scholarly journals Comparison of Two Mechanistic Microbial Growth Models to Estimate Shelf Life of Perishable Food Package under Dynamic Temperature Conditions

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Dong Sun Lee
Keyword(s):  
Shelf Life ◽  
Microbial Growth ◽  
Electronic Device ◽  
Growth Models ◽  
Model Parameters ◽  
Growth Data ◽  
Dynamic Temperature ◽  
Temperature Conditions ◽  
Primary Model ◽  
Set Up

Two mechanistic microbial growth models (Huang’s model and model of Baranyi and Roberts) given in differential and integrated equation forms were compared in predicting the microbial growth and shelf life under dynamic temperature storage and distribution conditions. Literatures consistently reporting the microbial growth data under constant and changing temperature conditions were selected to obtain the primary model parameters, set up the secondary models, and apply them to predict the microbial growth and shelf life under fluctuating temperatures. When evaluated by general estimation behavior, bias factor, accuracy factor, and root-mean-square error, Huang’s model was comparable to Baranyi and Roberts’ model in the capability to estimate microbial growth under dynamic temperature conditions. Its simple form of single differential equation incorporating directly the growth rate and lag time may work as an advantage to be used in online shelf life estimation by using the electronic device.

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans

2017 ◽  
Vol 81 (2) ◽  
pp. 308-315 ◽  
Author(s):  
Vijay K. Juneja ◽  
Abhinav Mishra ◽  
Abani K. Pradhan
Keyword(s):  
Bacillus Cereus ◽  
Growth Rates ◽  
Linear Models ◽  
Growth Models ◽  
Maximum Growth ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Three Phase ◽  
Primary Model

ABSTRACT Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol–egg yolk–polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between −0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

Prediction for Shelf Life and Safety of Minimally Processed CAP/MAP Chilled Foods: A Review

1992 ◽  
Vol 55 (9) ◽  
pp. 741-750 ◽  
Author(s):  
THEODORE P. LABUZA ◽  
BIN FU ◽  
PETROS S. TAOUKIS
Keyword(s):  
Shelf Life ◽  
Microbial Growth ◽  
Growth Models ◽  
Minimally Processed ◽  
Safety Assurance ◽  
Use Of Time ◽  
Modified Atmospheric Packaging ◽  
Shelf Life Prediction ◽  
Root Model ◽  
Nonisothermal Conditions

The reliance of minimally processed chilled foods on low temperature for distribution with optimized controlled/modified atmospheric packaging to maintain safety and quality poses new challenges to food microbiologists. Effects of controlled/modified atmospheric packaging conditions on microbial growth are briefly discussed. Microbial growth models are systematically examined with emphasis on the temperature dependence models—the Arrhenius model and the square root model. Their applicability for making predictions of both shelf life and safety under nonisothermal conditions is assessed. The use of time-temperature integrators for shelf-life prediction and safety assurance is also addressed.

scholarly journals Omnibus Modeling of Listeria monocytogenes Growth Rates at Low Temperatures

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1099
Author(s):  
Vincenzo Pennone ◽  
Ursula Gonzales Barron ◽  
Kevin Hunt ◽  
Vasco Cadavez ◽  
Olivia McAuliffe ◽  
...  
Keyword(s):  
Growth Rate ◽  
Listeria Monocytogenes ◽  
Case Fatality ◽  
Second Order ◽  
Lag Phase ◽  
Model Parameters ◽  
Growth Data ◽  
Temperature Growth ◽  
First Order ◽  
Primary Model

Listeria monocytogenes is a pathogen of considerable public health importance with a high case fatality. L. monocytogenes can grow at refrigeration temperatures and is of particular concern for ready-to-eat foods that require refrigeration. There is substantial interest in conducting and modeling shelf-life studies on L. monocytogenes, especially relating to storage temperature. Growth model parameters are generally estimated from constant-temperature growth experiments. Traditionally, first-order and second-order modeling (or primary and secondary) of growth data has been done sequentially. However, omnibus modeling, using a mixed-effects nonlinear regression approach, can model a full dataset covering all experimental conditions in one step. This study compared omnibus modeling to conventional sequential first-order/second-order modeling of growth data for five strains of L. monocytogenes. The omnibus model coupled a Huang primary model for growth with secondary models for growth rate and lag phase duration. First-order modeling indicated there were small significant differences in growth rate depending on the strain at all temperatures. Omnibus modeling indicated smaller differences. Overall, there was broad agreement between the estimates of growth rate obtained by the first-order and omnibus modeling. Through an appropriate choice of fixed and random effects incorporated in the omnibus model, potential errors in a dataset from one environmental condition can be identified and explored.

