Estimation of growth parameters of Listeria monocytogenes after sublethal heat and slightly acidic electrolyzed water (SAEW) treatment

Food Control 71 (2017) 17e25

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Estimation of growth parameters of Listeria monocytogenes after sublethal heat and slightly acidic electrolyzed water (SAEW) treatment Xiao-Ting Xuan a, Tian Ding a, *, Jiao Li a, Ju-Hee Ahn b, Yong Zhao c, Shi-Guo Chen a, Xing-Qian Ye a, Dong-Hong Liu a, ** a b c

Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang University, Hangzhou, Zhejiang 310058, China Department of Medical Biomaterials Engineering, Kangwon National University, Chuncheon, Gangwon 200701, Republic of Korea College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 May 2016 Received in revised form 16 June 2016 Accepted 18 June 2016 Available online 18 June 2016

Time to detection experiments (TTD) based on turbidometry using an automatic Bioscreen C is a useful and straightforward method for estimating microbial growth parameters (lag time (l), growth rate (m) and “work to be done” (h0)) at constant temperature. This study investigated the effects of slightly acidic electrolyzed water (SAEW) and heat treatment on Listeria monocytogenes growth at different recovery temperatures (10
C, 15
C, 25
C, and 30
C). Similar surviving and sublethally injured L. monocytogenes populations were obtained by heat treatment (55
C for 10 min) and SAEW treatment (available chlorine concentration of 30 mg/l and ratio of bacteria against SAEW of 8:2 for 30 s). In these experimental conditions, stresses had greater impact on the l and h0 parameter in comparison with recovery temperature while there was no great change in growth rate under isothermal conditions. Larger l values and h0 parameters were observed in sublethal-heat injured L. monocytogenes (the maximum l and h0 parameters are 30.199 h and 1.6492) as compared to SAEW groups (the maximum l and h0 parameters are 22.634 h and 1.4396). The sensitivity analysis of SAEW and heat treatments on h0 parameter indicated that SAEW treatment showed a higher influence. The collinearity diagnostics of independent variables [recovery temperature (T), m, l] for dependent variable (h0 parameter) demonstrated that T, m and l had strong collinearity. In addition, the established secondary models in this study have good performances on predicting the effect of recovery temperature on bacterial growth parameters. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Growth parameter Slightly acidic electrolyzed water Heat Listeria monocytogenes Time to detection

1. Introduction With the growing demand for convenient and healthy food, sales of fresh-cut and mildly processed fruits and vegetables (eg. ready-to-eat fruits) have increased. Mild process can preserve freshness and the characteristic flavor of food products. However, fruits and vegetables that have been mildly processed (washing, cutting, cooking, mixing, canning, packing etc.) can harbor foodborne pathogens such as Staphylococcus aureus, enterohemorrhagic Escherichia coli, Campylobacter jenuni, Salmonella spp., and Listeria monocytogenes (Issa-Zacharia, Kamitani, Miwa, Muhimbula, &

* Corresponding author. ** Corresponding author. E-mail addresses: [email protected] (T. Ding), [email protected] (D.-H. Liu). http://dx.doi.org/10.1016/j.foodcont.2016.06.018 0956-7135/© 2016 Elsevier Ltd. All rights reserved.

Iwasaki, 2011; Issa-Zacharia, Kamitani, Tiisekwa, Morita, & Iwasaki, 2010), which cause serious health problems. These bacteria can multiply during process, transportation, distribution, storage, and handling. In particular, L. monocytogenes in milk, cheese, vegetables, and meat products has become a major concern in terms of public health and food safety (Aureli et al., 2000; Brett, Short, & McLaughlin, 1998; Ding et al., 2013; Dorozynski, 2000; Guillier, Pardon, & Augustin, 2005). This species is widely distributed in nature and can survive in stressful environments, such as under refrigeration. Moreover, it is difficult to inactivate L. monocytogenes completely during mild process because of the self-repairing and regrowth capability of injured L. monocytogenes. It was previously reported that heat-injured L. monocytogenes was capable of selfrepair in whole and 2% fat milk stored at 4
C (Meyer & Donnelly, 1992). Therefore, an effective strategy is needed for controlling populations of sublethally injured L. monocytogenes in mildly

