Institute of Animal Science, Physiology Unit, University of Bonn, 53115 Bonn, Germany; College of Medical, Veterinary and Life Sciences, School of Veterinary Medicine, University of Glasgow, Garscube Estate, Switchback Road, Bearsden G611QH, United Kingdom.
Institute of Animal Science, Physiology Unit, University of Bonn, 53115 Bonn, Germany.
J Dairy Sci. 2022 Jul;105(7):6327-6338. doi: 10.3168/jds.2021-21434. Epub 2022 May 5.
The objectives of this study were (1) to characterize the interindividual variation in the relationship between antepartum (ap) backfat thickness (BFT) and subsequent BFT loss during early lactation in a large dairy herd using cluster analysis; (2) to compare the serum concentrations of metabolites (nonesterified fatty acids, β-hydroxybutyrate), metabolic hormones (leptin and adiponectin), and an inflammatory marker (haptoglobin) among the respective clusters; and (3) to compare lactation performance and uterine health status in the different clusters. An additional objective was (4) to investigate differences in these serum variables and in milk yield of overconditioned (OC) cows that differed in the extent of BFT loss. Using data from a large study of 1,709 multiparous Holstein cows, we first selected those animals from which serum samples and BFT results (mm) were available at d 25 (±10) ap and d 31 (±3 d) postpartum (pp). The remaining 713 cows (parity of 2 to 7) were then subjected to cluster analysis: different approaches based on the BFT of the cows were performed. K-means (unsupervised machine learning algorithm) clustering based on BFT-ap alone identified 5 clusters: lean (5-8 mm BFT, n = 50), normal (9-12 mm, n = 206), slightly fat (SF; 13-16 mm, n = 203), just fat (JF; 16-22 mm, n = 193), and very fat (VF; 23-43 mm, n = 61). Clustering by difference between BFT-ap and BFT-pp (ΔBFT) also revealed 5 clusters: extreme loss (17-23 mm ΔBFT, n = 16), moderate loss (9-15 mm, n = 119), little loss (4-8 mm, n = 326), no loss (0-3 mm, n = 203), and gain (-8 to -1 mm, n = 51). Based on the blood variables measured, our results confirm that cows with greater BFT losses had higher lipid mobilization and ketogenesis than cows with less BFT loss. The serum variables of cows that gained BFT did not differ from normal cows. Milk yield was affected by the BFT-ap cluster, but not by the ΔBFT cluster. Cows categorized as VF had lesser milk yield than other clusters. We further compared the OC cows that had little or no BFT loss (i.e., 2% of VF, 12% of JF, and 31% of SF, OC-no loss, n = 85) with the OC cows that lost BFT (OC-loss, n = 135). Both NEFA and BHB pp concentrations and milk yield were greater in OC-loss cows compared with the OC-no loss cows. The serum concentration of leptin ap was greater in OC-loss than in the OC-no loss cows. Overall, OC cows lost more BFT than normal or lean cows. However, those OC cows with a smaller loss of BFT produced less milk than OC cows with greater losses.
(1)利用聚类分析,描述大型奶牛场中产前(ap)背膘厚(BFT)与产后早期泌乳期 BFT 损失之间个体间变化的特征;(2)比较不同簇中代谢物(非酯化脂肪酸、β-羟丁酸)、代谢激素(瘦素和脂联素)和炎症标志物(触珠蛋白)的血清浓度;(3)比较不同簇的泌乳性能和子宫健康状况。另一个目的是(4)研究在 BFT 损失程度不同的过肥(OC)牛中,这些血清变量和牛奶产量的差异。使用来自一项大型荷斯坦奶牛多胎次研究的数据,我们首先选择了在 ap 第 25 天(±10 天)和产后第 31 天(±3 天)(pp)时可获得血清样本和 BFT 结果(mm)的动物。然后对其余 713 头奶牛(胎次 2 至 7)进行聚类分析:基于奶牛的 BFT 进行了不同的方法。基于 BFT-ap 单独使用 K-均值(无监督机器学习算法)聚类,确定了 5 个聚类:瘦(BFT 为 5-8mm,n = 50)、正常(9-12mm,n = 206)、轻度肥胖(SF;13-16mm,n = 203)、适度肥胖(JF;16-22mm,n = 193)和非常肥胖(VF;23-43mm,n = 61)。基于 BFT-ap 和 BFT-pp(ΔBFT)之间的差异聚类(聚类)也揭示了 5 个聚类:极端损失(17-23mmΔBFT,n = 16)、中度损失(9-15mm,n = 119)、少量损失(4-8mm,n = 326)、无损失(0-3mm,n = 203)和收益(-8 至-1mm,n = 51)。基于测量的血液变量,我们的结果证实,与 BFT 损失较少的奶牛相比,BFT 损失较大的奶牛具有更高的脂质动员和酮生成能力。BFT 增加的奶牛的血清变量与正常奶牛没有差异。产奶量受 BFT-ap 聚类的影响,但不受ΔBFT 聚类的影响。被归类为 VF 的奶牛的产奶量低于其他聚类。我们进一步比较了 BFT 损失很少或没有损失的 OC 奶牛(即 VF 的 2%、JF 的 12%和 SF 的 31%,OC-无损失,n = 85)与 BFT 损失的 OC 奶牛(OC-损失,n = 135)。与 OC-无损失的奶牛相比,OC-损失的奶牛在 pp 时的非酯化脂肪酸(NEFA)和β-羟丁酸(BHB)浓度和牛奶产量更高。与 OC-无损失的奶牛相比,OC-损失的奶牛在 ap 时的瘦素浓度更高。总的来说,OC 奶牛比正常或瘦奶牛损失更多的 BFT。然而,那些 BFT 损失较小的 OC 奶牛的产奶量比损失较大的 OC 奶牛少。