Next Article in Journal
U.S. Consumers’ Tree Nut Food Safety Knowledge, Perceptions, and Handling Practices across Demographic Groups
Next Article in Special Issue
Evaluation of the Effectiveness of Aeration and Chlorination during Washing to Reduce E. coli O157:H7, Salmonella enterica, and L. innocua on Cucumbers and Bell Peppers
Previous Article in Journal
Evaluation of the Quality and Lipid Content of Artisan Sausages Produced in Tungurahua, Ecuador
Previous Article in Special Issue
Effects of Pomegranate Peel Extract and/or Lactic Acid as Natural Preservatives on Physicochemical, Microbiological Properties, Antioxidant Activity, and Storage Stability of Khalal Barhi Date Fruits
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Foods
Volume 12
Issue 23
10.3390/foods12234287
foods-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage

by
Avninder Kaur
1 and
Veerachandra Yemmireddy
1,2,*
1
School of Integrative Biological and Chemical Sciences, The University of Texas Rio Grande Valley, 1201 W University Dr, Edinburg, TX 78539, USA
2
School of Earth, Environmental and Marine Sciences, The University of Texas Rio Grande Valley, 1201 W University Dr, Edinburg, TX 78539, USA
*
Author to whom correspondence should be addressed.
Foods 2023, 12(23), 4287; https://doi.org/10.3390/foods12234287
Submission received: 20 September 2023 / Revised: 14 November 2023 / Accepted: 22 November 2023 / Published: 28 November 2023
(This article belongs to the Special Issue Novel Strategies for the Preservation of Fresh and Fresh-Cut Fruits and Vegetables)
Browse Figures
Versions Notes

Abstract

:
The effect of the pre-growth temperature of bacterial cultures on their subsequent survival kinetics in fresh-cut produce during refrigerated storage was investigated in this study. Three-strain cocktails of Listeria monocytogenes and Salmonella enterica, cultured at different growth temperatures (4, 21, and 37 °C) were inoculated on fresh-cut mixed salad and on individual produce in the mixed salad. The inoculated samples were stored at 4 °C and 80 ± 2% relative humidity (RH) for up to 72 h and the growth, survival, or death kinetics were determined at regular intervals. The results indicate that depending upon the type of pathogen tested, the pre-growth temperature(s) and the type of produce showed a significant (p ≤ 0.05) effect on the survival kinetics. Among the tested produce, mixed salad showed the highest reduction in L. monocytogenes pre-grown at 37 °C (1.33 log CFU/g) followed by red cabbage (0.56 log CFU/g), iceberg lettuce (0.52 log CFU/g), and carrot (−0.62 log CFU/g), after 72 h, respectively. In the case of Salmonella, carrot showed the highest reduction (1.07 log CFU/g for 37 °C pre-grown culture) followed by mixed salad (0.78 log CFU/g for 37 °C pre-grown culture), cabbage (0.76 log CFU/g for 21 °C pre-grown culture), and lettuce (0.65 log CFU/g for 4 °C pre-grown culture), respectively. Among the tested ComBase predictive models, the Baranyi–Roberts model better fitted the experimental data. These findings indicate that the appropriate selection of pre-growth environmental conditions is critical to better understand the kinetics of foodborne pathogens.

1. Introduction

Leafy greens are a vital source of vitamins, minerals, dietary fiber, and phytonutrients and are attributed to lowering the risk of several chronic diseases such as diabetes, obesity, cardiovascular disease, hypertension, and cancer [1,2,3]. In the recent past, the demand for fresh, convenient, preservative-free, minimally processed, and health-promoting foods such as fresh-cut fruits and ready-to-eat (RTE) mixed salads [4,5,6] has increased. However, fresh-cut produce is prone to rapid deterioration due to moisture loss, accelerated enzymatic activity, and microbial proliferation [7,8,9]. Moreover, leafy greens have been implicated in several foodborne illness outbreaks [10,11,12]. Foodborne bacterial pathogens such as Listeria monocytogenes [13,14,15] and Salmonella [11,16,17] are associated with multiple illness outbreaks in fresh and fresh-cut produce.
Listeria monocytogenes is of particular concern in RTE salad mix due to its ability to grow in aerobic or anaerobic environments as well as at refrigeration temperatures [18,19,20]. In 2021, a multi-state outbreak of packaged salads was attributed to a contamination of L. monocytogenes [21]. Many studies have determined the survival kinetics of foodborne pathogens in fresh produce and fresh-cut salad during storage under different conditions, and found that depending upon storage conditions, few commodities supported the growth and proliferation of pathogens, while others were not very supportive. Studies have revealed that nutrients released from the exposed cytoplasm of cut fresh produce enable the proliferation and growth of foodborne pathogens [22,23]. A study by Waitt et al. [24] reported that a storage temperature of 12 °C increased Salmonella levels on lettuce roots and leaves, while 4 °C did not support the growth. Similarly, Lee et al. [25] reported that populations of E. coli O157:H7, S. enterica, and L. monocytogenes increased rapidly in red cabbage juice when stored at 10 °C for 72 h. A few studies have reported an increase in levels of L. monocytogenes by 1.5 (at 8 °C) and 2.3 (at 12 °C) log CFU/g in iceberg lettuce [26]; 3.02 log CFU/g in salad mixes of lettuce, cucumber, tomato, carrot, and red cabbage [27]; 1.85 (arugula), 0.88 (spinach), 0.51 (green salad), 0.49 (escarole), 0.30 (collard green), and 0.21 (watercress) log CFU/g at 7 °C [28]; and 1.4 (broccoli) and 1.6 (cauliflower) log CFU/g at 4 °C [29]; while other studies have reported a reduction in L. monocytogenes by 3 (Arabic salad at 4 °C), 2.3 (tahini salad at 4 °C), 3.3 (basil at 21 °C), 2.4 (cilantro at 21 °C), 2.6 (dill at 21 °C), 3.2 (parsley at 21 °C), and 3.61 (carrots at 7 °C) log CFU/g during storage [28,30,31]. Huang et al. [32] reported a decrease in S. enterica levels on cantaloupe, watermelon, and radish when stored at 4 °C for 7 days, while S. enterica levels on pineapple did not change under the same conditions. López-Gálvez et al. [33] and Singh and Yemmireddy [34] reported the effect of storage relative humidity on the survival characteristics of S. enterica on lettuce and fresh-cut papaya, respectively. Studies have also reported that the presence of antilisterial phytoalexins in carrots inhibited the growth of L. monocytogenes [14,35,36]. Huang et al. (2019) [32] concluded that cut radish hindered bacterial growth due to its antibacterial properties, whereas its juice supported the growth of Salmonella and L. monocytogenes. This shows that factors such as the type of pathogen, type of fresh produce, storage time, temperature, and relative humidity have a profound effect on the growth, survival, and death kinetics of foodborne bacterial pathogens [37,38,39].
A careful analysis of the past research work on fresh-cut produce reveals two important aspects: (i) the evaluation of microbial growth, survival, and death kinetics using cells that were grown or cultured under ideal laboratory conditions; (ii) the development, validation, and verification of interventions based on the perceived kinetics data from an earlier point. These scenarios are far from real-life conditions where microbes are constantly exposed to various environmental stresses such as stable and dynamic temperatures, relative humidity, pH, desiccation, salt stress, etc. These stressors either increase or decrease the susceptibility of respective organisms. Often the importance of key methodological aspects while designing post-harvest storage studies such as bacterial-strain characteristics, inoculum preparation, recovery, and enumeration or detection procedures is overlooked and lacks uniformity. Bolten et al. [40] emphasized these aspects in their scoping review on the population dynamics of Listeria spp., Salmonella spp., and E. coli on fresh produce in pre-harvest and post-harvest environments. Limited information exists on the effect of pre-growth environmental stresses on the survival kinetics of foodborne pathogens on food matrices. Harrand et al. [41] observed the effect of pre-growth conditions on the growth of Listeria and E. coli on select fresh fruits and vegetables. Similarly, L. monocytogenes when subjected to pre-growth stresses showed less reductions upon exposure to different chemical treatments than S. enterica and E. coli O157:H7 [34]. However, the effect of different pre-growth conditions on the fate of L. monocytogenes and Salmonella enterica in fresh-cut salad in a simulated real-world storage scenario is not well understood. Particularly, in pre-harvest, post-harvest, and distribution stages, fresh produce and associated microflora may be subject to varying temperature stresses. Thus, the main objective of this study was to determine the effect of pre-growth temperature on the growth, survival, and/or death kinetics of L. monocytogenes and Salmonella enterica in fresh-cut salad vegetables during simulated retail refrigerated storage. This information would help to better understand the population dynamics of foodborne bacterial pathogens and develop more robust food safety intervention strategies.

