Modelling the influence of temperature and carbon dioxide upon the growth of Pseudomonas fluorescens

Willocx, F; Mercier, Michel; Hendrickx, Marc; Tobback, Paul

doi:10.1006/fmic.1993.1016

Cited by 58 publications

(28 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Activation energies for max of pseudomonads and B. thermosphacta were 69.3 and 69.5 kJ/mol, respectively. These values are in agreement with the results of other studies on the effect of temperature on the growth of these bacteria on other foods or laboratory media (18,19,46). For Enterobacteriaceae and lactic acid bacteria, max showed much higher temperature dependence, with E A values of 95.8 and 99.6, respectively.…”

Section: Resultssupporting

confidence: 91%

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

Koutsoumanis

Stamatiou

Skandamis

et al. 2006

Appl Environ Microbiol

242

135

View full text Add to dashboard Cite

The changes in microbial flora and sensory characteristics of fresh ground meat (beef and pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal storage temperatures (0 to 20°C) under aerobic conditions. At all conditions tested, pseudomonads were the predominant bacteria, followed by Brochothrix thermosphacta, while the other members of the microbial association (e.g., lactic acid bacteria and Enterobacteriaceae) remained at lower levels. The results from microbiological and sensory analysis showed that changes in pseudomonad populations followed closely sensory changes during storage and could be used as a good index for spoilage of aerobically stored ground meat. The kinetic parameters (maximum specific growth rate [ max ] and the duration of lag phase []) of the spoilage bacteria were modeled by using a modified Arrhenius equation for the combined effect of temperature and pH. Meat pH affected growth of all spoilage bacteria except that of lactic acid bacteria. The "adaptation work," characterized by the product of max and ( max ؋ ) was found to be unaffected by temperature for all tested bacteria but was affected by pH for pseudomonads and B. thermosphacta. For the latter bacteria, a negative linear correlation between ln( max ؋ ) and meat pH was observed. The developed models were further validated under dynamic temperature conditions using different fluctuating temperatures. Graphical comparison between predicted and observed growth and the examination of the relative errors of predictions showed that the model predicted satisfactorily growth under dynamic conditions. Predicted shelf life based on pseudomonads growth was slightly shorter than shelf life observed by sensory analysis with a mean difference of 13.1%. The present study provides a "readyto-use," well-validated model for predicting spoilage of aerobically stored ground meat. The use of the model by the meat industry can lead to effective management systems for the optimization of meat quality.Fresh meat is a highly perishable food product and unless appropriately actions are taken, e.g., packaged, transported and stored at refrigeration temperatures, can spoil in relatively short time. Factors affecting meat spoilage include intrinsic (e.g., pH, a w , composition, type, and extent of initial contamination) and extrinsic parameters (e.g., temperature and packaging atmosphere). Among these, temperature is considered the most important factor. Although most countries have established regulations with maximum temperature limits for refrigeration storage, in practice these are often violated. Survey studies have shown that temperature conditions higher than 10°C are not unusual during transportation, retail storage, and consumer handling (13,15). Such temperature abuses during any stage of the chill chain may result in an unexpected loss of quality and a significant decrease of meat shelf life.Challenge tests are the main current method used by the meat industry and academia to evaluate product's shelf life. The disadv...

show abstract

Section: Resultssupporting

confidence: 91%

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

Koutsoumanis

Stamatiou

Skandamis

et al. 2006

Appl Environ Microbiol

242

135

View full text Add to dashboard Cite

show abstract

“…Texture is seldom maintained for more than 10 days, even under optimal storage conditions. The texture evaluation of the lettuce is relatively pH of minimally processed vegetables Minimally processed vegetables belong to the low-acid foods (pH 5.8e6.0) (Willkox, Mercier, Hendrickx, & Tobback, 1993). Processing and storage conditions can affect the pH of the samples, e.g.…”

Section: Texture Evaluation Of Minimally Processed Vegetablesmentioning

confidence: 99%

Extending and measuring the quality of fresh-cut fruit and vegetables: a review

Rico¹,

Martín‐Diana²,

Baviera

et al. 2007

Trends in Food Science & Technology

848

524

View full text Add to dashboard Cite

“…Since temperature is one of the most important factors influencing microbial growth, modeling the growth of the SSO as a function of temperature is essential in shelf life prediction. Although a large number of models for the prediction of growth of spoilage organisms at various temperatures have been developed, the majority of these studies have been carried out under constant conditions (5,26,32,47). However, unlike other factors affecting microbial growth (e.g., pH and water activity), temperature may vary extensively throughout the complete production and distribution chain.…”

mentioning

confidence: 99%

Predictive Modeling of the Shelf Life of Fish under Nonisothermal Conditions

Koutsoumanis

2001

Appl Environ Microbiol

165

View full text Add to dashboard Cite

The behavior of the natural microflora of Mediterannean gilt-head seabream (Sparus aurata) was monitored during aerobic storage at different isothermal conditions from 0 to 15°C. The growth data of pseudomonads, established as the specific spoilage organisms of aerobically stored gilt-head seabream, combined with data from previously published experiments, were used to model the effect of temperature on pseudomonad growth using a Belehradek type model. The nominal minimum temperature parameters of the Belehradek model (T min ) for the maximum specific growth rate ( max ) and the lag phase (t Lag ) were determined to be ؊11.8 and ؊12.8°C, respectively. The applicability of the model in predicting pseudomonad growth on fish at fluctuating temperatures was evaluated by comparing predictions with observed growth in experiments under dynamic conditions. Temperature scenarios designed in the laboratory and simulation of real temperature profiles observed in the fish chill chain were used. Bias and accuracy factors were used as comparison indices and ranged from 0.91 to 1.17 and from 1.11 to 1.17, respectively. The average percent difference between shelf life predicted based on pseudomonad growth and shelf life experimentally determined by sensory analysis for all temperature profiles tested was 5.8%, indicating that the model is able to predict accurately fish quality in real-world conditions.Fresh fish are among the most perishable food products, and the monitoring and controlling of fish quality is one of the main goals in the fish industry. Fish shelf life is influenced by a number of factors, such as initial microbiological quality, season, handling, and feeding (17,37,40,41) and consequently can vary significantly from batch to batch. The limited and variable shelf lives of fish are major problems for fish quality assurance. This is the reason for the extensive research which has been carried out in the last few decades on the development of direct product methods (microbial, sensory, and biochemical) for the evaluation of fish spoilage (14,15,16). Nevertheless, several problems are related to the use of these methods mainly due to time and sensitivity limitations. An alternative to direct product testing is predictive microbiology. Predictions of food quality can improve significantly distribution and marketing, especially for chilled foods such as fish (28).Application of mathematical modeling for shelf life prediction requires sufficient knowledge of the product spoilage mechanisms (20). In the case of fish and fish products, spoilage is caused by a fraction of the total fish microflora, the specific spoilage organisms (SSO) (16). Since temperature is one of the most important factors influencing microbial growth, modeling the growth of the SSO as a function of temperature is essential in shelf life prediction. Although a large number of models for the prediction of growth of spoilage organisms at various temperatures have been developed, the majority of these studies have been carried out under constant cond...

show abstract

Modelling the influence of temperature and carbon dioxide upon the growth of Pseudomonas fluorescens

Cited by 58 publications

References 0 publications

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

Development of a Microbial Model for the Combined Effect of Temperature and pH on Spoilage of Ground Meat, and Validation of the Model under Dynamic Temperature Conditions

Extending and measuring the quality of fresh-cut fruit and vegetables: a review

Predictive Modeling of the Shelf Life of Fish under Nonisothermal Conditions

Contact Info

Product

Resources

About