Bannink A, Kogut J, Dijkstra J, France J, Kebreab E, Van Vuuren A M, Tamminga S
Wageningen University Research Center, Animal Sciences Group, Nutrition & Food, P.O. Box 65, 8200AB Lelystad, The Netherlands.
J Theor Biol. 2006 Jan 7;238(1):36-51. doi: 10.1016/j.jtbi.2005.05.026. Epub 2005 Aug 18.
The purpose of this study was to improve the prediction of the quantity and type of Volatile Fatty Acids (VFA) produced from fermented substrate in the rumen of lactating cows. A model was formulated that describes the conversion of substrate (soluble carbohydrates, starch, hemi-cellulose, cellulose, and protein) into VFA (acetate, propionate, butyrate, and other VFA). Inputs to the model were observed rates of true rumen digestion of substrates, whereas outputs were observed molar proportions of VFA in rumen fluid. A literature survey generated data of 182 diets (96 roughage and 86 concentrate diets). Coefficient values that define the conversion of a specific substrate into VFA were estimated meta-analytically by regression of the model against observed VFA molar proportions using non-linear regression techniques. Coefficient estimates significantly differed for acetate and propionate production in particular, between different types of substrate and between roughage and concentrate diets. Deviations of fitted from observed VFA molar proportions could be attributed to random error for 100%. In addition to regression against observed data, simulation studies were performed to investigate the potential of the estimation method. Fitted coefficient estimates from simulated data sets appeared accurate, as well as fitted rates of VFA production, although the model accounted for only a small fraction (maximally 45%) of the variation in VFA molar proportions. The simulation results showed that the latter result was merely a consequence of the statistical analysis chosen and should not be interpreted as an indication of inaccuracy of coefficient estimates. Deviations between fitted and observed values corresponded to those obtained in simulations.
本研究的目的是改进对泌乳奶牛瘤胃中发酵底物产生的挥发性脂肪酸(VFA)的数量和类型的预测。构建了一个模型,该模型描述了底物(可溶性碳水化合物、淀粉、半纤维素、纤维素和蛋白质)向VFA(乙酸、丙酸、丁酸和其他VFA)的转化。模型的输入是观察到的底物在瘤胃中的真实消化率,而输出是瘤胃液中VFA的摩尔比例。一项文献调查收集了182种日粮(96种粗饲料日粮和86种精饲料日粮)的数据。通过使用非线性回归技术,将模型与观察到的VFA摩尔比例进行回归,以荟萃分析的方式估计了定义特定底物向VFA转化的系数值。特别是乙酸和丙酸产生的系数估计值,在不同类型的底物之间以及粗饲料日粮和精饲料日粮之间存在显著差异。拟合的VFA摩尔比例与观察值之间的偏差可100%归因于随机误差。除了对观察数据进行回归外,还进行了模拟研究以调查估计方法的潜力。尽管该模型仅解释了VFA摩尔比例变化的一小部分(最大45%),但从模拟数据集中拟合得到的系数估计值以及VFA产生的拟合速率看起来是准确的。模拟结果表明,后一结果仅仅是所选统计分析的结果,不应被解释为系数估计不准确的迹象。拟合值与观察值之间的偏差与模拟中得到的偏差一致。