Change in microbial resistance to heat in non-isothermal process of pasteurization and building of predictive model
Change in microbial resistance to heat in non-isothermal process of pasteurization and building of predictive model
批准号:
12650793
负责人:
TUCHIDO Tetsuaki
金额:
$2.24万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
2000
资助国家:
日本
项目状态:
已结题
起止时间:
2000 至 2001
中文摘要
近年来,热过程可靠性评价方法的建立和确定热过程可靠性的理论基础的建立,已成为热过程可靠性评价的重要内容。要求延长食品的保质期。本研究旨在建立一个考虑非等温过程对微生物耐热性影响的模型。在致死温度下热处理之前,将大肠杆菌细胞在0 - 45℃的不同温度下预孵育,并评价其抗性。因此,参数D值(小数还原时间)对预孵育温度的依赖性在低于和高于37℃之间表现出不同的模式。在37℃以上,D值的增长速率和稳态水平都很高。从预孵育到热处理的升温稀释率影响D值对预孵育的依赖性。为了了解D值的增加率对预孵育温度的依赖性,我们从本研究和我们以前获得的数据中绘制了Arrhenius图。研究结果可为热工过程实际评价中的热死预测提供参考。此外,我们获得了有关热死亡反应的数据,通过改变因素,如加热温度,pH值,氯化钠浓度,开发两个因素之间的预测方程和所有因素之间的二阶和三阶回归分析,分别。
英文摘要
Recently, the construction of reliable method for evaluation of heat process and the establishment of theorctical background for determ. ining shel-life of foods have been required. We conducted this study in order to build up such a model in which the effect of non-isothermal process on the heat resistance of microorganisms was considered. Escherichia coli cells were pre-incubated at different temperatures between 0 and 45℃ before heat treatment at a lethal temperature and their resistance was evaluated. As a result, the dependency of a parameter D value, the decimal reduction time, on the pre-incubation temperature demonsirated different patterns between below and above 37℃. Above 37℃, the rate of increase in and the steady state level of D value were found to be rather high. The rate of dilution for temperature rise from pre-incubation to heat treatment afiiected the dependency of D value on the pre-incubation. To see the dependency of rate of increase in D value on the preincubation temporature, we took its Arrhenius plot from the data obtained in this study and previously by us. The results should be available for prediction of the thermal death in practical evaluation of heat processes. Furthermore, we obtained data concerning thermal death reaction by changing factors such as heating temperature, pH, and sodium chloride concentration to develop predictive equations between two factors and also between all factors by second-order and third-order regression analyses, respectively.
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