Ingham Steven C, Fanslau Melody A, Burnham Greg M, Ingham Barbara H, Norback John P, Schaffner Donald W
University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.
J Food Prot. 2007 Jun;70(6):1446-56. doi: 10.4315/0362-028x-70.6.1446.
A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3 degrees C. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a delta log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as delta log CFU > 0.3) in 67, 85, and 95% of the experiments with E. coli 0157:H7, Salmonella serovars, and S. aureus, respectively, and yielded fail-safe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.
开发了一种基于计算机的工具(可在www.wisc.edu/foodsafety/meatresearch获取),用于预测生猪肉、牛肉和禽肉中病原体的生长情况。该工具THERM(生肉温度历史评估)可预测猪肉和牛肉(大肠杆菌O157:H7、沙门氏菌血清型和金黄色葡萄球菌)以及禽肉(沙门氏菌血清型和金黄色葡萄球菌)在短期温度滥用期间病原体的生长情况。该模型的开发过程如下:将25克生碎猪肉、牛肉和火鸡肉样本接种目标病原体的五菌株混合菌液,并在10至43.3摄氏度的等温温度下保存。获取每个病原体每个样本的对数CFU数据,并通过DMFit软件用于确定滞后期持续时间(LPD)和生长速率(GR)。LPD和GR用于开发THERM预测工具,将生肉加工和储存的时间顺序和温度数据输入该工具。然后,THERM工具会预测所需病原体 - 产品组合的对数CFU增量值。在涉及多种产品(粗磨牛肉、去皮鸡胸肉、火鸡肩胛骨肉和火鸡碎肉)和温度滥用情况的20个不同接种实验中测试了THERM的准确性。利用每个实验的时间 - 温度数据,THERM分别在67%、85%和95%的大肠杆菌O157:H7、沙门氏菌血清型和金黄色葡萄球菌实验中准确预测了病原体的生长和不生长(生长定义为对数CFU增量>0.3),并在其余实验中做出了可靠的预测。我们得出结论,THERM是一种用于定性预测生肉中病原体行为(生长和不生长)的有用工具。潜在应用包括在HACCP(危害分析关键控制点)系统下评估过程偏差和关键限值。