Dematawewa C M B, Pearson R E, Vanraden P M
Department of Dairy Science, Virginia Polytechnic Institute and State University, Blacksburg 24060, USA.
J Dairy Sci. 2007 Aug;90(8):3924-36. doi: 10.3168/jds.2006-790.
Modeling extended lactations for the US Holsteins is useful because a majority (>55%) of the cows in the present population produce lactations longer than 305 d. In this study, 9 empirical and mechanistic models were compared for their suitability for modeling 305-d and 999-d lactations of US Holsteins. A pooled data set of 4,266,597 test-day yields from 427,657 (305-d complete) lactation records from the AIPL-USDA database was used for model fitting. The empirical models included Wood (WD), Wilmink (WIL), Rook (RK), monophasic (MONO), diphasic (DIPH), and lactation persistency (LPM) functions; Dijkstra (DJ), Pollott (POL), and new-multiphasic (MULT) models comprised the mechanistic counterparts. Each model was separately tested on 305-d (>280 days in milk) and 999-d (>800 days in milk) lactations for cows in first parity and those in third and greater parities. All models were found to produce a significant fit for all 4 scenarios (2 parity groups and 2 lactation lengths). However, the resulting parameter estimates for the 4 scenarios were different. All models except MONO, DIPH, and LPM yielded residuals with absolute values smaller than 2 kg for the entire period of the 305-d lactations. For the extended lactations, the prediction errors were larger. However, the RK, DJ, POL, and MULT models were able to predict daily yield within a +/- 3 kg range for the entire 999-d period. The POL and MULT models (having 6 and 12 parameters, respectively) produced the lowest mean square error and Bayesian information criteria values, although the differences from the other models were small. Conversely, POL and MULT were often associated with poor convergence and highly correlated, unreliable, or biologically atypical parameter estimates. Considering the computational problems of large mechanistic models and the relative predictive ability of the other models, smaller models such as RK, DJ, and WD were recommended as sufficient for modeling extended lactations unless mechanistic details on the extended curves are needed. The recommended models were also satisfactory in describing fat and protein yields of 305-d and 999-d lactations of all parities.
对美国荷斯坦奶牛的延长泌乳期进行建模是有用的,因为当前群体中大多数(>55%)奶牛的泌乳期超过305天。在本研究中,比较了9种经验模型和机理模型对美国荷斯坦奶牛305天和999天泌乳期建模的适用性。使用来自美国动物改进协会-美国农业部数据库的427,657条(305天完整)泌乳记录中的4,266,597个测定日产奶量的汇总数据集进行模型拟合。经验模型包括伍德(WD)、威尔明克(WIL)、鲁克(RK)、单相(MONO)、双相(DIPH)和泌乳持久性(LPM)函数;迪杰斯特拉(DJ)、波洛特(POL)和新多相(MULT)模型构成了对应的机理模型。每个模型分别在头胎奶牛以及第三胎及以上胎次奶牛的305天(产奶>280天)和999天(产奶>800天)泌乳期上进行测试。发现所有模型对所有4种情况(2个胎次组和2种泌乳长度)都有显著拟合。然而,4种情况下得到的参数估计值不同。除MONO、DIPH和LPM外,所有模型在305天泌乳期的整个时间段内产生的残差绝对值均小于2千克。对于延长泌乳期,预测误差更大。然而,RK、DJ、POL和MULT模型在整个999天期间能够在±3千克范围内预测日产奶量。POL和MULT模型(分别有6个和12个参数)产生的均方误差和贝叶斯信息准则值最低,尽管与其他模型的差异很小。相反,POL和MULT常常与收敛性差以及参数估计高度相关、不可靠或生物学上不典型有关。考虑到大型机理模型的计算问题以及其他模型的相对预测能力,除非需要延长曲线的机理细节,建议使用RK、DJ和WD等较小的模型来对延长泌乳期进行建模就足够了。推荐的模型在描述所有胎次的305天和999天泌乳期的脂肪和蛋白质产量方面也令人满意。