Predictive models for growth of Salmonella typhimurium DT104 from low and high initial density on ground chicken with a natural microflora

2007 ◽  
Vol 24 (6) ◽  
pp. 640-651 ◽  
Author(s):  
T.P. Oscar
Keyword(s):  
Salmonella Typhimurium ◽  
Predictive Models ◽  
Initial Density ◽  
Natural Microflora ◽  
High Initial Density

Validation of a Tertiary Model for Predicting Variation of Salmonella Typhimurium DT104 (ATCC 700408) Growth from a Low Initial Density on Ground Chicken Breast Meat with a Competitive Microflora†

2006 ◽  
Vol 69 (9) ◽  
pp. 2048-2057 ◽  
Author(s):  
T. P. OSCAR
Keyword(s):  
Salmonella Typhimurium ◽  
Phage Type ◽  
Model Development ◽  
Initial Density ◽  
Most Probable Number ◽  
Chicken Breast ◽  
Breast Meat ◽  
Probable Number ◽  
Primary Model ◽  
Chicken Breast Meat

Growth of a multiple antibiotic–resistant strain (ATCC 700408) of Salmonella Typhimurium definitive phage type 104 (DT104) from a low initial density (100.6 most probable number [MPN] or CFU/g) on ground chicken breast meat with a competitive microflora was investigated and modeled as a function of time and temperature (10 to 40°C). MPN and viable counts (CFU) on a selective medium with four antibiotics enumerated the pathogen. Data from five replicate challenge studies per temperature were combined and fit to a primary model to determine maximum specific growth rate (μ), maximum population density (Nmax), and the 95% prediction interval (PI). Nonlinear regression was used to obtain secondary models as a function of temperature for μ, Nmax, and PI, which ranged from 0.04 to 0.4 h−1, 1.6 to 9.4 log MPN or CFU/g, and 1.4 to 2.4 log MPN or CFU/g, respectively. Secondary models were combined with the primary model to create a tertiary model for predicting variation (95% PI) of pathogen growth among batches of ground chicken breast meat with a competitive microflora. The criterion for acceptable model performance was that 90% of observed MPN or CFU data had to be in the 95% PI predicted by the tertiary model. For data (n = 344) used in model development, 93% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model, whereas for data (n = 236) not used in model development but collected using the same methods, 94% of observed MPN and CFU data were in the 95% PI predicted by the tertiary model. Thus, the tertiary model was successfully verified against dependent data and validated against independent data for predicting variation of Salmonella Typhimurium DT104 growth among batches of ground chicken breast meat with a competitive microflora and from a low initial density.

scholarly journals The effect of inoculation time and inoculum concentration on the productive response of Tetraselmis chuii (Butcher, 1958) mass cultured in F/2 and 2-F media

2011 ◽  
Vol 63 (3) ◽  
pp. 557-562 ◽  
Author(s):  
José López-Elías ◽  
Edgard Esquer-Miranda ◽  
Marcel Martínez-Porchas ◽  
María Garza-Aguirre ◽  
Martha Rivas-Vega ◽  
...  
Keyword(s):  
Cell Density ◽  
Initial Density ◽  
Inoculum Concentration ◽  
Tetraselmis Chuii ◽  
Shrimp Industry ◽  
Inoculation Time ◽  
High Initial Density ◽  
Outdoor Cultures

Diverse protocols have been used in the shrimp industry to produce microalgae. In this work, we evaluated the effect of inoculation time (0600 and 1200) and initial microalgae density (0.4 and 0.8 x105cells mL-1) in static outdoor cultures of Tetraselmis chuii, using F/2 and 2-F media. A significant effect on cell density (> 6.7 x 105 cells mL-1) was found after treatments with a high initial density and in the F/2 medium. The higher productive responses were observed in treatments inoculated at 0600. The better productive response was found in treatments inoculated at 0600 with 0.8 x 105 cells?mL-1 in the F/2 medium.

