scholarly journals Kinetics of Hydrothermal Inactivation of Endotoxins

2010 ◽  
Vol 77 (8) ◽  
pp. 2640-2647 ◽  
Author(s):  
Lixiong Li ◽  
Chris L. Wilbur ◽  
Kathryn L. Mintz
Keyword(s):  
Linear Models ◽  
Flow Reactor ◽  
Feed Water ◽  
Content Type ◽  
Linear Pattern ◽  
Log Reduction ◽  
Microbial Survival ◽  
Weibull Models ◽  
Modified Weibull ◽  
Log Linear

ABSTRACTA kinetic model was established for the inactivation of endotoxins in water at temperatures ranging from 210°C to 270°C and a pressure of 6.2 × 106Pa. Data were generated using a bench scale continuous-flow reactor system to process feed water spiked with endotoxin standard (Escherichia coliO113:H10). Product water samples were collected and quantified by theLimulusamebocyte lysate assay. At 250°C, 5-log endotoxin inactivation was achieved in about 1 s of exposure, followed by a lower inactivation rate. This non-log-linear pattern is similar to reported trends in microbial survival curves. Predictions and parameters of several non-log-linear models are presented. In the fast-reaction zone (3- to 5-log reduction), the Arrhenius rate constant fits well at temperatures ranging from 120°C to 250°C on the basis of data from this work and the literature. Both biphasic and modified Weibull models are comparable to account for both the high and low rates of inactivation in terms of prediction accuracy and the number of parameters used. A unified representation of thermal resistance curves for a 3-log reduction and a 3Dvalue associated with endotoxin inactivation and microbial survival, respectively, is presented.

The impact of corruption on sport demand

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carlo Amenta ◽  
Paolo Di Betta
Keyword(s):  
Design Methodology ◽  
Linear Models ◽  
Negative Externalities ◽  
Data Set ◽  
Content Type ◽  
Long Run ◽  
Log Linear ◽  
Systemic Corruption ◽  
The Impact

PurposeThe article presents an empirical analysis that evaluates the effects of a systemic corruption scandal on the demand in the short and the long run. In 2006, the Calciopoli scandal uncovered the match rigging in the Italian soccer first division. The exemplary sportive sanction of relegating the primary culprit to the second division imposed further negative externalities on the other clubs. Should we prefer the sportive sanction on the team or the monetary fines for the club?Design/methodology/approachWe estimated two log-linear models of the demand side (stadium attendance) using a fixed effect estimator, on two panel data set made of all the Italian soccer clubs in the first and second division (Serie A and Serie B) for the seasons 2004/2005 to 2009/2010, considering the relegation of the Juventus as the event which impacted the demand for soccer.FindingsRelegating Juventus to Serie B caused an immediate decrease of 18.4% in the attendance for all the teams, both in Serie A and in Serie B, for the three seasons considered, and 1% decrease when all the seasons are considered to measure the fallout of the scandal on the fans' disaffection.Originality/valueThe effect of corruption in sport on demand is an important issue, and there are few studies already published. As for sports economics and management, our results are of interest for sport-governing bodies – as a case study that can help in designing a more effective sanctioning system to prevent corruption episodes.

Monitoring multinomial logistic profiles in Phase I using log-linear models

2018 ◽  
Vol 35 (3) ◽  
pp. 678-689 ◽  
Author(s):  
Hamidreza Izadbakhsh ◽  
Rassoul Noorossana ◽  
Seyed Taghi Akhavan Niaki
Keyword(s):  
Phase I ◽  
Generalized Linear Model ◽  
Control Charts ◽  
Design Methodology ◽  
Linear Models ◽  
Multinomial Logistic Regression ◽  
Test Method ◽  
Ratio Test ◽  
Content Type ◽  
Log Linear

Purpose The purpose of this paper is to apply Poisson generalized linear model (PGLM) with log link instead of multinomial logistic regression to monitor multinomial logistic profiles in Phase I. Hence, estimating the coefficients becomes easier and more accurate. Design/methodology/approach Simulation technique is used to assess the performance of the proposed algorithm using four different control charts for monitoring. Findings The proposed algorithm is faster and more accurate than the previous algorithms. Simulation results also indicate that the likelihood ratio test method is able to detect out-of-control parameters more efficiently. Originality/value The PGLM with log link has not been used to monitor multinomial profiles in Phase I.

