Benda P, Vyletĕlová M, Tichácek A
Research Institute for Cattle Breeding, Rapotín, Czech Republic.
Vet Med (Praha). 1997 Apr;42(4):101-9.
Parallel quantitative determination executed in 92 herds at 107 sampling dates was focused on the counts of major pathogens (Staphylococcus aureus, Streptococcus agalactiae) in bulk milk samples and on the prevalence of the above pathogens in a herd by examination of individual milk samples. The counts of main pathogens were also determined in terms of quantity in rinsing water before milking and in bulk samples in 5 herds with pipeline milking. Tab. I shows the qualitative analysis of the relation. Sensitivity of the method is satisfactory for the pathogens observed (95% and 91%, resp.), but method is less specific for Staph. aureus (67% against 92% Str. agalactiae). Figs. 1 and 2 show coordinate graphs of the results obtained while Figs. 3 and 4 document the distribution of frequency of the particular values in data sets. The values do not exhibit normal distribution (P < 0.01). Spearman's coefficient of rank correlation of bulk milk and individual examinations amounted to 0.823 and 0.900 for Staph. aureus and Str. agalactiae, respectively. Four mathematical models were tested in the course of quantitative analysis, describing the relation between bulk milk examination and individual examination: (1) linear regression, (2) linear regression with fixed starting point, (3) logarithmic regression and (4) irrational function. A model based on the equation of irrational function (4) was found to be best: y = a + bx + c square root of x + k +/- a1 + i(t)c1 square root of x + k1. Tab. II shows the parameters of the equation for examined microorganisms. Correlation coefficients for the above equation are r = 0.733 and r = 0.842 for Staph. aureus and Str. agalactiae, respectively. Prediction curves (Figs. 5 to 8) and confidence regions of prediction curves were also determined for the best model, and a prediction table was constructed (Tab. III). It was confirmed that the milking machines were not a significant source of direct contamination of bulk milk samples with the examined pathogens (Tab. V).
在92个牛群的107个采样日期进行的平行定量测定,重点是测定原料奶样本中主要病原体(金黄色葡萄球菌、无乳链球菌)的数量,以及通过检测个体奶样来确定上述病原体在牛群中的流行情况。还测定了5个采用管道挤奶的牛群中挤奶前冲洗水中主要病原体的数量以及原料奶样本中的数量。表I显示了这种关系的定性分析。该方法对所观察到的病原体的敏感性令人满意(分别为95%和91%),但对金黄色葡萄球菌的特异性较低(67%,而无乳链球菌为92%)。图1和图2展示了所得结果的坐标图,而图3和图4记录了数据集中特定值的频率分布。这些值不呈现正态分布(P < 0.01)。原料奶和个体检测的斯皮尔曼等级相关系数,金黄色葡萄球菌为0.823,无乳链球菌为0.900。在定量分析过程中测试了四个数学模型,描述原料奶检测和个体检测之间的关系:(1)线性回归,(2)有固定起点的线性回归,(3)对数回归和(4)无理函数。发现基于无理函数方程(4)的模型最佳:y = a + bx + c√x + k +/- a1 + i(t)c1√x + k1。表II显示了所检测微生物的方程参数。上述方程的相关系数,金黄色葡萄球菌为r = 0.733,无乳链球菌为r = 0.842。还为最佳模型确定了预测曲线(图5至8)和预测曲线的置信区间,并构建了预测表(表III)。证实了挤奶机不是所检测病原体对原料奶样本直接污染的重要来源(表V)。