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Applied and Environmental Microbiology, March 2007, p. 1594-1600, Vol. 73, No. 5
0099-2240/07/$08.00+0 doi:10.1128/AEM.02145-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Department of Chemical Engineering, Food Technologies and Environmental Technologies, Universidad de Cádiz, Facultad de Ciencias del Mar y Ambientales, 11510 Puerto Real, Spain,1 Aguas de Jerez Empresa Municipal (AJEMSA), C/ Divina Pastora, Jerez, Spain2
Received 12 September 2006/ Accepted 21 December 2006
Because of the lack of readily available information about the influence of temperature on microorganism reactivation processes subsequent to inactivation with UV radiation, a series of batch reactivation studies were performed at 5, 10, 15, 20, 25, and 30°C. A special effort was made to model the reactivation process to enable the effect of the temperature variable to be quantified. Because an earlier-proposed kinetic model (K. Kashimada, N. Kamiko, K. Yamamoto, and S. Ohgaki, Water Sci. Technol. 33:261-269, 1996), a first-order saturation type, does not adequately fit the data obtained in experiments of reactivation in conditions of light and darkness, a modification of that model is proposed. The new model, which actually coincides with the classical logistic equation, incorporates two kinetic parameters: the maximum survival ratio (Sm) and the second-order reactivation rate constant (k2). In order to interpret correctly the reactivation occurring in conditions of darkness, a new term for the decay is added to the logistic equation. The new model accurately fits the data obtained in reactivation experiments, permitting the interpretation of the kinetic parameters Sm, k2, and M (for only repair in darkness), where M is mortality, a zero-order decay rate constant, and their relationship with various environmental conditions, such as microbial type, light, and temperature. The parameters Sm and k2 (and M for reactivation in conditions of darkness) show exponential dependence on the reactivating temperature, and it is possible to predict their values and hence the reactivation curve from the equations proposed in this work.
Published ahead of print on 5 January 2007.
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