학술논문

Assessing the optimal experiment setup for first order kinetic studies by Monte Carlo analysis
Document Type
Report
Source
Food Control. Dec, 2005, Vol. 16 Issue 10, p873, 10 p.
Subject
Pectin
Language
English
ISSN
0956-7135
Abstract
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.foodcont.2004.07.009 Byline: F. Poschet (a), A.H. Geeraerd (a), A.M. Van Loey (b), M.E. Hendrickx (b), J.F. Van Impe (a) Abstract: In inactivation studies of microorganisms and quality influencing enzymes a log linear relation between dependent and independent variables, generally denominated as a first order kinetic, is frequently encountered. Reliable application of a kinetic model to predict inactivation requires a proper quantification of the variation on the model parameters. The aim of the present research is the assessment of the most optimal experiment setup leading to first order kinetic parameters with minimal variation, and, by consequence, to model predictions with minimal variation. As a vehicle for this research, the first order inactivation of pectin methyl esterase (PME), commonly encountered in fruits, is considered. Based on a bootstrap assessment of the PME activity measurement variation, a Monte Carlo analysis fully reveals the optimal experiment setup and leads to two important conclusions, valid for all first order kinetic studies. First, if the logarithm of the dependent variable has a constant variance as function of the independent variable, the optimal sampling scheme is a 50-50 division at the two extremes of the independent variable range. It is indicated how this relates with classical linear regression analysis. Second, if the logarithm of the dependent variable has a non-constant variance, this variance should be fully characterized and the optimal sampling scheme should be obtained via Monte Carlo analysis. It is shown how, in such a case, a 50-50 division is not necessarily the most optimal. Author Affiliation: (a) BioTeC -- Bioprocess Technology and Control, Department of Chemical Engineering, Katholieke Universiteit Leuven, W. de Croylaan 46, B-3001 Leuven, Belgium (b) Laboratory of Food Technology, Department of Food and Microbial Technology, Katholieke Universiteit Leuven, Kasteelpark Arenberg 22, B-3001 Leuven, Belgium