Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety.

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

Action potential conduction in the mouse and rat vagus nerve is dependent on multiple voltage-gated sodium channels (NaV1s).

Action potential (AP) conduction depends on voltage-gated sodium channels, of which there are nine subtypes. The vagus nerve, comprising sensory afferent fibers and efferent parasympathetic fibers, provides autonomic regulation of visceral organs, but the voltage-gated sodium channels (NaV1) subtypes involved in its AP conduction are poorly defined. We studied the A- and C-waves of electrically stimulated compound action potentials (CAPs) of the mouse and rat vagus nerves with and without NaV1 inhibitor administration: tetrodotoxin (TTX), PF-05089771 (mouse NaV1.7), ProTX-II (NaV1.7), ICA-121341 (NaV1.1, NaV1.3, and NaV1.6), LSN-3049227 (NaV1.2, NaV1.6, and NaV1.7), and A-803467 (NaV1.8). We show that TTX-sensitive NaV1 channels are essential for all vagal AP conduction. PF-05089771 but not ICA-121341 inhibited the mouse A-wave, which was abolished by LSN-3049227, suggesting roles for NaV1.7 and NaV1.2. The mouse C-wave was abolished by LSN-3049227 and a combination of PF-05089771 and ICA-121341, suggesting roles for NaV1.7 and NaV1.6. The rat A-wave was inhibited by ProTX-II, ICA-121341, and a combination of these inhibitors but only abolished by LSN-3049227, suggesting roles for NaV1.7, NaV1.6, and NaV1.2. The rat C-wave was abolished by LSN-3049227 and a combination of ProTX-II and ICA-121341, suggesting roles for NaV1.7 and NaV1.6. A-803467 also inhibited the mouse and rat CAP suggesting a cooperative role for the TTX-resistant NaV1.8. Overall, our data demonstrate that multiple NaV1 subtypes contribute to vagal CAPs, with NaV1.7 and NaV1.8 playing predominant roles and NaV1.6 and NaV1.2 contributing to a different extent based on nerve fiber type and species. Inhibition of these NaV1 may impact autonomic regulation of visceral organs.NEW & NOTEWORTHY Distinct NaV1 channels are involved in action potential (AP) initiation and conduction from afferent terminals within specific organs. Here, we have identified the NaV1 necessary for AP conduction in the entire murine and rat vagus nerve. We show TTX-sensitive channels are essential for all AP conduction, predominantly NaV1.7 with NaV1.2 and NaV1.6 playing lesser roles depending on the species and fiber type. In addition, we show that NaV1.8 is also essential for most axonal AP conduction.

Salmonella Prevalence Is Strongly Associated with Spatial Factors while Listeria monocytogenes Prevalence Is Strongly Associated with Temporal Factors on Virginia Produce Farms.

The heterogeneity of produce production environments complicates the development of universal strategies for managing preharvest produce safety risks. Understanding pathogen ecology in different produce-growing regions is important for developing targeted mitigation strategies. This study aimed to identify environmental and spatiotemporal factors associated with isolating Salmonella and Listeria from environmental samples collected from 10 Virginia produce farms. Soil (n = 400), drag swab (n = 400), and irrigation water (n = 120) samples were tested for Salmonella and Listeria, and results were confirmed by PCR. Salmonella serovar and Listeria species were identified by the Kauffmann-White-Le Minor scheme and partial sigB sequencing, respectively. Conditional forest analysis and Bayesian mixed models were used to characterize associations between environmental factors and the likelihood of isolating Salmonella, Listeria monocytogenes (LM), and other targets (e.g., Listeria spp. and Salmonella enterica serovar Newport). Surrogate trees were used to visualize hierarchical associations identified by the forest analyses. Salmonella and LM prevalence was 5.3% (49/920) and 2.3% (21/920), respectively. The likelihood of isolating Salmonella was highest in water samples collected from the Eastern Shore of Virginia with a dew point of >9.4°C. The likelihood of isolating LM was highest in water samples collected in winter from sites where <36% of the land use within 122 m was forest wetland cover. Conditional forest results were consistent with the mixed models, which also found that the likelihood of detecting Salmonella and LM differed between sample type, region, and season. These findings identified factors that increased the likelihood of isolating Salmonella- and LM-positive samples in produce production environments and support preharvest mitigation strategies on a regional scale. IMPORTANCE This study sought to examine different growing regions across the state of Virginia and to determine how factors associated with pathogen prevalence may differ between regions. Spatial and temporal data were modeled to identify factors associated with an increased pathogen likelihood in various on-farm sources. The findings of the study show that prevalence of Salmonella and L. monocytogenes is low overall in the produce preharvest environment but does vary by space (e.g., region in Virginia) and time (e.g., season), and the likelihood of pathogen-positive samples is influenced by different spatial and temporal factors. Therefore, the results support regional or scale-dependent food safety standards and guidance documents for controlling hazards to minimize risk. This study also suggests that water source assessments are important tools for developing monitoring programs and mitigation measures, as spatiotemporal factors differ on a regional scale.

Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data.

AIMS: While fecal indicator bacteria (FIB) testing is used to monitor surface water for potential health hazards, observed variation in FIB levels may depend on the scale of analysis (SOA). Two decades of citizen science data, coupled with random effects models, were used to quantify the variance in FIB levels attributable to spatial versus temporal factors. METHODS AND RESULTS: Separately, Bayesian models were used to quantify the ratio of spatial to non-spatial variance in FIB levels and identify associations between environmental factors and FIB levels. Separate analyses were performed for three SOA: waterway, watershed, and statewide. As SOA increased (from waterway to watershed to statewide models), variance attributable to spatial sources generally increased and variance attributable to temporal sources generally decreased. While relationships between FIB levels and environmental factors, such as flow conditions (base versus stormflow), were constant across SOA, the effect of land cover was highly dependent on SOA and consistently smaller than the effect of stormwater infrastructure (e.g. outfalls). CONCLUSIONS: This study demonstrates the importance of SOA when developing water quality monitoring programs or designing future studies to inform water management.

Effects of Fumigation on the Reduction of Salmonella enterica in Soil.

Due to the phaseout of methyl bromide (MeBr), there is a need for broad-spectrum soil fumigation alternatives for pest management. Little is known about the impact of fumigation alternatives on foodborne pathogens, such as Salmonella, in agricultural soils. This study investigated the effect of MeBr alternative fumigants on Salmonella reduction in soil. Sandy loam soil was collected from a conventional farmed vegetable field and inoculated with either Salmonella Newport J1892 or Typhimurium ATCC 14028 (5.9 ± 0.3 log10 colony-forming unit [CFU]/g). Each of the four fumigants labeled for pest management (1,3-dichloropropene, chloropicrin, dimethyl disulfide, and metam sodium) was applied at labeled maximum application field levels to soil in pots and stored for a 2-week period. Sterile water was used as a control. Following the 2-week period, Salmonella concentrations in soil samples were enumerated at 1, 7, 14, and 21 days postfumigation. The mean concentration of Salmonella Newport was significantly higher than that of Salmonella Typhimurium 1 day after fumigation (p = 0.015). Fumigation using 1,3-dichloropropene or dimethyl disulfide significantly reduced Salmonella Newport and Salmonella Typhimurium concentrations, compared with the sterile water control. The rate of Salmonella reduction in soil treated with dimethyl disulfide was higher (0.17 ± 0.02 log10 CFU/g/day), compared with soil treated with the other fumigants (0.10-0.12 log10 CFU/g/day). Due to the reduction of Salmonella, alternative fumigation treatments may mitigate potential Salmonella contamination in soil within farm environments.

Structural Equation Models Suggest That On-Farm Noncrop Vegetation Removal Is Not Associated with Improved Food Safety Outcomes but Is Linked to Impaired Water Quality.

While growers have reported pressures to minimize wildlife intrusion into produce fields through noncrop vegetation (NCV) removal, NCV provides key ecosystem services. To model food safety and environmental tradeoffs associated with NCV removal, published and publicly available food safety and water quality data from the Northeastern United States were obtained. Because data on NCV removal are not widely available, forest-wetland cover was used as a proxy, consistent with previous studies. Structural equation models (SEMs) were used to quantify the effect of forest-wetland cover on (i) food safety outcomes (e.g., detecting pathogens in soil) and (ii) water quality (e.g., nutrient levels). Based on the SEMs, NCV was not associated with or had a protective effect on food safety outcomes (more NCV was associated with a reduced likelihood of pathogen detection). The probabilities of detecting Listeria spp. in soil (effect estimate [EE] = -0.17; P = 0.005) and enterohemorrhagic Escherichia coli in stream samples (EE = -0.27; P < 0.001) were negatively associated with the amount of NCV surrounding the sampling site. Larger amounts of NCV were also associated with lower nutrient, salinity, and sediment levels, and higher dissolved oxygen levels. Total phosphorous levels were negatively associated with the amount of NCV in the upstream watershed (EE = -0.27; P < 0.001). Similar negative associations (P < 0.05) were observed for other physicochemical parameters, such as nitrate (EE = -0.38). Our findings suggest that NCV should not be considered an inherent produce safety risk or result in farm audit demerits. This study also provides a framework for evaluating environmental tradeoffs associated with using specific preharvest food safety strategies. IMPORTANCE Currently, on-farm food safety decisions are typically made independently of conservation considerations, often with detrimental impacts on agroecosystems. Comanaging agricultural environments to simultaneously meet conservation and food safety aims is complicated because farms are closely linked to surrounding environments, and management decisions can have unexpected environmental, economic, and food safety consequences. Thus, there is a need for research on the conservation and food safety tradeoffs associated with implementing specific preharvest food safety practices. Understanding these tradeoffs is critical for developing adaptive comanagement strategies and ensuring the short- and long-term safety, sustainability, and profitability of agricultural systems. This study quantifies tradeoffs and synergies between food safety and environmental aims, and outlines a framework for modeling tradeoffs and synergies between management aims that can be used to support future comanagement research.