THE EFFECT OF DAMAGED VEHICLES EVACUATION ON TRAFFIC FLOW BEHAVIOR

2009 ◽  
Vol 20 (12) ◽  
pp. 1989-1998 ◽  
Author(s):  
ABDELAZIZ MHIRECH ◽  
HAMID EZ-ZAHRAOUY ◽  
ASSIA ALAOUI ISMAILI
Keyword(s):  
Steady State ◽  
Traffic Flow ◽  
Flow Behavior ◽  
Initial Density ◽  
Realistic Model ◽  
Collision Probability ◽  
One Dimensional ◽  
Parallel Dynamics ◽  
The One ◽  
High Initial Density

The effect of the damaged car evacuation on the traffic flow behavior is investigated, in the one-dimensional deterministic Nagel–Schreckenberg model, using parallel dynamics. A realistic model applied to the cars involved in collisions is considered. Indeed, in this model we suppose that the damaged cars must be removed from the ring with a probability P exit . This investigation enables us to understand how the combination of the two probabilities, namely P col and P exit , acts on density and current. It is found that the current and density at the steady state, depend strongly on the initial density of cars in the ring. However, for the intermediate initial density ρi, the current J decreases when increasing either P exit and/or P col . While, for high initial density, J increases passes through a maximum and decreases for large values of P exit . Furthermore, the current can decrease or increase with the collision probability depending on the initial density.

Detonation parameters of hydrogen-oxygen and hydrogen-air mixtures at high initial density

1984 ◽  
Vol 20 (1) ◽  
pp. 89-96 ◽  
Author(s):  
N. S. Astapov ◽  
Yu. A. Nikolaev ◽  
V. Yu. Ul'yanitskii
Keyword(s):  
Initial Density ◽  
Detonation Parameters ◽  
High Initial Density

THE PORE STRUCTURE AND ADSORPTIVE PROPERTIES OF SOME ACTIVATED CHARCOALS: III. THE APPARENT DENSITY OF WATER ADSORBED ON ACTIVE CHARCOAL

1946 ◽  
Vol 24b (4) ◽  
pp. 137-149 ◽  
Author(s):  
J. A. Morrison ◽  
R. McIntosh
Keyword(s):  
Apparent Density ◽  
Capillary Condensation ◽  
Initial Density ◽  
Adsorbed Water ◽  
Normal Density ◽  
Sharp Drop ◽  
Desorption Branch ◽  
Adsorptive Properties ◽  
Density Of Water ◽  
High Initial Density

The apparent density of water adsorbed on four different charcoals at 20 °C. has been measured by a method of helium displacement. At low relative pressures the density is appreciably higher than that of liquid water, but falls rapidly to nearly the normal density as the amount adsorbed increases. A very sharp drop in density occurs close to saturation, and is attributed to the blocking of the very small porous spaces through the advent of capillary condensation in this region. It is suggested that the apparent high initial density is due to the size of the molecules of the measuring fluid rather than to the compression of the adsorbed film.The apparent density of the adsorbed water on the desorption branch of the isotherm differs from that on the adsorption branch, which suggests that the mechanisms of adsorption and desorption differ. An attempt has been made to evaluate the constants Vm and C of the multimolecular adsorption theory from one of the adsorption isotherms.

Growth of Salmonella Typhimurium DT104 at 30°C Is Not Affected by Anatomical Location on the Chicken Carcass†

2012 ◽  
Vol 75 (1) ◽  
pp. 164-168 ◽  
Author(s):  
THOMAS P. OSCAR
Keyword(s):  
Salmonella Typhimurium ◽  
Predictive Models ◽  
Growth Curves ◽  
Storage Conditions ◽  
Inoculum Size ◽  
Anatomical Location ◽  
Two Phase ◽  
Chicken Carcass ◽  
Portion Sizes ◽  
Independent Variable

