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Inactivation Data (inactivation + data)
Selected AbstractsA PREDICTIVE MODEL FOR HIGH-PRESSURE CARBON DIOXIDE INACTIVATION OF MICROORGANISMSJOURNAL OF FOOD SAFETY, Issue 2 2009S. BUZRUL ABSTRACT The Weibull model, which is commonly used for thermal inactivation of microorganisms in literature, was used to describe microbial inactivation by high-pressure carbon dioxide (HPCD). The number of parameters of the model was reduced from two to one in order to avoid interrelationship of these parameters with a slight loss of goodness-of-fit. A second-order polynomial function fulfilling a number of constraints was proposed for the secondary modeling of the time-constant parameter of the reduced Weibull model. This function consists of both pressure and temperature and therefore can be used for HPCD treatments. PRACTICAL APPLICATIONS The application of any new technology in food preservation requires a reliable model that accurately describes and predicts the inactivation data of microorganisms. In principle, the methodology presented here could be used to describe and predict the survival data for high-pressure carbon dioxide inactivation of microorganisms at least for some pressure and temperature ranges if the isobaric/isothermal survival curves of these microorganisms are linear, concave upward or downward. [source] High Hydrostatic Pressure Pasteurization of Red WineJOURNAL OF FOOD SCIENCE, Issue 8 2006Chulkyoon Mok ABSTRACT:, Pasteurization of low-alcohol wine using a high hydrostatic pressure (HHP) process was studied. A total of 10 mL grape wine sealed in a nylon/LLDPE bag was placed inside the HHP chamber. The pressure applied to the treatment chamber was maintained at 1000 to 3500 atm for 0 to 30 min. The effects of HHP treatments on the physiochemical properties (alcohol, pH, acidity, total sugar) and microbes (aerobic bacteria, yeast, and lactic acid bacteria) were examined. The HHP treatments had little impact on the physiochemical properties. The pasteurization effect of the HHP treatments increased with treatment pressure and time. A total of 2 different stages in the microbial inactivation were noticed when the 1st-order reaction model was used to fit the inactivation data. The inactivation rate was higher in the initial stages than in the later stages, suggesting that might be 2 different groups of the microorganisms, a more HHP-susceptible group and a less HHP-susceptible group. [source] C. botulinum inactivation kinetics implemented in a computational model of a high-pressure sterilization processBIOTECHNOLOGY PROGRESS, Issue 1 2009Pablo Juliano Abstract High-pressure, high-temperature (HPHT) processing is effective for microbial spore inactivation using mild preheating, followed by rapid volumetric compression heating and cooling on pressure release, enabling much shorter processing times than conventional thermal processing for many food products. A computational thermal fluid dynamic (CTFD) model has been developed to model all processing steps, including the vertical pressure vessel, an internal polymeric carrier, and food packages in an axis-symmetric geometry. Heat transfer and fluid dynamic equations were coupled to four selected kinetic models for the inactivation of C. botulinum; the traditional first-order kinetic model, the Weibull model, an nth-order model, and a combined discrete log-linear nth-order model. The models were solved to compare the resulting microbial inactivation distributions. The initial temperature of the system was set to 90°C and pressure was selected at 600 MPa, holding for 220 s, with a target temperature of 121°C. A representation of the extent of microbial inactivation throughout all processing steps was obtained for each microbial model. Comparison of the models showed that the conventional thermal processing kinetics (not accounting for pressure) required shorter holding times to achieve a 12D reduction of C. botulinum spores than the other models. The temperature distribution inside the vessel resulted in a more uniform inactivation distribution when using a Weibull or an nth-order kinetics model than when using log-linear kinetics. The CTFD platform could illustrate the inactivation extent and uniformity provided by the microbial models. The platform is expected to be useful to evaluate models fitted into new C. botulinum inactivation data at varying conditions of pressure and temperature, as an aid for regulatory filing of the technology as well as in process and equipment design. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009 [source] High Pressure Processing , a Database of Kinetic InformationCHEMIE-INGENIEUR-TECHNIK (CIT), Issue 8 2008R. Buckow Abstract Hydrostatic high pressure technology is relatively new to food industry and is more and more considered as an alternative to traditional preservation methods like heat processing. The inactivation of bacteria, spores, viruses and enzymes has been demonstrated in numerous papers, and various schemes for modelling the experimental inactivation data have been suggested. Although there are similarities to heat inactivation kinetics it is generally agreed that the heat process safety assessment with its typical indicator organisms cannot simply be transferred to high pressure treatment. In this paper a database is introduced which aims at the comparison of published kinetic high pressure inactivation data by using suitable mathematical modelling tools. For the sake of clarity, the functional associations of pressure, temperature and exposure time is presented by means of pressure-temperature diagrams (pT -diagrams), which show pressure-temperature combinations yielding to a desired reaction (e.g. inactivation) rate constant. Thus, the database software was particularly designed to enable the user to call up pressure-temperature dependent function equations for a number of micro-organisms, enzymes and food constituents and to visualize them in pT -diagrams for predetermined treatment times or as kinetics under predetermined p - T conditions. In addition, the database also features a simple calculator tool which allows the user to make an entry in three of the four process conditions (pressure level, temperature level, inactivation level, dwell time) and calculate the remaining forth process condition. The database is accessible through the internet and is continuously updated on the basis of the most recent publications and own experimental data. [source] | ||||||||||