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利用牛奶红外光谱预测泌乳早期放牧奶牛血 β-羟丁酸含量和高酮血症的发生。

Prediction of blood β-hydroxybutyrate content and occurrence of hyperketonemia in early-lactation, pasture-grazed dairy cows using milk infrared spectra.

机构信息

Department of Comparative Biomedicine and Food Science (BCA), University of Padova, 35020 Legnaro, Italy.

DairyNZ Ltd., 3240 Hamilton, New Zealand.

出版信息

J Dairy Sci. 2019 Jul;102(7):6466-6476. doi: 10.3168/jds.2018-15988. Epub 2019 May 10.

DOI:10.3168/jds.2018-15988
PMID:31079906
Abstract

The objective of this study was to evaluate the ability of milk infrared spectra to predict blood β-hydroxybutyrate (BHB) concentration for use as a management tool for cow metabolic health on pasture-grazed dairy farms and for large-scale phenotyping for genetic evaluation purposes. The study involved 542 cows (Holstein-Friesian and Holstein-Friesian × Jersey crossbreds), from 2 farms located in the Waikato and Taranaki regions of New Zealand that operated under a seasonal-calving, pasture-based dairy system. Milk infrared spectra were collected once a week during the first 5 wk of lactation. A blood "prick" sample was taken from the ventral labial vein of each cow 3 times a week for the first 5 wk of lactation. The content of BHB in blood was measured immediately using a handheld device. After outlier elimination, 1,910 spectra records and corresponding BHB measures were used for prediction model development. Partial least square regression and partial least squares discriminant analysis were used to develop prediction models for quantitative determination of blood BHB content and for identifying cows with hyperketonemia (HYK). Both quantitative and discriminant predictions were developed using the phenotypes and infrared spectra from two-thirds of the cows (randomly assigned to the calibration set) and tested using the remaining one-third (validation set). A moderate accuracy was obtained for prediction of blood BHB. The coefficient of determination (R) of the prediction model in calibration was 0.56, with a root mean squared error of prediction of 0.28 mmol/L and a ratio of performance to deviation, calculated as the ratio of the standard deviation of the partial least squares model calibration set to the standard error of prediction, of 1.50. In the validation set, the R was 0.50, with root mean squared error of prediction values of 0.32 mmol/L, which resulted in a ratio of performance to deviation of 1.39. When the reference test for HYK was defined as blood concentration of BHB ≥1.2 mmol/L, discriminant models indicated that milk infrared spectra correctly classified 76% of the HYK-positive cows and 82% of the HYK-negative cows. The quantitative models were not able to provide accurate estimates, but they could differentiate between high and low BHB concentrations. Furthermore, the discriminant models allowed the classification of cows with reasonable accuracy. This study indicates that the prediction of blood BHB content or occurrence of HYK from milk spectra is possible with moderate accuracy in pasture-grazed cows and could be used during routine milk testing. Applicability of infrared spectroscopy is not likely suited for obtaining accurate BHB measurements at an individual cow level, but discriminant models might be used in the future as herd-level management tools for classification of cows that are at risk of HYK, whereas quantitative models might provide large-scale phenotypes to be used as an indicator trait for breeding cows with improved metabolic health.

摘要

本研究的目的是评估牛奶红外光谱预测血液β-羟丁酸(BHB)浓度的能力,以便将其用作牧场奶牛代谢健康管理工具,以及用于遗传评估的大规模表型分析。该研究涉及来自新西兰怀卡托和塔拉纳基地区的 2 个农场的 542 头奶牛(荷斯坦-弗里生牛和荷斯坦-弗里生牛×泽西牛杂交牛),这些奶牛采用季节性产犊、牧场奶牛系统。在泌乳的前 5 周内,每周采集一次牛奶红外光谱。在泌乳的前 5 周内,每周 3 次从每头奶牛的下唇静脉采集血液“刺破”样本。立即使用手持设备测量血液中 BHB 的含量。在剔除异常值后,使用 1910 个光谱记录和相应的 BHB 测量值来开发预测模型。偏最小二乘回归和偏最小二乘判别分析用于开发定量测定血液 BHB 含量和识别高酮血症(HYK)奶牛的预测模型。使用三分之二的奶牛(随机分配到校准集中)的表型和红外光谱来开发定量和判别预测,然后使用剩余的三分之一(验证集)进行测试。血液 BHB 的预测具有中等准确性。校准中预测模型的决定系数(R)为 0.56,预测值的均方根误差为 0.28mmol/L,性能与偏差之比,计算为偏最小二乘模型校准集的标准差与预测标准误差之比,为 1.50。在验证集中,R 为 0.50,预测值的均方根误差为 0.32mmol/L,性能与偏差之比为 1.39。当 HYK 的参考测试定义为血液 BHB 浓度≥1.2mmol/L 时,判别模型表明,牛奶红外光谱正确分类了 76%的 HYK 阳性奶牛和 82%的 HYK 阴性奶牛。定量模型无法提供准确的估计,但它们可以区分高浓度和低浓度的 BHB。此外,判别模型可以以合理的准确性对奶牛进行分类。本研究表明,在放牧奶牛中,从牛奶光谱预测血液 BHB 含量或发生 HYK 的可能性具有中等准确性,并且可以在常规牛奶测试中使用。红外光谱的适用性不太可能适合在个体奶牛水平上获得准确的 BHB 测量值,但判别模型将来可能用作 herd-level 管理工具,用于对患有 HYK 风险的奶牛进行分类,而定量模型可能提供大规模表型作为用于繁殖具有改善代谢健康的奶牛的指示性状。

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