Inactivation Kinetics of Pathogens during Thermal Processing in Acidified Broth and Tomato Purée (pH 4.5)

2017 ◽  
Vol 80 (12) ◽  
pp. 2014-2021 ◽  
Author(s):  
Evann L. Dufort ◽  
Jonathan Sogin ◽  
Mark R. Etzel ◽  
Barbara H. Ingham
Keyword(s):  
Thermal Inactivation ◽  
Weibull Model ◽  
Inactivation Kinetics ◽  
E Coli ◽  
Log Reduction ◽  
Tomato Puree ◽  
Weibull Models ◽  
Canned Foods ◽  
D Values ◽  
Log Linear

ABSTRACT Thermal inactivation kinetics for single strains of Shiga toxin–producing Escherichia coli (STEC), Listeria monocytogenes, and Salmonella enterica were measured in acidified tryptic soy broth (TSB; pH 4.5) heated at 54°C. Inactivation curves also were measured for single-pathogen five-strain cocktails of E. coli O157:H7, L. monocytogenes, and S. enterica heated in tomato purée (pH 4.5) at 52, 54, 56, and 58°C. Inactivation curves were fit using log-linear and nonlinear (Weibull) models. The Weibull model yields the time for a 5-log reduction (t*) and a curve shape parameter (β). Decimal reduction times (D-values) and thermal resistance constants (z-values) from the two models were compared by defining t* = 5D* for the Weibull model. When the log-linear and Weibull models match at the 5-log reduction time, then t* = 5D* = 5D and D = D*. In 18 of 20 strains heated in acidified TSB, D and D* for the two models were not significantly different, although nonlinearity was observed in 35 of 60 trials. Similarly, in 51 of 52 trials for pathogen cocktails heated in tomato purée, D and D* were not significantly different, although nonlinearity was observed in 31% of trials. At a given temperature, D-values for S. enterica << L. monocytogenes < E. coli O157:H7 in tomato purée (pH 4.5). When using the two models, z-values calculated from the D-values were not significantly different for a given pathogen. Across all pathogens, z-values for E. coli O157:H7 and S. enterica were not different but were significantly lower than the z-values for L. monocytogenes. These results are useful for supporting process filings for tomato-based acidified food products with pH 4.5 and below and are relevant to small processors of tomato-based acidified canned foods who do not have the resources to conduct research on and validate pathogen lethality.

scholarly journals Evaluation of the Thermal Inactivation of a Salmonella Serotype Oranienburg Strain During Cocoa Roasting at Conditions Relevant to the Fine Chocolate Industry

2021 ◽  
Vol 12 ◽  
Author(s):  
Runan Yan ◽  
Gabriella Pinto ◽  
Rebecca Taylor-Roseman ◽  
Karen Cogan ◽  
Greg D’Alesandre ◽  
...  
Keyword(s):  
Foodborne Pathogens ◽  
Thermal Inactivation ◽  
Linear Models ◽  
Control Point ◽  
Weibull Model ◽  
Inactivation Kinetics ◽  
Critical Control Point ◽  
Chocolate Industry ◽  
Weibull Models ◽  
Log Linear

Cocoa roasting produces and enhances distinct flavor of chocolate and acts as a critical control point for inactivation of foodborne pathogens in chocolate production. In this study, the inactivation kinetics of Salmonella enterica subsp. enterica serotype Oranienburg strain was assessed on whole cocoa beans using roasting protocols relevant to the fine chocolate industry. Beans were inoculated with 107–108 log10 CFU/bean of Salmonella Oranienburg and roasted at 100–150°C for 2–100 min. A greater than 5 log10 reduction of S. Oranienburg was experimentally achieved after 10-min roasting at 150°C. Data were fitted using log-linear and Weibull models. The log-linear models indicated that the roasting times (D) needed to achieve a decimal reduction of Salmonella at 100, 110, 115, 120, 130, and 140°C were 33.34, 18.57, 12.92, 10.50, 4.20, and 1.90 min, respectively. A Weibull model indicated a decrease in the Salmonella inactivation rate over time (β < 1). Statistical analysis indicated that the Weibull model fitted the data better compared to a log-linear model. These data demonstrate the efficacy of cocoa roasting in inactivation of Salmonella and may be used to guide food safety decision-making.

