Authors: Selinger, Stacia, Sivakumar, Mahesh, W. Gamage, Thushan, Green, Rick
Identifier: CSBE17050
Download file: https://library.csbe-scgab.ca/docs/meetings/2017/CSBE17050.pdf
Published in: CSBE-SCGAB Technical Conferences » AGM Winnipeg 2017 (with CIGR VI Technical Symposium)
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Description: The objective of this project was to develop prediction models using the Fourier Transform - Near Infrared (FT-NIR) spectrometer for quality analyses of fish oils. Most of the fish oils have high polyunsaturated fatty acids (PUFA) which rapidly oxidize during extraction, refining and storage processing. An inclusion of a rapid determination technique for the analysis of oxidative products in oils is vital in the fish oil processing industry. Standard wet chemistry is used to determine the oxidative products such as the free fatty acid (FFA) value, peroxide (PV) value, and para-Anisidine (p-AV) value for bleached and deodorized fish oils. The wet chemistry methods are time-consuming, labour-intensive and require the use of significant amounts of chemical reagents for performing multiple analyses. On the other hand, the FT-NIR spectroscopy requires minimal sample preparation. Also, it is a non-destructive and rapid analytical method with high sensitivity. The results showed that the correlations between the optimized FT-NIR chemical prediction models and FFA, p-AV, and PV were 92.83, 93.57, and 97% respectively. Also, these correlations had the minimum the Root Mean Square Error for Cross Validation (RMSECV) values of 0.0186, 0.612, and 0.662 for FFA, p-AV, and PV respectively. The models could now be used for in-process sample analyses.
Keywords: Fish oil, Near infrared, Spectroscopy
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Date: 2017-08-07
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Conference name: CSBE/SCGAB 2017 Annual Conference, Canad Inns Polo Park, Winnipeg, Manitoba, 6-10 August 2017.
Session name: Poster Session
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Type: Text.Article
Format: PDF
Publication type: Technical conference
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Coverage: Canada
Language 1: en
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Rights: Canadian Society for Bioengineering
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