董庆利, 高翠, 丁甜, 余华星. 不同试验条件下猪肉中气单胞菌生长预测模型的建立和验证[J]. 华南农业大学学报, 2012, 33(1): 82-86. DOI: 10.7671/j.issn.1001-411X.2012.01.017
    引用本文: 董庆利, 高翠, 丁甜, 余华星. 不同试验条件下猪肉中气单胞菌生长预测模型的建立和验证[J]. 华南农业大学学报, 2012, 33(1): 82-86. DOI: 10.7671/j.issn.1001-411X.2012.01.017
    DONG Qing-li, GAO Cui, DING Tian, YU Hua-xing. Establishment and Validation of Growth Predictive Model of Aeromonas spp.from Pork Under Different Experimental Conditions[J]. Journal of South China Agricultural University, 2012, 33(1): 82-86. DOI: 10.7671/j.issn.1001-411X.2012.01.017
    Citation: DONG Qing-li, GAO Cui, DING Tian, YU Hua-xing. Establishment and Validation of Growth Predictive Model of Aeromonas spp.from Pork Under Different Experimental Conditions[J]. Journal of South China Agricultural University, 2012, 33(1): 82-86. DOI: 10.7671/j.issn.1001-411X.2012.01.017

    不同试验条件下猪肉中气单胞菌生长预测模型的建立和验证

    Establishment and Validation of Growth Predictive Model of Aeromonas spp.from Pork Under Different Experimental Conditions

    • 摘要: 采用响应曲面模型(RSM)研究温度、pH、初始菌浓度对冷却猪肉中气单胞菌Aeromonas spp.生长的影响.应用Gompertz模型对不同试验条件下气单胞菌的生长曲线进行拟合,一级模型的参数生长率(U)和迟滞期(LPD)采用RSM方法构建冷却猪肉中气单胞菌生长的二级模型.然后随机选择试验组合对建立的方程进行验证,并应用计算均方误差(MSE)、准确因子(AF)和偏差因子(BF)的方法对建立的生长预测方程进行数学检验。结果表明,修正的Gompertz 模型可以较好地模拟不同试验条件下冷却猪肉中气单胞菌的生长情况(R2>0.96),温度、pH和初始菌浓度对气单胞菌生长影响显著(P<0.05),数学检验参数MSE较小,AF和BF接近1.0,均在可接受范围,用RSM方法建立的生长预测模型可以较好地模拟冷却猪肉中气单胞菌在不同试验条件下的生长情况。

       

      Abstract: The purpose of this paper was to study the effects of temperature, pH and inoculation level on the growth parameters of Aeromonas spp. in chilled pork under laboratory conditions. The curves generated within different conditions were fitted by Gompertz function as primary model. Then two parameters (growth rate and lag-time) of the growth curves were modeled using a quadratic polynomial equation of response surface model (RSM) as secondary model. Additional experimental conditions within the research domain were randomly selected for model validation, and mathematical testing were also applied for the developed models, including the mean square error (MSE), accuracy factor (AF) and bias factor (BF).The results indicated that modified Gompertz function could be used to model Aeromonas spp. growth under different experimental condtions (R2>0.96). Moreover, the temperature, pH and inoculation level on the growth of Aeromonas spp. were significant (P<0.05), and RSM with lower MSE and acceptable AF and BF values provided a useful and accurate method of predicting the growth parameters of Aeromonas spp.

       

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