scholarly journals Quality assessment and shelf life modeling of pulsed electric field pretreated osmodehydrofrozen kiwifruit slices

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Efimia Dermesonlouoglou ◽  
Ismini Zachariou ◽  
Varvara Andreou ◽  
Petros S. Taoukis
Keyword(s):  
Electric Field ◽  
Shelf Life ◽  
Osmotic Dehydration ◽  
Colour Change ◽  
Pulsed Electric Field ◽  
B Value ◽  
Drip Loss ◽  
Dynamic Temperature ◽  
Tissue Integrity ◽  
Temperature Conditions

The objective of this workwas to investigate the potential use of pulsed electric field (PEF) in combination with osmotic dehydration (OD) as a pre-freezing step and to evaluate the effect on quality characteristics and shelf life of frozen kiwifruit. Peeled kiwifruit was subjected to PEF (1.8 kV/cm), sliced and treated in OD-solution [containing glycerol, maltodextrin, trehalose, ascorbic acid, calcium chloride, citric acid, sodium chloride; 1/5 (wfruit/wsolution)] for 30 and 60 min at 35 °C. Combined, PEF only and OD only treated samples as well as nontreated and blanched (80 °C, 60 s) samples were frozen and stored at constant (-5, -10, -15, -25 °C) and dynamic temperature conditions (-18 °C-3 d, -8 °C-2.5 d, -15 °C-3 d). Quality of frozen samples was evaluated by means of drip loss, colour, texture, vitamin C and sensory evaluation (1-9 scale); and shelf life (SL) was calculated. Nontreated and blanched samples presented high drip loss and tissue softening (instrumentally measured as Fmax decrease). The tissue integrity was well retained in all osmotically pretreated samples. PEF pretreatment caused increase of fruit whiteness (increase of L value) and yellowness (a and/or b value increase); SL calculation was based on colour change. All OD samples had high vitamin content (24.6 mg/100 g fresh material compared to 138-154 mg/100 g osmodehydrated material); PEF led to 93% (of the initial) vitamin retention; blanched samples showed the lowest retention (86.9% of the initial) (criteria for SL calculation). OD and combined PEF-OD treatment increased the shelf life of frozen kiwifruit (up to 3 times; based on sensorial criteria). The developed kinetic models for colour change, vitamin loss, and sensory quality deterioration were validated at dynamic temperature conditions. PEF pretreated OD (at significantly shorter time, 30 min compared to 60 min) kiwifruits retained optimum quality and sensory characteristics. PEF and OD could be used as a preprocessing step of good quality, longer shelf life kiwi sliced frozen products.

scholarly journals Growth of Listeria monocytogenes in Partially Cooked Battered Chicken Nuggets as a Function of Storage Temperature

Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 533
Author(s):  
Alexandra Lianou ◽  
Ourania Raftopoulou ◽  
Evgenia Spyrelli ◽  
George-John E. Nychas
Keyword(s):  
Listeria Monocytogenes ◽  
Model Evaluation ◽  
Quantitative Description ◽  
Growth Behavior ◽  
Chicken Nuggets ◽  
Susceptible Population ◽  
Dynamic Temperature ◽  
Temperature Conditions ◽  
Poultry Products ◽  
Primary Model

Battered poultry products may be wrongly regarded and treated by consumers as ready-to-eat and, as such, be implicated in foodborne disease outbreaks. This study aimed at the quantitative description of the growth behavior of Listeria monocytogenes in fresh, partially cooked (non-ready-to-eat) battered chicken nuggets as function of temperature. Commercially prepared chicken breast nuggets were inoculated with L. monocytogenes and stored at different isothermal conditions (4, 8, 12, and 16 °C). The pathogen’s growth behavior was characterized via a two-step predictive modelling approach: estimation of growth kinetic parameters using a primary model, and description of the effect of temperature on the estimated maximum specific growth rate (μmax) using a secondary model. Model evaluation was undertaken using independent growth data under both constant and dynamic temperature conditions. According to the findings of this study, L. monocytogenes may proliferate in battered chicken nuggets in the course of their shelf life to levels potentially hazardous for susceptible population groups, even under well-controlled refrigerated storage conditions. Model evaluation demonstrated a satisfactory performance, where the estimated bias factor (Bf) was 0.92 and 1.08 under constant and dynamic temperature conditions, respectively, while the accuracy factor (Af) value was 1.08, in both cases. The collected data should be useful in model development and quantitative microbiological risk assessment in battered poultry products.