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processed foods. Various decontamination methods have been applied individually or in combination in order to reduce or eliminate pathogenic bacteria in mildly processed foods, including chemical disinfectants (e.g. hypochlorite, chlorine dioxide, hydrogen peroxide, hydrochloric acid, and ozone) and physical treatments (e.g. heat and irradiation) (Koide, Shitanda, Note, & Cao, 2011; Zhang et al., 2011). Heat treatment is a traditional inactivation method, which inactivates microbes by inhibiting the activity of intracellular proteins and enzymes and damaging cell membranes and nucleic acids (Juneja & Sofos, 2002). Nonetheless, many studies have demonstrated that sublethally injured cells can proliferate depending on environmental factors as well as the history of the cell, including physiological state and exposure to stressors (Guillier et al., 2005;
oz, Guevara, Palop, & Fernandez, 2010; Vasseur, Baverel, Mun Hebraud, & Labadie, 1999). Recently, slightly acidic electrolyzed water (SAEW) has been used as a disinfectant in food decontamination and preservation. SAEW could be prepared by electrolysis of an aqueous mixture containing dilute HCl and NaCl (or KCl) solutions using an oxidizing redox potential water generator equipped with an electrolytic cell without a separating membrane between anode and cathode. Besides it could also be produced by acidic and alkaline electrolyzed water by using an oxidizing redox potential water generator with a separating member. SAEW has strong bactericidal activity, and in comparison with strong acidic electrolyzed water, it has fewer adverse effects on human health and the environment owing to its chemical composition (with HClO as the main chlorine compound) and near-neutral pH (Ding et al., 2015). Many studies have investigated the disinfection efficacy of SAEW against different foodborne pathogens, e.g. L. monocytogenes, E. coli O157:H7, S. aureus, Salmonella typhimurium, and Vibrio parahaemolyticus (Al-Holy & Rasco, 2015; Cao, Zhu, Shi, Wang, & Li, 2009; McCarthy & Burkhardt, 2012; Wang et al., 2014). Electrolyzed water increases cell membrane permeability and disrupts cytoplasmic structures, leading to the rapid leakage of intracellular Kþ, DNA, and proteins and reducing the dehydrogenase activity of cells (Ding et al., 2016; Zeng et al., 2010, 2011). During inactivation, there is still a possibility that sublethally injured bacteria could be induced by SAEW which cause potential hazards for human beings. Hence, it is vital to study the sublethal injury of bacteria caused by SAEW treatment and its recovery condition. The behavior of microorganisms can be described by four basic parameters: initial and maximum cell densities, lag time, and
oz-Cuevas, Fernandez, George, & Pin, 2010). growth rate (Mun Thereinto, lag time is more difficult to predict than the growth rate due to its dependence on the initial physiological state of bacteria and the growth environments. Several different concepts have been introduced to quantify the lag time duration such as the “work to be
oz-Cuevas et al., 2010), the “physiological state” done” (Mun (Baranyi, Roberts, & McClure, 1993), and the “relative lag times” (Ross, 1999). Based on Baranyi et al. (1993), the duration of lag is determined by the value of that variable at inoculation and by the post-inoculation environments. The concept of “physiological state” (a) can be used to compare the effect of different treatments on the growth conditions of bacteria, even when the growth rates are different (George, Metris, & Stringer, 2008). Thereinto, the lag time (l), growth rate (m) and “work to be done” (h0) are the pa
tris, Li, & Baranyi, 2011). The rameters of a (Zhou, George, Me formulation of h0 is: Work to be done (h0) ¼ l  m

(1)

In addition, recovery conditions may influence the ability of microorganisms to survive upon exposure to environmental

stressors. Several methods have been developed to estimate growth parameters based on turbidity (Lindqvist, 2006); one of these is the time-to-detection (TTD) method based on the Baranyi growth model (Baranyi & Pin, 1999) and analysis of variance, which is useful for estimating growth rate and real lag time. The advantage of this method is that it does not require calibration between cell numbers and absorbance, with the initial dilution experiment being sufficient for making estimates (Lindqvist, 2006). Using various initial concentrations of bacteria, growth parameters can be calculated based on the detection time required to obtain a 0.03e0.05 unit increase in baseline optical density (OD) value corresponding to a cell density of approximately 107 log10 CFU/ml (Guillier et al., 2005; Lindqvist, 2006; Mytilinaios, Salih, Schofield, & Lambert, 2012). In the present study, we investigated the effects of SAEW and heat treatment on growth parameters (l, m and h0) of L. monocytogenes, and compared the effects of recovery temperature (10
C, 15
C, 25
C, and 30
C) on l, m and h0 parameters of stressed or sublethally injured L. monocytogenes. 2. Materials and methods 2.1. Strains and culture conditions L. monocytogenes cultures (ATCC19114-3; purchased from Hope Bio-Technology Co., Qingdao, China) were maintained in Trypticase Soy-Yeast Extract Broth (TSB-YE; Beijing Land Bridge Technology Co., Beijing, China) with 50% glycerol at 80
C. Prior to each experiment, a colony obtained from a streaked plate was inoculated in 100 ml TSB-YE in conical flasks and incubated with continuous shaking at 150 rpm and 37
C for 18 h. A 5-ml volume of the enriched culture was centrifuged at 5000 rpm and 4
C for 10 min. The pellet was washed twice and resuspended in 5 ml of 0.85% sterile saline solution to obtain a final bacterial cell density of approximately 109 CFU/ml. 2.2. Preparation of SAEW SAEW [200 ± 10 mg/l of available chlorine concentration (ACC)] was prepared by electrolysis of an aqueous mixture containing 0.6% NaCl and 0.15% HCl using an oxidizing redox potential water generator (Beijing Intercontinental Resources and Environmental Protection Technology Co., Beijing, China) equipped with an electrolytic cell without a separating membrane between anode and cathode. ACC was measured by a colorimetric method using the RC3F digital chlorine test kit (KRK Co., Osaka, Japan) with a detection range of 0e300 mg/l. Different concentrations of SAEW were obtained by diluting with distilled water. Approximately 30 mg/l ACC in SAEW [pH 6.3 and with an oxidization reduction potential (ORP) of 867.4 mV] was obtained by diluting with distilled water at a 1:4.5 ratio. The pH and ORP were measured using a dual scale S-40 pH/ ORP meter (Mettler Toledo Co., Zurich, Switzerland). 2.3. Stress experiment The TTD requires enough consecutive binary dilutions (about ten dilutions of sample), and inoculum sizes can influence the duration of lag time especially when it is less than 2 log10 CFU/ml (Augustin, Delattre, Rosso, & Carlier, 2000; Bidlas, Du, & Lambert, 2008; Gay, Cerf, & Davey, 1996). Hence, initial bacterial counts used to prepare dilutions were 102e105 CFU/ml (Lindqvist, 2006). In SAEW treatment experiments, L. monocytogenes cell suspensions (approximately 9.1 ± 0.2 log10 CFU/ml) and SAEW (ACC ¼ 30 mg/l, pH 6.3, ORP ¼ 867.4 mV) were mixed at ratios of 1:9, 1:1, 8:2, and 9:1 for 20, 30, and 40 s. Subsequently, 1 ml of each suspension was

