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.

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.

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.

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.

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.

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields.

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce.

Spatial and Temporal Factors Associated with an Increased Prevalence of Listeria monocytogenes in Spinach Fields in New York State.

While rain and irrigation events have been associated with an increased prevalence of foodborne pathogens in produce production environments, quantitative data are needed to determine the effects of various spatial and temporal factors on the risk of produce contamination following these events. This study was performed to quantify these effects and to determine the impact of rain and irrigation events on the detection frequency and diversity of Listeria species (including L. monocytogenes) and L. monocytogenes in produce fields. Two spinach fields, with high and low predicted risks of L. monocytogenes isolation, were sampled 24, 48, 72, and 144 to 192 h following irrigation and rain events. Predicted risk was a function of the field's proximity to water and roads. Factors were evaluated for their association with Listeria species and L. monocytogenes isolation by using generalized linear mixed models (GLMMs). In total, 1,492 (1,092 soil, 334 leaf, 14 fecal, and 52 water) samples were collected. According to the GLMM, the likelihood of Listeria species and L. monocytogenes isolation from soil samples was highest during the 24 h immediately following an event (odds ratios [ORs] of 7.7 and 25, respectively). Additionally, Listeria species and L. monocytogenes isolates associated with irrigation events showed significantly lower sigB allele type diversity than did isolates associated with precipitation events (P = <0.001), suggesting that irrigation water may be a point source of L. monocytogenes contamination. Small changes in management practices (e.g., not irrigating fields before harvest) may therefore reduce the risk of L. monocytogenes contamination of fresh produce.

Distributions of Salmonella subtypes differ between two U.S. produce-growing regions.

Salmonella accounts for approximately 50% of produce-associated outbreaks in the United States, several of which have been traced back to contamination in the produce production environment. To quantify Salmonella diversity and aid in identification of Salmonella contamination sources, we characterized Salmonella isolates from two geographically diverse produce-growing regions in the United States. Initially, we characterized the Salmonella serotype and subtype diversity associated with 1,677 samples collected from 33 produce farms in New York State (NYS). Among these 1,677 samples, 74 were Salmonella positive, yielding 80 unique isolates (from 147 total isolates), which represented 14 serovars and 23 different pulsed-field gel electrophoresis (PFGE) types. To explore regional Salmonella diversity associated with production environments, we collected a smaller set of samples (n = 65) from South Florida (SFL) production environments and compared the Salmonella diversity associated with these samples with the diversity found among NYS production environments. Among these 65 samples, 23 were Salmonella positive, yielding 32 unique isolates (from 81 total isolates), which represented 11 serovars and 17 different PFGE types. The most common serovars isolated in NYS were Salmonella enterica serovars Newport, Cerro, and Thompson, while common serovars isolated in SFL were Salmonella serovars Saphra and Newport and S. enterica subsp. diarizonae serovar 50:r:z. High PFGE type diversity (Simpson's diversity index, 0.90 ± 0.02) was observed among Salmonella isolates across both regions; only three PFGE types were shared between the two regions. The probability of three or fewer shared PFGE types was <0.000001; therefore, Salmonella isolates were considerably different between the two sampled regions. These findings suggest the potential for PFGE-based source tracking of Salmonella in production environments.

Listeria floridensis sp. nov., Listeria aquatica sp. nov., Listeria cornellensis sp. nov., Listeria riparia sp. nov. and Listeria grandensis sp. nov., from agricultural and natural environments.