scholarly journals Microbial growth models for shelf life prediction in an Icelandic cod supply chain

2011 ◽  
Author(s):  
R. Gospavic ◽  
H. L. Lauzon ◽  
V. Popov ◽  
E. Martinsdottir ◽  
M. N. Haque ◽  
...  
Keyword(s):  
Supply Chain ◽  
Shelf Life ◽  
Life Prediction ◽  
Microbial Growth ◽  
Growth Models ◽  
Shelf Life Prediction

scholarly journals Multiphasic growth models for cattle

2011 ◽  
Vol 50 (No. 8) ◽  
pp. 347-354 ◽  
Author(s):  
H. Nešetřilová
Keyword(s):  
Growth Models ◽  
Gompertz Model ◽  
Logistic Function ◽  
Complex Nature ◽  
Model Parameters ◽  
Growth Data ◽  
Unknown Parameters ◽  
Residual Variability ◽  
Low Degree ◽  
Best Fitting

There are several ways of generalizing classical growth models to describe the complex nature of animal growth. One possibility is to construct a model based on a sum of several classical growth functions. In this paper, such multiphasic growth models for breeding bulls of the Czech Pied cattle based on the sum of two logistic functions are studied. The logistic function was chosen as a base for the models due to the relatively low degree of nonlinearity for the growth data. The paper describes three steps of constructing such a multiphasic growth model: in the first step a model with four unknown parameters is considered, in the second step the number of model parameters which are to be estimated is increased to five and in the third step a general model with six parameters is used. In each step, statistical properties of the considered model are checked. The residual variability of the best fitting model is on average approx. 8 times lower than the residual variability of classical Gompertz model which is often used by breeders to model cattle growth.  

Dynamic Modeling of Listeria monocytogenes Growth in Pasteurized Vanilla Cream after Postprocessing Contamination

2008 ◽  
Vol 71 (9) ◽  
pp. 1828-1834 ◽  
Author(s):  
EFSTATHIOS Z. PANAGOU ◽  
GEORGE-JOHN E. NYCHAS
Keyword(s):  
Listeria Monocytogenes ◽  
Goodness Of Fit ◽  
Model Performance ◽  
Specific Model ◽  
Type Model ◽  
Square Root ◽  
Time Model ◽  
Dynamic Temperature ◽  
Temperature Conditions ◽  
Primary Model

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g−1, and stored at 3, 5, 10, and 15°C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (μmax) was further modeled as a function of temperature by means of a square root–type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15°C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (Bf), the accuracy factor (Af), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for Bf, Af, and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of Bf, Af, and GoF were 1.173, 1.174, and 1.162, and 1.267, 1.281, and 1.756 from Growth Predictor and Sym'Previus, respectively.

scholarly journals Using Sigmoid Growth Curves to Establish Growth Models of Tomato and Eggplant Stems Suitable for Grafting in Subtropical Countries

Horticulturae ◽  
2021 ◽  
Vol 7 (12) ◽  
pp. 537
Author(s):  
Chih-Yu Hsieh ◽  
Shih-Lun Fang ◽  
Yea-Fang Wu ◽  
Yung-Chu Chu ◽  
Bo-Jein Kuo
Keyword(s):  
Seedling Growth ◽  
Growth Models ◽  
Solanum Melongena ◽  
Growth Curves ◽  
Model Parameters ◽  
Growth Data ◽  
Growing Seasons ◽  
Different Seasons ◽  
Prime Objective ◽  
Autumn And Winter

In subtropical regions, tomato (Solanum lycopersicum) is mainly produced in autumn and winter. To enhance the off-season production of tomato, summer cultivation has become a prime objective. Grafting tomato scions onto eggplant (Solanum melongena) rootstocks is a key method to overcome the difficulties of tomato cultivation in summer. In this study, we collected seedling growth data over six growing seasons in Taiwan and established growth models by employing three commonly used sigmoid growth curves, namely the Gompertz, Richards, and Logistic curves. Cumulative temperature was introduced as an independent variable and its relationship with plant stem diameter determined. The R2 values of the growth models were 0.74–0.85 and 0.72–0.80 in calibration and validation, respectively. Performance did not differ markedly among models in the same growing season, but notable differences were observed among models for different growing seasons. In addition, the estimates of several model parameters differed significantly among the seasons; hence, separate models should be established for different seasons. The results of this study can be used in prediction of tomato and eggplant seedling growth and arrangement of the grafting schedule to improve the efficiency of seedling production in subtropical countries.

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