Shelf life of modified atmosphere packed cooked meat products: addition of Na-lactate as a fourth shelf life determinative factor in a model and product validation

Cooked meat products are often post-contaminated because of a packaging and/or slicing step after the pasteurisation process. The shelf life is therefore limited and can be extended by adding Na-lactate. A previously developed model for the spoilage of gas packed cooked meat products, including temperature, water activity and dissolved CO2 as independent variables, was extended with a fourth factor: the Na-lactate concentration in the aqueous phase of the meat product. Models were developed for the maximum specific growth rate mu(max) and the lag phase lambda of the specific spoilage organism Lactobacillus sake subsp. carnosum. Quadratic response surface equations were compared with extended Ratkowsky models. In general, response surface equations fitted the experimental data best but in the case of mu(max) the response surface model predicted illogical growth behaviour at low water activities and high Na-lactate concentrations. A extensive product validation of the mathematical models was performed by means of inoculated as well as naturally contaminated industrially prepared cooked meat products. The deviations of the experimentally determined versus predicted growth parameters in inoculated cooked meat products were in general small. Both types of models were also able to predict the shelf life of naturally contaminated cooked meat products, except for paté where an under-estimation of the shelf life was predicted by the response surface equations. The validation studies revealed higher accuracy of the extended Ratkowsky models in comparison to the response surface equations. A significant shelf life extending effect of Na-lactate was predicted, which was more pronounced at low refrigerated temperatures. A synergistic effect has also been noticed between Na-lactate and carbon dioxide which, at least partly, could be explained by the pH-decreasing effect of CO2.     

Growth of Aeromonas hydrophila in modified-atmosphere-packed cooked meat products

Growth of Aeromonas hydrophila was investigated in modified-atmosphere-packed cooked meat products by developing predictive models. Modified brain–heart infusion (BHI) was shown to be suitable as a simulation medium for cooked meat products. Predictive models were developed for the growth parameters (maximum specific growth rate and lag phase) of A. hydrophila in modified BHI as a function of temperature, water activity and concentration of dissolved carbon dioxide. The growth of A. hydrophila was compared with the growth of the Specific Spoilage Organism (SSO) for cooked meat products Lactobacillus sake, to determine possible risk areas for A. hydrophila in modified atmosphere-packed cooked meat products. Aeromonas hydrophila was shown to multiply very rapidly at refrigerated temperatures. The developed models clearly demonstrated however that proliferation of A. hydrophila could be prevented by the use of carbon dioxide in the package atmosphere in combination with a decreased water activity (<0·985). Gas-packed cured cooked meat products will not sustain the growth of A. hydrophila when kept at refrigerated temperatures (<7°C).     

腐生酵母菌在鲜榨苹果汁中的生长速率预测模型

通过研究温度、pH和水分活度对鲜榨苹果汁中腐生酵母菌生长情况的影响 ,建立了最大生长速率和迟滞时间与生长限制因子之间关系的数学预测模型 ,并对Ratkowsky扩展模型和响应面模型进行了对比。结果表明 ,Ratkowsky扩展模型的相关系数优于响应面模型 ,响应面模型在较高温度 ( 2 0℃以上 )最大生长速率呈现下降趋势的预测结果与实际情况不符。应用Ratkowsky扩展模型对鲜榨苹果汁的货架期进行预测时发现 ,温度、pH和水分活度对货架期的影响有协同作用。通过模型验证证实Ratkowsky扩展模型预测结果与实测值有良好的拟合性 ,相对误差在±1 0 %左右 ,可以用于鲜榨苹果汁货架期的预测     

Development of a Predictive Model for Spoilage of Cooked Cured Meat Products and Its Validation Under Constant and Dynamic Temperature Storage Conditions

