Calculating the efficacy of heat sterilization processes

Simulation and optimization of the thermal sterilization process of puree cans using the production of chestnut puree as an example

In the production process of puree cans such as chestnuts cans, it is easy to browning due to excessive heating, which causes a lot of waste every year. The heat and mass transfer model of Chinese Chestnut Puree was established through the finite element method. The model simulated the change process of the temperature field, heat flow velocity field and F value during the production of Chinese Chestnut Puree. After comparing and confirming the effectiveness of the model through the thermal penetration test, the model was used to adjust and optimize the production process. For #9121 cans, the two-stage sterilization method was adopted. Through the sterilization method at 10-65-48-14/118-110°C, a sterilization effect equivalent to that of the original process at 10-86-24/121°C was achieved, the browning problem of the product was alleviated, and the product quality was improved. This practice can also provide a reference for canning enterprises to adjust their production processes in the future.

On optimum dynamic temperature profiles for thermal inactivation kinetics determination

Determination of inactivation kinetics, associated with thermal processing of foods and obtained from dynamic temperature experiments, requires carefully designed experiments, the primary element being the selection of the appropriate temperature profile along with a carefully planned sampling schedule. In the present work, a number of different dynamic temperature profiles were investigated in terms of their ability to generate accurate kinetic parameters with low confidence intervals (CIs). Although alternative models have been also tested, our work was concentrated on thermal inactivation kinetics that could be described by the classical D-z values. A pair of D and z values was assumed, and for each temperature profile tested, concentration data at different processing times were generated through the appropriate models. Next, an error (up to ±2.5% or ±5%) was introduced on these theoretical values to generate pseudo-experimental data, and the back-calculation of the assumed kinetic parameters by non-linear regression was performed. The accuracy and the 95% CIs of the estimated kinetic parameters were evaluated; joint confidence regions were also constructed to investigate parameters correlation. The effect of temperature profile pattern, level of error, number of experimental points, and reference temperature was assessed. A stepwise increasing and a single triangle-pattern temperature profile were the best profiles among those tested. As a general observation, based on different kinetic models investigated, temperature profiles and sampling intervals that result in concentration versus time diagrams having shapes as suggested by the primary model used when isothermally applied are not considered appropriate for parameter estimation.

Thermal Inactivation Kinetics of Sporolactobacillus nakayamae Spores, a Spoilage Bacterium Isolated from a Model Mashed Potato-Scallion Mixture

Sporolactobacillus species have been occasionally isolated from spoiled foods and environmental sources. Thus, food processors should be aware of their potential presence and characteristics. In this study, the heat resistance and influence of the growth and recovery media on apparent heat resistance of Sporolactobacillus nakayamae spores were studied and described mathematically. For each medium, survivor curves and thermal death curves were generated for different treatment times (0 to 25 min) at different temperatures (70, 75, and 80°C) and Weibull and first-order models were compared. Thermal inactivation data for S. nakayamae spores varied widely depending on the media formulations used, with glucose yeast peptone consistently yielding the highest D-values for the three temperatures tested. For this same medium, the D-values ranged from 25.24 ± 1.57 to 3.45 ± 0.27 min for the first-order model and from 24.18 ± 0.62 to 3.50 ± 0.24 min for the Weibull model at 70 and 80°C, respectively. The z-values determined for S. nakayamae spores were 11.91 ± 0.29°C for the Weibull model and 11.58 ± 0.43°C for the first-order model. The calculated activation energy was 200.5 ± 7.3 kJ/mol for the first-order model and 192.8 ± 22.1 kJ/mol for the Weibull model. The Weibull model consistently produced the best fit for all the survival curves. This study provides novel and precise information on thermal inactivation kinetics of S. nakayamae spores that will enable reliable thermal process calculations for eliminating this spoilage bacterium.

Thermal inactivation kinetics of hepatitis A virus in homogenized clam meat (Mercenaria mercenaria)

AIMS

Epidemiological evidence suggests that hepatitis A virus (HAV) is the most common pathogen transmitted by bivalve molluscs such as clams, cockles, mussels and oysters. This study aimed to generate thermal inactivation kinetics for HAV as a first step to design adequate thermal processes to control clam-associated HAV outbreaks.

