Molluscan shellfish are high-valued seafood products that require careful supply chain management to guarantee both product safety and quality. Together, storage time and temperature exert the greatest influence on microbial food safety and quality, and must be controlled during oyster processing, transport and storage. Vibrio species are a natural component of marine and estuarine environments, unlike faecal bacteria which are typically introduced into growing waters by land run-off. Consequently, it is prudent to assume that all live shellfish may potentially contain naturally-occurring Vibrio spp. These risks, including the quality of oysters, can be controlled by proper cold chain management. Improper cold chain handling may increase risk, decrease quality and ultimately affect value and the brand. The negative consequences can easily be spread across the entire industry. Thus, a proactive strategy is required to control and predict risk, with added benefits for maintaining product quality. This can be achieved through validated tools (models) that allow all stakeholders in the cold chain to monitor how conditions influence the safety and quality of oysters. The impact will include 1) improved product safety, 2) an optimised cold chain, 3) higher product quality, 4) greater access to export markets and 5) a more cooperative regulatory environment.
Vibrio parahaemolyticus is a bacterial species indigenous to marine environments and can accumulate in oysters. Some V. parahaemolyticus strains are pathogenic and seafoodborne outbreaks are observed worldwide. This pathogen can reach infectious levels in oysters if post-harvest temperatures are not properly controlled. The aim of this thesis was to support oyster supply chain management by developing predictive microbiological tools to improve the safety and quality of oysters in the market. A predictive model was produced by injecting Pacific oysters (Crassostrea gigas) harvested in Tasmania with a cocktail of pathogenic and non-pathogenic V. parahaemolyticus strains, and measuring population changes over time at static storage temperatures from 4 to 30ºC. In parallel, the total viable bacteria count (TVC) model was measured.
The V. parahaemolyticus and TVC growth models were then evaluated with Pacific and Sydney Rock oysters (Saccostrea glomerata) harvested in New South Wales containing natural populations of V. parahaemolyticus. The model was developed into a software tool and evaluated in five different simulated oyster supply chains. Due to high uncertainty and variability associated with oyster supply chains a stochastic model which encompassed the operations from oyster farm to the consumer was built using ModelRisk® risk analysis software. The stochastic model may help the oyster industry evaluate the performance of oyster cold chains, and potentially enable real-time decisions if coupled with suitable traceability systems. It can also provide risk managers with valuable information about V. parahaemolyticus exposure levels..
Finally, in order to better understand microbial changes in oysters during distribution and storage, the dynamics of microbial communities in Pacific oysters was determined using 16S rRNA-based terminal restriction length polymorphism and clone library analyses. Significant differences in bacterial community composition were observed and the predominant bacteria were identified for fresh and stored oysters at different temperatures and storage temperature control and spoilage indicator organisms were identified..