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2011/752 World Seafood Congress and collaboration with Dr Salina Parveen to discuss comparisons of Vibrio parahaemolyticus models for Australian Pacific, Sydney Rock and American Oysters at the University of Maryland
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2011/752 World Seafood Congress and collaboration with Dr Salina Parveen to discuss comparisons of Vibrio parahaemolyticus models for Australian Pacific, Sydney Rock and American Oysters at the University of Maryland



By Mark Tamplin

 

Vibrio spp. are bacteria that naturally occur in oysters. Some Vibrio spp. such as V. parahaemolyticus cause human disease when levels are high and oysters are eaten raw. Predictive tools can be used to estimate V. parahaemolyticus levels in oysters, and to monitor and design cold chains that enhance oyster safety and quality. Historically, international risk management strategies have been driven mostly by data and predictive models generated in the USA for the American (Eastern) oyster. This presents a risk to Australian companies if USA models are not relevant to V. parahaemolyticus growth profiles in Australian oyster species.

 

The Seafood CRC project's, 2007/700 and 2008/719, produced predictive models that confirmed V. parahaemolyticus shows a different temperature growth profile in Pacific and Sydney rock oysters. Through this travel grant, the results of these projects were communicated to an international audience of industry and government representatives at the World Seafood Congress. This activity advanced relationships with key USA and international policy makers that could influence commercial markets for Australian oysters. The meeting also provided a forum to interact with key researchers in the field, resulting in better definition of research programs that may benefit Australian companies.

 

The travel grant also provided an opportunity to meet with Dr Salina Parveen, a key collaborator with USA Food and Drug Administration in the development of predictive models used to manage the risk of Vibrio species in oysters. As a result, a forthcoming manuscript will be published that shows separate predictive models are needed for Australian oyster species.