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中国精品科技期刊2020
贺群, 黄和, 刘亚, 蒋志红, 励建荣. 面包虾中副溶血性弧菌在pH影响下生长预测模型的建立[J]. 食品工业科技, 2014, (20): 107-110. DOI: 10.13386/j.issn1002-0306.2014.20.014
引用本文: 贺群, 黄和, 刘亚, 蒋志红, 励建荣. 面包虾中副溶血性弧菌在pH影响下生长预测模型的建立[J]. 食品工业科技, 2014, (20): 107-110. DOI: 10.13386/j.issn1002-0306.2014.20.014
HE Qun, HUANG He, LIU Ya, JIANG Zhi-hong, LI Jian-rong. Establishment of growth predictive model of Vibrio parahaemolyticus in bread shrimp under different pH condition[J]. Science and Technology of Food Industry, 2014, (20): 107-110. DOI: 10.13386/j.issn1002-0306.2014.20.014
Citation: HE Qun, HUANG He, LIU Ya, JIANG Zhi-hong, LI Jian-rong. Establishment of growth predictive model of Vibrio parahaemolyticus in bread shrimp under different pH condition[J]. Science and Technology of Food Industry, 2014, (20): 107-110. DOI: 10.13386/j.issn1002-0306.2014.20.014

面包虾中副溶血性弧菌在pH影响下生长预测模型的建立

Establishment of growth predictive model of Vibrio parahaemolyticus in bread shrimp under different pH condition

  • 摘要: 为探讨pH对面包虾生产过程中副溶血性弧菌的生长规律的影响,测定了不同pH(5.5、6.0、6.5、7.0、7.5、8.0、8.5)下副溶血性弧菌的生长曲线,运用Origin 8.0软件和DMFit软件,分别采用修正Gompertz模型、修正Logistic模型、Baranyi模型对生长曲线进行拟合,选择决定系数最高的方程建立初级模型,并求出最大比生长速率。应用修正Arrhenius模型拟合最大比生长速率和pH之间的曲线建立二级模型。结果表明,通过模型检验比较,修正Compertz模型的拟合度较好(决定系数=0.99),进一步拟合所得二级模型拟合度较好(决定系数=0.98),偏差因子为0.99,准确因子1.0,均在可接受的范围内,表明模型能较好的预测面包虾中副溶血性弧菌在pH为5.5~8.5环境下的生长动态。 

     

    Abstract: To study the impact of pH to the growth law of Vibrio parahaemolyticus in the process of bread shimp, growth curves under different pH (5.5, 6.0, 6.5, 7.0, 7.5, 8.0 and 8.5, respectively) were determined. The modified Compertz, modified Logistic and Baranyi models, respectively, were applied to fit the growth curves by Origin 8.0 software and DMFit software, the maximum specific growth rates was calculated by the primary model with the highest coefficient of determination. The modified Arrhenius model was used to fit the curves between the maximum specific growth rates and pH for the establishment of the secongary model. Results showed that the modified Compertz model (R2=0.99) was more accurate and useful in fitting V. parahaemolyticus growth curves than the modified Logistic and Baranyi & Robert models, respectively. And the secondary model had a high goodness-of-fit (R2=0.98) . The values of bias factor and accuracy factor were also acceptable statistically that were close to 1.0. The predictive models were highly reliable. These could effectively predict the growth of Vibrio parahaemolyticus under above pH condition.

     

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