{"title":"Models for the Inactivation of Foodborne Pathogens in Salad Dressing from Challenge Studies","authors":"Donald W Schaffner , W. Clifton Baldwin","doi":"10.1016/j.jfp.2024.100384","DOIUrl":null,"url":null,"abstract":"<div><div>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 (<em>p</em> < 1E−6), in predicting the number of days to a five-log reduction of <em>Escherichia coli</em> O157:H7, while the percentage of spices in the formulation is also quite significant (<em>p</em> = 0.01). <em>Salmonella</em> modeling showed that the most highly significant parameter was the percentage of water (<em>p</em> < 1E−8). Other parameters in order of descending significance include the percent fruit (<em>p</em> = 0.00032), incubation temperature (<em>p</em> = 0.00268), followed by percent sugar (<em>p</em> = 0.02161) and percent vegetables (<em>p</em> = 0.03149). The most significant parameter in predicting <em>Listeria monocytogenes</em> reduction was incubation temperature (<em>p</em> = 0.000687), followed by acid moisture ratio (<em>p</em> = 0.012423). The next two significant parameters in the <em>Listeria</em> model were percent lipid (<em>p</em> = 0.023772) and percent water (<em>p</em> = 0.025701). The least significant parameter that meets the minimum criteria for inclusion in the <em>Listeria</em> model (<em>p</em> < 0.05) was percent fruit (<em>p</em> = 0.047074). Our analysis will be useful in developing risk-based approaches to continue to assure the safety of commercially prepared salad dressings.</div></div>","PeriodicalId":15903,"journal":{"name":"Journal of food protection","volume":"87 12","pages":"Article 100384"},"PeriodicalIF":2.1000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of food protection","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0362028X24001686","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.