通过挑战研究建立沙拉酱中食源性病原体的失活模型。

IF 2.1 4区 农林科学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Journal of food protection Pub Date : 2024-10-16 DOI:10.1016/j.jfp.2024.100384
Donald W Schaffner , W. Clifton Baldwin
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引用次数: 0

摘要

沙拉酱和调味汁协会(ADS)的成员对沙拉酱产品进行了挑战研究,以评估病原体的存活率。本分析采用了 ADS 提供的 79 项不同挑战研究的数据。每项研究都提供了酸湿比、pH 值、培养温度和配料的详细信息。线性回归模型用于预测作为研究参数函数的 3-log、4-log 和 5-log降解时间。此外,还采用了一种基于统计的方法,根据测试历史来估计成分中的病原体浓度。再结合下降模型来估算病原体随时间变化的浓度。每种目标病原体的浓度下降 5 个对数的时间都是高度倾斜的。对减少 5 个对数的时间进行对数变换后,结果近似正态分布。孵育温度和配方 pH 值对预测大肠杆菌 O157:H7 降低 5 个对数值的天数非常重要(p < 1E-6),而配方中香料的百分比也非常重要(p = 0.01)。沙门氏菌模型显示,最显著的参数是水的百分比(p < 1E-8)。其他参数的显著性依次为水果百分比(p=0.00032)、培养温度(p=0.00268),其次是糖百分比(p=0.02161)和蔬菜百分比(p=0.03149)。预测李斯特菌减少的最重要参数是培养温度(p=0.000687),其次是酸水分比(p=0.012423)。李斯特菌模型中后两个重要参数是脂质百分比(p=0.023772)和水分百分比(p=0.025701)。符合李斯特菌模型最低标准的最不显著参数(p=0.023772)是脂肪百分比(p=0.023772)和水分百分比(p=0.025701)。
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Models for the Inactivation of Foodborne Pathogens in Salad Dressing from Challenge Studies
The Association for Dressings and Sauces’ (ADS) members have conducted challenge studies on salad dressing products to assess pathogen survival. Data from 79 different challenge studies provided by ADS were used in this analysis. The acid-moisture ratio, pH, incubation temperature, and ingredient details were provided for each study. Linear regression models were used to predict the time to 3-log, 4-log, and 5-log reduction as a function of study parameters. A statistically based approach also was used to estimate the concentration of pathogens in ingredients based on testing history. This was combined with decline modeling to estimate pathogen concentration over time. The time-to-five log reduction for each of the target pathogens were highly skewed. A logarithmic transformation of time to 5 log reduction resulted in approximately normal distributions. Incubation temperature and formulation pH were highly significant (p < 1E−6), in predicting the number of days to a five-log reduction of Escherichia coli O157:H7, while the percentage of spices in the formulation is also quite significant (p = 0.01). Salmonella modeling showed that the most highly significant parameter was the percentage of water (p < 1E−8). Other parameters in order of descending significance include the percent fruit (p = 0.00032), incubation temperature (p = 0.00268), followed by percent sugar (p = 0.02161) and percent vegetables (p = 0.03149). The most significant parameter in predicting Listeria monocytogenes reduction was incubation temperature (p = 0.000687), followed by acid moisture ratio (p = 0.012423). The next two significant parameters in the Listeria model were percent lipid (p = 0.023772) and percent water (p = 0.025701). The least significant parameter that meets the minimum criteria for inclusion in the Listeria model (p < 0.05) was percent fruit (p = 0.047074). Our analysis will be useful in developing risk-based approaches to continue to assure the safety of commercially prepared salad dressings.
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来源期刊
Journal of food protection
Journal of food protection 工程技术-生物工程与应用微生物
CiteScore
4.20
自引率
5.00%
发文量
296
审稿时长
2.5 months
期刊介绍: The Journal of Food Protection® (JFP) is an international, monthly scientific journal in the English language published by the International Association for Food Protection (IAFP). JFP publishes research and review articles on all aspects of food protection and safety. Major emphases of JFP are placed on studies dealing with: Tracking, detecting (including traditional, molecular, and real-time), inactivating, and controlling food-related hazards, including microorganisms (including antibiotic resistance), microbial (mycotoxins, seafood toxins) and non-microbial toxins (heavy metals, pesticides, veterinary drug residues, migrants from food packaging, and processing contaminants), allergens and pests (insects, rodents) in human food, pet food and animal feed throughout the food chain; Microbiological food quality and traditional/novel methods to assay microbiological food quality; Prevention of food-related hazards and food spoilage through food preservatives and thermal/non-thermal processes, including process validation; Food fermentations and food-related probiotics; Safe food handling practices during pre-harvest, harvest, post-harvest, distribution and consumption, including food safety education for retailers, foodservice, and consumers; Risk assessments for food-related hazards; Economic impact of food-related hazards, foodborne illness, food loss, food spoilage, and adulterated foods; Food fraud, food authentication, food defense, and foodborne disease outbreak investigations.
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