| Detection of omega-3 fatty acid in designer eggs using hyperspectral imaging. | |
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MedLine Citation:
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PMID: 21428720 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Quantification of n-3 polyunsaturated fatty acids (PUFA) is an important aspect in quality control of designer eggs. Prediction of these fatty acids would be of value for egg grading stations. The aim of the present study was to evaluate the ability of hyperspectral imaging (HSI) to classify the eggs according their content in n-3 PUFA as a rapid and non-destructive technique. Furthermore, HSI was used to predict the content of n-3 PUFA in designer eggs. Normal eggs, eggs containing 75 mg and eggs containing 125 mg docosahexaenoic acid were purchased from a grocery store. After hyperspectral transmittance images were collected in the spectral region of 900-1,700 nm, the eggs were broken and analyzed chemically in order to measure fatty acid content. Regions of interest (ROIs) of about 3,000 pixels from each egg were selected. K-means analysis was performed to classify eggs into the three aforementioned types. The classification accuracy was 100%. A partial least-squares regression model was built and used to link the ROIs with results obtained from the chemical analysis. The correlation coefficients between the measured and predicted values of alpha-linolenic acid, eicosapentaenoic acid, and docosahexaenoic acid were 0.94, 0.73 and 0.87, respectively. The root mean square error values for the validation sets were 38.65, 3.31 and 7.03, respectively. These results showed that HSI could be used both for discriminating the eggs between normal and designer eggs and for prediction of n-3 PUFA content in eggs. |
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Authors:
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Nicolas Abdel-Nour; Michael Ngadi |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-3-23 |
Journal Detail:
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Title: International journal of food sciences and nutrition Volume: - ISSN: 1465-3478 ISO Abbreviation: - Publication Date: 2011 Mar |
Date Detail:
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Created Date: 2011-3-24 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9432922 Medline TA: Int J Food Sci Nutr Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Bioresource Engineering, McGill UniversitySte-Anne-de-Bellevue, Quebec, Canada. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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