A novel simulated food model (ascorbic acid, thiamine and a mixture of glucose and glycine) incorporating celite was developed. Basic kinetic parameters were established and the analysis of this data led to a reconsideration of the fundamental aspects relating the TDT and Arrhenius systems of evaluating kinetic parameters and their meaning. Heat penetration data was obtained for both conduction and convection systems, with the conduction system being characterized by parameters calculated from the heat penetration data. Stainless steel micro-capsules were used to isolate and obtain centerpoint nutrient destruction and compared it to the predictions of two computer models. Computer models were tested and verified for the conduction system and an optimization technique based on a multi-factor objective function evaluated. / Celite simulated a typical conduction system and the kinetics of quality factor degradation varied depending on composition. Centerpoint capsules worked well in evaluating nutrient destruction and provided a means for verifying computer simulations. Predictions from the Teixeira and Ball models indicated that the Teixeira model was a better process predictor. Multi-factor objective functions for maximizing nutrient retention were shown to work well in defining optimal conditions using the Teixeira program, while those based on the Ball model were indeterminate.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.74358 |
Date | January 1989 |
Creators | Ghazala, Suad |
Publisher | McGill University |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Format | application/pdf |
Coverage | Doctor of Philosophy (Department of Agricultural Engineering.) |
Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
Relation | alephsysno: 001071056, proquestno: AAINN63775, Theses scanned by UMI/ProQuest. |
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