Development of models for growth of Salmonella in the chicken food matrix is time-consuming and expensive. The current study was undertaken to examine growth of Salmonella on different anatomical locations of the chicken carcass. The purpose was to determine whether anatomical location should be included as an independent variable in predictive models for chicken. Eleven anatomical locations were studied: skin (wing, breast, drumstick, and thigh), meat surface (wing, breast, drumstick, and thigh), and meat interior (breast, drumstick, and thigh). Background microflora, pH, and growth (lag time, λ; growth rate,μ; and time for a 3-log increase, t3) at 30°C for a small inoculum size (0.92 ±0.30 log per portion) of Salmonella Typhimurium DT104 were examined. Four or six replicate storage trials were conducted per anatomical location (n = 46 growth curves). Portion sizes were 1.12 ±0.17 g (mean ±standard deviation) for meat and 0.25 ±0.08 g for skin. A two-phase linear model was used to determine λ andμ. The effect of anatomical location on dependent variables was assessed by one-way analysis of variance. pH values differed (P < 0.001) among anatomical locations, with skin (6.86 ±0.20) > dark meat (6.39 ±0.20) > white meat (5.97 ±0.20). Background microflora (4.32 ±1.66 log per portion) was variable and not affected (P > 0.05) by anatomical location. Likewise, λ (1.90 ±0.75 h), μ (0.648 ±0.120 log/h), and t3 (6.71 ±0.82 h) at 30°C were not affected (P > 0.05) by anatomical location. Although there were differences in pH among anatomical locations, these differences were not sufficient to affect growth of Salmonella Typhimurium DT104 at 30°C. If this observation holds for other storage conditions and strains, then anatomical location does not need to be included as an independent variable in predictive models for chicken. This would save significant time and money for the predictive microbiologist.

Antimicrobial Activity of Butylated Hydroxyanisole and Potassium Sorbate Against Natural Microflora in Raw Turkey Meat and Salmonella typhimurium in Cooked Turkey Meat1

1982 ◽  
Vol 45 (11) ◽  
pp. 1038-1040 ◽  
Author(s):  
M. M. MORAD ◽  
A. L. BRANEN ◽  
C. J. BREKKE
Keyword(s):  
Antimicrobial Activity ◽  
Salmonella Typhimurium ◽  
Potassium Sorbate ◽  
Butylated Hydroxyanisole ◽  
Gram Negative ◽  
Turkey Meat ◽  
Natural Flora ◽  
Natural Microflora ◽  
Gram Negative Organisms ◽  
Slight Inhibition

The antimicrobial activity of butylated hydroxyanisole (BHA) (100 ppm) and potassium sorbate (1000 ppm), individually and in combination, was evaluated against growth of the natural microbial flora in raw turkey meat and against Salmonella typhimurium inoculated into cooked turkey meat. Growth of the natural flora was not inhibited by using either BHA or sorbate alone; however, slight inhibition was shown using a combination of the two. BHA, sorbate and a combination were effective to the same extent in preventing growth of naturally present gram-negative organisms. Sorbate and the BHA-sorbate combination did not differ in their effectiveness and were more effective than BHA alone in reducing numbers of S. typhimurium in cooked turkey.

Development and Validation of Primary, Secondary, and Tertiary Models for Growth of Salmonella Typhimurium on Sterile Chicken†

2005 ◽  
Vol 68 (12) ◽  
pp. 2606-2613 ◽  
Author(s):  
T. P. OSCAR
Keyword(s):  
Salmonella Typhimurium ◽  
Goodness Of Fit ◽  
Model Development ◽  
Initial Density ◽  
Model Performance ◽  
Growth Parameter ◽  
Zone Method ◽  
Validation Data ◽  
Primary Model ◽  
Acceptable Model

