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.

Factors Associated with the Prevalence of Salmonella, Generic Escherichia coli, and Coliforms in Florida's Agricultural Soils.

Limited data exist on the environmental factors that impact pathogen prevalence in the soil. The prevalence of foodborne pathogens, Salmonella and Listeria monocytogenes, and the prevalence and concentration of generic E. coli in Florida's agricultural soils were evaluated to understand the potential risk of microbial contamination at the preharvest level. For all organisms but L. monocytogenes, a longitudinal field study was performed in three geographically distributed agricultural areas across Florida. At each location, 20 unique 5 by 5 m field sampling sites were selected, and soil was collected and evaluated for Salmonella presence (25 g) and E. coli and coliform concentrations (5 g). Complementary data collected from October 2021 to April 2022 included: weather; adjacent land use; soil properties, including macro- and micro-nutrients; and field management practices. The overall Salmonella and generic E. coli prevalence was 0.418% (1/239) and 11.3% (27/239), respectively; with mean E. coli concentrations in positive samples of 1.56 log CFU/g. Farm A had the highest prevalence of generic E. coli, 22.8% (18/79); followed by Farm B, 10% (8/80); and Farm C 1.25% (1/80). A significant relationship (p < 0.05) was observed between generic E. coli and coliforms, and farm and sampling trip. Variation in the prevalence of generic E. coli and changes in coliform concentrations between farms suggest environmental factors (e.g. soil properties) at the three farms were different. While Salmonella was only detected once, generic E. coli was detected in Florida soils throughout the duration of the growing season meaning activities that limit contact between soil and horticultural crops should continue to be emphasized. Samples collected during an independent sampling trip were evaluated for L. monocytogenes, which was not detected. The influence of local environmental factors on the prevalence of indicator organisms in the soil presents a unique challenge when evaluating the applicability of more global models to predict pathogen prevalence in preharvest produce environments.

Southern Region Produce Safety Alliance Grower Training: Using Pre- and Post-Training Knowledge Assessments to Understand Training Effectiveness.

The Produce Safety Alliance (PSA) grower training was introduced in 2016 as the standardized curriculum to meet the training requirements of the Food and Drug Administration's (FDA) Food Safety Modernization Act's (FSMA) Produce Safety Rule (PSR). The PSR states that at least one supervisor or responsible party from each farm must have successfully completed this food safety training or one equivalent to the standardized curriculum, as recognized by the FDA. This study evaluated the effectiveness of PSA trainings conducted between 2017 and 2019 in the Southern United States by the Southern Regional Center for Food Safety Training, Outreach, and Technical Assistance by analyzing pre- and posttest assessments. Effectiveness was based on a 25-question knowledge assessment administered to participants before (n = 2494) and after (n = 2460) each training. The knowledge assessment indicated the overall effectiveness of the training, with average scores increasing significantly from pretest (15.9/25, 63.4%) to posttest (20.3/25, 81.3%) (P < 0.001). The greatest knowledge gains were seen in the Postharvest Handling and Sanitation, How to Develop a Farm Food Safety Plan, and Agricultural Water modules. Notably, these modules had lower posttest scores compared to the other modules, indicating that the amount of knowledge gained did not necessarily correspond with a sufficient understanding of the material. To ensure that participants understand all aspects of the PSR and best practices to minimize food safety risks, additional or advanced trainings may be needed. Additionally, the current testing instrument (pre-/posttest) used for PSA grower training, while validated, may not be optimal, thus alternative methods to assess the training effectiveness are likely needed.

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.

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.

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.

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.

Ranking Food Safety Priorities of the Fresh Produce Industry in the United States.

A broad understanding of community member food safety priorities in the fresh produce supply chain does not currently exist. This information is essential to improve food safety knowledge and practices effectively and efficiently throughout the fresh produce industry; therefore, the goal of this study was to identify and rank community produce safety priorities in the United States. Survey questions were designed and approved by food safety experts for participants to rank 24 fresh produce safety priorities. The anonymous survey was distributed online via Qualtrics™ to fresh produce community members from November 2020 to May 2021. A score was calculated for each priority by summing weighted ranking scores across responses. Descriptive statistics and logistic regression were used to determine frequencies and distribution of response and identify factors (e.g., role in produce safety, size/location of organization/operation) that influenced rankings. A total of 281 respondents represented fourteen different roles in the fresh produce industry, with most identified as growers (39.5%). Produce operations were distributed across the U.S. and annual produce sales ranged from below $25,000 to over $5,000,000. Health and hygiene, training, postharvest sanitation, traceability, and harvest sanitation were ranked as the top five food safety priorities. These findings provide insight into community member priorities in fresh produce safety and can be used to inform intervention efforts, ranging from specialized training for produce growers and packers, industry-driven research projects, and gaps in risk communication strategies.

