Author
Listed:
- Conte, Fred S.
- Ahmadi, Abbas
Abstract
According to the United States (U.S.), National Shellfish Sanitation Program (NSSP) standards, the shellfish growing areas in modeling, shellfish sanitation, water quality, shellfish closure rules the U.S. must be closed for harvest when the estimated 90th percentile of fecal coliform concentrations exceeds the NSSP limit of 14/43 Most Probable Number/100 mL (NSSP, 2009, NSSP, 2011). Pearl is a model that identifies harvest areas at risk for fecal coliform contamination (Conte and Ahmadi, 2012). Once the risk areas are identified, the Aquarius model can be used to adjust closure rules (Conte and Ahmadi, 2011). In multi-state analyses using the Pearl model, we have developed a hypothesis that state agencies are inadvertently applying the model's Pearl Limit of 8/26 MPN/100 mL in place of the NSSP limit of 14/43 MPN/100 mL for a 5-tube test to guard against shellfish-related illnesses (Conte and Ahmadi, 2012; 2013; 2014). The datasets used to develop the hypothesis were from Oakland Bay, Washington (Pacific Northwest), Arcata Bay, California (Pacific Northern California), and seven shellfish bays of the Texas Gulf Coast (Western Gulf of Mexico). The main purpose of this paper is to test this hypothesis using different datasets from shellfish growing areas in the states of Alabama (Eastern Gulf of Mexico), Florida (Eastern Gulf of Mexico and south Atlantic Coast) and Georgia (South Atlantic Coast), all located in the southeastern United States. An additional objective is to use the state’s datasets in Pearl analyses to detect the shellfish growing areas that pose a possible health risk to shellfish consumers during some periods
Suggested Citation
Conte, Fred S. & Ahmadi, Abbas, 2014.
"Analysis of Shellfish Growing Areas of Alabama, Florida and Georgia, USA - Using the Pearl Shellfish Sanitation Model,"
International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 5(4), pages 1-18, November.
Handle:
RePEc:ags:ijofsd:199382
DOI: 10.22004/ag.econ.199382
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