Use of a Modified Gompertz Equation to Predict the Effects of Temperature, pH, and NaCl on the Inactivation of Listeria monocytogenes Scott A Heated in Infant Formula

1996 ◽  
Vol 59 (1) ◽  
pp. 16-23 ◽  
Author(s):  
R. H. LINTON ◽  
W. H. CARTER ◽  
M. D. PIERSON ◽  
C. R. HACKNEY ◽  
J. D. EIFERT
Keyword(s):  
Listeria Monocytogenes ◽  
Infant Formula ◽  
Nonlinear Regression ◽  
Survival Curve ◽  
Interactive Effects ◽  
Parameter Estimates ◽  
Survival Curves ◽  
Gompertz Equation ◽  
Nacl Concentration ◽  
Effects Of Temperature

The heat resistance of Listeria monocytogenes was determined in infant formula for all possible combinations of temperature (50, 55, and 60°C), pH level (5, 6, and 7), and NaCl concentration (0, 2, and 4%). Survival curves were fit using nonlinear regression with a Gompertz equation. The Gompertz equation was flexible enough to fit the three most commonly observed survival curves: linear curves, those with an initial lag region followed by a linear region, and sigmoidal shaped. Parameter estimates obtained by the method of nonlinear least squares were used to describe the effect(s) of different heating treatments on the lag region, death rate, and tailing region of survival curves. These estimates were further used to predict single and interactive effects of temperature, pH, and percentage of NaCl on the log of the surviving fraction (LSF) of bacteria. Interactions among these variables significantly (P ≤ .05) affected the LSF. Generally, increased pH or NaCl concentration lead to an increased LSF, whereas increased time or temperature lead to a decreased LSF. All multiple-factor interactions significantly (P ≤ .05) affected the LSF. The correlation of observed LSF versus predicted LSF (R2 = .92) indicated that the estimated Gompertz equation was in close agreement with the observation. This study demonstrated that the Gompertz equation and nonlinear regression can be used as an effective means to predict survival curve shape and response to heat of L. monocytogenes under many different environmental conditions.

Use of a Modified Gompertz Equation to Model Nonlinear Survival Curves for Listeria monocytogenes Scott A

1995 ◽  
Vol 58 (9) ◽  
pp. 946-954 ◽  
Author(s):  
R. H. LINTON ◽  
W. H. CARTER ◽  
M. D. PIERSON ◽  
C. R. HACKNEY
Keyword(s):  
Listeria Monocytogenes ◽  
Nonlinear Regression ◽  
Survival Curve ◽  
Effective Means ◽  
Interactive Effects ◽  
Parameter Estimates ◽  
Survival Curves ◽  
Gompertz Equation ◽  
Nacl Concentration ◽  
Factor Interactions

The heat resistance of Listeria monocytogenes was determined in 0.1 M KH2PO4 buffer at three temperatures (50, 55, and 60°C), three pH levels (5, 6, and 7), and three NaCl concentrations (0, 2, and 4%). Survival curves were fit using nonlinear regression with a modified Gompertz equation. The Gompertz equation is capable of fitting survival curves which are linear, those which display an initial lag region followed by a linear region, and those which are sigmoidal. Parameter estimates were used to describe the lag region, death rate, and the tailing region of a survival curve. These estimates were also used to predict single and interactive effects of temperature, pH, and percentage of NaCl on the log surviving fraction (LSF) of bacteria. Interactions among these variables significantly (P < .05) affected the LSF. Generally, increased pH or NaCl concentration lead to an increased (P < .05) LSF, where as increased time or temperature lead to a decreased (P < .05) LSF. All multiple factor interactions significantly (P < .05) affected the LSF. These interactions differed depending on the heating medium and the region of the survival curve. The correlation of observed LSF and predicted LSF (R2 = .89) indicated that the Gompertz equation was in close agreement with the observations. This study demonstrated that the Gompertz equation and nonlinear regression can be used as an effective means to predict survival curve shape and response to heat of L. monocytogenes in many different environmental conditions.