METHODS AND RESULTS

Survivor curves and thermal death curves were generated for different treatment times (0-6 min) at different temperatures (50-72°C) and Weibull and first-order models were compared. D-values for HAV ranged from 47·37 ± 1·23 to 1·55 ± 0·12 min for the first-order model and 64·43 ± 3·47 to 1·25 ± 0·45 min for the Weibull model at temperatures from 50 to 72°C. z-Values for HAV in clams were 12·97 ± 0·59°C and 14·83 ± 0·0·28°C using the Weibull and first-order model respectively. The calculated activation energies for the first-order and Weibull model were 145 and 170 kJ mole(-1) respectively.

CONCLUSION

The Weibull model described the thermal inactivation behaviour of HAV better than the first-order model.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study provides novel and precise information on thermal inactivation kinetics of HAV in homogenized clams. This will enable reliable thermal process calculations for HAV inactivation in clams and closely related seafood.

Thermal Inactivation Kinetics of Human Norovirus Surrogates and Hepatitis A Virus in Turkey Deli Meat

Human noroviruses (HNoV) and hepatitis A virus (HAV) have been implicated in outbreaks linked to the consumption of presliced ready-to-eat deli meats. The objectives of this research were to determine the thermal inactivation kinetics of HNoV surrogates (murine norovirus 1 [MNV-1] and feline calicivirus strain F9 [FCV-F9]) and HAV in turkey deli meat, compare first-order and Weibull models to describe the data, and calculate Arrhenius activation energy values for each model. The D (decimal reduction time) values in the temperature range of 50 to 72°C calculated from the first-order model were 0.1 ± 0.0 to 9.9 ± 3.9 min for FCV-F9, 0.2 ± 0.0 to 21.0 ± 0.8 min for MNV-1, and 1.0 ± 0.1 to 42.0 ± 5.6 min for HAV. Using the Weibull model, the tD = 1 (time to destroy 1 log) values for FCV-F9, MNV-1, and HAV at the same temperatures ranged from 0.1 ± 0.0 to 11.9 ± 5.1 min, from 0.3 ± 0.1 to 17.8 ± 1.8 min, and from 0.6 ± 0.3 to 25.9 ± 3.7 min, respectively. The z (thermal resistance) values for FCV-F9, MNV-1, and HAV were 11.3 ± 2.1°C, 11.0 ± 1.6°C, and 13.4 ± 2.6°C, respectively, using the Weibull model. The z values using the first-order model were 11.9 ± 1.0°C, 10.9 ± 1.3°C, and 12.8 ± 1.7°C for FCV-F9, MNV-1, and HAV, respectively. For the Weibull model, estimated activation energies for FCV-F9, MNV-1, and HAV were 214 ± 28, 242 ± 36, and 154 ± 19 kJ/mole, respectively, while the calculated activation energies for the first-order model were 181 ± 16, 196 ± 5, and 167 ± 9 kJ/mole, respectively. Precise information on the thermal inactivation of HNoV surrogates and HAV in turkey deli meat was generated. This provided calculations of parameters for more-reliable thermal processes to inactivate viruses in contaminated presliced ready-to-eat deli meats and thus to reduce the risk of foodborne illness outbreaks.

Determination of thermal inactivation kinetics of hepatitis A virus in blue mussel (Mytilus edulis) homogenate

