Department of Food Science and Technology, University of Georgia, Athens, GA, USA.
Egg Safety and Quality Research Unit, U.S. National Poultry Research Center, Agricultural Research Service, United States Department of Agriculture, Athens, GA, USA.
Poult Sci. 2021 Jun;100(6):101122. doi: 10.1016/j.psj.2021.101122. Epub 2021 Mar 11.
Contamination of poultry products by Campylobacter is often associated with farm management practices and processing plant practices. A longitudinal study was conducted on 11 pastured poultry farms in southeastern United States from 2014 to 2017. In this study, farm practices and processing variables were used as predictors for a random forest (RF) model to predict Campylobacter prevalence in pastured poultry farms and processing environments. Individual RF models were constructed for fecal, soil and whole carcass rinse after processing (WCR-P) samples. The performance of models was evaluated by the area under curve (AUC) from the receiver operating characteristics curve. The AUC values were 0.902, 0.894, and 0.864 for fecal, soil, and WCR-P models, respectively. Relative importance plots were generated to predict the most important variable in each RF model. Animal source of feces was identified as the most important variable in fecal model and the soy content of the brood feed was the most important variable for soil model. For WCR-P model, the average flock age showed the strongest impact on RF model. These RF models can help pastured poultry growers with food safety control strategies to reduce Campylobacter prevalence in pastured poultry farms.
受污染的家禽产品中弯曲杆菌通常与农场管理实践和加工厂的实践有关。2014 年至 2017 年，在美国东南部的 11 个牧场家禽养殖场进行了一项纵向研究。在这项研究中，农场实践和加工变量被用作随机森林（RF）模型的预测因子，以预测牧场家禽养殖场和加工环境中弯曲杆菌的流行率。为粪便、土壤和加工后整个禽体冲洗（WCR-P）样本分别构建了个体 RF 模型。通过接收器工作特征曲线的曲线下面积（AUC）评估模型的性能。粪便、土壤和 WCR-P 模型的 AUC 值分别为 0.902、0.894 和 0.864。生成相对重要性图以预测每个 RF 模型中最重要的变量。粪便模型中动物粪便来源被确定为最重要的变量，而土壤模型中豆粕的含量是最重要的变量。对于 WCR-P 模型，平均禽群年龄对 RF 模型的影响最大。这些 RF 模型可以帮助牧场家禽养殖者制定食品安全控制策略，以降低牧场家禽养殖场中弯曲杆菌的流行率。