A Predictive Model to Determine the Effects of pH, Milkfat, and Temperature on Thermal Inactivation of Listeria monocytogenes

1999 ◽  
Vol 62 (10) ◽  
pp. 1143-1149 ◽  
Author(s):  
A. T. CHHABRA ◽  
W. H. CARTER ◽  
R. H. LINTON ◽  
M. A. COUSIN
Keyword(s):  
Listeria Monocytogenes ◽  
Heat Resistance ◽  
Regression Model ◽  
Predictive Model ◽  
Survival Curve ◽  
Individual Treatment ◽  
Parameter Estimates ◽  
Processing Temperature ◽  
Maximum Slope ◽  
Gompertz Equation

Listeria monocytogenes is a foodborne pathogen of significance because of its comparatively high heat resistance, zero tolerance in ready-to-eat foods, and growth at refrigeration temperatures. A 3 × 3 × 3 factorial study was done to determine the effects of milkfat (0%, 2.5%, 5.0%), pH (5.0, 6.0, 7.0), and processing temperature (55°C, 60°C, 65°C) on the thermal resistance of L. monocytogenes in a formulated and homogenized milk system. Data were fit to a modified Gompertz equation where parameter estimates characterized three regions of a survival curve: the shoulder, maximum slope, and tail. Statistical analysis was done for each of the 27 individual treatment sets to visualize individual effects on parameter estimates and to evaluate how well the Gompertz equation represented the data. A regression model for the Gompertz equation was generated to predict the logarithmic surviving fraction of L. monocytogenes based on all 27 treatments and their single and interactive effects. The shoulder region of the survival curve was affected by pH; however, the maximum slope was affected by temperature, milkfat, and the interaction of temperature × milkfat. Validation of the model suggests that the predictions are best suited for processing above 62°C. Trends over time for a 4-log reduction in cells (4D values) were evaluated using results from the 27 individual treatment sets, the regression model for the Gompertz equation, and a linear equation. At lower temperatures, 4D values by the three methods varied by twofold. At higher temperatures, all methods gave similar 4D values, suggesting that death became more linear. Based on this study all three factors affect heat resistance for specific regions of a survival curve, and a predictive model was developed that can be used as a preliminary estimate for L. monocytogenes inactivation.

A unified degree day model describes survivorship of Copitarsia corruda Pogue & Simmons (Lepidoptera: Noctuidae) at different constant temperatures

2008 ◽  
Vol 99 (1) ◽  
pp. 65-72 ◽  
Author(s):  
N.N. Gómez ◽  
R.C. Venette ◽  
J.R. Gould ◽  
D.F. Winograd
Keyword(s):  
Survival Curve ◽  
The United States ◽  
Physiological Age ◽  
Alien Invasive Species ◽  
Temperature Threshold ◽  
Base Temperature ◽  
Survival Curves ◽  
Degree Day ◽  
Effects Of Temperature ◽  
Lepidoptera Noctuidae

AbstractPredictions of survivorship are critical to quantify the probability of establishment by an alien invasive species, but survival curves rarely distinguish between the effects of temperature on development versus senescence. We report chronological and physiological age-based survival curves for a potentially invasive noctuid, recently described as Copitarsia corruda Pogue & Simmons, collected from Peru and reared on asparagus at six constant temperatures between 9.7 and 34.5°C. Copitarsia spp. are not known to occur in the United States but are routinely intercepted at ports of entry. Chronological age survival curves differ significantly among temperatures. Survivorship at early age after hatch is greatest at lower temperatures and declines as temperature increases. Mean longevity was 220 (±13 SEM) days at 9.7°C. Physiological age survival curves constructed with developmental base temperature (7.2°C) did not correspond to those constructed with a senescence base temperature (5.9°C). A single degree day survival curve with an appropriate temperature threshold based on senescence adequately describes survivorship under non-stress temperature conditions (5.9–24.9°C).

scholarly journals A Predictive Model To Describe the Effects of Temperature, Sodium Lactate, and Sodium Diacetate on the Inactivation of a Serotype 4b Strain of Listeria monocytogenes in a Frankfurter Slurry