2. Methodology

2.1. Selection of Bacterial Strains

A three-strain cocktail of L. monocytogenes (i. F8027, serotype 4b, celery isolate; ii. 101 M, serotype 4b, beef-associated outbreak isolate; and iii. F8385, serotype 1/2b, carrot isolate) and a three-strain cocktail of nalidixic-acid-adopted Salmonella enterica (i. Newport 11,590 K, beef isolate; ii. Poona A3279, cantaloupe-associated outbreak; and iii. St. Paul E20081236, jalapeno outbreak) were used as test pathogens. The cocktail inoculums of individual bacterial types were chosen over individual strains to identify population dynamics in worst-case scenarios. All the Salmonella strains were modified for antibiotic resistance with 0.05 g L−1 nalidixic acid (NA; Fisher Scientific, Fair Lawn, NJ, USA) using a continuous stepwise exposure [42]. The stocks of all the strains containing tryptic soy broth (TSB, Hardy diagnostics, Santa Maria, CA, USA) and 25% glycerol (wt/wt) were stored at −80 °C. The frozen stocks of selected strains were thawed at room temperature in a biosafety cabinet and activated by transferring a loopful of inoculum into 10 mL tryptic soy broth with 0.1% yeast extract (TSBY) for L. monocytogenes and 10 mL of tryptic soy broth with nalidixic acid (TSBN). These cultures were then grown under different temperature conditions as discussed below.

2.2. Growing Bacterial Cultures and Inoculum Preparation

Individual strains of selected bacteria were grown under three different temperatures, 37, 21, and 4 °C, to represent different real-world scenarios. Briefly, (i) strains of S. enterica and L. monocytogenes were grown in TSBN and TSBY, respectively, at 37 °C and 200 rpm in a shaker incubator for up to 18 h. This condition is referred to as the common laboratory growth conditions followed in many studies. (ii) Cells were grown at 21 °C for up to 36 ± 2 h reflecting growth at room temperature, and (iii) cells were grown at 37 °C for 8 h to increase the cell numbers initially and then adopted at 4 °C to reflect refrigerated storage for up to 40 h to achieve the desired working concentration of 107−8 CFU/mL bacterial cells. Afterward, an equal volume (5 mL) of each individual strain in each category was mixed to prepare the three-strain cocktails, which were harvested by centrifuging at 4000× g for 10 min (5920R, EppendorfTM, Hamburg, Germany). The resultant pellet(s) was/were resuspended in 10 mL of 0.1% buffered peptone water (BPW, Hardy diagnostics, Santa Maria, CA, USA), and serial dilutions were performed in BPW to achieve a working concentration of 106 CFU/mL. Cell concentrations were confirmed by plating 100 µL portions of the appropriate serial dilutions on selective media Oxford agar (Listeria) and xylose lysine deoxycholate supplemented with 0.05 g L−1 nalidixic acid agar (XLDN; Salmonella) plates and incubation at 37 °C for 24 h.

2.3. Sample Preparation, Inoculation, and Storage

Fresh iceberg lettuce (Lactuca sativa cv capitata), red cabbage (Brassica oleracea cv capitata f. rubra), and carrot (Daucus carota) were purchased from the local retail store (McAllen, TX, USA) and stored at 4 °C for use in experiments within 24 h. After removing the outer 2–3 layers of lettuce and cabbage, all the vegetables were thoroughly rinsed with deionized water and air-dried in a biosafety cabinet at room temperature. The dried lettuce and cabbage were aseptically chopped to a desirable size (5 cm length × 2 cm width), and the carrots were grated as shown in Figure 1. A 50 g sample(s) weighed in stomacher bags (Whirl-Pak™, Pleasant Prairie, WI, USA) and an aliquot of 5 mL of inoculum was/were added to each individual bag. The bags were thoroughly mixed by shaking and gentle massaging for about 2 min to achieve a uniform distribution of the inoculum of each sample. The individual batches of inoculated samples were pooled together in a sterile tray (250 g total sample size for each produce item) and mixed again using a sterile spatula. For the mixed-salad samples, 70:20:10 (wt %) of iceberg lettuce, red cabbage, and carrot were mixed and then followed the inoculation procedure as described above. All the samples were air-dried in a biosafety cabinet for 1 h, and portions of 25 g were weighed in 20 Oz clam-shell boxes (Dart, Troy, MI, USA) and then stored in an environmental chamber (Forma 3900 Series, Thermo Scientific™, Waltham, MA, USA) at 4 °C and 80 ± 2% RH (Figure 1) to simulate retail storage conditions. Appropriate control samples inoculated with just sterile deionized water and subjected to the same treatment conditions were also included. Samples were collected at regular intervals (0, 12, 24, 48, and 72 h), and the viability of test pathogens (both on the treatment and control samples) and spoilage organisms (only on control samples) were enumerated.

2.4. Enumeration

For each sampling time, an aliquot of samples (10 g) was collected from the clam-shell containers and transferred to Whirl-pak™ bags containing 90 mL (1:9 w/v) of 0.1% BPW. These samples were homogenized using a stomacher (Model 400 Seward™, Seward, NE, USA) for 2 min at 200 rpm. Appropriate serial dilutions of the samples were prepared in BPW and plated on Oxford agar (for L. monocytogenes) and XLDN (for Salmonella) in duplicates. The plates were incubated at 37 °C for 24 ± 2 h, and the surviving cells were reported as log CFU/g. The rate of spoilage during storage caused by yeast and mold and the aerobic plate count (APC), were determined using 3M Petrifilms (3M™, St. Paul, MN, USA) following the manufacturer’s instructions.

2.5. Modeling Survival Kinetics

ComBase predictive models were assessed to determine the models that best fit the experimental data using the Online DMFit tool. The data were analyzed using Baranyi and Roberts [43] and linear models to determine the predictive power of these models.

