Magro Silvia, Costa Angela, Cavallini Damiano, Chiarin Elena, De Marchi Massimo
Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Legnaro, Italy.
Department of Veterinary Medical Sciences, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Front Vet Sci. 2024 Nov 25;11:1437352. doi: 10.3389/fvets.2024.1437352. eCollection 2024.
The incidence of metabolic diseases tends to be highest during the transition period (±3 weeks around parturition) in dairy cows due to physiological changes and the onset of lactation. Although blood profile testing allows for the monitoring of nutritional and metabolic status, conducting extensive analyses in the herd is costly and stressful for cows due to invasive procedures. Therefore, mid-infrared spectroscopy (MIR) could be seen as a valid alternative.
In the present study, we used laboratory-determined reference blood data and milk spectra of 349 Holstein cows to (i) identify the non-genetic factors affecting the variability of major blood traits in healthy cows and, subsequently, (ii) test the predictive ability of milk MIR. Cows belonged to 14 Italian commercial farms and were sampled once between 5 and 38 days in milk. For -hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), cholesterol, glucose, urea, total protein, albumin, globulin, minerals, aspartate aminotransferase, gamma-glutamyl transferase, creatine kinase, total bilirubin, and cortisol, the effects of parity, days in milk, and season were investigated using a linear model.
The results indicate that all fixed effects significantly affected the hematic concentration of most of the traits. Regarding MIR, the most predictable traits were BHB, NEFA, and urea, with coefficients of determination equal to 0.57, 0.62, and 0.89, respectively. These values suggest that MIR predictions of BHB and NEFA are not sufficiently accurate for precise and punctual determination of the hematic concentration, however, still the spectrum of the milk can be exploited to identify cows at risk of negative energy balance and subclinical ketosis. Finally, the predictions can be useful for herd screening, decision-making, and genetic evaluation.
由于生理变化和泌乳开始，代谢疾病在奶牛围产期（分娩前后约3周）的发病率往往最高。尽管血液指标检测有助于监测营养和代谢状况，但由于侵入性操作，在牛群中进行广泛分析成本高昂且会给奶牛带来压力。因此，中红外光谱法（MIR）可被视为一种有效的替代方法。
在本研究中，我们使用了349头荷斯坦奶牛的实验室测定参考血液数据和牛奶光谱，以（i）确定影响健康奶牛主要血液性状变异性的非遗传因素，随后，（ii）测试牛奶MIR的预测能力。这些奶牛来自14个意大利商业农场，在产奶5至38天之间进行了一次采样。对于β-羟基丁酸（BHB）、非酯化脂肪酸（NEFA）、胆固醇、葡萄糖、尿素、总蛋白、白蛋白、球蛋白、矿物质、天冬氨酸转氨酶、γ-谷氨酰转移酶、肌酸激酶、总胆红素和皮质醇，使用线性模型研究了胎次、产奶天数和季节的影响。
结果表明，所有固定效应均显著影响了大多数性状的血液浓度。关于MIR，最可预测的性状是BHB、NEFA和尿素，决定系数分别为0.57、0.62和0.89。这些值表明，MIR对BHB和NEFA的预测对于精确和及时测定血液浓度不够准确，然而，牛奶光谱仍可用于识别有负能量平衡和亚临床酮病风险的奶牛。最后，这些预测对于牛群筛查、决策制定和遗传评估可能有用。