X.-T. Xuan et al. / Food Control 71 (2017) 17e25

transferred to a sterile tube containing 9 ml neutralizing buffer solution (0.85% NaCl solution and 0.5% sodium thiosulphate) to halt disinfection by SAEW, yielding a surviving L. monocytogenes population of approximately 5 log10 CFU/ml. In heat treatment experiments, the surviving and sublethally injured population of heated L. monocytogenes at various heat temperatures (50
C, 55
C, and 60
C) for different treatment times (3, 10, and 15 min) were evaluated according to the requirements of initial bacterial populations in the TTD method (Gabriel & Nakano, 2009; Guillier et al.,
oz et al., 2010). After heat treatment, test tubes were 2005; Mun immediately cooled by rinsing with tap water for 1 min. In order to maintain the same initial inoculum size for TTD experiments, one decimal dilution using 0.85% sterile saline solution was added to the tubes after heat treatment.

2.4. Viable and sublethally injured cell counts The sublethally injured cell counts were obtained following the methods reported by Gnanou-Besse, Dubois-Brissonnet, Lafarge, and Leclerc (2000). A 1-ml volume of each sample was serially diluted with 0.85% sterile saline solution; 0.1 ml of each dilution was plated on non-selective TSA-YE and selective PALCAM agar (Beijing Land Bridge Technology Co.), following by incubation at 37
C for 24 and 48 h, respectively. Viable and sublethally injured cells grew on non-selective medium, whereas the latter were unable to grow on selective medium (Gnanou-Besse, 2002; Jasson, Uyttendaele, Rajkovic, & Debevere, 2007). Non-selective and selective media were used for the recovery of stressed bacteria. The number of stressed or sublethally injured bacteria was calculated by determining the difference between counts of cells grew on nonselective and selective media. And the sublethally injured rate was calculated with the following equations:

Sublethally injured rate ð%Þ ¼

19

of incubation (OD600 ¼ 0.12) was determined. An OD (¼0.15) corresponded to a bacterial concentration of approximately 7.4 log10 CFU/ml, as determined by the count of plated viable cells. Growth parameters (l, m) of L. monocytogenes after SAEW or heat treatment at different recovery temperatures were calculated with the following equations (Lindqvist, 2006):

log ðNt Þ ¼ K  m  Td

(3)

K  logðXdet Þ

(4)

l¼

m

where Nt is the initial bacterial concentration (CFU/ml); Td is the turbidity detection time; The lag time is l (h) and the growth rate is m (h1). Xdet is the bacterial count at the turbidity detection level (CFU/ml); and K is the intercept (constant). The l, m values with standard deviation and 95% confidence intervals were obtained from the primary model and analyzed with Origin v.8.0 software (OriginLab, Northampton, MA, USA). And the h0 parameter was calculated based on the Eq. (1). Correlation coefficient was applied to conduct sensitivity analysis of stresses (SAEW and heat treatment) for h0 parameter. The rank order correlation analyses were showed by “tornado plots” which array the factors from the most influential at the top to the
oz et al., 2010). Moreover, all least influential at the bottom (Mun the independent variables (recovery temperature, m, l) for h0 parameter were tested the collinearity to analyze their relativity.