2006 ◽  
Vol 69 (7) ◽  
pp. 1552-1560 ◽  
Author(s):  
K. K. SCHULTZE ◽  
R. H. LINTON ◽  
M. A. COUSIN ◽  
J. B. LUCHANSKY ◽  
M. L. TAMPLIN
Keyword(s):  
Listeria Monocytogenes ◽  
Heat Resistance ◽  
Death Rate ◽  
Sodium Lactate ◽  
Microbial Inactivation ◽  
Interactive Effects ◽  
Effects Of Temperature ◽  
Sodium Diacetate ◽  
Serotype 4B ◽  
D Values

A modified Gompertz equation was used to model the effects of temperature (55, 60, and 65°C), sodium lactate (0, 2.4, and 4.8%), and sodium diacetate (0, 0.125, and 0.25%) on inactivation of Listeria monocytogenes strain MFS 102 (serotype 4b) in frankfurter slurry. The effects of these factors were determined on the shouldering region (parameter A), maximum death rate (parameter B), and tailing region (parameter C) of microbial inactivation curves. Increased temperature or sodium diacetate concentrations increased the death rate, whereas increased sodium lactate concentrations decreased heat resistance. Complex two-way interactive effects were also observed. As both temperature and sodium lactate increased, the death rate decreased; however, as temperature and sodium diacetate increased, the death rate increased. The effect of the interaction between sodium lactate and sodium diacetate on the maximum death rate varied with temperature. Increases in both acidulants at temperatures above 56.7°C decreased the death rate, whereas at temperatures below 56.7°C, increases in both acidulants increased the death rate. To test for significant differences between treatments, D-values were calculated and compared. This comparison revealed that, in general, sodium lactate increased heat resistance and sodium diacetate decreased heat resistance of L. monocytogenes. This information is important for reducing and minimizing contamination during postprocessing thermal treatments.

Detection of prognostically distinct subpopulations in non-small cell lung cancer patients treated with epidermal growth factor receptor (EGFR) inhibitors

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 18178-18178
Author(s):  
D. J. Stewart
Keyword(s):  
Nonlinear Regression ◽  
Survival Curve ◽  
Progression Free Survival ◽  
Compartment Model ◽  
Egfr Inhibitors ◽  
Therapeutic Modality ◽  
Continuous Variables ◽  
Survival Curves ◽  
Homogeneous Groups ◽  
Inflection Points

18178 Hypothesis: In patient survival curves that follow 1st order kinetics, prognostically distinct subpopulations will be identified by inflection points in plots of log % survival vs time. Prognostically important dichotomous variables (present vs absent, or above vs below a threshold) will give inflection points while important continuous variables will shift curve slope without giving inflection points. Methods: For overall and progression-free survival curves from 35 published clinical trials of EGFR inhibitors, curve height at different times was measured manually and converted to % of height at time 0. Curve nonlinear regression analyses were performed using the Pharsight WinNonlin 5.0.1 program. Results: In assessments done to date, the most common survival curve pattern was conformity to a 2-compartment model, indicating a single inflection point and ≥ 2 prognostically distinct subpopulations. The second most common pattern was conformity to a 1-compartment model, suggesting that some populations are relatively homogenous. Only a minority of curves could be fit to 3-compartment models that would have indicated ≥ 3 distinct subpopulations. In different studies, EGFR inhibitors shifted some patients from poorer to better prognosis compartments compared to placebo, and/or decreased the slope (ie, increased the t1/2) of one or both individual compartments. Similarly, factors that have been found to be associated with prognosis in these studies were associated with formation of prognostically homogeneous groups or with alterations of relative compartment sizes or slopes. Conclusions: It is feasible to perform nonlinear regression analysis of log-linear survival plots to define prognostically distinct subpopulations. Preliminary assessments suggest that EGFR inhibitors and factors known to be important prognostically are associated with alteration of size and survival t1/2 of these subpopulations. Helpful data that could potentially be obtained from such analyses include minimum number, size and t1/2 of prognostically distinct subpopulations, and impact of a therapeutic modality or potential prognostic factor on each subpopulation. No significant financial relationships to disclose.

