Department of Animal Science, Michigan State University, East Lansing 48824.
Department of Animal Science, The Ohio State University, Wooster 44691.
J Dairy Sci. 2018 Feb;101(2):1123-1135. doi: 10.3168/jds.2017-13344. Epub 2017 Nov 23.
Our objective was to determine the effects of dry matter intake (DMI), body weight (BW), and diet characteristics on total tract digestibilities of dry matter, neutral detergent fiber, and starch (DMD, NDFD, and StarchD, respectively) in high-producing dairy cows. Our database was composed of 1,942 observations from 662 cows in 54 studies from Michigan, Ohio, and Georgia. On average, cows ate 23 ± 4.5 kg of dry matter/d, weighed 669 ± 79 kg, and produced 38 ± 10 kg of milk/d. Diets were 31 ± 5% neutral detergent fiber, 27 ± 6% starch, 2.6 ± 1.2% fatty acids, and 17 ± 1.4% crude protein. Digestibility means were 66 ± 6, 42 ± 11, and 93 ± 5% for DMD, NDFD, and StarchD, respectively. Forage sources included corn silage, alfalfa, and grasses. Corn source was classified by its ruminal fermentability. Data were analyzed using a mixed effects model, including diet chemical composition, forage source, and corn source, all expressed as percentage of dry matter, except for DMI, which was expressed as percentage of BW (DMI%BW); location and 2-way interactions were fixed effects. Cow, block, period, treatment, and study were included as random effects. Best fitting candidate models were generated using backward and stepwise regression methods. Additionally, the simplest model was generated using only DMI and location as fixed effects and all random effects. Candidate models were cross-validated across studies, and the resulting predictive correlation coefficients across studies (PC) and root mean square error of prediction (RMSEP) were compared by t-test. For each nutrient, the digestibility model that resulted in the highest PC and lowest RMSEP was determined to be the best fitting model. We observed heterogeneous coefficients among the different locations, suggesting that specific location factors influenced digestibilities. The overall location-averaged best fitting prediction equations were: DMD = 69 - 0.83 × DMI%BW (PC = 0.22, RMSEP = 5.39); NDFD = 53 + 0.26 × grass %DM - 0.59 × starch %DM + 3.06 × DMI%BW - 0.46 × DMI%BW (PC = 0.53, RMSEP = 9.70); and StarchD = 96 + 0.19 × HFERM%DM - 0.12 × starch %DM - 1.13 × DMI%BW (PC = 0.34, RMSEP = 4.77); where HFERM%DM is highly-fermentable corn source as percentage of DM. Our results confirm that digestibility is reduced as DMI increases, albeit at a lower rate than that reported in National Research Council. Furthermore, dietary starch depresses NDFD. Whereas DMD can be predicted based on DMI only, the best predictions for NDFD and StarchD require diet characteristics in addition to DMI.
我们的目标是确定干物质采食量（DMI）、体重（BW）和饮食特征对高产奶牛的干物质、中性洗涤纤维和淀粉（分别为 DMD、NDFD 和 StarchD）全肠道消化率的影响。我们的数据库由来自密歇根州、俄亥俄州和佐治亚州的 54 项研究中的 662 头奶牛的 1942 个观测值组成。平均而言，奶牛每天进食 23 ± 4.5 公斤干物质，体重为 669 ± 79 公斤，每天产奶 38 ± 10 公斤。日粮的中性洗涤纤维含量为 31 ± 5%，淀粉含量为 27 ± 6%，脂肪酸含量为 2.6 ± 1.2%，粗蛋白含量为 17 ± 1.4%。DMD、NDFD 和 StarchD 的消化率平均值分别为 66 ± 6%、42 ± 11%和 93 ± 5%。饲料来源包括玉米青贮、苜蓿和草。玉米来源按其瘤胃可发酵性进行分类。数据采用混合效应模型进行分析，包括日粮化学组成、饲料来源和玉米来源，除 DMI 外，所有成分均以干物质的百分比表示（DMI%BW）；DMI 以 BW 的百分比表示（DMI%BW）；位置和 2 向交互作用为固定效应。牛、块、时期、处理和研究被包含为随机效应。使用后退和逐步回归方法生成最佳拟合候选模型。此外，仅使用 DMI 和位置作为固定效应和所有随机效应生成最简单的模型。候选模型在研究之间进行交叉验证，通过 t 检验比较研究之间的预测相关系数（PC）和预测均方根误差（RMSEP）。对于每种营养素，确定产生最高 PC 和最低 RMSEP 的消化率模型为最佳拟合模型。我们观察到不同地点之间的系数存在异质性，这表明特定地点的因素会影响消化率。确定的最佳拟合预测方程为：DMD = 69 - 0.83 × DMI%BW（PC = 0.22，RMSEP = 5.39）；NDFD = 53 + 0.26 × 草 %DM - 0.59 × 淀粉 %DM + 3.06 × DMI%BW - 0.46 × DMI%BW（PC = 0.53，RMSEP = 9.70）；StarchD = 96 + 0.19 × HFERM%DM - 0.12 × 淀粉 %DM - 1.13 × DMI%BW（PC = 0.34，RMSEP = 4.77）；其中 HFERM%DM 是高可发酵性玉米源占 DM 的百分比。我们的结果证实，随着 DMI 的增加，消化率降低，尽管降低速度低于国家研究委员会报告的速度。此外，日粮淀粉会降低 NDFD。尽管 DMD 可以仅根据 DMI 进行预测，但 NDFD 和 StarchD 的最佳预测需要除 DMI 之外的饮食特征。
