Animal Nutrition Group, Wageningen University, PO Box 338, 6700 AH, Wageningen, the Netherlands.
J Dairy Sci. 2013 Jul;96(7):4310-22. doi: 10.3168/jds.2012-6265. Epub 2013 May 9.
A meta-analysis was conducted on the effect of dietary and animal factors on the excretion of total urinary nitrogen (UN) and urinary urea nitrogen (UUN) in lactating dairy cattle in North America (NA) and northwestern Europe (EU). Mean treatment data were used from 47 trials carried out in NA and EU. Mixed model analysis was used with experiment included as a random effect and all other factors, consisting of dietary and animal characteristics, included as fixed effects. Fixed factors were nested within continent (EU or NA). A distinction was made between urinary excretions based on either urine spot samples or calculated assuming a zero N balance, and excretions that were determined by total collection of urine only. Moreover, with the subset of data based on total collection of urine, a new data set was created by calculating urinary N excretion assuming a zero N balance. Comparison with the original subset of data allowed for examining the effect of such an assumption on the relationship established between milk urea N (MUN) concentration and UN. Of all single dietary and animal factors evaluated to predict N excretion in urine, MUN and dietary crude protein (CP) concentration were by far the best predictors. Urinary N excretion was best predicted by the combination of MUN, CP, and dry matter intake, whereas UUN was best predicted by the combination of MUN and CP. All other factors did not improve or only marginally improved the prediction of UN or UUN. The relationship between UN and MUN differed between NA and EU, with higher estimated regression coefficients for MUN for the NA data set. Precision of UN and UUN prediction improved substantially when only UN or UUN data based on total collection of urine were used. The relationship between UN and MUN for the NA data set, but not for the EU data set, was substantially altered when UN was calculated assuming a zero N balance instead of being based on the total collection of urine. According to results of the present meta-analysis, UN and UUN are best predicted by the combination of MUN and CP and that, in regard to precision and accuracy, prediction equations for UN and UUN should be derived from the total collection of urine.
对北美（NA）和西北欧（EU）地区泌乳奶牛的饮食和动物因素对总尿氮（UN）和尿尿素氮（UUN）排泄的影响进行了荟萃分析。使用来自北美和欧盟的 47 项试验的平均处理数据。采用混合模型分析，将试验作为随机效应，所有其他因素（包括饮食和动物特征）作为固定效应。固定因素嵌套在大陆（EU 或 NA）内。根据尿液斑样本或假设零氮平衡计算的尿液排泄量进行区分，仅通过尿液总量收集确定的排泄量进行区分。此外，对于基于尿液总量收集的子数据集，通过假设零氮平衡来计算尿氮排泄量，创建了一个新的数据集。与原始子集数据进行比较，可检查这种假设对建立的牛奶尿素氮（MUN）浓度与 UN 之间关系的影响。在所评估的所有单一饮食和动物因素中，MUN 和饮食粗蛋白（CP）浓度是预测尿氮排泄的最佳指标。MUN、CP 和干物质摄入量的组合可最佳预测氮排泄，而 MUN 和 CP 的组合可最佳预测 UUN。所有其他因素都没有改善或仅略有改善 UN 或 UUN 的预测。UN 与 MUN 之间的关系在 NA 和 EU 之间存在差异，对于 NA 数据集，MUN 的估计回归系数更高。当仅使用基于尿液总量收集的 UN 或 UUN 数据时，UN 和 UUN 的预测精度会大大提高。当假设氮平衡为零时而不是基于尿液总量收集时，对于 NA 数据集而非 EU 数据集，UN 和 MUN 之间的关系发生了重大变化。根据本荟萃分析的结果，MUN 和 CP 的组合可最佳预测 UN 和 UUN，并且在精度和准确性方面，UN 和 UUN 的预测方程应从尿液总量收集得出。
