associated with low BCS in multi-group scenarios. Lower feed costs in multi-group scenarios were mainly due to less rumen-undegradable protein consumption. The percentage of total NEL consumed captured in milk for >1 nutritional group was slightly lower than that for 1 nutritional group due to better distribution of energy throughout the lactation and higher energy retained in body tissue, which resulted in better herd BCS distribution. The percentage of fed N captured in milk increased with >1 group and was the most important factor for improved economic efficiency of grouping strategies.
本文使用随机蒙特卡洛模拟模型评估了商业奶牛群营养分组的估计经济影响。该模型由从5个商业奶牛群获得的单独数据集初始化。选择这些牛群是为了根据营养分组策略探索牛群规模、结构和特征对营养利用的经济性和效率的影响。每天更新每头奶牛的模拟状态以及泌乳净能量（NEL）和可代谢蛋白质（MP）的营养需求。能量消耗量直接影响体重（BW）和体况评分（BCS）变化。此外，为了控制模型中观察到的BCS范围，设定了BCS下限（2.0）和上限（4.5）的约束。每月使用聚类方法根据奶牛的营养浓度需求对其进行均匀重新分组。考虑组的平均NEL浓度和MP水平（平均MP、平均MP + 0.5标准差或平均MP + 1标准差）来制定组日粮。当以平均NEL浓度和平均MP + 1标准差浓度饲喂组时，牛群中拥有>1个营养组的计算饲料成本收益（IOFC，美元/头/年）范围为33美元至58美元，2组平均为39美元，3组平均为46美元。IOFC的提高是由于牛奶销售量增加和饲料成本降低。牛奶销售量增加是多组情况下因BCS低而产奶量损失的奶牛数量减少的结果。多组情况下饲料成本降低主要是由于瘤胃不可降解蛋白质消耗量减少。由于整个泌乳期能量分布更好且身体组织中保留的能量更高，导致牛群体况评分分布更好，>1个营养组的牛奶中捕获的总NEL消耗百分比略低于1个营养组。随着组数量>1，饲料中N在牛奶中的捕获百分比增加，这是分组策略提高经济效率的最重要因素。