2.7. Predictive model and validation The l and m values were used to develop the secondary model from Eqs. (4) and (5):

cell counts in non­slective medium  cell counts in selective medium  100% cell counts in non­selective medium

(2)

2.5. OD measurements The effects of SAEW, heat treatment, and recovery temperature on L. monocytogenes growth were determined from turbidity growth curves using an automatic Bioscreen C (Labsystems, Helsinki, Finland). A 200-ml volume of bacterial suspension at appropriate concentrations (approximately 106 CFU/ml) treated with SAEW, heat, or left untreated (control) were diluted 2-fold in a 100well honeycomb plate containing 200 ml TSB-YE medium in each well. The concentrations of 10 different dilutions ranged from 102 to 105 CFU/ml. In addition, 200 ml of TSB-YE medium were added to three of the wells as blank controls. The honeycomb plate was placed in the Bioscreen C reader set at 10
C, 15
C, 25
C, and 30
C. The OD600 was measured at 10-min intervals and the honeycomb plates were shaken at medium intensity for 20 s before every measurement. Each stress experiment was repeated four times. 2.6. Estimation and analysis of growth parameters and h0 parameter Growth parameters of sublethally injured L. monocytogenes were measured by the TTD method as previously described (Guillier et al., 2005; Lindqvist, 2006). Briefly, the time taken for the population to show an increase in OD600 of 0.03 units from the start

pffiffiffi

m ¼ b  ðT  T0 Þ

(5)

1 pffiffiffi ¼ b  ðT  T0 Þ

(6)

l

where l is the lag time (h), and m represents the specific growth rate (h1); b is the regression constant and T0 is the minimum temperature (T) required for growth (
C). Several mathematical indices were used to confirm the reliability and applicability of the predictive models, including the root mean squared error [RMSE; Eq. (7)], median relative error [MRE; Eq. (8)], and mean absolute relative error [MARE; Eq. (9)]:

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P ðX0  XP Þ2 RMSE ¼ n   1 X Xp  X0 MRE ¼  n X0

(7)

(8)

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X.-T. Xuan et al. / Food Control 71 (2017) 17e25

  1 X Xp  X0  MARE ¼    n X0

(9)

where n represents the number of observations, Xp and Xo indicate predicted and observed lag time (l, h) and specific growth rate (m, h1) values, respectively. 2.8. Statistical analysis All measurements performed in triplicate and means and standard deviations were determined from independent trials. Data were analyzed to obtain the confidence intervals, correlation coefficient and collinearity by SPSS v.20 (SPSS Inc., Chicago, IL, USA) and Origin v.8.0 (OriginLab, Northampton, MA, USA) software. Differences between means were evaluated by single-factor analysis of variance and Tukey’s test was used for pairwise comparisons. Differences were considered significant at P < 0.05. Collinearity was evaluated by variance inflation factor (VIF) test. 3. Results and discussion 3.1. L. monocytogenes inactivation by heat and SAEW

monocytogenes after different treatment temperatures (50
C, 55
C, and 60
C) and times (3, 10, and 15 min) were shown in Table 2. The L. monocytogenes population was reduced by between 1.3 and 4.1 log10 CFU/ml and the sublethally injured rate ranged from 20.57% to 93.69%. The fraction of injured L. monocytogenes after heating at 55
C for 3, 10, and 15 min was 20.57%, 60.19%, and 93.69%, respectively. However, another study found that approximately 98.1%e99.9% of L. monocytogenes F5069 (initial bacteria population ¼ 107 CFU/ml) were injured by a 50-min exposure to a temperature of 56
C (Busch & Donnelly, 1992). Growth parameters of L. monocytogenes after treated by SAEW and heat were determined according to TTD method and the initial bacterial populations for TTD experiments required approximately 102e105 CFU/ml (Lindqvist, 2006). The neutralizing buffer solution in SAEW treatment was necessary to stop disinfection which was equivalent to a decimal dilution. Hence, the surviving L. monocytogenes for recovery experiments required approximately 106 CFU/ml. The sizes of surviving populations of L. monocytogenes after 10 min at 55
C were 6.4 ± 0.1 log10 CFU/ml; similar results were achieved by treatment with a 8:2 ratio of SAEW for 30 s (6.2 ± 0.1 log10 CFU/ml). These two stress conditions were therefore selected for subsequent recovery experiments. 3.2. Effect of recovery temperature and stress on TTD

The bactericidal effects of SAEW (ACC ¼ 30 mg/l, pH 6.3, ORP ¼ 867.4 mV) were assessed in order to determine the appropriate conditions for L. monocytogenes inactivation (Table 1). The initial bacterial cell concentration was approximately 9.1 ± 0.2 log10 CFU/ml. After 20, 30, and 40 s of SAEW treatment at 1:9, 1:1, and 8:2 ratios, the population size was reduced by between 2.6 and 5.1 log10 CFU/ml and sublethally injured rate ranged from 36.90% to 90.00%. Preliminary experiments demonstrated that SAEW at a 9:1 ratio with bacteria resulted in minimal/negligible inactivation of L. monocytogenes (data not shown), which did not meet the initial bacterial population requirement for dilutions in the TTD experiments and was unfeasible for observing growth conditions of sublethally injured bacteria. Several studies have demonstrated that SAEW can effectively inactivate E. coli, S. aureus, and L. monocytogenes (Issa-Zacharia, Kamitani, Morita, & Iwasaki, 2010; Zeng et al. 2010). For instance, one study showed that a 30-s treatment with SAEW (ACC ¼ 21.2 ± 1.1 mg/l, pH 5.8 ± 0.09, ORP ¼ 948 ± 11 mV) at a 9:1 ratio with bacteria led to a reduction of E. coli and S. aureus populations by 3.9 and 2.8 log10 CFU/ml, respectively (Issa-Zacharia, Kamitani, Morita, et al., 2010), as compared to the reduction of 4.7 log10 CFU/ml in L. monocytogenes observed here. The number of sublethally injured bacteria determined from non-selective and selective medium (Table 1) were higher when cells were culture at a 1:9 ratio in SAEW as compared to other ratios. Better disinfection efficacy could probably induce appearing more injured bacteria. Data for surviving and sublethally injured populations of L.

