| Determination of protein content of Auricularia auricula using near infrared spectroscopy combined with linear and nonlinear calibrations. | |
MedLine Citation:
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PMID: 19489615 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Near infrared (NIR) spectroscopy was investigated to determine the protein content of Auricularia auricula (commonly called black woody ear or tree ear) using partial least-squares (PLS), multiple linear regression (MLR), and least-squares-support vector machine (LS-SVM). The performances of different preprocessing were compared including Savitzky-Golay (SG) smoothing, standard normal variate, multiplicative scatter correction (MSC), first derivative, second derivative, and direct orthogonal signal correction. A successive projections algorithm (SPA) was applied for relevant effective wavelengths selection. The combinations of various pretreatment and calibration methods were compared based on the prediction performance. The optimal full-spectrum PLS model was achieved by raw spectra, whereas the optimal SPA-MLR, SPA-PLS, and SPA-LS-SVM models were achieved by MSC spectra. The best prediction performance was achieved by the SPA-LS-SVM model, with correlation coefficients (r) = 0.9839 and a root mean squares error of prediction (RMSEP) = 0.16. The results indicated that NIR spectroscopy combined with SPA-LS-SVM was the most successful to determine the protein content of A. auricula. |
Authors:
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Fei Liu; Yong He; Guangming Sun |
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Publication Detail:
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Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Journal of agricultural and food chemistry Volume: 57 ISSN: 1520-5118 ISO Abbreviation: J. Agric. Food Chem. Publication Date: 2009 Jun |
Date Detail:
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Created Date: 2009-06-03 Completed Date: 2009-07-28 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0374755 Medline TA: J Agric Food Chem Country: United States |
Other Details:
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Languages: eng Pagination: 4520-7 Citation Subset: IM |
Affiliation:
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College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Basidiomycota
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chemistry* Calibration Fungal Proteins / chemistry* Linear Models Models, Statistical Spectroscopy, Near-Infrared / methods*, standards |
| Chemical | |
Reg. No./Substance:
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0/Fungal Proteins |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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