| Near-infrared hyperspectral imaging for grading and classification of pork. | |
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MedLine Citation:
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PMID: 21821367 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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In this study, a hyperspectral imaging technique was developed to achieve fast, accurate, and objective determination of pork quality grades. Hyperspectral images were acquired in the near-infrared (NIR) range from 900 to 1700nm for 75 pork cuts of longissimus dorsi muscle from three quality grades (PSE, RFN and DFD). Spectral information was extracted from each sample and six significant wavelengths that explain most of the variation among pork classes were identified from 2nd derivative spectra. There were obvious reflectance differences among the three quality grades mainly at wavelengths 960, 1074, 1124, 1147, 1207 and 1341nm. Principal component analysis (PCA) was carried out using these particular wavelengths and the results indicated that pork classes could be precisely discriminated with overall accuracy of 96%. Algorithm was developed to produce classification maps of the tested samples based on score images resulting from PCA and the results were compared with the ordinary classification method. Investigation of the misclassified samples was performed and showed that hyperspectral based classification can aid in class determination by showing spatial location of classes within the samples. |
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Authors:
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Douglas Barbin; Gamal Elmasry; Da-Wen Sun; Paul Allen |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-7-21 |
Journal Detail:
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Title: Meat science Volume: - ISSN: 1873-4138 ISO Abbreviation: - Publication Date: 2011 Jul |
Date Detail:
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Created Date: 2011-8-8 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101160862 Medline TA: Meat Sci Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2011 Elsevier Ltd. All rights reserved. |
Affiliation:
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Food Refrigeration and Computerised Food Technology (FRCFT), School of Agriculture, Food Science & Veterinary Medicine, University College Dublin, National University of Ireland, Agriculture & Food Science Centre, Belfield, Dublin 4, Ireland. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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