The effects of SAEW and heat stress on the TTD of initial inoculum sizes (ranging from 2 to 5 log10 CFU/ml) at different recovery temperatures (10
C, 15
C, 25
C, and 30
C) were investigated (Fig. 1). TTD plots showed strong linear relationships with inoculum sizes (R2 > 0.98). The TTD of L. monocytogenes after SAEW treatments was longer than those after heat or no treatment at all recovery temperatures tested. It suggested that sublethally injured cells by SAEW require a relatively long time to recover, and that recovery temperature plays a significant role in this process. Various factors have been reported to influence the TTD of L. monocytogenes (DuPont & Augustin, 2009; Swinnen, Bernaerts, Dens, Geeraerd, & Van Impe, 2004); one study of the effects of nine common food-associated stresses encountered in the food industry (i.e., HCl, cold, lactic acid, chlorine, NaOH, NaCl, starvation, chloride, and heat) found that heat stress resulted in the greatest increase in TTD (Guillier et al., 2005). It has also been reported that general environmental factors such as temperature, pH, and water activity influenced the lag time of L. monocytogenes (Francois et al., 2005; 2006). In the present study, TTD inversely related to recovery temperature, while TTD increased to a greater degree by SAEW than by heat stress. 3.3. Lag time and growth rate under different temperature and stress conditions Lag time and growth rate of L. monocytogenes after SAEW and

Table 1 Surviving L. monocytogenes and sublethally injured rate after SAEW treatment for different times and ratio of bacteria to SAEW. Ratio of bacteria to SAEW

20 s

30 s

40 s

Non-selective medium (log10 CFU/ml)

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

Non-selective medium (log10 CFU/ml)

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

Non-selective medium (log10 CFU/ml)

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

1:9 1:1 8:2

4.6 ± 0.2a,B* 5.5 ± 0.1b,C 6.5 ± 0.0c,B

3.6 ± 0.1a,B 4.8 ± 0.1b,B 6.3 ± 0.0c,C

90.00 80.05 36.90

4.4 ± 0.3a,A,B 5.0 ± 0.2b,B 6.2 ± 0.1c,B

3.4 ± 0.1a,B 4.6 ± 0.2b,B 5.9 ± 0.1c,B

90.00 60.19 49.88

3.9 ± 0.1a,A 4.6 ± 0.2b,A 5.6 ± 0.3c,A

3.0 ± 0.1a,A 4.1 ± 0.1b,A 4.9 ± 0.1c,A

87.41 68.38 80.04

Note: Initial bacterial population was approximately 9.1 ± 0.2 log10 CFU/ml; SAEW parameters were ACC ¼ 30 mg/l, pH 6.3, and ORP ¼ 867.4 mV. *Values are the mean of triplicate measurements ±standard deviation; values with different lowercase letters in the same column and uppercase letters in the same row showed a significant difference at P < 0.05.

X.-T. Xuan et al. / Food Control 71 (2017) 17e25

21

Table 2 Surviving L. monocytogenes and sublethally injured rate after heat treatment for different times and at different temperatures. Temperature 3 min (
C) Non-selective medium (log10 CFU/ml) 50 55 60

7.8 ± 0.2c,C* 7.4 ± 0.1b,C 7.1 ± 0.1a,C

10 min

15 min

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

Non-selective medium (log10 CFU/ml)

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

Non-selective medium (log10 CFU/ml)

Selective medium (log10 CFU/ml)

Sublethally injured rate (%)

7.6 ± 0.0c,B 7.3 ± 0.1b,C 7.0 ± 0.1a,C

36.90 20.57 20.57

7.6 ± 0.0c,B 6.4 ± 0.1b,B 5.6 ± 0.2a,B

7.5 ± 0.0c,A 6.0 ± 0.1b,B 5.0 ± 0.3a,B

20.57 60.19 74.88

7.5 ± 0.1c,A 5.7 ± 0.0b,A 5.0 ± 0.1a,A

7.4 ± 0.1b,A 4.5 ± 0.1a,A 4.5 ± 0.2a,A

20.57 93.69 68.38

Note: Initial bacterial population was approximately 9.1 ± 0.2 log10 CFU/ml. *Values are the mean of triplicate measurements ±standard deviation; values with different lowercase letters in the same column and uppercase letters in the same row show a significant difference at P < 0.05.

