The formation of heterocyclic amines (HAs) have been proven to be carcinogenic and mutagenic and these compounds have been found in cooked food such as meat, poultry, and fish. There are strong relationships between potential cancer development and HAs through intake of the cooked food. / The yield of HAs along with the influence of fat content and soy protein on the formation of HAs were determined during heating (as in cooking) at different temperatures using the kinetic modeling approach. The formation of HAs is dependent on temperature, time, fat content, and soy protein. The increase of fat content in samples resulted in a lower concentration of HAs' concentrations and a lower activation energy of reaction. Fat apparently enhanced the formation of HAs in meats but diluted availability of precursors for reactions. An increase in soy protein concentration decreased the maximum concentration of HAs formed in the different cooking conditions. / Two different approaches were used in order to model the formation of HAs. First, an artificial neural network (ANN) was used with two data sets to train and test the ANN. An ANN consisting of 18 processing elements and two hidden layers showed the best performance for predicting the formation of HAs. Second, the formation of HAs were predicted using temperature profiles in a cooked sample during pan-frying. The temperature profiles in cooked meat patty were predicted using finite element method. The concentration of HAs depended on the meat patty's surface temperature developed during pan frying. The result of this study can be used to develop methods to reduce HAs in food thus optimize product quality and safety.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.33778 |
| Date | January 2002 |
| Creators | Hwang, Dae Kun, 1972- |
| Contributors | Ngadi, Michael (advisor) |
| 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 | Master of Science (Department of Agricultural and Biosystems Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001873981, proquestno: MQ78895, Theses scanned by UMI/ProQuest. |
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