Development of predictive growth models of Aeromonas hydrophila on raw tuna Thunnus orientalis as a function of storage temperaturesopen access
- Kim, Ji Yoon; Jeon, Eun Bi; Song, Min Gyu; Park, Sung Hee; Park, Shin Young
- Issue Date
- Raw tuna; Aeromonas hydrophila; Temperature; Baranyi model; Predictive growth model
- LWT-FOOD SCIENCE AND TECHNOLOGY, v.156
- Journal Title
- LWT-FOOD SCIENCE AND TECHNOLOGY
- This study developed predictive growth models for Aeromonas hydrophila on raw tuna as a function of storage temperatures (2-15 degrees C). At these storage temperatures, the primary models fit well (R-2 ; 0.97-0.98) with the Baranyi model to obtain lag time (LT) and specific growth rate (SGR). As the temperature increased, A. hydrophila growth increased. However, at 2 and 5 degrees C, no growth of A. hydrophila was observed over 7 days. The LT values were 4.99, 3.41, and 3.21 h, and SGR values were 0.02, 0.06, and 0.18 log CFU/h at 8, 11, and 15 degrees C, respectively. The secondary models were determined by nonlinear regression analysis; LT = 15.288-1.864 x T+0.069 x T-2, SGR = 0.149-0.037 x T+0.003 x T-2 (T; storage temperature). The suitability of the secondary models for LT and SGR was verified using mean square error (MSE; <0.01 internal validation, <0.02 external validation), bias factor (Br, 0.980-1.056 internal validation, 0.841-0.995 external validation), and accuracy factor (A(f), 1.296-1.305 internal validation, 1.127-1.231 external validation). These predictive models may be used in the prediction of A. hydrophila growth on raw tuna at various cold temperatures. Ultimately, the developed models could be beneficial for maintaining safe levels A. hydrophila during the processing and distribution of raw fish.
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- 해양과학대학 > Seafood science & Technology > Journal Articles
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