NDLI: Two modeling methods for near infrared spectroscopy nondestructive quantitative analysis of the protein contents in Coredyceps militaris mycelia powder

Content Provider	IEEE Xplore Digital Library
Author	Wei-liang Guo Jia Song Jia-hui Lu Li-rong Teng Yan Wang Wei Du
Copyright Year	2010
Description	Author affiliation: College of Computer Science and Technology, Jilin University, Changchun, China (Yan Wang; Wei Du) \|\| College of Life Science, Jilin University, Changchun, China (Wei-liang Guo; Jia Song; Jia-hui Lu; Li-rong Teng)
Abstract	This paper presents a comparative study between Partial Least Squares (PLS) method and support vector regression (SVR) in modeling the relationship between the near infrared spectra (NIRS) and the protein contents in Cordyceps militaris mycelia powder samples. Both of the models were optimized by selecting the suitable spectra preprocessing methods and the best modeling parameters. And then the optimum models were obtained. The results demonstrated that the SVR model was superior to PLS model. The root mean square error of cross-validation (RMSECV), the coefficient relation between actual values and predictive values obtained by cross-validation (Rv) and root mean square error of prediction set (RMSEP) of the optimum SVR model were 0.0146, 0.9874 and 0.0130, which indicated that the stability, the fit and the predictive capability of the model were satisfied.
Starting Page	4385
Ending Page	4389
File Size	284084
Page Count	5
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5583527
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Training Near infrared spectroscopy Analytical models Spectroscopy Powders Cordyceps militaris Predictive models Support vector regression Stability analysis Partial least squares
Content Type	Text
Resource Type	Article

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