Logistic modeling to predict the minimum inhibitory concentration (MIC) of olive leaf extract (OLE) against Listeria monocytogenes

Abstract

Olive leaf extract (OLE) has been increasingly recognized as a natural and effective antimicrobial against a host of foodborne pathogens. This study attempts to predict the minimum inhibitory concentration (MIC) of OLE against Listeria monocytogenes F2365 by utilizing the asymptotic deceleration point (PDA) in a logistic model (LM), namely MIC-PDA. The experimental data obtained from the inhibitory rate (IR) versus OLE concentration against L. monocytogenes were sufficiently fitted (R2 = 0.88957). Five significant critical points were derived by taking the multi-order derivatives of the LM function: the inflection point (PI), the maximum acceleration point (PAM), the maximum deceleration point (PDM), the absolute acceleration point (PAA), and the asymptotic deceleration point (PDA). The PDA ([OLE] = 37.055 mg/mL) was employed to approximate the MIC-PDA. This MIC value was decreased by over 42% compared to the experimental MIC of 64.0 mg/mL, obtained using the conventional 2-fold dilution method (i.e., MIC-2fold). The accuracy of MIC-PDA was evaluated by an in vitro L. monocytogenes growth inhibition assay. Finally, the logistic modeling method was independently validated using our previously published inhibition data of OLE against the growths of Escherichia coli O157:H7 and Salmonella enteritidis. The MIC-PDA (for [OLE]) values were estimated to be 41.083 and 35.313 mg/mL, respectively, compared to the experimental value of 62.5 mg/mL. Taken together, MIC-PDA, as estimated from the logistic modeling, holds the potential to shorten the time and reduce cost when OLE is used as an antimicrobial in the food industry.