Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites' levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

中文翻译：

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泌乳早期荷斯坦奶牛的血液和牛奶生物标志物的群内和群内变化。

在研究环境中，基于血液和牛奶的生物标记物已经进行了数十年的分析，尽管通常只在一个牛群中进行，而且没有关注与牛群或饮食特别相关的生物标记物的变化。生物标记物可用于检测生理失衡和疾病风险，并可能在精准畜牧业（PLF）中发挥作用。对于PLF中的使用，重要的是量化特定生物标志物的正常变异以及这种变异的来源。这项研究的目的是评估多种血液代谢产物（β-羟基丁酸酯（BHB），非酯化脂肪酸，葡萄糖和血清IGF-1），乳代谢产物（游离葡萄糖， 6-磷酸葡萄糖，尿素，异柠檬酸，BHB和尿酸），牛奶酶（乳酸脱氢酶和N-乙酰基-β-D-氨基葡萄糖苷酶（NAGase））和代谢失衡的综合指标（生理失衡指数和能量平衡），以帮助促进它们在PLF中的采用。从欧洲不同国家的6个实验牛群的234头荷斯坦奶牛中抽取了血液和牛奶，共提供10种不同的饮食。在大约14天的牛奶中（DIM）和35 DIM中两次采样血液。每周从DIM 1至50收集两次牛奶样品（总共2750个样品）。使用多级随机回归模型估计方差成分并计算类内相关性（ICC）。调整乳品代谢产物的ICC时，应在抽样时按均价和DIM进行调整，研究表明，代谢物水平变化的12％（6-磷酸葡萄糖）至46％（尿素）可能与牛群-饮食组合有关。与牛群-饮食组合相关的类内相关性对于血液代谢产物通常更高，从17％（胆固醇）到大约46％（BHB和尿素）。尿素的ICC高表明该生物标记物可用于畜群水平的监测。牛内NAGase的低方差表明描述状态所需的样本很少，并且有可能使用一般参考值。大多数生物标志物的ICC较低，而奶牛变异较大，这表明需要多个样本（最有可能在单个母牛身上），以使生物标志物可用于监测。