2.6. Statistical Analysis

All the experiments were conducted in triplicate, and duplicate samples were included in each replicated experiment. The CFU data were transformed into log CFU/g and arranged to conduct statistical analysis by comparing the results within the same commodity and across different commodities during storage for different pre-growth temperature conditions. Data were analyzed by the analysis of variance (ANOVA) procedure using SPSS™ (Version 28, IBM®, Armonk, NY, USA). A Tukey’s multiple comparison test was performed to determine the mean differences. All the tests were performed with a 0.05 level of significance.

3. Results and Discussion

3.1. Effect of Pre-Growth Temperature on the Survival Kinetics of L. monocytogenes

Figure 2 shows the survival kinetics of L. monocytogenes that were pre-cultured at 37 (Figure 2a), 21 (Figure 2b), and 4 (Figure 2c) °C, respectively, and subsequently inoculated on different types of fresh-cut produce (i.e., iceberg lettuce, red cabbage, and grated carrot) and mixed salad during simulated retail storage for 72 h at 4 °C and 80 ± 2% RH. The results indicate that both factors, the culture pre-growth temperature and the type of produce, have a significant (p ≤ 0.05) effect on the survival kinetics of L. monocytogenes. When L. monocytogenes was pre-cultured in nutrient-rich media under normal laboratory growth conditions at 37 °C and subsequently inoculated on carrot, it showed a slight increase in its levels (p > 0.05), while the other produce items, lettuce, red cabbage, and mixed salad, showed a decrease in its levels (p ≤ 0.05) at the end of 72 h storage (Figure 2a). At the end of refrigerated storage, the levels of L. monocytogenes on the mixed salad were significantly (p ≤ 0.05) lower when compared to red cabbage or iceberg lettuce and grated carrot alone. A decrease of 1.33 log CFU/g was observed in the case of mixed salad followed by 0.56 log CFU/g (red cabbage) and 0.52 log CFU/g (iceberg lettuce), respectively. However, no significant (p > 0.05) change in the levels of L. monocytogenes was observed in the case of grated carrot. These findings can be attributed to two main factors: (i) the ability of L. monocytogenes to survive at refrigerated temperatures and (ii) the physical condition and/or chemical properties of the tested produce and its interaction with L. monocytogenes. It is understandable that L. monocytogenes is able to survive at low storage temperatures due to its psychotropic properties. However, the type of produce and storage time were found to be rate limiting factors.
Most previous studies have used bacteria that were cultured at ideal laboratory growth conditions of 37 °C in nutrient-rich media. However, increasing evidence shows that pre-growth environmental conditions affect the tolerance, growth, and survival kinetics of pathogens [34,41]. Thus, we investigated the survival kinetics of L. monocytogenes when subjected to different (21 and 4 °C) pre-growth temperatures than the earlier-mentioned 37 °C. In our study, relative humidity was also included as an additional factor to best simulate the survival kinetics of L. monocytogenes in tested produce during short-term retail or consumer storage. When using the L. monocytogenes cells that were pre-cultured at 21 °C, irrespective of the type of produce, no significant (p > 0.05) change in their levels was observed during storage (Figure 2b). Non-significant fluctuations across all the produce types were noticed for the first 24 h (Figure 2a,b). This can be attributed to the adjustment of cells to new environmental conditions during subsequent storage at the refrigerated temperature (4 °C) compared to their prior culturing and growth temperatures of 37 and 21 °C, respectively. Further decreasing the culture growth temperature to 4 °C and the subsequent inoculation on different produce showed almost a similar trend as cells that were pre-cultured at 21 °C (Figure 2c). Thus, L. monocytogenes which was pre-cultured at 37, 21, and 4 °C showed an overall reduction of 1.33, 0.8, and 0.87 log CFU/cm2, respectively, on mixed salads, while on grated carrot, it showed a growth of 0.62, 050, and 0.45 log CFU/cm2, respectively. These respective reductions on mixed salad and/or growth on carrot significantly differ from other tested produce (i.e., lettuce and red cabbage) under the same test conditions. However, the changes were not significantly different within the same produce (mixed salad/carrot) across different pre-growth conditions. One possible reason for the growth on carrots could be due to the oxidation of phenolic compounds in shredded carrots which reduced its potential antimicrobial activity. The antioxidant activity of fresh produce can also be reduced by its direct oxidation by polyphenol oxidase and peroxidase enzymes [44].
Studies have reported that minimally processed fresh-cut or grated vegetables facilitate the attachment and further survival of pathogens due to the release of nutrients to nourish the attached bacteria, which aids their proliferation [19,23,45] or death due to the release of antimicrobial compounds such as phytochemicals and the presence of natural microbiota [46,47,48]. Carrasco et al. [49] reported a 3 log CFU/g increase in an L. monocytogenes population in RTE lettuce after storage at 13 °C for 7 days. On the other hand, studies have reported that cut red cabbage at low temperatures did not support the growth of L. monocytogenes [50] and Salmonella [14], respectively. Red cabbage is a rich source of antioxidants such as anthocyanins, glucosinolates, and sulfur compounds such as methyl methanethiosulfinate, known to have inhibitory effects on foodborne pathogens [51,52,53,54]. Similarly, the inhibitory effect of grated or cut carrots on L. monocytogenes [25,36] and S. typhimurium [55] was reported. Additionally, phenolic phytoalexins such as 6-methoxymellein present in carrot [55] and red cabbage have the ability to change the permeability of microbial cell membranes, which can result in the leakage of cellular content, the denaturation or inhibition of crucial metabolic enzymes, and ultimately death [53,56]. In fresh carrot juice, carotol (20.20%) and sabinene (12.80%) were found to be major constituents exhibiting inhibitory effects on Gram-positive and Gram-negative bacteria [35]. A study by Demirdoven et al. [51] reported the extracted total anthocyanin value as 593 mg/L and total phenolic acid content as 16,320 mg/L in red cabbage samples. A similar metabolic-profiling study reported a total phenolic content (majorly composed of rutin, quercetin, and catechin) of 1114.60 μg/g and sixteen anthocyanins in red Chinese cabbage showing a positive correlation to pathogenic growth inhibition [57]. In the current study, no significant difference in the levels of L. monocytogenes was observed between iceberg lettuce and red cabbage (Figure 2). This can be potentially attributed to limited or no exposure to the available phytochemicals in red cabbage and grated carrot within the tested short-term retail storage period to potentially exert a significant reduction as noticed in previous studies. As per our observation, inoculated fresh-cut red cabbage (Figure 1B) looked dry in appearance after air-drying and during refrigerated storage with no signs of damage and exposure to intracellular components. The level of reductions that were observed in mixed salad when cells were pre-grown at 37 °C was not maintained when cells were pre-grown at temperatures of 21 and 4 °C. This shows that pre-growth environmental conditions in addition to time and temperature are critical factors that affect the growth, survival, and/or death kinetics of L. monocytogenes on fresh-cut salad during refrigerated storage. Depending upon the type of produce, L. monocytogenes was found to better survive when pre-growth culture temperatures were 4 or 21 °C compared to the commonly used culture growth temperature of 37 °C. To further understand the effect of the type of pathogen and its dependence on the culture growth temperature, follow-up studies were conducted on S. enterica.

