Protecting the safety and quality of liveoysters through the integration ofpredictive microbiology in cold supplychains

摘要: Vibrio parahaemolyticus is a bacterial species indigenous to marine environments and can accumulate in oysters. Some V. strains are pathogenic seafoodborne outbreaks observed worldwide. This pathogen can reach infectious levels in oysters if post-harvest temperatures not properly controlled. The aim of this thesis was to support oyster supply chain management by developing predictive microbiological tools to improve the safety quality oysters market. A model was produced injecting Pacific (Crassostrea gigas) harvested Tasmania with cocktail non-pathogenic V. strains, measuring population changes over time at static storage temperatures from 4 30oC. In parallel, total viable bacteria count (TVC) was measured. The TVC growth models were then evaluated and Sydney Rock (Saccostrea glomerata) harvested New South Wales containing natural populations parahaemolyticus. Oysters stored temperatures from 15 28oC, viability measured. In Pacific oysters, all tested while V. only 23 28oC. Sydney oysters, TVC 24oC did grow any storage temperature tested. These interesting findings potentially indicate that have enhanced anti-bacterial defences compared that commercial controls manage be different. Consistently higher rates in Tasmanian versus may been caused different factors. They include variations background competitive flora, rates among and/or natural community structure influenced conditions harvest site or during shipment laboratory. Nevertheless, overall performance “fail-safe” for predicting growth of would preferred public health tool. The integrated in an Excel® software tool. allows users input time-temperature profiles and analyse effects dynamic storage normally found supply chains on growth. tool five simulated oyster supply chains (refrigerated non-refrigerated). Observed predicted V. over-estimation mean 2.30 2.40 as determined by the bias factor index. Reasons over-estimations likely same those model validation experiments. Uncertainty variability associated chains. Therefore, a stochastic which encompassed operations farm consumer was built using ModelRisk® risk analysis software. case study generated probabilistic distributions percentage containing each operation chain. results used an objective evaluation influence short long summer winter seasons. stochastic help industry evaluate of oyster cold chains, enable real-time decisions coupled suitable traceability systems. It also provide managers valuable information about V. exposure levels. Finally, order better understand microbial distribution and storage, dynamics communities using 16S rRNA-based terminal restriction length polymorphism clone library analyses. Significant differences community composition observed, the predominant identified fresh temperatures. High diversity up 73 genera-related identified clones among samples. Psychrilyobacter spp. a potential spoilage indicator future shelf-life studies, Polynucleobacter a bacterial group related Alkaliflexus possible indicators control in quantitative correlations and the freshness should explored determine whether predominant microbes represent significant “specific organisms”, if they antagonistic human pathogens