Progress 10/01/11 to 09/30/14
Outputs
Target Audience: Target audiences include other academic researchers as well as industry and government involved in assuring the microbial safety of fresh produce production. A specific key target audience are; small and medium farmers that grow and harvest produce in New York. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? The project has provided training and professional development opportunities for two post-doctoral fellows that have been partially supported by this project; this project thus is has made contributions to the training of future food safety professionals; one of these pot-docs is now employed by FDA, while the other one is a faculty member at a US university. How have the results been disseminated to communities of interest? Results from this project have been communicated through a peer-reviewed manuscript in the Journal of Food Protection as well as an oral presentation at the 2013 International Association of Food Protection Annual Meeting in Charlotte, NC (July 18-31, 2013); this meeting is heavily attended by food safety professionals from industry and government and this presentation thus allowed for communication of our data to potential end users. Results were also reported the PI M. Wiedmann through a presentation entitled "Listeria 101", which was given at the Center for Produce Safety (CPS) 2013 Produce Research Symposium in Rochester, NY (June 25 - 26, 2013). What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Initial work under this project developed GIS-enabled modeling tools to predict the risk of produce contamination in the production environment. Previously collected research data was used in combination with remotely-sensed data to identify key factors (output from CT analysis) that may predict pathogen prevalence in the environment. Using the topographical factors (e.g., proximity to impervious surfaces, water) identified for each of the respective foodborne pathogens in the CTs, we can develop maps to identify locations that may be more, or less likely to act as reservoirs for environmental pathogen contamination. These maps, with the use of GIS technologies, can be produced for any geographical location (baring remotely-sensed data exists). This would allow growers to develop GAPs aimed at reducing the risk of contamination in the production environment which are specific to individual farms. For example, this highly individualized information may lead growers to plant higher risk crops in locations where the pathogen prevalence is predicted to be extremely low, as outlined by the GIS algorithm. Subsequent work has focused on applying landscape ecology tools to better understand transmission and ecology of Listeria monocytogenes and Listeria spp. on produce preharvest environments and surrounding environments that may serve as sources of these pathogens. Listeria species have been isolated from diverse environments, often at considerable prevalence, and are known to persist in food processing facilities. The presence of generic Listeria spp. has been suggested to be a marker for L. monocytogenes contamination. Therefore, a specific study was conducted to (i) determine the prevalence and diversity of Listeria spp. in produce preharvest and natural environments and (ii) identify geographical and meteorological factors that affect the prevalence of Listeria spp. in these environments. These data were also used to evaluate generic Listeria spp. as index organisms for L. monocytogenes in the produce preharvest environment. Samples were collected from produce preharvest (n=588) and natural (n=734) environments in New York State (NYS) and analyzed for Listeria spp. The prevalence of Listeria spp. was approximately 34% and 33% for samples obtained from the produce preharvest (201/588) and natural environment (245/734), respectively. The co-isolation of L. monocytogenes and at least one other Listeria spp. from a sample was significantly higher in the produce preharvest environment (9%), compared to the natural environment (3%). Soil moisture and proximity to water and pastures were identified as important predictors for detection of each Listeria spp. detected in the produce preharvest environment, while elevation, study site and proximity to pastures were identified as important predictors for detection of each Listeria spp. detected in the natural environment. Our data show that Listeria spp. were commonly isolated in both agricultural and non-agricultural environments in NYS. The prevalence of Listeria spp. was similar in produce preharvest and natural environments; however, the prevalence of L. monocytogenes was higher in the produce preharvest environment. Of fourteen factors evaluated, only proximity to pastures was identified as an important factor for classification of samples as L. monocytogenes-, L. innocua-, L. seeligeri- and L. welshimeri- positive in both produce preharvest and natural environments, suggesting an important role of pastures as a source of Listeria spp. Our data also show certain species of Listeria are more prevalent in each environment and Listeria spp. isolation is influenced by different environmental factors that exist in these two environments. Sampling locations were in NYS so findings may only be applicable to the northeastern US; therefore, further studies are needed to determine if these findings presented here can be applied to other regions. Our findings suggest limited value to the application of Listeria spp. as index organisms for L. monocytogenes in NYS produce preharvest environments. Instead, testing directly for L. monocytogenes may be more effective due to the relatively high prevalence of the pathogen, compared to other pathogens of interest in produce, in NYS produce preharvest environments. Additional work conducted as part of this project valuated foodborne the impact of flooding on foodborne pathogen transmission and presence in agricultural environments, using flooding in the Schoharie River Valley of New York associated with the 2011 Hurricane Irene as a model. Approximately 35,125 acres of agricultural lands were impacted by flooding in Schoharie County. The economic loss to agriculture in New York State was estimated at $45 million. Microbiological and heavy metal contamination in the flooded areas were the primary concerns reported by farm owners who permitted sampling of soils, water and surfaces on impacted farms. In