Document Detail


Determination of protein content of Auricularia auricula using near infrared spectroscopy combined with linear and nonlinear calibrations.
MedLine Citation:
PMID:  19489615     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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:
Fei Liu; Yong He; Guangming Sun
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of agricultural and food chemistry     Volume:  57     ISSN:  1520-5118     ISO Abbreviation:  J. Agric. Food Chem.     Publication Date:  2009 Jun 
Date Detail:
Created Date:  2009-06-03     Completed Date:  2009-07-28     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0374755     Medline TA:  J Agric Food Chem     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4520-7     Citation Subset:  IM    
Affiliation:
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China.
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MeSH Terms
Descriptor/Qualifier:
Basidiomycota / chemistry*
Calibration
Fungal Proteins / chemistry*
Linear Models
Models, Statistical
Spectroscopy, Near-Infrared / methods*,  standards
Chemical
Reg. No./Substance:
0/Fungal Proteins

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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