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.

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).

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.

Survival of Inoculated Campylobacter jejuni and Escherichia coli O157:H7 on Kale During Refrigerated Storage.

Campylobacter and pathogenic Escherichia coliillnesses have been attributed to the consumption of fresh produce. The leafy green, kale, is increasingly consumed raw. In comparison to other leafy greens, kale has a longer shelf-life. Due to the extended shelf-life of kale, it is warranted to examine the survival of pathogenic Campylobacter jejuni and E. coli O157:H7 inoculated on the surface of kale stored in a controlled environment at 4 ± 1.4°C, and average humidity of 95 ± 1.9% over a 23-day period. At predetermined time points (days 0, 1, 2, 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21), inoculated kale was destructively sampled and the surviving bacteria determined by serial dilution and plating onto Tryptic soy agar, Charcoal cefoperozone deoxycholate agar, and Eosin methylene blue for total aerobic bacteria, C. jejuni, and E. coli O157:H7, respectively. Enrichment and PCR were used for detection when pathogens were not detected using serial dilution and plating. Aerobic heterotrophic bacteria increased over the 23-day period, in contrast, significant declines in the inoculated pathogens were observed. Inoculated E. coli O157:H7 survived longer on kale (up to 19 d); in comparison, C. jejuni was undetectable by day 13 using enrichment and PCR or plating. In conclusion, C. jejuni and E. coli O157:H7 declined on fresh kale over time when held at refrigerated temperatures but were still detected during the majority of the time when the kale would likely still be considered edible by consumers.

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.

Microbubbles Remove Listeria monocytogenes from the Surface of Stainless Steel, Cucumber, and Avocado.

Fresh produce may be contaminated by bacterial pathogens, including Listeria monocytogenes, during harvesting, packaging, or transporting. A low-intensity cavitation process with air being injected into water was studied to determine the microbubbles' efficiency when detaching L. monocytogenes from stainless steel and the surface of fresh cucumber and avocado. Stainless steel coupons (1″ × 2″), cucumber, and avocado surfaces were inoculated with L. monocytogenes (LCDC strain). After 1, 24 or 48 h, loosely attached cells were washed off, and inoculated areas were targeted by microbubbles (~0.1-0.5 mm dia.) through a bubble diffuser (1.0 L air/min) for 1, 2, 5, or 10 min. For steel, L. monocytogenes (48 h drying) detachment peaked at 2.95 mean log reduction after 10 min of microbubbles when compared to a no-bubble treatment. After 48 h pathogen drying, cucumbers treated for 10 min showed a 1.78 mean log reduction of L. monocytogenes. For avocados, L. monocytogenes (24 h drying) detachment peaked at 1.65 log reduction after 10 min of microbubbles. Microbubble applications may be an effective, economical, and environmentally friendly way to remove L. monocytogenes, and possibly other bacterial pathogens, from food contact surfaces and the surfaces of whole, intact fresh produce.

Factors that predict Listeria prevalence in distribution centers handling fresh produce.

Listeria species prevalence has been investigated at nearly all stages of the fresh produce supply chain; however, it has not been examined in transportation and distribution center (DC) related environments. Between December 2019 and March 2021, 18 DCs handling fresh produce were environmentally sampled for Listeria. Swab samples were collected from a variety of surfaces (e.g., floors, pallets, forklifts) in several areas of each DC (e.g., cold storage, shipping and receiving docks). Impaction air samples, relative humidity, and temperature data were also collected. While no Listeria spp. were isolated from air samples (n = 170), they were isolated from 49 of 982 (ca. 5%) environmental samples. The proportion of Listeria spp. positive samples varied significantly across individual DCs (P < 0.01). Several facility characteristics were significantly associated with a Listeria spp. positive sample, such as zone, sampling site dryness, and cleaning regimen. A random forest model (sensitivity: 0.786, specificity: 0.874) identified geographical location and general sampling location (e.g., cold storage rooms, shipping docks) as the two most important variables associated with Listeria spp. detection. This study identified likely harborage sites (e.g., floors, cleaning equipment) of Listeria spp. in DCs across the US and emphasized the importance of sanitation operations in Listeria-prone areas.