3.2. Effect of Pre-Growth Temperature on the Survival Kinetics of S. enterica

Figure 3 shows the survival kinetics of S. enterica pre-cultured at 37 (Figure 3a), 21 (Figure 3b), and 4 (Figure 3c) °C, respectively, and subsequently inoculated on different types of produce during simulated retail storage at 4 °C and 80% RH for up to 72 h. Unlike L. monocytogenes, pre-growth temperature and the type of produce did not show a significant (p > 0.05) effect on the survival kinetics of Salmonella. Within the same produce type, Salmonella levels neither increased nor decreased during the storage time (Figure 3a–c). In general, red cabbage showed the lowest survival rate when compared to other tested produce. A study by Vandamm et al. [58] reported the −0.15 log CFU/g growth of Salmonella on cut celery stored in containers at 4 °C for 7 days. Harrand et al. [41,59] reported that pre-growth conditions such as 37 °C, 21 °C, low pH, high salt, and a minimal medium had varying effects on S. enterica, E. coli, and Listeria when tested on lettuce, cantaloupe rind, and tomatoes. As per their study, depending upon the pre-growth condition tested, E. coli showed an overall decline (<1 log) over a 7-day period, while S. enterica and Listeria showed regrowth after an initial reduction. Similarly, the findings of our study indicate that S. enterica and L. monocytogenes levels showed a slight decline initially for certain produce items and afterward either survived or declined (<1.5 log) during the short-term refrigerated storage (Figure 2 and Figure 3). This could potentially be attributed to a range of adaptive mechanisms of the bacteria to adjust to different environmental conditions. Thakur et al. [60] explained the possible mechanisms of adaptations by differential gene expression in pathogens under adverse environmental conditions. The presence of transcription factors, such as sigma factors, is responsible for the transcription of genes involved in the resistance to diverse stresses [61]. A study reported that Salmonella Enteritidis upregulates the genes involved in the resistance to heat (rpoH, uspB, and htrA), cold (cspA, cspC, and csdA), acid (SEN1564A and cfa), and salt (proP, proV, and osmW) [62]. However, further studies need to be conducted to understand the possibility of these mechanisms under the conditions tested in the current study.

3.3. Determination of Aerobic Plate Count (APC), Yeast, and Mold during Storage

Table 1 shows the APC and yeast and mold counts on the iceberg lettuce, red cabbage, grated carrot, and mixed-salad samples during refrigerated storage for 72 h. No significant (p > 0.05) change in the APC was observed during storage within and across the different produce tested. Red cabbage was comparatively found to have a lower APC, though it was not statistically different from the other produce at the end of 72 h. A study by Nagarajan et al. [63] reported low APC levels in red cabbage, and this was attributed to the activity of antimicrobial polyphenolic oxidases. Yeast counts were found to be higher than the APC. Similarly, a higher mold count was observed in shredded carrot (1.13 log CFU/g) and mixed salad (1.04 log CFU/g) by the end of the storage period. Similarly, an increase in yeast (4.1 log CFU/g) and mold (3.85–6.7 log CFU/g) count was reported on spinach leaves when stored at 5 °C [64]. As per our observation, the tested produce maintained its freshness during the storage period, and no visual deterioration and quality changes were observed. As such, the effect of naturally present microbiota on the survival kinetics of pathogens in the tested produce is beyond the scope of the current study; however, it is a key factor that should not be overlooked. Typically, fruits and vegetables carry naturally present microbiota such as Pseudomonas spp., Erwinia herbicola, Flavobacterium, Xanthomonas, and Enterobacter, as well as various yeasts and molds [22,65]. Lactic-acid bacteria such as Lactobacillus spp. and other natural microbiota can exhibit antagonistic properties against pathogens [66,67]. In our study, we tried to deduce the potential relationship between pathogenic (L. monocytogenes, S. enterica) and spoilage organisms (APC, Y&M), but the data were just not sufficient to provide any conclusive details.

3.4. Modeling the Survival Kinetics of L. monocytogenes and S. enterica

Table 2 shows the parameter estimates of L. monocytogenes and S. enterica when pre-cultured at different temperatures and subsequently inoculated onto fresh-cut produce including mixed fresh-cut salad during refrigerated storage. The experimental data were tested to check the goodness of fit using ComBase predictive models and the DMFit online tool. Among the different models in the tool, both the Baranyi and Roberts and linear models fitted the data. However, the Baranyi and Roberts model (with no lag) in the majority of cases better fitted the data (R2 ranging from 0.054 to 0.967 for L. monocytogenes and 0.194 to 0.994 for S. enterica) with a lower standard error of fit when compared to linear models (Supplementary Materials). Under the tested conditions, the maximum inactivation rates ranged from −0.0296 ± 0.00845 (for L. monocytogenes grown at 37 °C on mixed salad) to −0.00772 ± 0.0106 (for L. monocytogenes grown at 21 °C on iceberg lettuce). In the case of Salmonella, the maximum inactivation rates ranged from −0.0328 ± 0.00718 (for cells grown at 4 °C on carrot) to −0.00796 ± 0.00791 (for cells grown at 37 °C on red cabbage). It should be noted that the calculated standard error rates are greater than or almost equal to the actual growth or inactivation rates. This could be attributed to the limited availability of experimental data during the short-term storage period. Further studies involving longer storage periods and more produce categories are warranted to better understand the effect of pre-growth temperatures on the survival kinetics of tested pathogens.

4. Conclusions

This study investigated the effect of different pre-growth temperatures, 37, 21, and 4 °C on the subsequent growth, survival, and/or death kinetics of L. monocytogenes and S. enterica in fresh-cut produce during short-term simulated retail or consumer refrigerated storage conditions. Among the tested produce, mixed salad supported less the growth of L. monocytogenes but showed no effect on S. enterica. However, when pre-growth temperatures were changed to 21 and 4 °C, L. monocytogenes was found to be not affected (<1 log reduction), even in the mixed salad. Both S. enterica and L. monocytogenes, irrespective of pre-growth temperatures, survived well (<0.6 log reduction) in iceberg lettuce, red cabbage, and grated carrot during refrigerated storage. The findings of this study highlight the importance of considering the effect of appropriate pre-growth environmental conditions on the subsequent microbial survival kinetics in fresh-cut produce. This type of data would help to better estimate the risk in real-world scenarios and to develop robust interventions. Further studies should be focused on investigating the effect of other environmental stresses and the role of naturally present microbiota on the survival kinetics of foodborne pathogens across different fresh-cut produce commodities.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/foods12234287/s1.

Author Contributions

Conceptualization, V.Y. and A.K.; methodology, V.Y. and A.K.; formal analysis, A.K.; investigation, A.K.; resources, V.Y.; data curation, V.Y.; writing—original draft preparation, A.K.; writing—review and editing, V.Y.; visualization, V.Y.; supervision, V.Y.; project administration, V.Y.; funding acquisition, V.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the College of Sciences, University of Texas Rio Grande Valley startup funds, and University of Texas System Rising STARs Award to Veerachandra Yemmireddy.