scholarly journals Environmental Factors Associated with High Fly Densities and Diarrhea in Vellore, India

2015 ◽  
Vol 81 (17) ◽  
pp. 6053-6058 ◽  
Author(s):  
Stefan Collinet-Adler ◽  
Sudhir Babji ◽  
Mark Francis ◽  
Deepthi Kattula ◽  
Prasanna Samuel Premkumar ◽  
...  
Keyword(s):  
Linear Models ◽  
Significant Risk ◽  
Enteric Bacteria ◽  
Enteric Pathogens ◽  
Indian Children ◽  
Content Type ◽  
E Coli ◽  
Relative Risks ◽  
Log Linear ◽  
Children Under 5

ABSTRACTDiarrhea causes significant morbidity and mortality in Indian children under 5 years of age. Flies carry enteric pathogens and may mediate foodborne infections. In this study, we characterized fly densities as a determinant of infectious diarrhea in a longitudinal cohort of 160 urban and 80 rural households with 1,274 individuals (27% under 5 years of age) in Vellore, India. Household questionnaires on living conditions were completed at enrollment. Fly abundance was measured during the wet and dry seasons using fly ribbons placed in kitchens. PCRs for enteric bacteria, viruses, and protozoa were performed on 60 fly samples. Forty-three (72%) fly samples were positive for the following pathogens: norovirus (50%),Salmonellaspp. (46.7%), rotavirus (6.7%), andEscherichia coli(6.7%). Ninety-one episodes of diarrhea occurred (89% in children under 5 years of age). Stool pathogens isolated in 24 of 77 (31%) samples includedE. coli,Shigellaspp.,Vibriospp.,Giardia,Cryptosporidium, and rotavirus. Multivariate log-linear models were used to explore the relationships between diarrhea and fly densities, controlling for demographics, hygiene, and human-animal interactions. Fly abundance was 6 times higher in rural than urban sites (P< 0.0001). Disposal of garbage close to homes and rural living were significant risk factors for high fly densities. The presence of latrines was protective against high fly densities and diarrhea. The adjusted relative risks of diarrheal episodes and duration of diarrhea, associated with fly density at the 75th percentile, were 1.18 (95% confidence interval [CI], 1.03 to 1.34) and 1.15 (95% CI, 1.02 to 1.29), respectively. Flies harbored enteric pathogens, including norovirus, a poorly documented pathogen on flies.

scholarly journals Combined Effect of Temperature and Relative Humidity on the Survival of Salmonella Isolates on Stainless Steel Coupons

2022 ◽  
Vol 19 (2) ◽  
pp. 909
Author(s):  
Amreen Bashir ◽  
Peter A. Lambert ◽  
Yvonne Stedman ◽  
Anthony C. Hilton
Keyword(s):  
Stainless Steel ◽  
Relative Humidity ◽  
Storage Conditions ◽  
Effect Of Temperature ◽  
Inactivation Kinetics ◽  
Survival Curves ◽  
Weibull Models ◽  
Higher Temperature ◽  
Modified Weibull ◽  
Log Linear

The survival on stainless steel of ten Salmonella isolates from food factory, clinical and veterinary sources was investigated. Stainless steel coupons inoculated with Salmonella were dried and stored at a range of temperatures and relative humidity (RH) levels representing factory conditions. Viability was determined from 1 to 22 days. Survival curves obtained for most isolates and storage conditions displayed exponential inactivation described by a log-linear model. Survival was affected by environmental temperatures and RH with decimal reduction times (DRTs) ranging from <1 day to 18 days. At 25 °C/15% RH, all isolates survived at levels of 103 to 105 cfu for >22 days. Furthermore, temperatures and RH independently influenced survival on stainless steel; increasing temperatures between 10 °C and 37 °C and increasing RH levels from 30–70% both decreased the DRT values. Survival curves displaying a shoulder followed by exponential death were obtained for three isolates at 10 °C/70% RH. Inactivation kinetics for these were described by modified Weibull models, suggesting that cumulative injury occurs before cellular inactivation. This study highlights the need to control temperature and RH to limit microbial persistence in the food manufacturing environment, particularly during the factory shut-down period for cleaning when higher temperature/humidity levels could be introduced.

