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Rapid detection of cellulose and hemicellulose contents of corn stover based on near-infrared spectroscopy combined with chemometrics
- Source :
- Applied Optics. 60:4282
- Publication Year :
- 2021
- Publisher :
- Optica Publishing Group, 2021.
-
Abstract
- The feasibility of near-infrared spectroscopy (NIRS) combined with chemometrics for the rapid detection of the cellulose and hemicellulose contents in corn stover is discussed. Competitive adaptive reweighted sampling (CARS) and genetic simulated annealing algorithm (GSA) were combined (CARS-GSA) to select the characteristic wavelengths of cellulose and hemicellulose and to reduce the dimensionality and multicollinearity of the NIRS data. The whole spectra contained 1845 wavelength variables. After CARS-GSA optimization, the number of characteristic wavelengths of cellulose (hemicellulose) was reduced to 152 (260), accounting for 8.24% (14.09%) of all wavelengths. The coefficients of determination of the regression models for predicting the cellulose and hemicellulose contents were 0.968 and 0.996, the root mean square errors of prediction (RMSEPs) were 0.683 and 0.648, and the residual predictive deviations (RPDs) were 5.213 and 16.499, respectively. The RMSEP of the cellulose and hemicellulose regression models was 0.152 and 0.190 lower for CARS-GSA than for the full-spectrum, and the RPD was increased by 0.949 and 3.47, respectively. The results showed that the CARS-GSA model substantially reduced the number of characteristic wavelengths and significantly improved the predictive ability of the regression model.
- Subjects :
- Analytical chemistry
Zea mays
01 natural sciences
010309 optics
Root mean square
Chemometrics
chemistry.chemical_compound
Optics
Polysaccharides
0103 physical sciences
Hemicellulose
Electrical and Electronic Engineering
Cellulose
Spectroscopy
Engineering (miscellaneous)
Spectroscopy, Near-Infrared
business.industry
Regression analysis
Atomic and Molecular Physics, and Optics
Corn stover
chemistry
Multicollinearity
business
Algorithms
Subjects
Details
- ISSN :
- 21553165 and 1559128X
- Volume :
- 60
- Database :
- OpenAIRE
- Journal :
- Applied Optics
- Accession number :
- edsair.doi.dedup.....a0fd863504e48bb354c60dc7f9c0aa78