Data Availability Statement

The data used to support the findings of this study can be made available by the corresponding author upon request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Boeing, H.; Bechthold, A.; Bub, A.; Ellinger, S.; Haller, D.; Kroke, A.; Leschik-Bonnet, E.; Müller, M.J.; Oberritter, H.; Schulze, M.; et al. Critical review: Vegetables and fruit in the prevention of chronic diseases. Eur. J. Nutr. 2012, 51, 637–663. [Google Scholar] [CrossRef] [PubMed]
  2. Zhang, Y.J.; Gan, R.Y.; Li, S.; Zhou, Y.; Li, A.N.; Xu, D.P.; Li, H.B. Antioxidant Phytochemicals for the Prevention and Treatment of Chronic Diseases. Molecules 2015, 20, 21138–21156. [Google Scholar] [CrossRef] [PubMed]
  3. Aune, D. Plant Foods, Antioxidant Biomarkers, and the Risk of Cardiovascular Disease, Cancer, and Mortality: A Review of the Evidence. Adv. Nutr. 2019, 10 (Suppl. S4), S404–S421. [Google Scholar] [CrossRef] [PubMed]
  4. Miranda, J.M.; Mondragón, A.C.; Lamas, A.; Roca-Saavedra, P.; Ibarra, I.S.; Rodriguez, J.A.; Cepada, A.; Franco, C.M. Effect of Packaging Systems on the Inactivation of Microbiological Agents. In Antimicrobial Food Packaging; Academic Press: Cambridge, MA, USA, 2016; pp. 107–116. [Google Scholar]
  5. Miceli, A.; Settanni, L. Influence of agronomic practices and pre-harvest conditions on the attachment and development of Listeria monocytogenes in vegetables. Ann. Microbiol. 2019, 69, 185–199. [Google Scholar] [CrossRef]
  6. Almenar, E. Innovations in packaging technologies for produce. In Controlled and Modified Atmospheres for Fresh and Fresh-Cut Produce; Academic Press: Cambridge, MA, USA, 2020; pp. 211–264. [Google Scholar]
  7. Francis, G.A.; Gallone, A.; Nychas, G.J.; Sofos, J.N.; Colelli, G.; Amodio, M.L.; Spano, G. Factors affecting quality and safety of fresh-cut produce. Crit. Rev. Food Sci. Nutr. 2012, 52, 595–610. [Google Scholar] [CrossRef] [PubMed]
  8. Yousuf, B.; Deshi, V.; Ozturk, B.; Siddiqui, M.W. Fresh-cut fruits and vegetables: Quality issues and safety concerns. In Fresh-Cut Fruits and Vegetables; Academic Press: Cambridge, MA, USA, 2020; pp. 1–15. [Google Scholar]
  9. Botondi, R.; Barone, M.; Grasso, C. A Review into the Effectiveness of Ozone Technology for Improving Safety and Preserving the Quality of Fresh-Cut Fruits and Vegetables. Foods 2021, 10, 748. [Google Scholar] [CrossRef] [PubMed]
  10. Callejón, R.M.; Rodríguez-Naranjo, M.I.; Ubeda, C.; Hornedo-Ortega, R.; Garcia-Parrilla, M.C.; Troncoso, A.M. Reported foodborne outbreaks due to fresh produce in the United States and European Union: Trends and causes. Foodborne Pathog. Dis. 2015, 12, 32–38. [Google Scholar] [CrossRef] [PubMed]
  11. Carstens, C.K.; Salazar, J.K.; Darkoh, C. Multistate Outbreaks of Foodborne Illness in the United States Associated with Fresh Produce from 2010 to 2017. Front. Microbiol. 2019, 10, 2667. [Google Scholar] [CrossRef]
  12. Irvin, K.; Viazis, S.; Fields, A.; Seelman, S.; Blickenstaff, K.; Gee, E.; Wise, M.E.; Marshall, K.E.; Gieraltowski, L.; Harris, S. An Overview of Traceback Investigations and Three Case Studies of Recent Outbreaks of Escherichia coli O157:H7 Infections Linked to Romaine Lettuce. J. Food Prot. 2021, 84, 1340–1356. [Google Scholar] [CrossRef] [PubMed]
  13. Zhu, Q.; Gooneratne, R.; Hussain, M.A. Listeria monocytogenes in Fresh Produce: Outbreaks, Prevalence and Contamination Levels. Foods 2017, 6, 21. [Google Scholar] [CrossRef]
  14. Alegbeleye, O.; Sant’Ana, A.S. Survival and growth behavior of Listeria monocytogenes in ready-to-eat vegetable salads. Food Control 2022, 138, 109023. [Google Scholar] [CrossRef]
  15. Gu, G.; Kroft, B.; Lichtenwald, M.; Luo, Y.; Millner, P.; Patel, J.; Nou, X. Dynamics of Listeria monocytogenes and the microbiome on fresh-cut cantaloupe and romaine lettuce during storage at refrigerated and abusive temperatures. Int. J. Food Microbiol. 2022, 364, 109531. [Google Scholar] [CrossRef] [PubMed]
  16. Wadamori, Y.; Gooneratne, R.; Hussain, M.A. Outbreaks and factors influencing microbiological contamination of fresh produce. J. Sci. Food Agric. 2017, 97, 1396–1403. [Google Scholar] [CrossRef] [PubMed]
  17. Glaize, A.; Young, M.; Harden, L.; Gutierrez-Rodriguez, E.; Thakur, S. The effect of vegetation barriers at reducing the transmission of Salmonella and Escherichia coli from animal operations to fresh produce. Int. J. Food Microbiol. 2021, 347, 109196. [Google Scholar] [CrossRef] [PubMed]
  18. Pereira, S.A.; Alves, Â.; Ferreira, V.; Teixeira, P.C.M. The impact of environmental stresses in the virulence traits of Listeria monocytogenes relevant to food safety. In Listeria monocytogenes; Intechopen: London, UK, 2018; Volume 89. [Google Scholar]
  19. Smith, A.; Moorhouse, E.; Monaghan, J.; Taylor, C.; Singleton, I. Sources and survival of Listeria monocytogenes on fresh, leafy produce. J. Appl. Microbiol. 2018, 125, 930–942. [Google Scholar] [CrossRef]
  20. Ly, V.; Parreira, V.R.; Farber, J.M. Current understanding and perspectives on Listeria monocytogenes in low-moisture foods. Curr. Opin. Food Sci. 2019, 26, 18–24. [Google Scholar] [CrossRef]
  21. CDC. 2021. Available online: https://www.cdc.gov/listeria/outbreaks/packaged-salad-mix-12-21/details.html (accessed on 20 November 2022).
  22. Qadri, O.S.; Yousuf, B.; Srivastava, A.K. Fresh-cut fruits and vegetables: Critical factors influencing microbiology and novel approaches to prevent microbial risks—A review. Cogent Food Agric. 2015, 1, 1121606. [Google Scholar] [CrossRef]
  23. Jideani, A.I.; Anyasi, T.A.; Mchau, G.R.; Udoro, E.O.; Onipe, O.O. Processing and preservation of fresh-cut fruit and vegetable products. In Postharvest Handling; IntechOpen: London, UK, 2017; Volume 47. [Google Scholar]
  24. Waitt, J.A.; Kuhn, D.D.; Welbaum, G.E.; Ponder, M.A. Postharvest transfer and survival of Salmonella enterica serotype enteritidis on living lettuce. Lett. Appl. Microbiol. 2014, 58, 95–101. [Google Scholar] [CrossRef]
