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IMPROVEMENTS OF THE VIS-NIRS MODEL IN THE PREDICTION OF SOIL ORGANIC MATTER CONTENT USING SPECTRAL PRETREATMENTS, SAMPLE SELECTION, AND WAVELENGTH OPTIMIZATION
Lin, Z. D.1,2,3; Wang, Y. B.1; Wang, R. J.1; Wang, L. S.1; Lu, C. P.1; Zhang, Z. Y.1; Song, L. T.1; Liu, Y.1
2017-07-01
Source PublicationJOURNAL OF APPLIED SPECTROSCOPY
Volume84Issue:3Pages:529-534
AbstractA total of 130 topsoil samples collected from Guoyang County, Anhui Province, China, were used to establish a Vis-NIR model for the prediction of organic matter content (OMC) in lime concretion black soils. Different spectral pretreatments were applied for minimizing the irrelevant and useless information of the spectra and increasing the spectra correlation with the measured values. Subsequently, the Kennard-Stone (KS) method and sample set partitioning based on joint x-y distances (SPXY) were used to select the training set. Successive projection algorithm (SPA) and genetic algorithm (GA) were then applied for wavelength optimization. Finally, the principal component regression (PCR) model was constructed, in which the optimal number of principal components was determined using the leave-one-out cross validation technique. The results show that the combination of the Savitzky-Golay (SG) filter for smoothing and multiplicative scatter correction (MSC) can eliminate the effect of noise and baseline drift; the SPXY method is preferable to KS in the sample selection; both the SPA and the GA can significantly reduce the number of wavelength variables and favorably increase the accuracy, especially GA, which greatly improved the prediction accuracy of soil OMC with R-cc, RMSEP, and RPD up to 0.9316, 0.2142, and 2.3195, respectively.
SubtypeArticle
KeywordVis-nir Spectroscopy Organic Matter Content Spectral Pretreatment Sample Selection Wavelength Optimization
WOS HeadingsScience & Technology ; Technology
Funding OrganizationScience and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069)
DOI10.1007/s10812-017-0505-4
WOS KeywordINFRARED REFLECTANCE SPECTROSCOPY ; LEAST-SQUARES ; CARBON ; ACCURACY
Indexed BySCI
Language英语
Funding OrganizationScience and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069)
WOS Research AreaSpectroscopy
WOS SubjectSpectroscopy
WOS IDWOS:000407256200028
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.hfcas.ac.cn:8080/handle/334002/33604
Collection中科院合肥智能机械研究所
Affiliation1.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Anhui, Peoples R China
2.Univ Sci & Technol China, Dept Automat, Hefei 230026, Anhui, Peoples R China
3.Inst Elect Engn, Hefei 230037, Anhui, Peoples R China
Recommended Citation
GB/T 7714
Lin, Z. D.,Wang, Y. B.,Wang, R. J.,et al. IMPROVEMENTS OF THE VIS-NIRS MODEL IN THE PREDICTION OF SOIL ORGANIC MATTER CONTENT USING SPECTRAL PRETREATMENTS, SAMPLE SELECTION, AND WAVELENGTH OPTIMIZATION[J]. JOURNAL OF APPLIED SPECTROSCOPY,2017,84(3):529-534.
APA Lin, Z. D..,Wang, Y. B..,Wang, R. J..,Wang, L. S..,Lu, C. P..,...&Liu, Y..(2017).IMPROVEMENTS OF THE VIS-NIRS MODEL IN THE PREDICTION OF SOIL ORGANIC MATTER CONTENT USING SPECTRAL PRETREATMENTS, SAMPLE SELECTION, AND WAVELENGTH OPTIMIZATION.JOURNAL OF APPLIED SPECTROSCOPY,84(3),529-534.
MLA Lin, Z. D.,et al."IMPROVEMENTS OF THE VIS-NIRS MODEL IN THE PREDICTION OF SOIL ORGANIC MATTER CONTENT USING SPECTRAL PRETREATMENTS, SAMPLE SELECTION, AND WAVELENGTH OPTIMIZATION".JOURNAL OF APPLIED SPECTROSCOPY 84.3(2017):529-534.
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