Limitations of the Log-Logistic Model for the Analysis of Sigmoidal Microbial Inactivation Data for High-Pressure Processing (HPP)

作者：Serment Moreno Vinicio; Torres J Antonio; Fuentes Claudio; Guadalupe Rios Alejandro Jose; Barbosa Canovas Gustavo; Welti Chanes Jorge

来源：Food and Bioprocess Technology, 2016, 9(5): 904-916.

DOI：10.1007/s11947-016-1677-2

• High-pressure processing (HPP)
• Log-logistic model
• Microbial inactivation kinetics
• Sigmoidal curves
• Information theory criteria
• Akaike information criteria (AIC)

This study identified limitations of the log-logistic model to evaluate microbial inactivation kinetics by high-pressure processing (HPP) including the need to assign a numerical value to "approximate" the undefined expression log(10) t = 0 and the misinterpretation of its parameters due to a derivation flaw. Peer-reviewed HPP microbial inactivation data were adjusted to a sigmoidal equation (SIG), the original "vitalistic" log-logistic models (VIT-1, VIT-6), and two functions that did not follow the original derivation procedure (LOG-1, LOG-6). Their goodness of fit was determined utilizing the coefficient of determination (R (2) ) and Akaike information criteria (AIC). The shape of the survival curve greatly influenced the performance of log-logistic models. VIT and LOG models performed equally when the kinetic curve showed a sigmoidal shape, and the numerical values of their parameter estimates were identical regardless of the log(10) (t = 0) approximation. Conversely, most concave curves yielded inaccurate parameter estimates for all models. LOG-1 and VIT-1 performed best when log(10) t = 0 was -1 or -2, whereas LOG-6 and VIT-6 yielded best results for values of -3 to -9. SIG ranked last for most datasets but occasionally performed best (Akaike weight factor w(AICi) = 0.40-1.00) when microbial survival counts showed clear sigmoidal shapes. VIT models consistently displayed R (2) a parts per thousand yenaEuro parts per thousand 0.98, and their parameters can be interpreted within a "biological" context using the corrected derivation shown for LOG models. However, concave curves are more frequently observed for HPP microbial inactivation, and fitting the experimental data to log-logistic models deems unnecessary.

• 出版日期2016-5