  25. Lee, S.; Han, A.; Yoon, J.H.; Lee, S.Y. Growth evaluation of Escherichia coli O157: H7, Salmonella typhimurium, and Listeria monocytogenes in fresh fruit and vegetable juices via predictive modeling. LWT 2022, 162, 113485. [Google Scholar] [CrossRef]
  26. Tucci, P.; Centorotola, G.; Salini, R.; Iannetti, L.; Sperandii, A.F.; D’Alterio, N.; Migliorati, G.; Pomilio, F. Challenge test studies on Listeria monocytogenes in ready-to-eat iceberg lettuce. Food Sci. Nutr. 2019, 7, 3845–3852. [Google Scholar] [CrossRef]
  27. György, É.; Laslo, É.; Csató, E. Antibacterial activity of plant extracts against isolated from ready-to-eat salads. Act. Aliment. 2020, 13, 131–143. [Google Scholar]
  28. Sant’Ana, A.S.; Barbosa, M.S.; Destro, M.T.; Landgraf, M.; Franco, B.D. Growth potential of Salmonella spp. and Listeria monocytogenes in nine types of ready-to-eat vegetables stored at variable temperature conditions during shelf-life. Int. J. Food Microbiol. 2012, 157, 52–58. [Google Scholar] [CrossRef] [PubMed]
  29. Pinton, S.C.; Bardsley, C.A.; Marik, C.M.; Boyer, R.R.; Strawn, L.K. Fate of Listeria monocytogenes on Broccoli and Cauliflower at Different Storage Temperatures. J. Food Prot. 2020, 83, 858–864. [Google Scholar] [CrossRef]
  30. Olaimat, A.N.; Abu Ghoush, M.; Al-Holy, M.; Abu Hilal, H.; Al-Nabulsi, A.A.; Osaili, T.M.; Ayyash, M.; Holley, R.A. Survival and growth of Listeria monocytogenes and Staphylococcus aureus in ready-to-eat Mediterranean vegetable salads: Impact of storage temperature and food matrix. Int. J. Food Microbiol. 2021, 346, 109149. [Google Scholar] [CrossRef] [PubMed]
  31. Bardsley, C.A.; Boyer, R.R.; Rideout, S.L.; Strawn, L.K. Survival of Listeria monocytogenes on the surface of basil, cilantro, dill, and parsley plants. Food Control 2019, 95, 90–94. [Google Scholar] [CrossRef]
  32. Huang, J.; Luo, Y.; Zhou, B.; Zheng, J.; Nou, X. Growth and survival of Salmonella enterica and Listeria monocytogenes on fresh-cut produce and their juice extracts: Impacts and interactions of food matrices and temperature abuse conditions. Food Control 2019, 100, 300–304. [Google Scholar] [CrossRef]
  33. López-Gálvez, F.; Gil, M.I.; Allende, A. Impact of relative humidity, inoculum carrier and size, and native microbiota on Salmonella ser. Typhimurium survival in baby lettuce. Food Microbiol. 2018, 70, 155–161. [Google Scholar] [CrossRef]
  34. Singh, A.; Yemmireddy, V. Pre-Growth Environmental Stresses Affect Foodborne Pathogens Response to Subsequent Chemical Treatments. Microorganisms 2022, 10, 786. [Google Scholar] [CrossRef]
  35. Ma, T.; Luo, J.; Tian, C.; Sun, X.; Quan, M.; Zheng, C.; Kang, L.; Zhan, J. Influence of technical processing units on chemical composition and antimicrobial activity of carrot (Daucus carrot L.) juice essential oil. Food Chem. 2015, 170, 394–400. [Google Scholar] [CrossRef]
  36. Ziegler, M.; Kent, D.; Stephan, R.; Guldimann, C. Growth potential of Listeria monocytogenes in twelve different types of RTE salads: Impact of food matrix, storage temperature and storage time. Int. J. Food Microbiol. 2019, 296, 83–92. [Google Scholar] [CrossRef]
  37. Lokerse, R.F.A.; Maslowska-Corker, K.A.; Van de Wardt, L.C.; Wijtzes, T. Growth capacity of Listeria monocytogenes in ingredients of ready-to-eat salads. Food Control 2016, 60, 338–345. [Google Scholar] [CrossRef]
  38. Jechalke, S.; Schierstaedt, J.; Becker, M.; Flemer, B.; Grosch, R.; Smalla, K.; Schikora, A. Salmonella Establishment in Agricultural Soil and Colonization of Crop Plants Depend on Soil Type and Plant Species. Front. Microbiol. 2019, 10, 967. [Google Scholar] [CrossRef] [PubMed]
  39. Jacob, C.; Melotto, M. Human Pathogen Colonization of Lettuce Dependent Upon Plant Genotype and Defense Response Activation. Front. Plant Sci. 2020, 10, 1769. [Google Scholar] [CrossRef] [PubMed]
  40. Bolten, S.; Belias, A.; Weigand, K.A.; Pajor, M.; Qian, C.; Ivanek, R.; Weidmann, M. Population dynamics of Listeria spp., Salmonella spp., and Escherichia coli on fresh produce: A scoping review. Compr. Rev. Food Sci. Food Saf. 2023, 22, 4537–4572. [Google Scholar] [CrossRef] [PubMed]
  41. Harrand, A.S.; Kovac, J.; Carroll, L.M.; Guariglia-Oropeza, V.; Kent, D.J.; Wiedmann, M. Assembly and Characterization of a Pathogen Strain Collection for Produce Safety Applications: Pre-growth Conditions Have a Larger Effect on Peroxyacetic Acid Tolerance Than Strain Diversity. Front. Microbiol. 2019, 10, 1223. [Google Scholar] [CrossRef] [PubMed]
  42. Parnell, T.L.; Harris, L.J.; Suslow, T.V. Reducing Salmonella on cantaloupes and honeydew melons using wash practices applicable to postharvest handling, foodservice, and consumer preparation. Int. J. Food Microbiol. 2005, 99, 59–70. [Google Scholar] [CrossRef] [PubMed]
  43. Baranyi, J.; Roberts, T.A. A dynamic approach to predicting bacterial growth in food. Int. J. Food Microbiol. 1994, 23, 277–294. [Google Scholar] [CrossRef] [PubMed]
  44. Espin, J.C.; Wichers, H.J. Study of the oxidation of resveratrol catalyzed by polyphenol oxtoase, effect of polyphenol oxidase, laccase, and peroxidase on the antiradical capacity of resveratrol. J. Food Biochem. 2000, 24, 225–250. [Google Scholar] [CrossRef]
  45. Patel, J.; Sharma, M. Differences in attachment of Salmonella enterica serovars to cabbage and lettuce leaves. Int. J. Food Microbiol. 2010, 139, 41–47. [Google Scholar] [CrossRef]
  46. Salazar, J.K.; Sahu, S.N.; Hildebrandt, I.M.; Zhang, L.; Qi, Y.; Liggans, G.; Datta, A.R.; Tortorello, M.L. Growth kinetics of Listeria monocytogenes in cut produce. J. Food Prot. 2017, 80, 1328–1336. [Google Scholar] [CrossRef]
  47. Gu, G.; Ottesen, A.; Bolten, S.; Ramachandran, P.; Reed, E.; Rideout, S.; Luo, Y.; Patel, J.; Brown, E.; Nou, X. Shifts in spinach microbial communities after chlorine washing and storage at compliant and abusive temperatures. Food Microbiol. 2018, 73, 73–84. [Google Scholar] [CrossRef] [PubMed]