ABSTRACT:  In the present study, the spoilage flora of a sliced cooked cured meat product was studied to determine the specific spoilage organism (SSO). The physicochemical changes of the product during its storage in a temperature range of 0 to 12 °C were also studied. Among the primary models used to model the temperature effect on SSO growth, the modified Gompertz described better the experimental data than modified logistic and Baranyi. The derived growth kinetic parameters, such as maximum specific growth rate (μ_max) and lag phase duration (LPD), were modeled by using the square root and Arrhenius equation (secondary models). The latter described better the data of μ_max and LPD; therefore, this model was chosen for correlating temperature with kinetic parameters. The selection of the best model (primary or secondary) was based on some statistical indices (the root mean square error of residuals of the model, the coefficient of multiple determination, the F -test, the goodness of fit, the bias, and accuracy factor). The validation of the developed model was carried out under constant and dynamic temperature storage conditions. To validate its usefulness to similar products, another sliced cooked cured meat product stored under constant temperature conditions was also used. The log shelf life model was used for shelf life predictions based on the evident (visual defects) or the incipient spoilage (attainment of a certain spoilage level by SSO and/or chemical spoilage index). The possibility for shelf life predictions constitutes a valuable information source for the quality assurance systems of meat industries.     

Effect of temperature, water-phase salt and phenolic contents on Listeria monocytogenes growth rates on cold-smoked salmon and evaluation of secondary models

Salting and smoking are ancient processes for fish preservation. The effects of salt and phenolic smoke compounds on the growth rate of L. monocytogenes in cold-smoked salmon were investigated through physico-chemical analyses, challenge tests on surface of cold-smoked salmon at 4 degrees C and 8 degrees C, and a survey of the literature. Estimated growth rates were compared to predictions of existing secondary models, taking into account the effects of temperature, water phase salt content, phenolic content, and additional factors (e.g. pH, lactate, dissolved CO2). The secondary model proposed by Devlieghere et al. [Devlieghere, F., Geeraerd, A.H., Versyck, K.J., Vandewaetere, B., van Impe, J., Debevere, J., 2001. Growth of Listeria monocytogenes in modified atmosphere packed cooked meat products: a predictive model. Food Microbiology 18, 53-66.] and modified by Giménez and Dalgaard [Giménez, B., Dalgaard, P., 2004. Modelling and predicting the simultaneous growth of Listeria monocytogenes and spoilage micro-organisms in cold-smoked salmon. Journal of Applied Microbiology 96, 96-109.] appears appropriate. However, further research is needed to understand all effects affecting growth of L. monocytogenes in cold-smoked salmon and to obtain fully validated predictive models for use in quantitative risk assessment.     

Development and validation of a tertiary simulation model for predicting the potential growth of Salmonella typhimurium on cooked chicken

The growth of Salmonella typhimurium (ATCC 14028) on the surface of autoclaved ground chicken breast and thigh burgers incubated at constant temperatures from 8 to 48 degrees C in 2 degrees C increments was investigated and modeled. Growth curves at each temperature were fit to a two-phase linear primary model to determine lag time (lambda) and specific growth rate (mu). Growth of S. typhimurium on breast and thigh meat was not different. Consequently, secondary models that predicted lag time and specific growth rate as a function of temperature were developed with the combined data for breast and thigh meat. Five secondary models for lag time and three secondary models for specific growth rate were compared. A new version of the hyperbola model and a cardinal temperature model were selected as the best secondary models for lag time and specific growth rate, respectively. The secondary models were combined in a computer spreadsheet to create a tertiary simulation model that predicted the potential growth (log10) increase) of S. typhimurium on cooked chicken as a function of time and temperature. Probability distributions and simulation were used in the tertiary model to model the secondary model parameters and the times and temperatures of abuse. The outputs of the tertiary model were validated (prediction bias of -4% for lambda and 1% for mu and prediction accuracy of 10% for lambda and 8% for mu) and integrated with a previously developed risk assessment model for Salmonella.     