Anaerobic soil disinfestation, amendment-type, and irrigation regimen influence Salmonella survival and die-off in agricultural soils.

AIMS: This study investigated Salmonella concentrations following combinations of horticultural practices including anaerobic soil disinfestation (ASD), soil amendment type and irrigation regimen. METHODS AND RESULTS: Sandy-loam soil was inoculated with a five-serovar Salmonella cocktail (5.5 ± 0.2 log CFU per gram) and subjected to one of six treatments: (i) no soil amendment, ASD (ASD control), (ii) no soil amendment, no-ASD (non-ASD control) and (iii-vi) soil amended with pelletized poultry litter, rye, rapeseed or hairy vetch with ASD. The effect of irrigation regimen was determined by collecting samples 3 and 7 days after irrigation. Twenty-five-gram soil samples were collected pre-ASD, post-soil saturation (i.e. ASD-process), and at 14 time-points post-ASD, and Salmonella levels enumerated. Log-linear models examined the effect of amendment type and irrigation regimen on Salmonella die-off during and post-ASD. During ASD, Salmonella concentrations significantly decreased in all treatments (range: -0.2 to -2.7 log CFU per gram), albeit the smallest decrease (-0.2 log CFU per gram observed in the pelletized poultry litter) was of negligible magnitude. Salmonella die-off rates varied by amendment with an average post-ASD rate of -0.05 log CFU per gram day (CI = -0.05, -0.04). Salmonella concentrations remained highest over the 42 days post-ASD in pelletized poultry litter, followed by rapeseed, and hairy vetch treatments. Findings suggested ASD was not able to eliminate Salmonella in soil, and certain soil amendments facilitated enhanced Salmonella survival. Salmonella serovar distribution differed by treatment with pelletized poultry litter supporting S. Newport survival, compared with other serovars. Irrigation appeared to assist Salmonella survival with concentrations being 0.14 log CFU per gram (CI = 0.05, 0.23) greater 3 days, compared with 7 days post-irrigation. CONCLUSIONS: ASD does not eliminate Salmonella in soil, and may in fact, depending on the soil amendment used, facilitate Salmonella survival. SIGNIFICANCE AND IMPACT OF THE STUDY: Synergistic and antagonistic effects on food safety hazards of implementing horticultural practices should be considered.

Salmonella and Listeria monocytogenes survival on Field Packed Cantaloupe Contact Surfaces.

Field-packing of cantaloupes involves numerous food contact surfaces that can contamination melons with foodborne pathogens; the soil on these surfaces increases throughout the harvest day. Data is lacking on the cross-contamination risk from contaminated food contact surfaces under the dry conditions typical of cantaloupe field-packing operations. This study sought to evaluate the survival of Salmonella and Listeria monocytogenes on cantaloupe field-pack food contact surfaces using both a wet and dry inoculum to provide insights into managing foodborne pathogen contamination risks. Five clean or fouled materials (cotton gloves, nitrile gloves, rubber gloves, cotton rags, and stainless steel) were inoculated with a cocktail of either Salmonella or L. monocytogenes. A wet inoculum was spot inoculated (100 µL) onto coupons. A dry inoculum was prepared by mixing wet inoculum with 100 g of sterile sand, and shaking the coupons with the inoculated sand for 2min. Coupons were held at 35°C (35% RH) and enumerated at 0, 2, 4, 6 and 8 h. Significant differences in pathogen concentrations over time were calculated and the GInaFiT add-in tool for Excel was used to build Log-linear, Weibull, and Biphasic die-off models. Depending on the material type, coupon condition, and inoculum type, Salmonella and L. monocytogenes reductions over 8 h ranged from 0.3-3.3 and -0.4-4.2 log10 CFU/coupon, respectively. For all material types, Salmonella reductions were highest on wet-inoculated clean coupons; L. monocytogenes varied by material type. Weibull and biphasic models were a better fit of respective pathogen die-off curves than linear models. Overall, faster die-off rates were seen for wet inoculated and clean materials. Since pathogen populations remained viable over the study duration and both inoculum type and coupon condition impacted survival, frequent sanitation or replacement of food contact surfaces during the operational day is needed to reduce the risk of cross-contamination.

