Development of predictive growth models of Aeromonas hydrophila on raw tuna Thunnus orientalis as a function of storage temperatures

嗜水气单胞菌 金枪鱼 图努斯 生物 滞后时间 食品科学 渔业 数学 动物科学 生物系统
作者
Ji Yoon Kim,Eun Bi Jeon,Min Gyu Song,Sung‐Hee Park,Shin Young Park
出处
期刊:Lebensmittel-Wissenschaft & Technologie [Elsevier BV]
卷期号:156: 113052-113052 被引量:13
标识
DOI:10.1016/j.lwt.2021.113052
摘要

This study developed predictive growth models for Aeromonas hydrophila on raw tuna as a function of storage temperatures (2–15 °C). At these storage temperatures, the primary models fit well (R2; 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 °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 °C, respectively. The secondary models were determined by nonlinear regression analysis; LT = 15.288–1.864 × T+0.069 × T2, SGR = 0.149–0.037 × T+0.003 × T2 (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 (Bf; 0.980–1.056 internal validation, 0.841–0.995 external validation), and accuracy factor (Af; 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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