Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 43820
Title Modelling of chemical reaction in foods: a multiresponse approach.
Author(s) Boekel, M.A.J.S. van
Source Acta Horticulturae 476 (1998). - ISSN 0567-7572 - p. 149 - 155.
Department(s) Integrated Food Science and Food Physics
VLAG
Publication type Refereed Article in a scientific journal
Publication year 1998
Abstract The quality of foods depends on several factors. One of these factors is the occurrence of (bio)chemical changes taking place during the post-harvest period and during processing, storage and distribution. In order to optimise quality it is of utmost importance to control (bio)chemical changes as much as possible. That means that the kinetics of relevant chemical changes needs to be studied, i.e. the dependence of reaction rates on concentration of reactants and conditions such as pH and temperature. A complicating factor with foods is that reactions are not simple straightforward chemical reactions. Rather, consecutive and parallel reactions take place, each of which may have an effect on the other. For instance, if in one reaction organic acids are formed as a result of which the pH drops, this decrease in pH may have an effect on another reaction taking place simultaneously. Whenever possible, one should try to model all changes in concentrations of reactants and products in parallel and consecutive reactions that have parameters in common, i.e. multiresponse modelling, as opposed to analysing only one step at a time, i.e. uniresponse modelling (van Boekel, 1996). By applying multiresponse modelling, more realistic models and more accurate parameter estimates will be obtained and this ultimately means better control of (chemical) quality. Some implications of multiresponse modelling will be discussed here and, as an example, the concept will be applied to chlorophyll degradation in vegetables.
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