Use of mathematical modeling to predict microbial inactivation kinetics (D- and Z-like values) after exposure to gaseous chlorine dioxide

Travis L Selby, Purdue University

Abstract

Currently, 65% of microbial tests performed in the food industry are done using traditional/conventional methods; thus, there is significant room for improvement. Disadvantages of using traditional/conventional methods include the length of time until results are ready for analysis and the amount of labor required. Therefore, the long-term objective of this research was to integrate optical density with mathematical modeling as a means of rapidly determining inactivation kinetics (D- and z-values) after exposure to ClO 2. Specific objectives were: (1) to develop a rapid method for enumeration/survival of microbes after exposure to ClO2 by integrating mathematical models and optical density based detection technology, (2) to determine inactivation kinetics of Gram-negative (E. coli O157:H7-EC) and Gram-positive (L. monocytogenes-LM) vegetative cells and a Gram positive spore former (B. thuringiensis-BT) using ClO2, and (3) to see how cell conditions (wet vs. dry) affect inactivation kinetics. Calculated D-values for EC and LM were 10.4 sec and 33.1 sec using 1.2 ppm aqueous ClO2, respectively. The inactivation kinetics for BT spores were far more resistant and required a much higher level of ClO 2. At 0.09 and 0.3 mg/l, the corresponding D-values were 4.4 min and 0.8 min, respectively. Mathematicaliy derived D-values for gaseous chlorine dioxide at 0.3, 0.6, and 0.9 ppm for wet and dried LM were 3.35, 3.39, 1.68, and 61.35, 3.32, and 3.24 min, respectively. While the D-values for gaseous ClO2 at 0.6, 0.9, 1.1, and 1.7 mg/l for wet EC were 1.82, 1.13, 0.95, and 0.72 min, respectively, and the derived D-values for dried EC were 2.76 and 1.99 min using 0.6 and 0.9 mg/l ClO2, respectively. D-values for wet BT were 3.58, 1.60, 0.83 min at 1, 3, and 5 mg/l ClO2, respectively. Additionally, relative humidity (RH) was evaluated at different levels (23, 60, and 90%) to see how this factor influenced inactivation kinetics. As the percent of RH increased, the number of survivors decreased for dried spores; however, for wet spores RH was not a significant factor. The integration of mathematical modeling and optical density for determining growth and inactivation kinetics (D- and z-like values) was an effective technique for determining antimicrobial effectiveness.

Degree

Ph.D.

Advisors

Gerrard, Purdue University.

Subject Area

Food science|Microbiology

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