order to better understand the extent, retention and remediation of microbiological contaminants in croplands, we conducted a spatially structured field study of E. coli and Salmonella prevalence in two farms that were heavily impacted by flooding from Hurricane Irene. Sampling was conducted 21, 44, and 238 days post-flooding. At 21 days post-flood, there were still visible signs of flooding, such as standing water in fields and elevated water levels in surrounding water bodies (e.g., Schoharie River) to fields. Analysis using a randomForest model indicated that (i) the prevalence of microbial contaminants on farm surfaces and in soil decreased over time, (ii) there was no difference in microbial contamination attributable to farm alone, (iii) the spatial pattern of microbiological contamination on farm surfaces changed over increasing time post-flooding. We also found the overall prevalence of Salmonella highest at 21 days post-flood (4.7%). At 44 days post-flood, the prevalence of Salmonella had dropped to nearly half (2.5%). Consistent with previous studies that have shown an association between precipitation and Salmonella prevalence, we found a 4.6% prevalence of Salmonella at 238 days post-flood, a sampling time point that was not pre-ceded by 36 mm of rainfall over the five previous days.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2014
Citation:
Chapin, T.C., K.K. Nightingale, R.W. Worobo, M. Wiedmann, L.K. Strawn. 2014. Geographical and Meteorological Factors Associated with Isolation of Listeria species in New York State Produce Production and Natural Environments. J. Food Prot. 77: 19191928
|
Progress 10/01/12 to 09/30/13
Outputs
Target Audience: Target audiences include other academic researchers as well as industry and government involved in assuring the microbial safety of fresh produce production. Specific key target audiences are small and medium farmers that grow and harvest produce in New York. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? The project has provided training and professional development opportunities for a post-doctoral fellow that have been partially supported by this project; this project thus is continuing to make contributions to the training of future food safety professionals that can address the produce safety challenges faced by the US produce industry. How have the results been disseminated to communities of interest? As detailed in the publication section above, results from this project have been communicated through an oral presentation at the 2013 International Association of Food Protection Annual Meeting in Charlotte, NC ( July 18-31, 2013); this meeting is heavily attended by food safety professionals from industry and government and this presentation thus allowed for communication of our data to potential end users. Results were also reported the PI M. Wiedmann through a presentation entitled “Listeria 101”, which was given at the Center for Produce Safety (CPS) 2013 Produce Research Symposium in Rochester, NY (June 25 – 26, 2013). What do you plan to do during the next reporting period to accomplish the goals? In the next reporting period, we plan to (i) use molecular subtyping tools to further characterize the genetic diversity among pathogen isolates from pre-harvest produce environments to understand how foodborne pathogens are transmitted across landscapes (this will complete Obj. 2) and to (ii) complete independent testing of our models on Listeria transmission on an independent data set to further refine possible intervention strategies that could be used by industry.
Impacts
What was accomplished under these goals?
This reporting period we have focused on applying landscape ecology tools to better understand transmission and ecology of Listeria monocytogenes and Listeria spp. on produce preharvest environments and surrounding environments that may serve as sources of these pathogens. Listeria species have been isolated from diverse environments, often at considerable prevalence, and are known to persist in food processing facilities. The presence of generic Listeria spp. has been suggested to be a marker for L. monocytogenes contamination. Therefore, a specific study was conducted to (i) determine the prevalence and diversity of Listeria spp. in produce preharvest and natural environments and (ii) identify geographical and meteorological factors that affect the prevalence of Listeria spp. in these environments. These data were also used to evaluate generic Listeria spp. as index organisms for L. monocytogenes in the produce preharvest environment. Samples were collected from produce preharvest (n=588) and natural (n=734) environments in New York State (NYS) and analyzed for Listeria spp. The prevalence of Listeria spp. was approximately 34% and 33% for samples obtained from the produce preharvest (201/588) and natural environment (245/734), respectively. The co-isolation of L. monocytogenes and at least one other Listeria spp. from a sample was significantly higher in the produce preharvest environment (9%), compared to the natural environment (3%). Soil moisture and proximity to water and pastures were identified as important predictors for detection of each Listeria spp. detected in the produce preharvest environment, while elevation, study site and proximity to pastures were identified as important predictors for detection of each Listeria spp. detected in the natural environment. Our data show that Listeria spp. were commonly isolated in both agricultural and non-agricultural environments in NYS. The prevalence of Listeria spp. was similar in produce preharvest and natural environments; however, the prevalence of L. monocytogenes was higher in the produce preharvest environment. Of fourteen factors evaluated, only proximity to pastures was identified as an important factor for classification of samples as L. monocytogenes-, L. innocua-, L. seeligeri- and L. welshimeri- positive in both produce preharvest and natural environments, suggesting an important role of pastures as a source of Listeria spp. Our data also show certain species of Listeria are more prevalent in each environment and Listeria spp. isolation is influenced by different environmental factors that exist in these two environments. Sampling locations were in NYS so findings may only be applicable to the northeastern US; therefore, further studies are needed to determine if these findings presented here can be applied to other regions. Our findings suggest limited value to the application of Listeria spp. as index organisms for L. monocytogenes in NYS produce preharvest environments. Instead, testing directly for L. monocytogenes may be more effective due to the relatively high prevalence of the pathogen, compared to other pathogens of interest in produce, in NYS produce preharvest environments.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2013
