Department of Animal Science, South Dakota State University, Brookings, SD.
Department of Natural Resource Management, South Dakota State University, Brookings, SD.
J Anim Sci. 2018 May 4;96(5):1914-1928. doi: 10.1093/jas/sky089.
Six ruminally cannulated cows (570 ± 73 kg) fed corn residues were placed in a 6 × 6 Latin square to evaluate predictions of diet composition from ruminally collected diet samples. After complete ruminal evacuation, cows were fed 1-kg meals (dry matter [DM]-basis) containing different combinations of cornstalk and leaf and husk (LH) residues in ratios of 0:100, 20:80, 40:60, 60:40, 80:20, and 100:0. Diet samples from each meal were collected by removal of ruminal contents after 1-h and were either unrinsed, hand-rinsed or machine-rinsed to evaluate effects of endogenous compounds on predictions of diet composition. Diet samples were analyzed for neutral (NDF) and acid (ADF) detergent fiber, acid detergent insoluble ash (ADIA), acid detergent lignin (ADL), crude protein (CP), and near infrared reflectance spectroscopy (NIRS) to calculate diet composition. Rinsing type increased NDF and ADF content and decreased ADIA and CP content of diet samples (P < 0.01). Rinsing tended to increase (P < 0.06) ADL content of diet samples. Differences in concentration between cornstalk and LH residues within each chemical component were standardized by calculating a coefficient of variation (CV). Accuracy and precision of estimates of diet composition were analyzed by regressing predicted diet composition and known diet composition. Predictions of diet composition were improved by increasing differences in concentration of chemical components between cornstalk and LH residues up to a CV of 22.6 ± 5.4%. Predictions of diet composition from unrinsed ADIA and machine-rinsed NIRS had the greatest accuracy (slope = 0.98 and 0.95, respectively) and large coefficients of determination (r2 = 0.86 and 0.74, respectively). Subsequently, a field study (Exp. 2) was performed to evaluate predictions of diet composition in cattle (646 ± 89 kg) grazing corn residue. Five cows were placed in 1 of 10 paddocks and allowed to graze continuously or to strip-graze corn residues. Predictions of diet composition from ADIA, ADL, and NIRS did not differ (P = 0.99), and estimates of cornstalk intake tended to be greater (P = 0.09) in strip-grazed compared to continuously grazed cows. These data indicate that diet composition can be predicted by chemical components or NIRS by ruminal collection of diet samples among cattle grazing corn residues.
六头安装有瘤胃瘘管的奶牛（570 ± 73 kg）用于评估从瘤胃液中采集的日粮样本预测日粮组成的准确性。在完全排空瘤胃后，奶牛饲喂含有不同玉米秸秆和叶与壳（LH）比例的 1 千克日粮（以干物质为基础），比例分别为 0:100、20:80、40:60、60:40、80:20 和 100:0。通过在 1 小时后移出瘤胃液来采集每个日粮的样本，然后对样本进行未冲洗、手冲洗或机洗，以评估内源性化合物对预测日粮组成的影响。分析日粮样本的中性（NDF）和酸性（ADF）洗涤纤维、酸性洗涤不溶灰分（ADIA）、酸性洗涤木质素（ADL）、粗蛋白（CP）和近红外反射光谱（NIRS），以计算日粮组成。冲洗类型增加了日粮样本的 NDF 和 ADF 含量，降低了 ADIA 和 CP 含量（P < 0.01）。冲洗趋于增加（P < 0.06）日粮样本的 ADL 含量。通过计算变异系数（CV），使每个化学组分中玉米秸秆和 LH 残体之间的浓度差异标准化。通过回归预测日粮组成和已知日粮组成来分析日粮组成估计的准确性和精度。通过增加玉米秸秆和 LH 残体之间化学组分浓度的差异，预测日粮组成的精度提高到 22.6 ± 5.4%。未冲洗的 ADIA 和机洗的 NIRS 预测日粮组成的准确性最高（斜率分别为 0.98 和 0.95），决定系数也较大（r2 分别为 0.86 和 0.74）。随后，进行了一项田间研究（Exp. 2），以评估在采食玉米残茬的牛中的日粮组成预测。将 5 头奶牛放置在 10 个围栏中的 1 个围栏中，让它们连续采食或条带状采食玉米残茬。ADIA、ADL 和 NIRS 预测的日粮组成没有差异（P = 0.99），与连续采食相比，条带采食的牛的玉米秸秆采食量估计值偏高（P = 0.09）。这些数据表明，在采食玉米残茬的牛中，通过瘤胃液采集日粮样本，可以通过化学组分或 NIRS 预测日粮组成。