Initial and Final Cell Concentrations Significantly Influence the Maximum Growth Rate of Listeria monocytogenes in Published Literature Data for Whole Intact Fresh Produce.

ABSTRACT: Listeria monocytogenes has shown the ability to grow on fresh uncut produce; however, the factors that control growth are not well understood. Peer-reviewed journal articles (n = 29) meeting the inclusion criteria and related to the growth of L. monocytogenes on fresh produce were found through university library databases and Google Scholar searches. Growth models were fit to each of the extracted 130 data sets to estimate log CFU per day rates of growth by using the DMFit tool. Multiple linear stepwise regression models for factors influencing growth rate were developed using R software. Factors included were temperature, nutrient level of inoculation buffer, initial cell concentration, final cell concentration, inoculation method, container permeability, and surface characteristics. The full model produced adjusted R2, Akaike information criterion, and root mean square error values of 0.41, 488, and 1.61, respectively. Stepwise regression resulted in a reduced model with parameters for incubation temperature, inoculation buffer type, initial and final cell concentrations, container characteristics, and produce surface characteristics. Model fit statistics improved slightly in the reduced model. A further reduced three-parameter model included storage temperature and initial and final cell concentrations, with interaction terms. This three-parameter model had adjusted R2, Akaike information criterion, and root mean square error values of 0.66, 417, and 1.24, respectively. Incubation temperature (P = 1.00E-09) initial cell concentration (P = 3.05E-12), and final cell concentration (P = 4.17E-09) all had highly significant effects on maximum growth rate. Our findings show the importance of inoculum concentration and produce microbial carrying capacity on the estimated growth rate and highlight the overall importance that temperature has on growth rate. Future experiments should consider initial inoculum concentration carefully when conducting growth studies for L. monocytogenes on whole produce.

Prevalence of Listeria monocytogenes and indicator microorganisms in Florida cantaloupe packinghouses, 2013-2014.

Prior to the 2013 cantaloupe season, the US Food and Drug Administration notified the industry that inspections of a subset of packinghouses would commence that year in response to the 2011 Listeria monocytogenes outbreak associated with cantaloupe. In May 2013, five Florida cantaloupe packinghouses participated in an environmental monitoring survey to evaluate their sanitary conditions prior to a potential FDA inspection. Two facilities participated again in 2014. Surface swabs (n = 374) were collected in each facility and included up to 60 food contact and non-food contact surfaces, including water. Samples were enumerated for total plate counts (TPC), generic Escherichia coli, and coliforms, and enriched for Listeria. Listeria were confirmed and speciated by sequencing of the partial sigB gene, and further characterized by pulsed field gel electrophoresis (AscI and Apal). In 2013, two zone 1 surfaces in same facility, were positive for L. monocytogenes (2/233). No L. monocytogenes was detected (n = 103) in the two facilities sampled the following year, including the previously L. monocytogenes-positive facility. Prevalence of L. monocytogenes in FL cantaloupe packinghouses was generally low (2/374), compared to other food environments. TPC, coliforms, E. coli and Listeria spp. were poor indicators of L. monocytogenes contamination in Florida packinghouses.

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.

A Systematic Review of Listeria Species and Listeria monocytogenes Prevalence, Persistence, and Diversity throughout the Fresh Produce Supply Chain.

Listeria monocytogenes is an increasing food safety concern throughout the produce supply chain as it has been linked to produce associated outbreaks and recalls. To our knowledge, this is the first systematic literature review to investigate Listeria species and L. monocytogenes prevalence, persistence, and diversity at each stage along the supply chain. This review identified 64 articles of 4863 candidate articles obtained from four Boolean search queries in six databases. Included studies examined naturally detected/isolated Listeria species and L. monocytogenes in fresh produce-related environments, and/or from past fresh produce associated outbreaks or from produce directly. Listeria species and L. monocytogenes were detected in each stage of the fresh produce supply chain. The greatest prevalence of Listeria species was observed in natural environments and outdoor production, with prevalence generally decreasing with each progression of the supply chain (e.g., packinghouse to distribution to retail). L. monocytogenes prevalence ranged from 61.1% to not detected (0.00%) across the entire supply chain for included studies. Listeria persistence and diversity were also investigated more in natural, production, and processing environments, compared to other supply chain environments (e.g., retail). Data gaps were identified for future produce safety research, for example, in the transportation and distribution center environment.