scholarly journals Comparing Log-Linear and Best-Fit Models to Evaluate the Long-Term Persistence of Enteric Markers in Sewage Spiked River Water

2021 ◽  
Vol 3 ◽  
Author(s):  
Yolanda M. Brooks ◽  
Joan B. Rose
Keyword(s):  
Water Quality ◽  
River Water ◽  
Linear Models ◽  
Decay Rates ◽  
Fecal Indicator ◽  
Quality Models ◽  
Linear Pattern ◽  
Log Linear ◽  
Water Quality Models ◽  
Best Fit

Water quality models use log-linear decay to estimate the inactivation of fecal indicator bacteria (FIB). The decay of molecular measurements of FIB does not follow a log-linear pattern. This study examined the factors associated with the persistence of Escherichia coli uidA, enterococci 23S rDNA, and Bacteroides thetataiotaomicron 1,6 alpha mannanase in microcosms containing 10% (vol/vol) sewage spiked river water stored at 4°C for up to 337 days. The study estimated the markers' persistence with log-linear models (LLMs) to the best-fit models, biphasic exponential decay (BI3) and log-logistic (JM2) and compared the estimates from the models. Concentrations of B. thetataiotaomicon decreased to levels below detection after 31 days in storage and were not fit to models. BI3 and JM2 were fit to E. coli and enterococci, respectively. LLMs had larger Bayesian information criterion values than best-fit models, indicating poor fit. LLMs over-estimated the time required for 90% reduction of the indicators (T90) and did not consider dynamic rates of decay. Time in storage and indicator species were associated with the persistence of the markers (p &lt; 0.001). Using the T90 values of the best-fit models, enterococci was the most persistent indicator. Our data supports the use of best fit models with dynamic decay rates in water quality models to evaluate the decay of enteric markers.

Thermal Inactivation Kinetics of Three Heat-Resistant Salmonella Strains in Whole Liquid Egg

2019 ◽  
Vol 82 (9) ◽  
pp. 1465-1471 ◽  
Author(s):  
JOSHUA B. GURTLER ◽  
VIJAY K. JUNEJA ◽  
DEANA R. JONES ◽  
ANUJ PUROHIT
Keyword(s):  
Survival Data ◽  
Thermal Inactivation ◽  
Inactivation Kinetics ◽  
Glass Capillary ◽  
Circulating Water ◽  
Log Reduction ◽  
Heat Resistant ◽  
Weibull Models ◽  
D Values ◽  
Log Linear

ABSTRACT The heat resistance of three heat-resistant strains of Salmonella was determined in whole liquid egg (WLE). Inoculated samples in glass capillary tubes were completely immersed in a circulating water bath and held at 56, 58, 60, 62, and 64°C for predetermined lengths of time. The recovery medium was tryptic soy agar with 0.1% sodium pyruvate and 50 ppm of nalidixic acid. Survival data were fitted using log-linear, log-linear with shoulder, and Weibull models using GInaFiT version 1.7. Based on the R2 and mean square error, the log-linear with shoulder and Weibull models consistently produced a better fit to Salmonella survival curves obtained at these temperatures. Contaminated WLE must be heated at 56, 60, and 64°C for at least 33.2, 2.7, and 0.31 min, respectively, to achieve a 4-log reduction of Salmonella; 39.0, 3.1, and 0.34 min, respectively, for a 5-log reduction; and 45.0, 3.5, and 0.39 min, respectively, for a 6-log reduction. The z-values calculated from the D-values were 3.67 and 4.18°C for the log-linear with shoulder and Weibull models, respectively. Thermal death times presented in this study will be beneficial for WLE distributors and regulatory agencies when designing pasteurization processes to effectively eliminate Salmonella in WLE, thereby ensuring the microbiological safety of the product.

When and why are log-linear models self-normalizing?

2015 ◽  
Author(s):  
Jacob Andreas ◽  
Dan Klein
Keyword(s):  
Linear Models ◽  
Log Linear
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