저장온도에 따른 마른김(Pyropia pseudolinearis)의 Bacillus cereus 성장예측모델 개발

Abstract

Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25°C). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R2≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25°C, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228- 0.0069*T1+0.0005*T1 2; LT=113.0685-9.6256*T1+0.2079*T1 2; MPD=1.6630+0.4284*T1-0.0080*T1 2 (where T1 is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤Bf ≤1.07), and accuracy factor (1.01≤Af ≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.