Development of a new mathematical modelling approach for prediction of growth kinetics of Listeria monocytogenes in milk
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Vup Food Research Inst, Bratislava
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The main objective of the present study was to develop a new modelling method, inverse dynamic modelling approach, as an alternative to two-step modelling approach, which is traditionally used n predictive food microbiology. For this purpose, the growth data of Listeria monocytogenes in milk subjected to isothermal and non-isothermal storage conditions were gathered from previously published growth curves. The bacterial growth data were described as a function of time and temperature using the direct two-step, direct one-step and inverse dynamic modelling approaches based on the Baranyi and Huang models. Maximum specific growth rate (mu(max)) and lag phase duration (lambda) estimated by different modelling approaches and primary models were statistically compared. Results revealed that there was no significant difference (p > 0.05) between the growth kinetic parameters obtained from direct and inverse modelling approaches. The prediction capability of inverse dynamic modelling approach was validated by externally gathering growth curves. The inverse dynamic modelling approach provided satisfactory statistical indices (0.99 > Bias factor > 1.10 and 1.16 > Accuracy factor > 1.19), meaning that it can be reliably used as an alternative way of describing the growth behaviour of Listeria monocytogenes in milk in a fast way with a minimal labour requirement.
Açıklama
Anahtar Kelimeler
Inverse Dynamic Modelling, Milk, Growth Kinetic, Food Safety, Predictive Microbiology, Lag Phase, Temperature, Validation
Kaynak
Journal of Food and Nutrition Research
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
60
Sayı
4