Hepatitis A virus (HAV) is a food-borne enteric virus responsible for outbreaks of hepatitis associated with shellfish consumption. The objectives of this study were to determine the thermal inactivation behavior of HAV in blue mussels, to compare the first-order and Weibull models to describe the data, to calculate Arrhenius activation energy for each model, and to evaluate model efficiency by using selected statistical criteria. The times required to reduce the population by 1 log cycle (D-values) calculated from the first-order model (50 to 72°C) ranged from 1.07 to 54.17 min for HAV. Using the Weibull model, the times required to destroy 1 log unit (tD = 1) of HAV at the same temperatures were 1.57 to 37.91 min. At 72°C, the treatment times required to achieve a 6-log reduction were 7.49 min for the first-order model and 8.47 min for the Weibull model. The z-values (changes in temperature required for a 90% change in the log D-values) calculated for HAV were 15.88 ± 3.97°C (R(2), 0.94) with the Weibull model and 12.97 ± 0.59°C (R(2), 0.93) with the first-order model. The calculated activation energies for the first-order model and the Weibull model were 165 and 153 kJ/mol, respectively. The results revealed that the Weibull model was more appropriate for representing the thermal inactivation behavior of HAV in blue mussels. Correct understanding of the thermal inactivation behavior of HAV could allow precise determination of the thermal process conditions to prevent food-borne viral outbreaks associated with the consumption of contaminated mussels.

Use of linear, Weibull, and log-logistic functions to model pressure inactivation of seven foodborne pathogens in milk

Survival curves of six foodborne pathogens suspended in ultra high-temperature (UHT) whole milk and exposed to high hydrostatic pressure at 21.5 degrees C were obtained. Vibrio parahaemolyticus was treated at 300 MPa and other pathogens, Listeria monocytogenes, Escherichia coli O157:H7, Salmonella enterica serovar Enteritidis, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus were treated at 600 MPa. All the survival curves showed a rapid initial drop in bacterial counts followed by tailing caused by a diminishing inactivation rate. A linear model and two nonlinear models were fitted to these data and the performances of these models were compared using mean square error (MSE) values. The log-logistic and Weibull models consistently produced better fits to the inactivation data than the linear model. The mean MSE value of the linear model was 6.1, while the mean MSE values were 0.7 for the Weibull model and 0.3 for the log-logistic model. There was no correlation between pressure resistance and the taxonomic group the bacteria belong to. The order, most to least pressure-sensitive, of the single strains tested was: V. parahaemolyticus (gram negative)<L. monocytogenes (gram positive)<Salmonella Typhimurium (gram negative) approximately = Salmonella Enteritidis (gram negative)<E. coli O157:H7 approximately = Staphylocollus aureus (gram positive)<Shigella flexneri (gram negative). The most pressure-resistant gram-negative bacterium, Shigella flexneri, and most pressure resistant gram-positive bacterium, Staphylocollus aureus, were pressurized at 50 degrees C. Staphylocollus aureus was treated at 500 MPa and Shigella flexneri at 600 MPa. Elevated temperature considerably enhanced pressure inactivation of these two pathogens, but did not affect the overall shape of the survival curves. Pressure level (250 MPa) and substrate (1% peptone water plus 3% NaCl) in which V. parahaemolyticus was suspended affected the shape of survival curves of V. parahaemolyticus.

Generating microbial survival curves during thermal processing in real time

AIMS

To develop a method to calculate and record theoretical microbial survival curves during thermal processing of foods and pharmaceutical products simultaneously with the changing temperature. Moreover, to demonstrate that the method can be used to calculate nonisothermal survival curves, with widely available software such as Microsoft Excel.

METHODS AND RESULTS

It has been assumed that the targeted organism's isothermal survival curves are not log linear and hence, the inactivation rate in nonisothermal processes is a function of the momentary temperature and the corresponding survival ratio. This could be expressed by a difference equation, which is an approximation to the continuous rate model. The concept was tested with the isothermal survival parameters of Clostridium botulinum and Bacillus sporothermodurans spores, and Salmonella enteritidis cells, using different kinds of survival models and under temperature profiles resembling those of commercial processes. As expected, there was an excellent agreement between the curves produced by solving the differential equation of the continuous model and by the incremental method, which has been posted on the web as freeware.

CONCLUSIONS

It is possible to calculate nonisothermal survival curves, in real time, with an algorithm that can be written in the language of general purpose software, to follow the inactivation of one or more targeted organisms simultaneously and to simulate microbial survival patterns under existing or planned industrial thermal processes.

SIGNIFICANCE AND IMPACT OF THE STUDY

Replacement of the traditional 'F0-value', which requires the log linearity of the organism's isothermal survival curves, by the more realistic theoretical survival ratio estimate as a measure of the thermal process efficacy.