Norwegian School of Veterinary Science, P.O. Box 8146 Dep., N-0033 Oslo, Norway.
J Food Prot. 2005 Aug;68(8):1600-5. doi: 10.4315/0362-028x-68.8.1600.
In the Norwegian Action Plan against Campylobacter in broilers, carcasses from flocks identified as positive before slaughter are either heat treated or frozen for 5 weeks to reduce the number of Campylobacter. The objective of this study was to estimate the effect of freezing time and predict the number of Campylobacter on naturally infected or contaminated broiler carcasses following freezing for 2, 4, 6, 8, 10, 13, 21, 35, and 120 days by nonparametric and parametric linear statistical models. From each of the five flocks, 27 carcasses were sampled. Each carcass was cut in two pieces along the chest bone. Half was put into the freezer (-20 degrees C), whereas the other was deskinned and quantitative culturing was conducted from a 10-g sample of the skin. Fifteen frozen halves were selected at random at each time point following freezing from 2 to 120 days, and skin samples from these were cultured quantitatively and qualitatively. In regard to the log reduction of Campylobacter, almost similar results were obtained using three statistical methods; median regression on the change in Campylobacter counts, zero-inflated negative binomial regression, and a Bayesian Markov chain Monte Carlo (decay) model on original counts. Overall, a 2-log reduction of Campylobacter was obtained after 3 weeks of freezing. Only a marginal extra effect was observed when extending the freezing to 5 weeks. Although freezing appears to be an efficient way to reduce the level of Campylobacter on broiler carcasses, in 80% of the carcasses Campylobacter could still be detected using quantitative culturing following 120 days of freezing. Based on the high number of zeros, these data should be modeled by a zero-inflated model. The best statistical fit in regard to goodness-of-fit measures was the zero-inflated negative binomial log link model, closely followed by the Poisson model. Thus, in our continued search for a better way to describe the data, we used the Poisson distribution in the mixed Bayesian decay models.
在挪威针对肉鸡弯曲杆菌的行动计划中，在屠宰前被确定为阳性的鸡群的胴体要么进行热处理，要么冷冻 5 周，以减少弯曲杆菌的数量。本研究的目的是通过非参数和参数线性统计模型来估计冷冻时间的影响，并预测在冷冻 2、4、6、8、10、13、21、35 和 120 天后，自然感染或污染的肉鸡胴体上弯曲杆菌的数量。从五个鸡群中，每个鸡群取 27 个胴体进行采样。每个胴体沿着胸骨切成两半。一半放入冷冻室（-20°C），另一半去皮，并从 10 克皮肤样本中进行定量培养。在冷冻 2 至 120 天后的每个时间点，随机选择 15 个冷冻半体，从这些半体中提取皮肤样本进行定量和定性培养。在弯曲杆菌的对数减少方面，使用三种统计方法几乎得到了相似的结果；基于弯曲杆菌计数变化的中位数回归、零膨胀负二项式回归，以及原始计数的贝叶斯马尔可夫链蒙特卡罗（衰减）模型。总体而言，冷冻 3 周后可获得 2 个对数的弯曲杆菌减少。在延长冷冻至 5 周时，仅观察到微小的额外效果。尽管冷冻似乎是一种有效的方法，可以降低肉鸡胴体上弯曲杆菌的水平，但在冷冻 120 天后，通过定量培养仍可检测到 80%的胴体中的弯曲杆菌。基于大量的零值，这些数据应该通过零膨胀模型进行建模。在拟合优度方面，最好的统计拟合是零膨胀负二项式对数链接模型，紧随其后的是泊松模型。因此，在我们继续寻找更好的方法来描述数据时，我们在混合贝叶斯衰减模型中使用了泊松分布。