Performance of response surface and Davey model for prediction of Staphylococcus aureus growth parameters under different experimental conditions

The combined effect of different temperatures (7 to 19 degrees C), pH levels (4.5 to 8.5), sodium chloride levels (0 to 8%), and sodium nitrite levels (0 to 200 ppm) on the predicted growth rate and lag time of Staphylococcus aureus under aerobic and anaerobic conditions was studied. The two predictive models developed, response surface (RS) and the Davey model, provided reliable estimates of the two kinetic parameters studied. The RS provided better predictions of maximum specific growth rate, with bias factors of 1.06 and 1.31 and accuracy factors of 1.17 and 1.37, respectively, in aerobic and anaerobic conditions. The Davey model performed more accurately for lag time, with a bias factor of 1.12 and an accuracy factor of 1.49, for both aerobic and anaerobic conditions. Predictive growth models are a valuable tool, enabling swift determination of Staphylococcus aureus growth rate and lag time. These data are essential for ensuring staphylococcus-related quality and safety of food products.     

Shelf life establishment of a sliced, cooked, cured meat product based on quality and safety determinants

In the present study, the distribution of the shelf life of cooked, cured meat products based on lactic acid bacteria growth and the distribution of the time to cause health risks based on Listeria monocytogenes growth were studied. Growth models, developed and validated on cooked meat products, were used to predict the growth of microorganisms. Temperature data were obtained from retail and home refrigerators. Distribution predictions were conducted by two approaches (time-temperature profiles and Monte Carlo simulation). Time-temperature profiles were more appropriate to be used, because Monte Carlo simulation overestimated the growth of L. monocytogenes. Shelf life was greatly influenced by storage temperature, but initial microbial load had a smaller effect. The expiration date of cooked meat products might be based on only the growth of the spoilage microorganisms, and only when product contamination with L. monocytogenes cell concentrations is high does a product fraction pose health risks for consumers. Sensitivity analysis confirmed that storage temperature and temperature variability were the most important factors for the duration of shelf life. Distributions of shelf life and time to cause health risks give valuable information on the quality and safety of cooked meat products and may be used as practical tools by meat processors.     

Comparison of primary predictive models to study the growth of Listeria monocytogenes at low temperatures in liquid cultures and selection of fastest growing ribotypes in meat and turkey product slurries

This study compared the performance of four primary mathematical models to study the growth kinetics of Listeria monocytogenes ribotypes grown at low temperature so as to identify the best predictive model. The parameters of the best-fitting model were used to select the fastest growing strains with the shortest lag time and greatest growth rate. Nineteen food, human and animal L. monocytogenes isolates with distinct ribotype were grown at 4, 8, and 12 degrees C in tryptic soy broth and slurries prepared from cooked uncured sliced turkey breasts (with or without potassium lactate and sodium diacetate, PL/SD) and cooked cured frankfurters (with or without PL/SD). Separate regressions were performed on semi-logarithm growth curves to fit linear (based on Monod) and non-linear (Gompertz, Baranyi-Roberts, and Logistic) equations and performance of each model was evaluated using an F-test. No significant differences were found in the performance of linear and non-linear models, but the Baranyi model had the best fit for most growth curves. The maximum growth rate (MGR) of Listeria strains increased with the temperature. Similarly MGR was found significantly greater when no antimicrobials were present in the formulation of turkey or frankfurter products. The variability in lag times and MGRs in all media as determined by the Baranyi model was not consistent among strains. No single strain consistently had the fastest growth (shortest lag time, fastest MGR, or shortest time to increase 100-fold), but nine strains were identified as fastest growing strains under most growth conditions. The lack of association between serotype and fastest strain was also observed in the slurry media study. The fastest growing strains resulting from this study can be recommended for future use in L. monocytogenes challenge studies in delicatessen meat and poultry food matrices, so as to develop conservative pathogen growth predictions.     