Fig. 1. Effect of inoculum size (log10 I) on the time to detection (TTD) of SAEW and heat treated Listeria monocytogenes at different recovery temperatures of 30
C (A), 25
C (B), 15
C (C) and 10
C (D).

heat treatments at recovery temperatures of 10
C, 15
C, 25
C, and 30
C (Table 3) were estimated. Plots of lag time, growth rate and recovery temperature were shown in Fig. 2 with 95% confidence intervals. Lower m and longer l were observed at lower recovery temperature among SAEW, heat and control groups. The duration of l varied in the range of 3.339e4.954 h for control, 3.773e22.634 h for SAEW treatment, and 3.814 he30.199 h for heat treatment at recovery temperature from 30
C to 10
C. Results demonstrated that stresses had great impact on the l and larger l values was observed in sublethal-heat injured L. monocytogenes as compared to SAEW groups.

The rapid increase in lag time duration in response to increased stress level is in agreement with other reports (Francois et al., 2006;
oz-Cuevas et al., 2010; Vasseur et al., 1999). Guillier et al., 2005; Mun This trend was also observed for recovery temperature, which had a greater impact on sublethally injured L. monocytogenes. Guillier et al. (2005) has studied the effects of nine common food industry stresses (HCl, cold, lactic acid, NaOH, chlorine, starvation, NaCl, benzalkonium chloride (BAC) and heat) on the times to turbidity distribution (Td) of L. monocytogenes. Thereinto, the heat and BAC stresses induced the greatest increase of the mean of Td. Vasseur et al. (1999) found that lag time varied from 17.7 h at 55
C

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X.-T. Xuan et al. / Food Control 71 (2017) 17e25

Table 3 Growth parameters and h0 of L. monocytogenes after SAEW and heat treatment and recovery at 10
C, 15
C, 25
C, and 30
C. Stress

Control

SAEW

Heat

Recovery temperature (
C)

10 15 25 30 10 15 25 30 10 15 25 30

Growth rate (h1)

Lag time (h)

h0

Mean

SD

LCL

UCL

Mean

SD

LCL

UCL

Mean

SD

LCL

UCL

0.0521 0.0996 0.3059 0.4031 0.0465 0.0871 0.2981 0.3478 0.0507 0.1000 0.3072 0.3901

0.0021 0.0016 0.0029 0.0075 0.0016 0.0035 0.0079 0.0037 0.0011 0.0029 0.0033 0.0042

0.0472 0.0959 0.2990 0.3856 0.0427 0.0788 0.2794 0.3388 0.0482 0.0933 0.2992 0.3803

0.0569 0.1034 0.3129 0.4205 0.0503 0.0953 0.3167 0.3569 0.0532 0.1067 0.3151 0.3999

4.954 4.386 3.921 3.339 22.634 11.427 4.706 3.773 30.199 14.783 5.412 3.814

2.657 0.6202 0.114 0.173 2.807 1.885 0.3970 0.1070 1.589 1.110 0.141 0.109

1.173 2.956 3.651 2.941 15.997 6.969 3.767 3.511 26.532 12.223 5.080 3.562

11.083 5.816 4.191 3.739 29.272 15.886 5.645 4.036 33.865 17.343 5.745 4.067

0.3464 0.4841 1.2034 1.3653 1.1006 1.0539 1.4396 1.2495 1.5665 1.5541 1.6492 1.4958

0.2002 0.0590 0.4821 0.2848 0.2831 0.2602 0.2621 0.2519 0.3341 0.6414 0.0664 0.1466

0.0278 0.3903 1.1267 0.9122 0.6501 0.6398 1.0225 0.8487 1.0349 0.5336 1.5435 1.2625

0.6649 0.5780 1.2801 1.8186 1.5511 1.4680 1.8568 1.6503 2.0982 2.5747 1.7550 1.7290

Note: SD represents standard deviation; LCL is low 95% confidence limits; UCL is upper 95% confidence limits.

Fig. 2. Growth parameters (confidence interval) of L. monocytogenes after untreated (A), SAEW treatment (B) and heat treatment (C) and recovery at 10
C, 15
C, 25
C, and 30
C.

to 30.5 h at 63
C after heat shocks for 30 min (recovery temperature is 20
C) whereas the lag time is 9.3 h at 55
C after heat treatment for 10 min (recovery temperature is 15
C) in this manuscript. Francois et al. (2007) reported an increase in lag time which was also been linked to interactions between two or more factors. In addition, results determined that recovery temperature affected both lag time and growth rate, whereas stressors influenced lag time only. In this study, the population lag time of sublethally injured L.

monocytogenes has been estimated. However, foods can also be contaminated with low level of microorganism initially. For instance, the initial contamination numbers of Listeria monocytogenes are almost at 1/10 and 10/g level (Uyttendaele, De Troy, & Debevere, 1999; Uyttendaele, Neyts, Lips, & Debevere, 1997). The growth parameters of individual cells is more valuable than population cells because the single cell: (1) can shorten the lag time of population cells unexpectedly; (2) reflect the history of the cells; and (3) probably survive, recover and grow in a future environment

