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Estabiishment of growth/no growth model for Bacillus cereus on different temperature, pH and water activity

机译:不同温度,pH和水活动的芽孢杆菌生长/无生长模型

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The aim of this research was to establish a probabilistic model to predict the growth probability of B. cereus. The five strains of B.cereus were studied and a logistic regression model was chosen to study the interaction of different temperature (10°C, 15°C, 20°C, 25°C, 30°C, 35°C), pH(4.5, 5, 5.5, 6, 6.5, 7, 7.5), A_w( 14 levels from 0.992 to 0.932) on the probability of growth. This paper made a fractional factorial design and the experimental data was divided to two parts: 80% of data was chosen as model data and 20% of data was chosen as validation data . At last comparison was made between the predicted values and observed value by choosing 19 experimental data from the published studies. The results showed the concordance index of model data was 0.991 while the validation data was 0.976, indicating that the data was correctly classified and model had a high predictive ability. Also The performance statistics obtained indicate a reasonable goodness of fit of the model obtained, mainly due to the high values of R~2-Nagelkerke (0.954) and χ~2=0.0119, P=1 of the Hosmer-Lemeshow statistic. A high predictive accuracy is obtained (89.47%) with test data, showing a good predictive ability. In this paper, the growth/no growth model can quantized the combination of environmental factors for B. cereus. This study can help food manufacturers in making decision on the more reasonable and safer formulations for food products in order to prevent the growth of B.cereus along their shelf-life.
机译:这项研究的目的是要建立一个概率模型来预测蜡样芽胞杆菌的生长概率。研究蜡状芽孢杆菌的5个菌株和选择研究不同温度(10°C,15°C,20°C,25°C,30°C,35°C)的相互作用的逻辑回归模型,pH值(4.5,5,5.5,6,6.5,7,7.5),A_W(14级水平从0.992到0.932)生长的概率。本文提出了部分因子设计和实验数据被划分到两个部分:80%的数据被选为模型的数据和数据的20%被选作验证数据。最后比较是通过从已发表的研究实验19点的数据的预测值和观测值之间进行比较。结果表明,模型数据的一致性指数为0.991,而验证数据为0.976,表明数据被正确分类和模型具有较高的预测能力。也获得性能统计特性表示所获得的模型的拟合的优度合理,这主要是由于R〜2-Nagelkerke的高的值(0.954)和χ〜2 = 0.0119,P = 1的霍斯默-Lemeshow统计。高预测准确度与测试数据获得的(89.47%),显示出良好的预测能力。在本文中,生长/无生长模型可以量化为蜡样芽胞杆菌的环境因素的组合。这项研究可以帮助食品制造商在做,以防止蜡状芽孢杆菌沿着它们的保质期的增长对粮食产品的更合理,更安全的配方决定。

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