Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection
The contents of cellulose and hemicellulose (C and H) in corn stover (CS) have an important influence on its biochemical transformation and utilization. To rapidly detect the C and H contents in CS by near-infrared spectroscopy (NIRS), the characteristic wavelength selection algorithms of backward p...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/27/11/3373 |
| _version_ | 1827664707244261376 |
|---|---|
| author | Na Wang Jinrui Feng Longwei Li Jinming Liu Yong Sun |
| author_facet | Na Wang Jinrui Feng Longwei Li Jinming Liu Yong Sun |
| author_sort | Na Wang |
| collection | DOAJ |
| description | The contents of cellulose and hemicellulose (C and H) in corn stover (CS) have an important influence on its biochemical transformation and utilization. To rapidly detect the C and H contents in CS by near-infrared spectroscopy (NIRS), the characteristic wavelength selection algorithms of backward partial least squares (BIPLS), competitive adaptive reweighted sampling (CARS), BIPLS combined with CARS, BIPLS combined with a genetic simulated annealing algorithm (GSA), and CARS combined with a GSA were used to select the wavelength variables (WVs) for C and H, and the corresponding regression correction models were established. The results showed that five wavelength selection algorithms could effectively eliminate irrelevant redundant WVs, and their modeling performance was significantly superior to that of the full spectrum. Through comparison and analysis, it was found that CARS combined with GSA had the best comprehensive performance; the predictive root mean squared errors of the C and H regression model were 0.786% and 0.893%, and the residual predictive deviations were 3.815 and 12.435, respectively. The wavelength selection algorithm could effectively improve the accuracy of the quantitative analysis of C and H contents in CS by NIRS, providing theoretical support for the research and development of related online detection equipment. |
| first_indexed | 2024-03-10T01:05:41Z |
| format | Article |
| id | doaj.art-aa097f2efb7d45c89062b755f5e321d0 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T01:05:41Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-aa097f2efb7d45c89062b755f5e321d02023-11-23T14:27:46ZengMDPI AGMolecules1420-30492022-05-012711337310.3390/molecules27113373Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength SelectionNa Wang0Jinrui Feng1Longwei Li2Jinming Liu3Yong Sun4College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Engineering, Northeast Agricultural University, Harbin 150030, ChinaThe contents of cellulose and hemicellulose (C and H) in corn stover (CS) have an important influence on its biochemical transformation and utilization. To rapidly detect the C and H contents in CS by near-infrared spectroscopy (NIRS), the characteristic wavelength selection algorithms of backward partial least squares (BIPLS), competitive adaptive reweighted sampling (CARS), BIPLS combined with CARS, BIPLS combined with a genetic simulated annealing algorithm (GSA), and CARS combined with a GSA were used to select the wavelength variables (WVs) for C and H, and the corresponding regression correction models were established. The results showed that five wavelength selection algorithms could effectively eliminate irrelevant redundant WVs, and their modeling performance was significantly superior to that of the full spectrum. Through comparison and analysis, it was found that CARS combined with GSA had the best comprehensive performance; the predictive root mean squared errors of the C and H regression model were 0.786% and 0.893%, and the residual predictive deviations were 3.815 and 12.435, respectively. The wavelength selection algorithm could effectively improve the accuracy of the quantitative analysis of C and H contents in CS by NIRS, providing theoretical support for the research and development of related online detection equipment.https://www.mdpi.com/1420-3049/27/11/3373near-infrared spectroscopycellulose and hemicellulose contentsbackward partial least squarescompetitive adaptive reweighted samplinggenetic simulated annealing algorithm |
| spellingShingle | Na Wang Jinrui Feng Longwei Li Jinming Liu Yong Sun Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection Molecules near-infrared spectroscopy cellulose and hemicellulose contents backward partial least squares competitive adaptive reweighted sampling genetic simulated annealing algorithm |
| title | Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection |
| title_full | Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection |
| title_fullStr | Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection |
| title_full_unstemmed | Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection |
| title_short | Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection |
| title_sort | rapid determination of cellulose and hemicellulose contents in corn stover using near infrared spectroscopy combined with wavelength selection |
| topic | near-infrared spectroscopy cellulose and hemicellulose contents backward partial least squares competitive adaptive reweighted sampling genetic simulated annealing algorithm |
| url | https://www.mdpi.com/1420-3049/27/11/3373 |
| work_keys_str_mv | AT nawang rapiddeterminationofcelluloseandhemicellulosecontentsincornstoverusingnearinfraredspectroscopycombinedwithwavelengthselection AT jinruifeng rapiddeterminationofcelluloseandhemicellulosecontentsincornstoverusingnearinfraredspectroscopycombinedwithwavelengthselection AT longweili rapiddeterminationofcelluloseandhemicellulosecontentsincornstoverusingnearinfraredspectroscopycombinedwithwavelengthselection AT jinmingliu rapiddeterminationofcelluloseandhemicellulosecontentsincornstoverusingnearinfraredspectroscopycombinedwithwavelengthselection AT yongsun rapiddeterminationofcelluloseandhemicellulosecontentsincornstoverusingnearinfraredspectroscopycombinedwithwavelengthselection |