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Quality evaluation of frying oil and chicken nuggets using visiblenear-infrared hyper-spectral analysis

The application of visible/near-infrared hyper-spectral analysis to monitor the quality of frying oil and fried breaded chicken nuggets was investigated. / Partial least squares (PLS) calibration models were developed to predict the acid value, total polar components and viscosity of heated oils with different ratios of hydrogenation. Coefficient of determination (R2) and root mean square error (RMSE) were calculated to assess the performance of each model. Results of the study demonstrated good prediction ability of the calibration models for the quality parameters with R2 values of over 0.92. / The second study was based on developing calibration models for prediction of moisture and fat contents of fried breaded chicken nuggets with different levels of moisture and fat contents. Performing the same procedure for evaluation of the PLS calibration models, results of the study demonstrated that moisture and fat contents of fried breaded chicken nuggets could be predicted with R2 values of 0.92.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.84043
Date January 2005
CreatorsKazemi Sangdehi, Samira
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Science (Department of Bioresource Engineering.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 002269610, proquestno: AAIMR22735, Theses scanned by UMI/ProQuest.

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