Citation:
Chapin, T.K., S.N. Masiello, M. Wiedmann, P.W. Bergholz and L.K. Strawn. The Effect of Species on Spatio-temporal Distribution and Geographical Predictors of Listeria in Natural Areas and the Produce Preharvest Environment of New York State. International Association of Food Protection Annual Meeting, Charlotte, NC, July 18-31, 2013 (oral presentation
|
Progress 10/01/11 to 09/30/12
Outputs
OUTPUTS: Despite the implementation of produce safety practices, foodborne outbreaks associated with fresh produce continue to result in significant illnesses, hospitalizations and deaths. Many of these produce associated outbreaks have been traced back to environmental reservoirs located in the production environment. Each farm landscape represents a unique combination of numerous environmental characteristics that we hypothesize to set the baseline conditions for persistence of foodborne pathogens in or near produce fields. Therefore, we aimed to identify specific, remotely-sensed, landscape features, soil properties, and meteorological events that may be associated with foodborne pathogen prevalence. Classification tree (CT) models were employed to identify factors that delineated the presence and absence of the respective pathogen. Briefly, CTs start with a root node containing all samples and recursively split sample sites by minimizing the mixture between positive and negative samples for the selected pathogen. The L. monocytogenes CT identified soil moisture, temperature, and proximity to three land cover classes: water, impervious surfaces, and pasture/hay grass, as factors that influence the likelihood of detecting L. monocytogenes. The prevalence of L. monocytogenes in samples collected within 37.5 m of waterways was 39%, compared to only 12% in samples located farther than 37.5 m from waterways. In samples locations ≥ 37.5 m from water, temperature was identified as the next split. Temperatures that were lower than approximately 2 degrees C below average had 21% prevalence, but samples from warmer temperatures had only 7% prevalence. Soil moisture was the next identified factor. Using remotely sensed soil property data for available water storage, it was shown soils with available water storage in 0-25 cm depth > 4 cm yielded samples with 31% prevalence versus 10% prevalence in less moist soils. Proximity to pastures was also identified as an important factor in the prediction of L. monocytogenes prevalence. Moist soil locations sampled at cooler temperatures within 62.5 m of a pasture had 50% versus 7.5% L. monocytogenes prevalence in similar sample locations further than 62.5 m from pasture class land areas. The Salmonella CT identified drainage class, precipitation and soil moisture as the most important factors in dividing Salmonella positive and negative samples. A location where drainage is classified as very poor, somewhat poor, poor, and somewhat drained was determined to have a higher Salmonella prevalence (9%) than a location where drainage is classified as moderately well drained and well drained (1.2%). After the tree determined that poorly drained soils contained more Salmonella, the algorithm then produced a rule indicating that soils near the upper limit of available water storage were more likely to be negative. Salmonella was less likely to occur in soils with available water storage (at 0-25 cm) of 10 cm, which was the maximum value in the soil database. Precipitation formed another split, predicting Salmonella was more prevalent (12%) when measurable precipitation occurred within 3 days prior to sampling. PARTICIPANTS: Individuals who worked on this project during the reporting period include Dr. Martin Wiedmann, PD, Cornell University; Dr. Randy Worobo, co-PD, Cornell University; Dr. Elizabeth Bihn, Senior Extension Associate, Cornell University; Dr. Peter Bergholz, North Dakota State University; Laura Strawn, PhD Candidate, Cornell University; Travis Chapin, PhD Student, Cornell University. TARGET AUDIENCES: Target audiences include other academic researchers, fruit and vegetable growers, as well as industry and government agencies that work in the area of produce safety; specifically individuals or bodies who develop and mandate Good Agricultural Practices (GAPs) plans. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
The major outcome from this research project over the last year is the development of a framework for using GIS-enabled modeling to predict the risk of produce contamination in the production environment. Previously collected research data was used in combination with remotely-sensed data to identify key factors (output from CT analysis) that may predict pathogen prevalence in the environment. Using the topographical factors (e.g., proximity to impervious surfaces, water) identified for each of the respective foodborne pathogens in the CTs, we can develop maps to identify locations that may be more, or less likely to act as reservoirs for environmental pathogen contamination. These maps, with the use of GIS technologies, can be produced for any geographical location (baring remotely-sensed data exists). This would allow growers to develop GAPs aimed at reducing the risk of contamination in the production environment which are specific to individual farms. For example, this highly individualized information may lead growers to plant higher risk crops in locations where the pathogen prevalence is predicted to be extremely low, as outlined by the GIS algorithm. Validation (Obj 3) is required to determine the ultimate usefulness of the information obtained from the CTs, and will provide us with high confidence that the recommendations to growers derived from the CTs are robust and applicable.
Publications
- Chapin TK, Wiedmann M., Bergholz PW. T8-06 Geographical Factors that Influence the Spatio-temporal Distrubution of Listeria monocytogenes in Natural Environments of New York State. International Association of Food Protection Annual Meeting, Providence, RI. July 2012.
|
|