Shellfish monitoring for lipophilic phycotoxins in France, recommendation for an updated sampling strategy
Type | Proceedings paper | ||||||||
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Date | 2014 | ||||||||
Language | English | ||||||||
Other localization | http://www.cawthron.org.nz/publications/ICHA16-Proceedings.pdf | ||||||||
Author(s) | Thebault Anne1, Arnich Nathalie1, Belin Catherine2, Neaud-Masson Nadine2 | ||||||||
Affiliation(s) | 1 : Anses, Maisons-Alfort, France 2 : Ifremer, Nantes, France |
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Meeting | ICHA16 - 16th International Conference on Harmful Algae. 27th-31st October 2014, Wellington, New Zealand | ||||||||
Source | A. Lincoln MacKenzie [Ed]. Marine and Freshwater Harmful Algae. Proceedings of the 16 th International Confer ence on Harmful Algae, Wellington, New Zealand 27th - 31 st October 2014. Cawthron Institute, Nelson, New Zealand and International Society for the Study of Harmful Algae (ISSHA). ISBN 978 - 87 - 990827 - 5 - 9. Part. Surveillance and Managment. pp.242-245 | ||||||||
Keyword(s) | monitoring, shellfish, lipophilic phycotoxins, Bayesian inference | ||||||||
Abstract | In France, the sampling strategy for the official monitoring of lipophilic phycotoxins in bivalve shellfish relies on the definition of risk areas and high risk periods, during which a systematic weekly analysis of toxins in shellfish is performed. Since 2010, high risk periods are defined as follows: the occurrence of one result above the European regulatory limit (160 μg equivalent okadaic acid/kg shellfish) over the last 3 years leads to that month being considered a high risk period. This definition was established according to a statistical analysis of the official monitoring results for the period 2003-2008, based on the mouse bioassay (MBA) as the official analytical method. As of the 1st January 2010, the MBA has been replaced by LC-MS/MS. In 2014, a new statistical analysis was performed, based this time on results for the period 2010-2013 for which quantitative LC-MS/MS data are available. We tested the robustness of the definition set in 2010 and identified a new methodology to improve our sampling strategy for lipophilic toxins in bivalve shellfish, based on Bayesian inference. |
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