X.-T. Xuan et al. / Food Control 71 (2017) 17e25

23

treatments at recovery temperatures of 10
C, 15
C, 25
C, and 30
C were calculated and the bacteria behaviors under different stresses were observed and compared. Results displayed a different adaptation pattern of L. monocytogenes depending on the stresses. The maximum h0 parameter of L. monocytogenes was by heat treatment (1.4958e1.6492) while the control group showed the minimal h0 parameter (0.3464e1.3653). Based on the SAEW and heat experimental conditions in this study, the heat treatment showed higher inactivation efficacy and induced more sublethally injured bacteria compared with SAEW treatment. Hence, higher h0 parameter for heated L. monocytogenes with more sublethally injured bacteria were estimated in comparison with SAEW and control groups which was corresponding to the results of Zhou et al. (2011) that h0
oz et al. (2010) studied parameter increases with higher stress. Mun the effect of heat stress, pH and eugenol on the h0 and lag time of L. monocytogenes and found that an increase of h0 parameter from

Fig. 3. Correlation coefficients of SAEW and heat treatment for h0 parameter.

Table 4 Collinearity diagnosticsa of recovery temperature and growth parameters for h0 parameter.

% of variance 1 2 3 4 a

3.673 0.325 0.002 0

1.000 3.360 46.708 184.142

0 0 0.010 0.990

Growth rate (h1)

Recovery temperature (
C)

Dimension Eigen value Condition index Constant C

% of variance 0 0 0.140 0.860

T

Tolerance 0.004

T

VIF

T

Lag time (h)

% of variance m Tolerance m VIF m

262.042 0 0 0.440 0.560

0.008

% of variance l Tolerance l VIF l

128.750 0 0 0.040 0.960

0.022

46.221

Dependent variable is h0 parameter.

(such as storage, packaging etc.) (Baranyi, 2002). Francois et al. (2006) has investigated the effect of environmental parameters including temperature, pH and aw on the single cell lag period and
tris, George, Peck, and generation time of L. monocytogenes. Me Baranyi (2002, 2003) found that salt stress can also induce an increase in variation of lag time distribution of isolated L. monocytogenes cells. Therefore, conducting the quantitative microbiological risk assessment should also consider and incorporate predictive models for microbiological single or individual cell. 3.4. Analysis of h0 parameter The h0 parameters of L. monocytogenes after SAEW and heat

Fig. 4. Square root of the special growth rate of Listeria monocytogenes after SAEW and heat treatment as a function of recovery temperature.

3.23 to 3.74 h when heat treatments at 65
C for 25 s and 75 s. These results also supported that h0 parameter increases with higher stress. The correlation coefficients of stresses (SAEW and heat) for h0 parameter have been evaluated and illustrated in Fig. 3. According to the sensitivity analysis by tornado plots, the effects of different stresses on h0 parameter were compared. The correlation coefficient of SAEW treatment for h0 was 0.7181 which was higher than heat treatment (0.1337). Results indicated that SAEW treatment showed a higher influence on the h0 parameter of L. monocytogenes. Collinearity diagnostics allow a relativity evaluation of all the independent variables (recovery temperature, m, l) for dependent variable (h0 parameter) (Table 4). The statistical literature provide several quantifications of collinearity, with tolerance, VIF

Fig. 5. Square root of lag time of Listeria monocytogenes after SAEW and heat treatment as a function of recovery temperature.

24

X.-T. Xuan et al. / Food Control 71 (2017) 17e25

Table 5 Secondary model of growth parameters and validation. Growth parameters

Groups

Secondary model

RMSEa

MRE

MARE

Specific growth rate

Control SAEW Heat Control SAEW Heat

m ¼ (0.012 þ 0.021T)2 m ¼ (0.013 þ 0.020T)2 m ¼ (0.013 þ 0.021T)2 l ¼ 1/(0.005T þ 0.374)2 l ¼ 1/(0.018T þ 0.025)2 l ¼ 1/(0.021  0.021)2

0.0115 0.0273 0.0133 0.2297 1.3843 1.2632

0.0322 0.0094 0.0291 0.0003 0.0978 0.0182

0.0520 0.1014 0.0549 0.0425 0.1483 0.1384

Lag time

a

RMSE: root mean square error; MRE: median relative error; MARE: mean absolute relative error.