Sampling of agricultural and natural environments in two US states (Colorado and Florida) yielded 18 Listeria-like isolates that could not be assigned to previously described species using traditional methods. Using whole-genome sequencing and traditional phenotypic methods, we identified five novel species, each with a genome-wide average BLAST nucleotide identity (ANIb) of less than 85% to currently described species. Phylogenetic analysis based on 16S rRNA gene sequences and amino acid sequences of 31 conserved loci showed the existence of four well-supported clades within the genus Listeria; (i) a clade representing Listeria monocytogenes, L. marthii, L. innocua, L. welshimeri, L. seeligeri and L. ivanovii, which we refer to as Listeria sensu stricto, (ii) a clade consisting of Listeria fleischmannii and two newly described species, Listeria aquatica sp. nov. (type strain FSL S10-1188(T) = DSM 26686(T) = LMG 28120(T) = BEI NR-42633(T)) and Listeria floridensis sp. nov. (type strain FSL S10-1187(T) = DSM 26687(T) = LMG 28121(T) = BEI NR-42632(T)), (iii) a clade consisting of Listeria rocourtiae, L. weihenstephanensis and three novel species, Listeria cornellensis sp. nov. (type strain TTU A1-0210(T) = FSL F6-0969(T) = DSM 26689(T) = LMG 28123(T) = BEI NR-42630(T)), Listeria grandensis sp. nov. (type strain TTU A1-0212(T) = FSL F6-0971(T) = DSM 26688(T) = LMG 28122(T) = BEI NR-42631(T)) and Listeria riparia sp. nov. (type strain FSL S10-1204(T) = DSM 26685(T) = LMG 28119(T) = BEI NR- 42634(T)) and (iv) a clade containing Listeria grayi. Genomic and phenotypic data suggest that the novel species are non-pathogenic.

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.

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.

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.

Risk factors associated with Salmonella and Listeria monocytogenes contamination of produce fields.

Identification of management practices associated with preharvest pathogen contamination of produce fields is crucial to the development of effective Good Agricultural Practices (GAPs). A cross-sectional study was conducted to (i) determine management practices associated with a Salmonella- or Listeria monocytogenes-positive field and (ii) quantify the frequency of these pathogens in irrigation and nonirrigation water sources. Over 5 weeks, 21 produce farms in New York State were visited. Field-level management practices were recorded for 263 fields, and 600 environmental samples (soil, drag swab, and water) were collected and analyzed for Salmonella and L. monocytogenes. Management practices were evaluated for their association with the presence of a pathogen-positive field. Salmonella and L. monocytogenes were detected in 6.1% and 17.5% of fields (n = 263) and 11% and 30% of water samples (n = 74), respectively. The majority of pathogen-positive water samples were from nonirrigation surface water sources. Multivariate analysis showed that manure application within a year increased the odds of a Salmonella-positive field (odds ratio [OR], 16.7), while the presence of a buffer zone had a protective effect (OR, 0.1). Irrigation (within 3 days of sample collection) (OR, 6.0), reported wildlife observation (within 3 days of sample collection) (OR, 6.1), and soil cultivation (within 7 days of sample collection) (OR, 2.9) all increased the likelihood of an L. monocytogenes-positive field. Our findings provide new data that will assist growers with science-based evaluation of their current GAPs and implementation of preventive controls that reduce the risk of preharvest contamination.

Landscape and meteorological factors affecting prevalence of three food-borne pathogens in fruit and vegetable farms.

Produce-related outbreaks have been traced back to the preharvest environment. A longitudinal study was conducted on five farms in New York State to characterize the prevalence, persistence, and diversity of food-borne pathogens in fresh produce fields and to determine landscape and meteorological factors that predict their presence. Produce fields were sampled four times per year for 2 years. A total of 588 samples were analyzed for Listeria monocytogenes, Salmonella, and Shiga toxin-producing Escherichia coli (STEC). The prevalence measures of L. monocytogenes, Salmonella, and STEC were 15.0, 4.6, and 2.7%, respectively. L. monocytogenes and Salmonella were detected more frequently in water samples, while STEC was detected with equal frequency across all sample types (soil, water, feces, and drag swabs). L. monocytogenes sigB gene allelic types 57, 58, and 61 and Salmonella enterica serovar Cerro were repeatedly isolated from water samples. Soil available water storage (AWS), temperature, and proximity to three land cover classes (water, roads and urban development, and pasture/hay grass) influenced the likelihood of detecting L. monocytogenes. Drainage class, AWS, and precipitation were identified as important factors in Salmonella detection. This information was used in a geographic information system framework to hypothesize locations of environmental reservoirs where the prevalence of food-borne pathogens may be elevated. The map indicated that not all croplands are equally likely to contain environmental reservoirs of L. monocytogenes. These findings advance recommendations to minimize the risk of preharvest contamination by enhancing models of the environmental constraints on the survival and persistence of food-borne pathogens in fields.

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.

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.