کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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4363296 | 1301550 | 2010 | 5 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Quantification of spore resistance for assessment and optimization of heating processes: A never-ending story Quantification of spore resistance for assessment and optimization of heating processes: A never-ending story](/preview/png/4363296.png)
The assessment and optimization of food heating processes require knowledge of the thermal resistance of target spores. Although the concept of spore resistance may seem simple, the establishment of a reliable quantification system for characterizing the heat resistance of spores has proven far more complex than imagined by early researchers. This paper points out the main difficulties encountered by reviewing the historical works on the subject.During an early period, the concept of individual spore resistance had not yet been considered and the resistance of a strain of spore-forming bacterium was related to a global population regarded as alive or dead. A second period was opened by the introduction of the well-known D parameter (decimal reduction time) associated with the previously introduced z-concept. The present period has introduced three new sources of complexity: consideration of non log-linear survival curves, consideration of environmental factors other than temperature, and awareness of the variability of resistance parameters. The occurrence of non log-linear survival curves makes spore resistance dependent on heating time. Consequently, spore resistance characterisation requires at least two parameters. While early resistance models took only heating temperature into account, new models consider other environmental factors such as pH and water activity (“horizontal extension”). Similarly the new generation of models also considers certain environmental factors of the recovery medium for quantifying “apparent heat resistance” (“vertical extension”).Because the conventional F-value is no longer additive in cases of non log-linear survival curves, the decimal reduction ratio should be preferred for assessing the efficiency of a heating process.
Journal: Food Microbiology - Volume 27, Issue 5, August 2010, Pages 568–572