不同温度条件下三文鱼中荧光假单胞菌生长预测模型的建立

荧光假单胞菌SBW25(Pseudomonas fluorescence SBW25)作为三文鱼的特定腐败菌(specific spoilage organisms,SSOs),在三文鱼腐败过程中起着主导作用。实验选择以三文鱼的鱼肉和鱼汁为生长介质,采用修正的Gompertz方程和Belehradek方程拟合三文鱼特定腐败菌之一的荧光假单胞菌SBW25在不同温度条件下的生长动力学模型,同时探究鱼汁中蛋白酶活力对动力学参数的影响,并对模型的适用性进行评价。结果显示,修正的Gompertz方程所拟合出的各温度下货架期方程的决定系数(R~2)都达到0.999,适用于描述三文鱼鱼肉和鱼汁中微生物的生长曲线。随着温度升高,鱼肉和鱼汁中的荧光假单胞菌的最大比生长速率和延滞期出现上升和缩短。鱼汁中温度和最大比生长速率、延滞期的Belehradek平方根方程取得较高的决定系数,分别达到0.930 3和0.988 7,高于鱼肉中取得的。在鱼汁中蛋白酶活力和对应时期荧光假单胞菌的最大比生长速率出现相同变化趋势。基于Belehradek方程的鱼汁不同温度模型偏差度和准确度都更接近于1.00,说明鱼汁中SSOs的生长曲线能较好地反映出各温度条件下的三文鱼货架期。     

Predictive model for growth of Clostridium perfringens in cooked cured pork

Mathematical models have been developed and used for predicting growth of foodborne pathogens in various food matrices. However, these early models either used microbiological media or other model systems to develop the predictive models. Some of these models have been shown to be inaccurate for applications in meat and specific food matrices, especially under dynamic conditions, such as constantly changing temperatures that are encountered during food processing. The objective of this investigation was to develop a model for predicting growth of Clostridium perfringens from spore inocula in cured pork ham. Isothermal growth of C. perfringens at various temperatures from 10 to 48.9 degrees C were evaluated using a methodology that employed a numerical technique to solve a set of differential equations. The estimated theoretical minimum and maximum growth temperatures of C. perfringens in cooked cured pork were 13.5 and 50.6 degrees C, respectively. The kinetic and growth parameters obtained from this study can be used in evaluating growth of C. perfringens from spore populations during dynamically changing temperature conditions such as those encountered in meat processing. Further, this model can be successfully used to design microbiologically "safe" cooling regimes for cured pork hams and similar products.     

冷鲜梅条肉中热杀索丝菌生长预测模型建立与检验

研究冷鲜梅条肉中热杀索丝菌在0℃、5℃、10℃、15℃、20℃不同温度下生长变化情况,利用Modified Gompertz模型建立热杀索丝菌一级生长预测模型(R2＞0.99);利用平方根模型描述温度与最大比生长速率和延滞期的关系,得到热杀索丝菌的生长预测二级模型,验证模型的数学参数准确因子Af、Bf在1左右.表明数学模型可用于预测0℃～20℃范围内热杀索丝菌的变化情况,为冷鲜肉的货架期预报提供了基础数据.     

卤制鸭腿中乳酸菌生长预测模型研究

测定了卤制鸭腿中的乳酸菌在5、10、15、20、25℃条件下的生长情况,并利用Gompertz模型拟合了测定温度下的乳酸菌生长一级模型和乳酸菌生长状况。结果表明:模型拟合的R2都大于0.99,利用平方根模型描述温度与最大比生长速率和延滞期的关系,建立了乳酸菌在鸭腿基质上的生长预测二级模型,方差分析表明二级模型拟合显著。模型可用于预测5～25℃范围内乳酸菌在鸭腿上的生长变化情况,为卤制鸭腿中腐败微生物的预测研究提供参考。     

Determination of the growth limits and kinetic behavior of Listeria monocytogenes in a sliced cooked cured meat product: validation of the predictive growth model under constant and dynamic temperature storage conditions

