Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, 35020 Legnaro (PD), Italy.
Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, 35020 Legnaro (PD), Italy.
J Dairy Sci. 2019 Dec;102(12):11298-11307. doi: 10.3168/jds.2019-16937. Epub 2019 Sep 11.
Dairy cows commonly experience an unbalanced energy status in early lactation, and this condition can lead to the onset of several metabolic disorders. Blood metabolic profile testing is a valid tool to monitor and detect the most common early lactation disorders, but blood sampling and analysis are time-consuming and expensive, and the procedure is invasive and stressful for the cows. Mid-infrared (MIR) spectroscopy is routinely used to analyze milk composition, being a cost-effective and nondestructive method. The present study aimed to assess the feasibility of using routine milk MIR spectra for the prediction of main blood metabolites in dairy cows, and to investigate associations between measured blood metabolites and milk traits. Twenty herds of Holstein Friesian, Brown Swiss, or Simmental cows located in Northeast Italy were visited 1 to 4 times between December 2017 and June 2018, and blood and milk samples were collected from all lactating cows within 35 d in milk. Concentrations of main blood metabolites and milk MIR spectra were recorded from 295 blood and milk samples and used to develop prediction models for blood metabolic traits through backward interval partial least squares analysis. Blood β-hydroxybutyrate (BHB), urea, and nonesterified fatty acids were the most predictable traits, with coefficients of determination of 0.63, 0.58, and 0.52, respectively. On the contrary, predictive performance for blood glucose, triglycerides, cholesterol, glutamic oxaloacetic transaminase, and glutamic pyruvic transaminase were not accurate. Associations of blood BHB and urea with their respective contents in milk were moderate to strong, whereas all other correlations were weak. Predicted blood BHB showed an improved performance in detecting cows with hyperketonemia (blood BHB ≥ 1.2 mmol/L), compared with commercial calibration equation for milk BHB. Results highlighted the opportunity of using milk MIR spectra to predict blood metabolites and thus to collect routine information on the metabolic status of early-lactation cows at a population level.
奶牛在泌乳早期通常会经历能量失衡，这种情况会导致几种代谢紊乱的发生。血液代谢谱检测是监测和检测最常见的泌乳早期疾病的有效工具，但血液采样和分析既费时又昂贵，而且对奶牛来说具有侵入性和应激性。中红外（MIR）光谱分析常用于分析牛奶成分，是一种具有成本效益和非破坏性的方法。本研究旨在评估使用常规牛奶 MIR 光谱预测奶牛主要血液代谢物的可行性，并研究测量的血液代谢物与牛奶特性之间的关系。2017 年 12 月至 2018 年 6 月期间，在意大利东北部的 20 个荷斯坦弗里森、瑞士褐牛或西门塔尔牛牛群中进行了 1 到 4 次访问，在泌乳 35 天内从所有泌乳牛中采集了血液和牛奶样本。从 295 个血液和牛奶样本中记录了主要血液代谢物和牛奶 MIR 光谱，并通过向后间隔偏最小二乘分析为血液代谢特征开发预测模型。血液 β-羟丁酸（BHB）、尿素和非酯化脂肪酸是最可预测的特征，其决定系数分别为 0.63、0.58 和 0.52。相反，血糖、甘油三酯、胆固醇、谷草转氨酶和谷丙转氨酶的预测性能并不准确。血液 BHB 和尿素与其在牛奶中的含量之间的相关性从中等到强，而其他所有相关性都很弱。与牛奶 BHB 的商业校准方程相比，预测的血液 BHB 用于检测高酮血症（血液 BHB≥1.2mmol/L）的奶牛时表现出了更好的性能。结果突出了使用牛奶 MIR 光谱预测血液代谢物的机会，从而可以在群体水平上收集泌乳早期奶牛代谢状况的常规信息。