(reciprocal of tolerance), eigenvalue (how many distinct dimensions among the variables), condition index (the square root of the ratio of each eigenvalue to the smallest eigenvalue) and variance proportions (proportions of variance of estimate accounted for by each principal component associated with each eigenvalues). When all the independent variables with low tolerance and large VIF (>10) demonstrate that they have a collinearity. Several eigenvalues of dimensions close to 0 reveals that variables are highly correlated. When the condition index is greater than 15, it suggests a problem with collinearity. Moreover, large variances of independent variance indicate highly intercorrelation between them (Dormann et al., 2013; Liu, Kuang, Gong, & Hou, 2003). Table 4 displayed that VIF T (262.042), VIF m (128.750) and VIF l (46.221) were much larger than 10, the 3rd and 4th eigenvalues are close to 0 (0.002 and 0), condition indexes are more than 15 (46.708 and 184.142) and the various proportions of the variables (recovery temperature and lag time) are large (0.860 and 0.960). Therefore, results clearly indicated that there is collinearity between T, m and l. 3.5. Secondary model and validation The square root of the specific growth rate and lag time of L. monocytogenes showed linear and reciprocal relationships, respectively, with recovery temperature in the control, SAEW, and heat experiments (Figs. 4e5). To date, several secondary modelse.g., hyperbolic, polynomial, and square root-have been reported } (Aguirre, Gonzάlez, Ozcelik, Rodríguez, & García de Fernando, 2013; Guillier & Augustin, 2006; Ratkowsky, Olley, McMeekin, & Ball, 1982; Swinnen, Bernaerts, Dens, Geeraerd, & Van Impe, 2004; Standaert et al., 2007). A hyperbolic equation best describes the effects of various growth environments on L. monocytogenes lag phase (Standaert et al., 2007), whereas a square root model adequately described the effect of temperature on the growth rates of a wide range of bacteria (Ratkowsky et al., 1982). In the present study, the square root model was used to represent the relationship between recovery temperature and growth parameters. The reliability of secondary models for validation treatments was assessed based on RMSE, MRE, and MARE (Table 5). RMSE represents the discrepancy between predicted and observed values by evaluating the standard deviation of the differences between them. MRE is a measure of the mean difference between observed and predicted values, and MARE estimates the model prediction accuracy by measuring the degree of deviation between observed and predicted values. The secondary model in this study adequately predicted bacterial growth parameters. Predicted values for lag time upon SAEW and heat treatment showed greater divergence from measured values than those of other growth parameters, possibly because stressors alter the physiological state of bacteria, thereby increasing their heterogeneity and making it difficult to predict their behavior (Ross, Dalgaard, & Tienungoon, 2000). 4. Conclusions L. monocytogenes cells were sublethal injured by SAEW (ratio of

bacteria against SAEW of 8:2 for 30 s) and heat (55
C for 10 min) stress and similar surviving and sublethally injured L. monocytogenes populations were obtained in these experimental conditions. In this study, we confirmed that TTD method based on turbidometry would be a useful and straightforward method for estimating growth parameters. The duration of l varied in the range of 3.339e4.954 h for control, 3.773e22.634 h for SAEW treatment, and 3.814 he30.199 h for heat treatment at recovery temperature from 30
C to 10
C. The maximum h0 parameter of L. monocytogenes was obtained by heat treatment (1.4958e1.6492) while the control group showed the minimal h0 parameter (0.3464e1.3653). Results demonstrated that stresses had greater impact on the l and h0 parameters in comparison with recovery temperature while there was no great change in growth rate under isothermal conditions. Larger l values and h0 parameters were observed in sublethal-heat injured L. monocytogenes as compared to SAEW groups. Based on the sensitivity analysis of SAEW and heat treatments on h0 parameter, it indicated that SAEW treatment showed a higher influence. The collinearity diagnostics of independent variables (recovery temperature, m, l) for dependent variable (h0 parameter) demonstrated that T, m and l had strong collinearity. In addition, for SAEW, heat treated and untreated L. monocytogenes, the square roots of specific growth rate and lag time were linearly and reciprocally related, respectively, to recovery temperature. The reliability of secondary models was validated by RMSE, MRE, and MARE, with the results indicating good performances of the models. Acknowledgement The authors are grateful to Dr. Vijay K. Juneja and Mr. Zhao-Huan Zhang for their technical assistances. Also, the authors greatly appreciate the financial support by the National Natural Science Funds of China (grant no. 31401608) and Zhejiang Provincial Natural Science Foundation of China (grant no. LQ13C200001). References } Aguirre, J. S., Gonzάlez, A., Ozcelik, N., Rodríguez, M. A., & García de Fernando, G. D. (2013). Modeling the Listeria innocua micropopulation lag phase and its variability. International Journal of Food Microbiology, 164, 60e69. Al-Holy, M. A., & Rasco, B. A. (2015). The bactericidal activity of acidic electrolyzed oxidizing water against Escherichia coli O157:H7, Salmonella Typhimurium, and Listeria monocytogenes on raw fish, chicken and beef surfaces. Food Control, 54, 317e321. Augustin, J. C., Delattre, A. B., Rosso, L., & Carlier, V. (2000). Significance of inoculum size in the lag time of Listeria monocytogenes. Applied and Environmental Microbiology, 4, 1706e1710. Aureli, P., Fiorucci, G. C., Caroli, D., Novara, O., Lenonello, L., & Salmaso, S. (2000). An outbreak of febrile gastroenteritis associated with corn contaminated by Listeria monocytogenes. The New England Journal of Medicine, 342, 1236e1241. Baranyi, J. (2002). Stochastic modelling of bacterial lag phase. International Journal of Food Microbiology, 73, 203e206. Baranyi, J., & Pin, C. (1999). Estimating bacterial growth parameters by means of detection times. Applied and Environmental Microbiology, 65, 732e736. Baranyi, J., Roberts, T. A., & McClure, P. (1993). A non-autonomous differential equation to model bacterial growth. Food Microbiology, 10, 43e59. Bidlas, E., Du, T. T., & Lambert, R. J. W. (2008). An explanation for the effect of inoculum size on MIC and the growth/no growth interface. International Journal

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