To describe the growth limits of Listeria monocytogenes NCTC10527 in a sliced vacuum-packaged cooked cured meat product, the binary logistic regression model was used to develop an equation to determine the probability of growth or no growth of L. monocytogenes as a function of temperature (from 0 to 10 degrees C) and water activity (from 0.88 to 0.98). Two inoculum concentrations were used (10 and 10(4) CFU g(-1)), and the growth limits for the two inocula were different. The kinetic behavior of L. monocytogenes as a function of temperature (4, 8, 12, and 16 degrees C) on the same meat product at the lower concentration (10 CFU g(-1)) was also studied. The Baranyi model appeared to fit the overall experimental data better than did the modified Gompertz and the modified logistic models. Maximum specific growth rate (micromax), lag phase duration (LPD), and maximum cell concentration (Nmax) derived from the primary model were modeled using the square root function (micromax and LPD) and a second order polynomial (Nmax) (secondary models). The selection of the best model (primary or secondary) was based on some statistical indices (the root mean square error of residuals of the model, the regression coefficient, the F test, the goodness of fit, and the bias and accuracy factor). The developed kinetic behavior model was validated under constant and dynamic temperature storage conditions. This prediction of L. monocytogenes growth provides useful information for improving meat safety and can be used for in-depth inspection of quality assurance systems in the meat industry.     

Effect of pre-incubation conditions on growth and survival of Staphylococcus aureus in sliced cooked chicken breast

In this work, the effect of pre-incubation conditions (temperature: 10, 15, 37°C; pH 5.5, 6.5 and water activity, a(w): 0.997, 0.960) was evaluated on the subsequent growth, survival and enterotoxin production (SE) of Staphylococcus aureus in cooked chicken breast incubated at 10 and 20°C. Results showed the ability of S. aureus to survive at 10°C when pre-incubated at low a(w) (0.960) what could constitute a food risk if osmotic stressed cells of S. aureus which form biofilms survive on dried surfaces, and they are transferred to cooked meat products by cross-contamination. Regarding growth at 20°C, cells pre-incubated at pH 5.5 and a(w) 0.960 had a longer lag phase and a slower maximum growth rate. On the contrary, it was highlighted that pre-incubation at optimal conditions (37°C/pH 6.5/a(w) 0.997) produced a better adaptation and a faster growth in meat products what would lead to a higher SE production. These findings can support the adoption of management strategies and preventive measures in food industries leading to avoid growth and SE production in meat products.     

Validating an artificial neural network model of <Emphasis Type="Italic">Leuconostoc mesenteroides</Emphasis> in vacuum packaged sliced cooked meat products for shelf-life estimation

An Artificial Neural Network-based predictive model (ANN) for Leuconostoc mesenteroides growth in response to temperature, pH, sodium chloride and sodium nitrite, developed by Garcia-Gimeno et al. [Int. J. Food Microbiol. (2005)]) was validated on vacuum packed, sliced, cooked meat products and applied to shelf-life determination. Lag-time (Lag), growth rate (Gr), and maximum population density (yEnd) of L. mesenteroides, estimated by the ANN model, were compared to those observed in vacuum-packed cooked ham, turkey breast meat, and chicken breast meat stored at 10.5°C, 13.5°C and 17.7°C, using bias and accuracy factors. The ANN model provided reliable estimates for the three kinetic parameters studied; with a bias factor of 1.09; 0.73 and 1.00 for Lag, Gr and yEnd, respectively and an accuracy factor of 1.26; 1.58 and 1.13 for Lag, Gr and yEnd, respectively. From the three kinetic parameters obtained by the ANN model, commercial shelf-life were estimated for each temperature and compared with the tasting panel evaluation. The commercial shelf life estimated microbiologically, i.e. times to reach 10^6.5 cfu/g, was shorter than the period estimated using sensory methods.     