  48. Hellström, J.; Granato, D.; Mattila, P.H. Accumulation of Phenolic Acids during Storage over Differently Handled Fresh Carrots. Foods 2020, 9, 1515. [Google Scholar] [CrossRef] [PubMed]
  49. Carrasco, E.; Pérez-Rodríguez, F.; Valero, A.; Garcı, R.M.; Zurera, G. Growth of Listeria monocytogenes on shredded, ready-to-eat iceberg lettuce. Food Control 2008, 19, 487–494. [Google Scholar] [CrossRef]
  50. Salazar, J.K.; Fay, M.; Qi, Y.; Liggans, G. Growth Kinetics of Listeria monocytogenes on Cut Red Cabbage. J. Food Prot. 2022, 85, 1128–1132. [Google Scholar] [CrossRef] [PubMed]
  51. Demirdöven, A.; Karabıyıklı, Ş.; Tokatlı, K.; Öncül, N. Inhibitory effects of red cabbage and sour cherry pomace anthocyanin extracts on food borne pathogens and their antioxidant properties. LWT-Food Sci. Technol. 2015, 63, 8–13. [Google Scholar] [CrossRef]
  52. Alvarez, M.V.; Moreira, M.D.R.; Roura, S.I.; Ayala-Zavala, J.F.; González-Aguilar, G.A. Using natural antimicrobials to enhance the safety and quality of fresh and processed fruits and vegetables: Types of antimicrobials. In Handbook of Natural Antimicrobials for Food Safety and Quality; Elsevier: Amsterdam, The Netherlands, 2015; pp. 287–313. [Google Scholar]
  53. Barbieri, R.; Coppo, E.; Marchese, A.; Daglia, M.; Sobarzo-Sánchez, E.; Nabavi, S.F.; Nabavi, S.M. Phytochemicals for human disease: An update on plant-derived compounds antibacterial activity. Microbiol. Res. 2017, 196, 44–68. [Google Scholar] [CrossRef] [PubMed]
  54. Favela-González, K.M.; Hernández-Almanza, A.Y.; De la Fuente-Salcido, N.M. The value of bioactive compounds of cruciferous vegetables (Brassica) as antimicrobials and antioxidants: A review. J. Food Biochem. 2020, 44, e13414. [Google Scholar] [CrossRef] [PubMed]
  55. Viswanathan, P.; Kaur, R. Prevalence and growth of pathogens on salad vegetables, fruits and sprouts. Int. J. Hyg. Environ. Health 2001, 203, 205–213. [Google Scholar] [CrossRef] [PubMed]
  56. Takó, M.; Kerekes, E.B.; Zambrano, C.; Kotogán, A.; Papp, T.; Krisch, J.; Vágvölgyi, C. Plant phenolics and phenolic-enriched extracts as antimicrobial agents against food-contaminating microorganisms. Antioxidants 2020, 9, 165. [Google Scholar] [CrossRef]
  57. Yeo, H.J.; Ki, W.Y.; Lee, S.; Kim, C.Y.; Kim, J.K.; Park, S.U.; Park, C.H. Metabolite Profiles and Biological Activities of Different Phenotypes of Chinese cabbage (Brassica rapa ssp. Pekinensis). Food Res. Int. 2023, 174, 113619. [Google Scholar] [CrossRef]
  58. Vandamm, J.P.; Li, D.; Harris, L.J.; Schaffner, D.W.; Danyluk, M.D. Fate of Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella on fresh-cut celery. Food Microbiol. 2013, 34, 151–157. [Google Scholar] [CrossRef] [PubMed]
  59. Harrand, A.S.; Guariglia-Oropeza, V.; Skeens, J.; Kent, D.; Wiedmann, M. Nature versus Nurture: Assessing the Impact of Strain Diversity and Pregrowth Conditions on Salmonella enterica, Escherichia coli, and Listeria Species Growth and Survival on Selected Produce Items. Appl. Environ. Microbiol. 2021, 87, e01925-20. [Google Scholar] [CrossRef] [PubMed]
  60. Thakur, M.; Asrani, R.K.; Patial, V. Listeria monocytogenes: A food-borne pathogen. In Foodborne Diseases; Academic Press: Cambridge, MA, USA, 2018; pp. 157–192. [Google Scholar]
  61. Wu, R.A.; Yuk, H.G.; Liu, D.; Ding, T. Recent advances in understanding the effect of acid-adaptation on the cross-protection to food-related stress of common foodborne pathogens. Crit. Rev. Food Sci. Nutr. 2022, 62, 7336–7353. [Google Scholar] [CrossRef] [PubMed]
  62. Ye, B.; He, S.; Zhou, X.; Cui, Y.; Zhou, M.; Shi, X. Response to Acid Adaptation in Salmonella enterica Serovar Enteritidis. J. Food Sci. 2019, 84, 599–605. [Google Scholar] [CrossRef] [PubMed]
  63. Nagarajan, M.; Prodpran, T.; Benjakul, S.; Songtipya, P. Properties and characteristics of multi-layered films from tilapia skin gelatin and poly (lactic acid). Food Biophys. 2017, 12, 222–233. [Google Scholar] [CrossRef]
  64. Najafi, H.; Mohammad, B.; Bahreini, M. Microbiological quality of mixed fresh-cut vegetable salads and mixed ready-to-eat fresh herbs in Mashhad, Iran. In Proceedings of the International Conference on Nutrition and Food Sciences IPCBEE, Singapore, 23–24 July 2012; Volume 39, pp. 62–66. [Google Scholar]
  65. Sui, Y.; Zhao, Q.; Wang, Z.; Liu, J.; Jiang, M.; Yue, J.; Lan, J.; Liu, J.; Liao, Q.; Wang, Q.; et al. A comparative analysis of the microbiome of kiwifruit at harvest under open-field and rain-shelter cultivation systems. Front. Microbiol. 2021, 12, 757719. [Google Scholar] [CrossRef] [PubMed]
  66. Mohamed, W.F.; Shady, H.M.A.; Sayed-Ahmed, E.S.F.; Amer, S.A. Antibacterial activity of Egyptian propolis and pollen extracts and their synergistic/antagonistic effect with lactic acid bacteria (lab) against food borne pathogenic bacteria. Egypt J. Exp. Biol. 2016, 12, 31–43. [Google Scholar]
  67. Raman, J.; Kim, J.S.; Choi, K.R.; Eun, H.; Yang, D.; Ko, Y.J.; Kim, S.J. Application of lactic acid bacteria (LAB) in sustainable agriculture: Advantages and limitations. Int. J. Mol. Sci. 2022, 23, 7784. [Google Scholar] [CrossRef]
Foods 12 04287 g001
Figure 1. Samples of fresh-cut produce: (A) iceberg lettuce, (B) red cabbage, (C) grated carrot, and (D) mixed salad. (E) Clam-shell containers stored in an environmental chamber at 4 °C and 80 ± 2% RH.
Figure 1. Samples of fresh-cut produce: (A) iceberg lettuce, (B) red cabbage, (C) grated carrot, and (D) mixed salad. (E) Clam-shell containers stored in an environmental chamber at 4 °C and 80 ± 2% RH.
Foods 12 04287 g001
Foods 12 04287 g002
Figure 2. Survival kinetics of Listeria monocytogenes on iceberg lettuce (♦), red cabbage (▲), shredded carrot (•), and mixed salad (■) when pre-cultured at (a) 37 °C, (b) 21 °C, and (c) 4 °C. Lower-case letters indicate a significant difference within the same produce during the storage period, whereas upper-case letters indicate a significant difference across different produce at a single time point. L. monocytogenes was not detected on control samples; hence, they are not shown in the figure above.