Models are used in the food industry to predict pathogen growth and to help assess food safety. However, criteria are needed to determine whether models provide acceptable predictions. In the current study, primary, secondary, and tertiary models for growth of Salmonella Typhimurium (104.8 CFU/g) on sterile chicken were developed and validated. Kinetic data obtained at 10 to 40°C were fit to a primary model to determine initial density (N0), lag time (λ), maximum specific growth rate (μmax), and maximum population density (Nmax). Secondary models for N0, λ, μmax, and Nmax as a function of temperature were developed and combined with the primary model to create a tertiary model that predicted pathogen density (N) at times and temperatures used and not used in model development. Performance of models was evaluated using the acceptable prediction zone method in which experimental error associated with growth parameter determinations was used to set criteria for acceptable model performance. Models were evaluated against dependent and independent (validation) data. Models with 70% prediction or relative errors (RE) in an acceptable prediction zone from −0.3 to 0.15 for μmax, −0.6 to 0.3 for λ, and −0.8 to 0.4 for N, N0, and Nmax were classified as acceptable. All secondary models had acceptable goodness of fit and were validated against independent (interpolation) data. Percent RE in the acceptable prediction zone for the tertiary model was 90.7 for dependent data and 97.5 for independent (interpolation) data. Although the tertiary model was validated for interpolation, an unacceptable %RE of 2.5 was obtained for independent (extrapolation) data obtained with a lower N0 (100.8 CFU/g). The tertiary model provided overly fail-dangerous predictions of N from a lower N0. Because Salmonella concentrations on chicken are closer to 100.8 than 104.8 CFU/g, the tertiary model should not be used to help assess chicken safety.

Development and Validation of a Stochastic Model for Predicting the Growth of Salmonella Typhimurium DT104 from a Low Initial Density on Chicken Frankfurters with Native Microflora†

2008 ◽  
Vol 71 (6) ◽  
pp. 1135-1144 ◽  
Author(s):  
T. P. OSCAR
Keyword(s):  
Stochastic Model ◽  
Salmonella Typhimurium ◽  
Prediction Interval ◽  
Initial Density ◽  
Poultry Meat ◽  
Lag Phase ◽  
Single Strain ◽  
Primary Model ◽  
Native Microflora ◽  
T Values

The presence of native microflora is associated with increased variation of Salmonella growth among batches and portions of chicken meat and as a function of temperature. However, variation of Salmonella growth can be modeled using a 95% prediction interval (PI). Because there are no reports of predictive models for growth of Salmonella on ready-to-eat poultry meat products with native microflora and because Salmonella is usually present at low levels on poultry meat, the current study was conducted to develop and validate a stochastic model for predicting the growth of Salmonella from a low initial density on chicken frankfurters with native microflora. One-gram portions of chicken frankfurters were inoculated with 0.5 log CFU of a single strain (ATCC 700408) of Salmonella Typhimurium DT104. Changes in pathogen numbers over time, N(t), were fit to a two-phase linear primary model to determine lag time (λ), growth rate (μ), and the 95% PI, which characterized the variation of pathogen growth. Secondary quadratic polynomial models for natural log transformations of λ, μ, and PI as a function of temperature (10 to 40°C) were obtained by nonlinear regression. The primary and secondary models were combined in a computer spreadsheet to create a tertiary model that predicted the growth curve and PI. The pathogen did not grow on chicken frankfurters incubated at 10 to 12°C, but μ ranged from 0.003 log CFU/g/h at 14°C to 0.176 log CFU/g/h at 30°C to 0.1 log CFU/g/h at 40°C. Variation of N(t) increased as a function of time (i.e., PI was lower during lag phase than during growth phase) and temperature (i.e., PI was higher at 18 to 40°C than at 10 to 14°C). For dependent data (n = 338), 90.5% of observed N(t) values were in the PI predicted by the tertiary model, whereas for independent data (n = 86), 89.5% of observed N(t) values were in the PI predicted by the tertiary model. Based on this performance evaluation, the tertiary model was considered acceptable and valid for stochastic predictions of Salmonella Typhimurium DT104 growth from a low initial density on chicken frankfurters with native microflora.

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