Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions
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A dynamic growth model under variable temperature conditions was implemented and calibrated using raw data for microbial growth of Pseudomonas spp. in poultry under aerobic conditions. The primary model was implemented using measurement data under a set of fixed temperatures. The two primary models used for predicting the growth under constant temperature conditions were: Baranyi and modified Gompertz. For the
Baranyi model the maximum specific growth rate and the lag phase at constant environmental conditions are expressed in exact form and it has been shown that in limit case when maximal cells concentration is much higher than the initial concentration the maximum specific growth rate is approximately equal to the specific growth rate. The model parameters are determined in a temperature range of 2–20 °C. As a secondary model the square root model was used for maximum specific growth rate in both models.
In both models the main assumption, that the initial physiological state of t...he inoculum is constant and independent of the environmental parameters, is used, and a free parameter was implemented which was determined by minimizing the mean square error (MSE) relative to the measurement data. Two temperature profiles were used for calibration of the models on the initial conditions of the cells.
Keywords:
Poultry spoilage / Shelf life modelling / Predictive microbiology / Pseudomonas spp.Source:
International Journal of Food Microbiology, 2008, 127, 290-297Publisher:
- Elsevier
Funding / projects:
- CHILL-ON project, contract number: FP6-016333-2
- the federal state North Rhine Westphalia (USL PN 33108, USL PN 33110)
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GraFarTY - JOUR AU - Gospavić, Radovan AU - Kreyenschmidt, Judith AU - Bruckner, Stefanie AU - Popov, Viktor AU - Haque, Nasimul PY - 2008 UR - https://grafar.grf.bg.ac.rs/handle/123456789/3102 AB - A dynamic growth model under variable temperature conditions was implemented and calibrated using raw data for microbial growth of Pseudomonas spp. in poultry under aerobic conditions. The primary model was implemented using measurement data under a set of fixed temperatures. The two primary models used for predicting the growth under constant temperature conditions were: Baranyi and modified Gompertz. For the Baranyi model the maximum specific growth rate and the lag phase at constant environmental conditions are expressed in exact form and it has been shown that in limit case when maximal cells concentration is much higher than the initial concentration the maximum specific growth rate is approximately equal to the specific growth rate. The model parameters are determined in a temperature range of 2–20 °C. As a secondary model the square root model was used for maximum specific growth rate in both models. In both models the main assumption, that the initial physiological state of the inoculum is constant and independent of the environmental parameters, is used, and a free parameter was implemented which was determined by minimizing the mean square error (MSE) relative to the measurement data. Two temperature profiles were used for calibration of the models on the initial conditions of the cells. PB - Elsevier T2 - International Journal of Food Microbiology T1 - Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions EP - 297 SP - 290 VL - 127 DO - 10.1016/j.ijfoodmicro.2008.07.022 ER -
@article{ author = "Gospavić, Radovan and Kreyenschmidt, Judith and Bruckner, Stefanie and Popov, Viktor and Haque, Nasimul", year = "2008", abstract = "A dynamic growth model under variable temperature conditions was implemented and calibrated using raw data for microbial growth of Pseudomonas spp. in poultry under aerobic conditions. The primary model was implemented using measurement data under a set of fixed temperatures. The two primary models used for predicting the growth under constant temperature conditions were: Baranyi and modified Gompertz. For the Baranyi model the maximum specific growth rate and the lag phase at constant environmental conditions are expressed in exact form and it has been shown that in limit case when maximal cells concentration is much higher than the initial concentration the maximum specific growth rate is approximately equal to the specific growth rate. The model parameters are determined in a temperature range of 2–20 °C. As a secondary model the square root model was used for maximum specific growth rate in both models. In both models the main assumption, that the initial physiological state of the inoculum is constant and independent of the environmental parameters, is used, and a free parameter was implemented which was determined by minimizing the mean square error (MSE) relative to the measurement data. Two temperature profiles were used for calibration of the models on the initial conditions of the cells.", publisher = "Elsevier", journal = "International Journal of Food Microbiology", title = "Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions", pages = "297-290", volume = "127", doi = "10.1016/j.ijfoodmicro.2008.07.022" }
Gospavić, R., Kreyenschmidt, J., Bruckner, S., Popov, V.,& Haque, N.. (2008). Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions. in International Journal of Food Microbiology Elsevier., 127, 290-297. https://doi.org/10.1016/j.ijfoodmicro.2008.07.022
Gospavić R, Kreyenschmidt J, Bruckner S, Popov V, Haque N. Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions. in International Journal of Food Microbiology. 2008;127:290-297. doi:10.1016/j.ijfoodmicro.2008.07.022 .
Gospavić, Radovan, Kreyenschmidt, Judith, Bruckner, Stefanie, Popov, Viktor, Haque, Nasimul, "Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions" in International Journal of Food Microbiology, 127 (2008):290-297, https://doi.org/10.1016/j.ijfoodmicro.2008.07.022 . .