Role of Whole Genome Sequencing in Assessing Resident and Transient Listeria monocytogenes in a Produce Packinghouse.

Whole genome sequencing (WGS) is a powerful tool that may be used to assist in identifying Listeria contamination sources and movement within environments, and to assess persistence. This study investigated sites in a produce packinghouse where Listeria had been historically isolated; and aimed to characterize dispersal patterns and identify cases of transient and resident Listeria. Environmental swab samples (n = 402) were collected from 67 sites at two time-points on three separate visits. Each sample was tested for Listeria, and Listeria isolates were characterized by partial sigB sequencing to determine species and allelic type (AT). Representative isolates from the three most common L. monocytogenes ATs (n = 79) were further characterized by WGS. Of the 144 Listeria species positive samples (35.8%), L. monocytogenes was the most prevalent species. L. monocytogenes was often coisolated with another species of Listeria. WGS identified cases of sporadic and continued reintroduction of L. monocytogenes from the cold storages into the packinghouse and demonstrated cases of L. monocytogenes persistence over 2 years in cold storages, drains, and on a forklift. Nine distinct clusters were found in this study. Two clusters showed evidence of persistence. Isolates in these two clusters (N = 11, with one historical isolate) were obtained predominantly and over multiple samplings from cold storages, with sporadic movement to sites in the packing area, suggesting residence in cold storages with opportunistic dispersal within the packinghouse. The other seven clusters demonstrated evidence of transient Listeria, as isolation was sporadic over time and space during the packing season. Our data provide important insights into likely L. monocytogenes harborage points and transfer in a packinghouse, which is key to root cause analysis. While results support Listeria spp. as a suitable indicator organism for environmental monitoring surveys, findings were unable to establish a specific species as an index organism for L. monocytogenes. Findings also suggest long-term persistence with substantial SNP diversification, which may assist in identifying potential contamination sources and implementing control measures.

Sanitizer Type and Contact Time Influence Salmonella Reductions in Preharvest Agricultural Water Used on Virginia Farms.

No Environmental Protection Agency (EPA) chemical treatments for preharvest agricultural water are currently labeled to reduce human health pathogens. The goal of this study was to examine the efficacy of peracetic acid- (PAA) and chlorine (Cl)-based sanitizers against Salmonella in Virginia irrigation water. Water samples (100 mL) were collected at three time points during the growing season (May, July, September) and inoculated with either the 7-strain EPA/FDA-prescribed cocktail or a 5-strain Salmonella produce-borne outbreak cocktail. Experiments were conducted in triplicate for 288 unique combinations of time point, residual sanitizer concentration (low: PAA, 6 ppm; Cl, 2-4 ppm or high: PAA, 10 ppm; Cl, 10-12 ppm), water type (pond, river), water temperature (12°C, 32°C), and contact time (1, 5, 10 min). Salmonella were enumerated after each treatment combination and reductions were calculated. A log-linear model was used to characterize how treatment combinations influenced Salmonella reductions. Salmonella reductions by PAA and Cl ranged from 0.0 ± 0.1 to 5.6 ± 1.3 log10 CFU/100 mL and 2.1 ± 0.2 to 7.1 ± 0.2 log10 CFU/100 mL, respectively. Physicochemical parameters significantly varied by untreated water type; however, Salmonella reductions did not (p = 0.14), likely due to adjusting the sanitizer amounts needed to achieve the target residual concentrations regardless of source water quality. Significant differences (p < 0.05) in Salmonella reductions were observed for treatment combinations, with sanitizer (Cl > PAA) and contact time (10 > 5 > 1 min) having the greatest effects. The log-linear model also revealed that outbreak strains were more treatment-resistant. Results demonstrate that certain treatment combinations with PAA- and Cl-based sanitizers were effective at reducing Salmonella populations in preharvest agricultural water. Awareness and monitoring of water quality parameters are essential for ensuring adequate dosing for the effective treatment of preharvest agricultural water.

Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds.

Surface water environments are inherently heterogenous, and little is known about variation in microbial water quality between locations. This study sought to understand how microbial water quality differs within and between Virginia ponds. Grab samples were collected twice per week from 30 sampling sites across nine Virginia ponds (n = 600). Samples (100 mL) were enumerated for total coliform (TC) and Escherichia coli (EC) levels, and physicochemical, weather, and environmental data were collected. Bayesian models of coregionalization were used to quantify the variance in TC and EC levels attributable to spatial (e.g., site, pond) versus nonspatial (e.g., date, pH) sources. Mixed-effects Bayesian regressions and conditional inference trees were used to characterize relationships between data and TC or EC levels. Analyses were performed separately for each pond with ≥3 sampling sites (5 intrapond) while one interpond model was developed using data from all sampling sites and all ponds. More variance in TC levels were attributable to spatial opposed to nonspatial sources for the interpond model (variance ratio [VR] = 1.55) while intrapond models were pond dependent (VR: 0.65-18.89). For EC levels, more variance was attributable to spatial sources in the interpond model (VR = 1.62), compared to all intrapond models (VR < 1.0) suggesting that more variance is attributable to nonspatial factors within individual ponds and spatial factors when multiple ponds are considered. Within each pond, TC and EC levels were spatially independent for sites 56-87 m apart, indicating that different sites within the same pond represent different water quality for risk management. Rainfall was positively and pH negatively associated with TC and EC levels in both inter- and intrapond models. For all other factors, the direction and strength of associations varied. Factors driving microbial dynamics in ponds appear to be pond-specific and differ depending on the spatial scale considered.

Efficacy of Peracetic Acid and Chlorine on the Reduction of Shiga Toxin-producing Escherichia coli and a Nonpathogenic E. coli Strain in Preharvest Agricultural Water.

Produce-borne outbreaks of Shiga toxin-producing Escherichia coli (STEC) linked to preharvest water emphasize the need for efficacious water treatment options. This study quantified reductions of STEC and generic E. coli in preharvest agricultural water using commercially available sanitizers. Water was collected from two sources in Virginia (pond, river) and inoculated with either a seven-strain STEC panel or environmental generic E. coli strain TVS 353 (∼9 log10 CFU/100 mL). Triplicate inoculated water samples were equilibrated to 12 or 32°C and treated with peracetic acid (PAA) or chlorine (Cl) [low (PAA:6ppm, Cl:2-4 ppm) or high (PAA:10 ppm, Cl:10-12 ppm) residual concentrations] for an allotted contact time (1, 5, or 10 min). Strains were enumerated, and a log-linear model was used to characterize how treatment combinations influenced reductions. All Cl treatment combinations achieved a ≥3 log10 CFU/100 mL reduction, regardless of strain (3.43 ± 0.25 to 7.05 ± 0.00 log10 CFU/100 mL). Approximately 80% (19/24) and 67% (16/24) of PAA treatment combinations achieved a ≥3 log10 CFU/100 mL for STEC and E. coli TVS 353, respectively. The log-linear model showed contact time (10 > 5 > 1 min) and sanitizer type (Cl > PAA) had the greatest impact on STEC and E. coli TVS 353 reductions (p < 0.001). E. coli TVS 353 in water samples was more resistant to sanitizer treatment (p < 0.001) indicating applicability as a good surrogate. Results demonstrated Cl and PAA can be effective agricultural water treatment strategies when sanitizer chemistry is managed. These data will assist with the development of in-field validation studies and may identify suitable candidates for the registration of antimicrobial pesticide products for use against foodborne pathogens in preharvest agricultural water treatment.

16S microbiome analysis of microbial communities in distribution centers handling fresh produce.