Response surface models for effects of temperature and previous growth sodium chloride on growth kinetics of Salmonella typhimurium on cooked chicken breast

Response surface models were developed and validated for effects of temperature (10 to 40 degrees C) and previous growth NaCl (0.5 to 4.5%) on lag time (lambda) and specific growth rate (mu) of Salmonella Typhimurium on cooked chicken breast. Growth curves for model development (n = 55) and model validation (n = 16) were fit to a two-phase linear growth model to obtain lambda and mu of Salmonella Typhimurium on cooked chicken breast. Response surface models for natural logarithm transformations of lambda and mu as a function of temperature and previous growth NaCl were obtained by regression analysis. Both lambda and mu of Salmonella Typhimurium were affected (P < 0.0001) by temperature but not by previous growth NaCl. Models were validated against data not used in their development. Mean absolute relative error of predictions (model accuracy) was 26.6% for lambda and 15.4% for mu. Median relative error of predictions (model bias) was 0.9% for lambda and 5.2% for mu. Results indicated that the models developed provided reliable predictions of lambda and mu of Salmonella Typhimurium on cooked chicken breast within the matrix of conditions modeled. In addition, results indicated that previous growth NaCl (0.5 to 4.5%) was not a major factor affecting subsequent growth kinetics of Salmonella Typhimurium on cooked chicken breast. Thus, inclusion of previous growth NaCl in predictive models may not significantly improve our ability to predict growth of Salmonella spp. on food subjected to temperature abuse.     

肉制品预测微生物模型的研究进展

肉制品贮藏过程的预测微生物模型是预测微生物学的重要分支。简述了肉制品货架期与特定腐败菌的相关性,综述了预测微生物模型的发展过程及其最新研究进展,分析预测微生物模型实际应用于肉制品质量监测的可行性,介绍几种有关食品微生物的数据库和预测软件,讨论了预测微生物模型存在的问题,展望了预测微生物模型的发展方向和应用前景。     

真空冷却技术在熟肉制品工业化生产中的应用研究

真空冷却技术是依据较高温度的含水物料在密封环境中真空的条件下通过水分迅速蒸发使物料自身得到迅速降温冷却的原理,这项快速蒸发冷却技术过去仅局限应用在蔬菜和鲜花的冷却保鲜等领域中,本课题研究真空冷却技术应用在熟肉制品生产的冷却工艺中,实验结果表明:相同的熟肉产品从95℃冷却到20℃,真空冷却比传统自然冷却速度快20倍以上,该技术可有效防止微生物在产品中的污染和增殖,提高产品的质量和安全性,延长产品货架期。研究同时就真空冷却技术对产品失水率的影响作了探讨。     

Mathematical Modeling of Lactobacillus Viridescens Growth in Vacuum Packed Sliced Ham under non Isothermal Conditions

Lactic acid bacteria (LAB) are responsible for the spoilage of vacuum packed meat products, as ham. Temperature is the main factor affecting the microbial dynamics and its variation during the production, distribution and storage of foods is considerable. Thus, the use of mathematical models to describe the microbial behavior under variable temperatures can be very useful in predicting the food shelf life. This study evaluated the growth of Lactobacillus viridescens in sliced ham under non isothermal conditions, and assessed the predictive ability of the Baranyi and Roberts model using parameters obtained isothermally in culture medium (MRS). To obtain the BAL growth, the fresh ham piece was sterilized, sliced, inoculated with bacteria and stored in a temperature-controlled incubator. For the establishment of the secondary models, the primary model parameters were obtained isothermally in the culture medium at 4, 8, 12, 16, 20 and 30° C, in which there was no lag phase observed; the square root model was selected to describe the dependence of the μ_max parameter (maximum specific growth rate) with the temperature, and the y_max parameter (maximum population) was represented by an average because there was no significant influence of the temperature. The mathematical models were validated with L. viridescens growth data in ham under five variable temperature conditions (NI-1 (4-8-12-16°C), NI-2 (12-16-20-25°C), NI-3 (25-20-16-12-8-4°C), NI-4 (16-12-8-4°C) and NI-5 (12-8-4-8-12°C)), and its predictive ability were assessed through statistical indexes (bias factor, accuracy factor and RMSE), with good results (bias factor between 0.9450 and 1.0326; accuracy factor between 1.0382 and 1.0682, and RMSE between 0.7641 and 1.3317), especially in increasing temperature, where the prediction was safe. The validated model can be used to estimate the shelf life of a commercial ham under different temperature conditions.