Interactive effects of temperature and redox on soil carbon and iron cycling

2021 ◽  
Vol 157 ◽  
pp. 108235
Author(s):  
Nikhil R. Chari ◽  
Yang Lin ◽  
Yuan S. Lin ◽  
Whendee L. Silver
Keyword(s):  
Soil Carbon ◽  
Interactive Effects ◽  
Iron Cycling ◽  
Effects Of Temperature

Modeling the Effects of Temperature, Sodium Chloride, and Green Tea and Their Interactions on the Thermal Inactivation of Listeria monocytogenes in Turkey†

2014 ◽  
Vol 77 (10) ◽  
pp. 1696-1702 ◽  
Author(s):  
VIJAY K. JUNEJA ◽  
JIMENA GARCIA-DÁVILA ◽  
JULIO CESAR LOPEZ-ROMERO ◽  
ETNA AIDA PENA-RAMOS ◽  
JUAN PEDRO CAMOU ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Sodium Chloride ◽  
Protective Effect ◽  
Heat Resistance ◽  
Green Tea ◽  
Thermal Inactivation ◽  
Heating Temperature ◽  
Lethal Effect ◽  
Interactive Effects ◽  
D Values

The interactive effects of heating temperature (55 to 65°C), sodium chloride (NaCl; 0 to 2%), and green tea 60% polyphenol extract (GTPE; 0 to 3%) on the heat resistance of a five-strain mixture of Listeria monocytogenes in ground turkey were determined. Thermal death times were quantified in bags that were submerged in a circulating water bath set at 55, 57, 60, 63, and 65°C. The recovery medium was tryptic soy agar supplemented with 0.6% yeast extract and 1% sodium pyruvate. D-values were analyzed by second-order response surface regression for temperature, NaCl, and GTPE. The data indicated that all three factors interacted to affect the inactivation of the pathogen. The D-values for turkey with no NaCl or GTPE at 55, 57, 60, 63, and 65°C were 36.3, 20.8, 13.2, 4.1, and 2.9 min, respectively. Although NaCl exhibited a concentration-dependent protective effect against heat lethality on L. monocytogenes in turkey, addition of GTPE rendered the pathogen more sensitive to the lethal effect of heat. GTPE levels up to 1.5% interacted with NaCl and reduced the protective effect of NaCl on heat resistance of the pathogen. Food processors can use the predictive model to design an appropriate heat treatment that would inactivate L. monocytogenes in cooked turkey products without adversely affecting the quality of the product.

scholarly journals Empirical Model With Excellent Statistical Properties for Describing Temperature-Dependent Developmental Rates of Insects and Mites

2017 ◽  
Vol 110 (3) ◽  
pp. 302-309 ◽  
Author(s):  
David A. Ratkowsky ◽  
Gadi V. P. Reddy
Keyword(s):  
Nonlinear Regression ◽  
Empirical Model ◽  
Minimum Variance ◽  
Statistical Properties ◽  
Parameter Estimates ◽  
Regression Equations ◽  
Temperature Dependent ◽  
Temperature Range ◽  
Least Squares Estimators ◽  
Development Rates

Abstract Previous empirical models for describing the temperature-dependent development rates for insects include the Briére, Lactin, Beta, and Ratkowsky models. Another nonlinear regression model, not previously considered in population entomology, is the Lobry–Rosso–Flandrois model, the shape of which is very close to that of the Ratkowsky model in the suboptimal temperature range, but which has the added advantage that all four of its parameters have biological meaning. A consequence of this is that initial parameter estimates, needed for solving the nonlinear regression equations, are very easy to obtain. In addition, the model has excellent statistical properties, with the estimators of the parameters being “close-to-linear,” which means that the least squares estimators are close to being unbiased, normally distributed, minimum variance estimators. The model describes the pooled development rates very well throughout the entire biokinetic temperature range and deserves to become the empirical model of general use in this area.

Influence of partial inactivation on growth of Listeria monocytogenes under sub-optimal conditions of increased NaCl concentration or increased acidity

2009 ◽  
Vol 10 (2) ◽  
pp. 267-271 ◽  
Author(s):  
Andreja Rajkovic ◽  
Mieke Uyttendaele ◽  
Nancy Van Houteghem ◽  
Sandra Maria Osés Gómez ◽  
Johan Debevere ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Optimal Conditions ◽  
Nacl Concentration ◽  
Partial Inactivation
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