Little is known about the microbial communities found in distribution centers (DCs), especially in those storing and handling food. As many foodborne bacteria are known to establish residence in food facilities, it is reasonable to assume that DCs handling foods are also susceptible to pathogen colonization. To investigate the microbial communities within DCs, 16S amplicon sequencing was completed on 317 environmental surface sponge swabs collected in DCs (n = 18) across the United States. An additional 317 swabs were collected in parallel to determine if any viable Listeria species were also present at each sampling site. There were significant differences in median diversity measures (observed, Shannon, and Chao1) across individual DCs, and top genera across all reads were Carnobacterium_A, Psychrobacter, Pseudomonas_E, Leaf454, and Staphylococcus based on taxonomic classifications using the Genome Taxonomy Database. Of the 39 16S samples containing Listeria ASVs, four of these samples had corresponding Listeria positive microbiological samples. Data indicated a predominance of ASVs identified as cold-tolerant bacteria in environmental samples collected in DCs. Differential abundance analysis identified Carnobacterium_A, Psychrobacter, and Pseudomonas_E present at a significantly greater abundance in Listeria positive microbiological compared to those negative for Listeria. Additionally, microbiome composition varied significantly across groupings within variables (e.g., DC, season, general sampling location).

Wet versus Dry Inoculation Methods Have a Significant Effect of Listeria monocytogenes Growth on Many Types of Whole Intact Fresh Produce.

ABSTRACT: Listeria monocytogenes causes relatively few outbreaks linked to whole fresh produce but triggers recalls each year in the United States. There are limited data on the influence of wet versus dry inoculation methods on pathogen growth on whole produce. A cocktail of five L. monocytogenes strains that included clinical, food, and environmental isolates associated with foodborne outbreaks and recalls was used. Cultures were combined to target a final wet inoculum concentration of 4 to 5 log CFU/mL. The dry inoculum was prepared by mixing wet inoculum with 100 g of sterile sand and drying for 24 h. Produce investigated belonged to major commodity families: Ericaceae (blackberry, raspberry, and blueberry), Rutaceae (lemon and mandarin orange), Rosaceae (sweet cherry), Solanaceae (tomato), Brassaceae (cauliflower and broccoli), and Apiaceae (carrot). Whole intact, inoculated fruit and vegetable commodities were incubated at 2, 12, 22, and 35 ± 2°C. Commodities were sampled for up to 28 days, and the experiment was replicated six times. The average maximum growth increase was obtained by measuring the maximum absolute increase for each replicate within a specific commodity, temperature, and inoculation method. Data for each commodity, replicate, and temperature were used to create primary growth or survival models describing the lag phase and growth or shoulder and decline as a function of time. Use of a liquid inoculum (versus dry inoculum) resulted in a markedly increased L. monocytogenes growth rate and growth magnitude on whole produce surfaces. Temperature highly influenced this difference: a greater effect seen with more commodities at higher temperatures (22 and 35°C) versus lower temperatures (2 and 12°C). These findings need to be explored for other commodities and pathogens. The degree to which wet or dry inoculation techniques more realistically mimic contamination conditions throughout the supply chain (e.g., production, harvest, postharvest, transportation, or retail) should be investigated.

ComBase Models Are Valid for Predicting Fate of Listeria monocytogenes on 10 Whole Intact Raw Fruits and Vegetables.

ABSTRACT: Listeria monocytogenes was associated with more than 60 produce recalls, including tomato, cherry, broccoli, lemon, and lime, between 2017 and 2020. This study describes the effects of temperature, time, and food substrate as factors influencing L. monocytogenes behavior on whole intact raw fruits and vegetables. Ten intact whole fruit and vegetable commodities were chosen based on data gaps identified in a systematic literature review. Produce investigated belong to major commodity families: Ericaceae (blackberry, raspberry, and blueberry), Rutaceae (lemon and mandarin orange), Roseaceae (sweet cherry), Solanaceae (tomato), Brassaceae (cauliflower and broccoli), and Apiaceae (carrot). A cocktail of five L. monocytogenes strains that included clinical, food, or environmental isolates linked to foodborne outbreaks was used to inoculate intact whole fruits and vegetables. Samples were incubated at 2, 12, 22, 30, and 35°C with relative humidities matched to typical real-world conditions. Foods were sampled (n = 6) for up to 28 days, depending on temperature. Growth and decline rates were estimated using DMFit, an Excel add-in. Growth rates were compared with ComBase modeling predictions for L. monocytogenes. Almost every experiment showed initial growth, followed by subsequent decline. L. monocytogenes was able to grow on the whole intact surface of all produce tested, except for carrot. The 10 produce commodities supported growth of L. monocytogenes at 22 and 35°C. Growth and survival at 2 and 12°C varied by produce commodity. The standard deviation of the square root growth and decline rates showed significantly larger variability in both growth and decline rates within replicates as temperature increased. When L. monocytogenes growth occurred, it was conservatively modeled by ComBase Predictor, and growth was generally followed by decreases in concentration. This research will assist in understanding the risks of foodborne disease outbreaks and recalls associated with L. monocytogenes on fresh whole produce.