Green L E, Schukken Y H, Green M J
Ecology and Epidemiology Group, Department of Biological Sciences, University of Warwick, Coventry CV4 7AL, UK.
Prev Vet Med. 2006 Sep 15;76(1-2):74-89. doi: 10.1016/j.prevetmed.2006.04.012. Epub 2006 Jun 14.
Researchers have reported that as milk yield increases composite milk somatic cell count (SCC) is diluted in cattle with no intramammary infection (IMI) and as a consequence, estimates of SCC from high yields are lower than estimates of SCC from low yields in dairy cows without an IMI. To date, estimates of reduced milk yield associated with high SCC because of intramammary infection have not been adjusted for any dilution of SCC. Ignoring dilution is therefore likely to lead to an overestimate of reduction in yield with increasing SCC. This paper investigates scenarios of the possible impact of dilution and inflammation on the association between somatic cell count and yield. The data used to investigate this relationship come from 8373 monthly records of milk yield and composite somatic cell count, together with incidence of clinical mastitis, which were recorded on 850 cows from five dairy cattle farms in Gloucestershire, UK. Two sets of models were used to investigate dilution and inflammation using two-level hierarchical models. The first set of models was used to estimate the linear (dilution) and log10-linear (inflammation) impact of SCC on the outcome variable milk yield. Five general linear models with increasing inclusion of higher test day SCC values were run. The cumulative categories were test day SCC values of up to and inclusive of 30, 50, 100, 200 and 400x10(3)cells/ml. Linear and log linear SCC influences on milk yield were estimated. At low SCC values the linear SCC predictor was dominant, while at higher values the log linear predictor was dominant. Up to 100x10(3)cells/ml there was mostly a slightly negative linear relationship between SCC and yield, potentially indicating a dilution effect. In the second set of models, three approaches to adjust milk loss for dilution were compared with an unadjusted model. In general, dilution-adjusted SCC values fitted the data better and resulted in a slightly lower milk loss per SCC category compared with unadjusted SCC. In all models with a dilution term there was a significant reduction in yield with SCC>200x10(3)cells/ml.
研究人员报告称，随着产奶量增加，在没有乳房内感染（IMI）的奶牛中，混合乳体细胞计数（SCC）会被稀释，因此，在没有IMI的奶牛中，高产奶量时的SCC估计值低于低产奶量时的SCC估计值。迄今为止，由于乳房内感染导致的与高SCC相关的产奶量减少估计值尚未针对SCC的任何稀释情况进行调整。因此，忽略稀释情况可能会导致随着SCC增加而高估产奶量的减少。本文研究了稀释和炎症对体细胞计数与产奶量之间关联的可能影响情况。用于研究这种关系的数据来自英国格洛斯特郡五个奶牛场850头奶牛的8373条月度产奶量和混合体细胞计数记录，以及临床乳腺炎发病率记录。使用两级分层模型，通过两组模型来研究稀释和炎症情况。第一组模型用于估计SCC对结果变量产奶量的线性（稀释）和对数线性（炎症）影响。运行了五个逐步纳入更高检测日SCC值的一般线性模型。累积类别为检测日SCC值高达并包括30、50、100、200和400×10³个细胞/毫升。估计了线性和对数线性SCC对产奶量的影响。在低SCC值时，线性SCC预测因子占主导，而在高SCC值时，对数线性预测因子占主导。高达100×10³个细胞/毫升时，SCC与产奶量之间大多存在轻微的负线性关系，这可能表明存在稀释效应。在第二组模型中，将三种针对稀释调整产奶量损失的方法与未调整模型进行了比较。总体而言，经稀释调整的SCC值与数据拟合得更好，与未调整的SCC相比，每个SCC类别导致的产奶量损失略低。在所有带有稀释项的模型中，当SCC>200×10³个细胞/毫升时，产奶量显著减少。