Figure 2. Survival kinetics of Listeria monocytogenes on iceberg lettuce (♦), red cabbage (▲), shredded carrot (•), and mixed salad (■) when pre-cultured at (a) 37 °C, (b) 21 °C, and (c) 4 °C. Lower-case letters indicate a significant difference within the same produce during the storage period, whereas upper-case letters indicate a significant difference across different produce at a single time point. L. monocytogenes was not detected on control samples; hence, they are not shown in the figure above.
Foods 12 04287 g002
Foods 12 04287 g003
Figure 3. Survival kinetics of Salmonella enterica on iceberg lettuce (♦), red cabbage (▲), shredded carrot (•), and mixed salad (■) when pre-cultured at (a) 37 °C, (b) 21 °C, and (c) 4 °C. Lower-case letters indicate a significant difference within the same produce during the storage period, whereas upper-case letters indicate a significant difference across different produce at a single time point. S. enterica was not detected on control samples; hence, they are not shown in the figure above.
Figure 3. Survival kinetics of Salmonella enterica on iceberg lettuce (♦), red cabbage (▲), shredded carrot (•), and mixed salad (■) when pre-cultured at (a) 37 °C, (b) 21 °C, and (c) 4 °C. Lower-case letters indicate a significant difference within the same produce during the storage period, whereas upper-case letters indicate a significant difference across different produce at a single time point. S. enterica was not detected on control samples; hence, they are not shown in the figure above.
Foods 12 04287 g003
Table 1. Aerobic plate count (APC),and yeast and mold counts (log CFU/gm) in control samples during storage.
Table 1. Aerobic plate count (APC),and yeast and mold counts (log CFU/gm) in control samples during storage.
Type of Organism(s)Time (h)Iceberg LettuceRed CabbageGrated CarrotMixed Salad
APC01.88 ± 1.26 a,A2.52 ± 0.56 a,A2.55 ± 0.25 a,A2.60 ± 0.50 a,A
122.25 ± 0.57 a,AB1.50 ± 0.91 a,B2.46 ± 0.29 a,AB2.72 ± 0.27 a,A
241.32 ± 0.83 a,A1.55 ± 1.00 a,A2.54 ± 0.32 a,A2.14 ± 0.64 a,A
482.02 ± 1.18 a,A1.65 ± 1.23 a,A2.47 ± 0.18 a,A2.24 ± 0.68 a,A
721.53 ± 1.01 a,A1.08 ± 0.86 a,A2.30 ± 0.47 a,A2.56 ± 0.40 a,A
Yeast04.09 ± 0.15 a,A3.99 ± 0.29 a,A4.02 ± 0.17 a,A4.08 ± 0.06 a,A
124.09 ± 0.09 a,A4.14 ± 0.07 a,A4.10 ± 0.05 a,A4.10 ± 0.03 a,A
244.15 ± 0.14 a,A4.15 ± 0.12 a,A4.16 ± 0.08 a,A4.12 ± 0.04 a,A
484.16 ± 0.05 a,A4.23 ± 0.05 a,A4.13 ± 0.12 a,A4.17 ± 0.16 a,A
724.06 ± 0.17 a,A4.02 ± 0.24 a,A4.08 ± 0.23 a,A4.14 ± 0.15 a,A
Mold00.66 ± 0.62 a,A0.96 ± 0.57 a,A0.94 ± 0.92 a,A0.90 ± 0.83 a,A
121.40 ± 0.55 a,A0.52 ± 0.74 a,A2.06 ± 0.44 ab,B1.52 ± 0.40 a,A
240.56 ± 0.76 a,A0.46 ± 0.64 a,A2.26 ± 0.23 ab,B1.46 ± 0.53 a,A
480.56 ± 0.76 a,A0.82 ± 0.75 a,A1.51 ± 1.38 ab,B1.49 ± 0.36 a,AB
720.40 ± 0.55 a,A0.72 ± 0.67 a,A2.07 ± 1.16 b,B1.94 ± 0.23 a,A
The mean ± standard deviation is represented in the table (five replications). Lower-case letters within a row indicate a significant difference within a produce item during the storage period, and upper-case letters represent a significant difference among the different commodities at a single time point within a row.
Table 2. Parameter estimates of L. monocytogenes and Salmonella enterica survival kinetics in different produce using the Baranyi–Roberts model.
Table 2. Parameter estimates of L. monocytogenes and Salmonella enterica survival kinetics in different produce using the Baranyi–Roberts model.
Type of PathogenPre-Growth Temp a (°C)Type of Produce R2SE of Fit bInitial Value (log CFU/g)Maximum Rate c (1/h)
L. monocytogenes37Lettuce0.8170.09884.241 ± 0.0789−0.00944 ± 0.0033
Cabbage0.9670.04174.137 ± 0.0241−0.018 ± 0.00275
Carrot *----
Mixed salad0.9250.1434.392 ± 0.13−0.0296 ± 0.00845
21Lettuce0.0540.09984.174 ± 0.0982−0.00772 ± 0.0106
Cabbage0.2430.2094.332 ± 0.209−0.0213 ± 0.0243
Carrot0.6570.1194.0434 ± 0.07070.0122 ± 0.00734
Mixed salad0.9520.07094.4 ± 0.0709−0.052 ± 0.00956
4Lettuce0.8470.14.507 ± 0.1−0.0291 ± 0.0119
Cabbage0.2040.1564.5 ± 0.156−0.0184 ± 0.0191
Carrot0.6530.184.0927 ± 0.165−0.0166 ± 0.0108
Mixed salad0.8470.14.507 ± 0.1−0.0291 ± 0.0119
S. enterica37Lettuce0.9940.02156.0802 ± 0.0147−0.0143 ± 0.00111
Cabbage0.1940.1995.372 ± 0.165−0.00796 ± 0.00791
Carrot0.9850.05756.0964 ± 0.0339−0.03 ± 0.00349
Mixed salad0.920.1066.136 ± 0.0983−0.0296 ± 0.00702
21Lettuce0.8010.1116.33 ± 0.0879−0.00954 ± 0.00345
Cabbage0.9190.1015.843 ± 0.0933−0.0279 ± 0.00667
Carrot0.950.1066.318 ± 0.0723−0.0245 ± 0.00549
Mixed salad0.9570.05646.403 ± 0.0529−0.0105 ± 0.00168
4Lettuce0.8760.1026.269 ± 0.0794−0.0101 ± 0.00301
Cabbage0.8320.115.688 ± 0.0922−0.0122 ± 0.00466
Carrot0.9390.1146.297 ± 0.0663−0.0328 ± 0.00718
Mixed salad0.860.09936.225 ± 0.0909−0.0163 ± 0.00599
a Culture growth temperature prior to inoculation on different types of produce; b SE of fit, standard error of fit. c Maximum Rate: rate of inactivation (negative value) and growth (positive value). * Baranyi–Roberts model failed to fit the experimental data at these conditions.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kaur, A.; Yemmireddy, V. Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage. Foods 2023, 12, 4287. https://doi.org/10.3390/foods12234287

AMA Style

Kaur A, Yemmireddy V. Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage. Foods. 2023; 12(23):4287. https://doi.org/10.3390/foods12234287

Chicago/Turabian Style

Kaur, Avninder, and Veerachandra Yemmireddy. 2023. "Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage" Foods 12, no. 23: 4287. https://doi.org/10.3390/foods12234287

APA Style

Kaur, A., & Yemmireddy, V. (2023). Effect of Different Pre-Growth Temperatures on the Survival Kinetics of Salmonella enterica and Listeria monocytogenes in Fresh-Cut Salad during Refrigerated Storage. Foods, 12(23), 4287. https://doi.org/10.3390/foods12234287

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop