A comparison of <i>Listeria monocytogenes</i> growth monitoring in ground pork samples by real-time polymerase chain reaction to conventional agar and most probable number methods

Abstract

To construct a predictive growth model of Listeria monocytogenes in ground pork, growth data were collected by real-time PCR and Listeria selective agar according to Ottaviani and Agosti (ALOA). Most probable number (MPN) was used to estimate viable numbers of L. monocytogenes at the beginning, middle, and end of the incubation period. Growth curves obtained from this study were fitted to the Baranyi and Roberts model to obtain growth parameters. Furthermore, the theoretical minimum temperature of growth was estimated by Ratkowsky's model. L. monocytogenes growth rates estimated from ALOA data were lower than those estimated by real-time PCR. Moreover, cell concentrations at all incubation temperatures were underestimated and lag phase duration at refrigeration temperature (4 °C) was overestimated by ALOA. However, the estimation from MPN more closely resembled the real-time PCR quantification results. Thus, the direct plate count tends to result in fail-dangerous prediction for bacterial risk from the model.

Predicting the Growth Behavior of Foodborne Pathogenic Bacteria by Real-time Polymerase Chain Reaction Method

“…Although numerous bacterial growth models have been published (da Silva et al 2017, Stavropoulou & Bezirtzoglou 2019, the data was collected solely using agar methods. However, considering the lack of accuracy in determining the actual bacterial viable cell number under different conditions, there are several concerns regarding the construction of predictive models using the data generated from conventional plate counts (Noviyanti et al 2021). As emphasized previously, accurate estimation of viable cell number is often difficult when samples contain high levels of background microflora.…”

“…Furthermore, the growth behavior of L. monocytogenes in pasteurized cow milk and ground pork was simulated using time-temperature models (Noviyanti et al 2020(Noviyanti et al , 2021. In the case study of L. monocytogenes growth in ground pork, a series of six growth curves at incubation temperatures of 4°C, 8°C, 12°C, 16°C, 20°C, and 35°C were successfully described (Noviyanti et al 2021).…”

“…Furthermore, the growth behavior of L. monocytogenes in pasteurized cow milk and ground pork was simulated using time-temperature models (Noviyanti et al 2020(Noviyanti et al , 2021. In the case study of L. monocytogenes growth in ground pork, a series of six growth curves at incubation temperatures of 4°C, 8°C, 12°C, 16°C, 20°C, and 35°C were successfully described (Noviyanti et al 2021). Figure 1 shows the growth curves of L. monocytogenes in ground pork samples at 4°C fitted to a primary Baranyi and Roberts model (Baranyi & Roberts 1994) constructed using the data plots obtained from realtime PCR, direct plate counts on Agar Listeria according to Ottaviani and Agosti (ALOA) medium, and the most probable number (MPN) method (Noviyanti et al 2021).…”

“…The growth of these background microflora typically masks the colonies of target pathogenic bacteria; hence, feasible methods to differentiate between them are not available. Conversely, selective media will tend to underestimate viable numbers of bacterial cells because injured bacteria from highstress environments cannot form colonies on agar plates (Noviyanti et al 2021). Moreover, as the conventional plate count method has low specificity, skills and experience are required to distinguish target colonies from background flora that may be present in the samples (Kawasaki et al 2011).…”

“…In recent years, real-time polymerase chain reaction (PCR) analysis has emerged as a novel technique for the rapid, specific, and high-throughput quantification of pathogenic bacteria (Kawasaki et al 2014;Noviyanti et al 2018Noviyanti et al , 2020Noviyanti et al , 2021. Real-time PCR enables the collection of multiple growth data plots of pathogenic bacteria in various food materials containing background flora.…”