HFCAS OpenIR  > 中科院合肥智能机械研究所
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
发表期刊JOURNAL OF APPLIED SPECTROSCOPY
卷号84期号:3页码:529-534
摘要A 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.
文章类型Article
关键词Vis-nir Spectroscopy Organic Matter Content Spectral Pretreatment Sample Selection Wavelength Optimization
WOS标题词Science & Technology ; Technology
资助者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) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069)
DOI10.1007/s10812-017-0505-4
关键词[WOS]INFRARED REFLECTANCE SPECTROSCOPY ; LEAST-SQUARES ; CARBON ; ACCURACY
收录类别SCI
语种英语
资助者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) ; Science and Technology Service Network Initiative of Chinese Academy of Sciences(KFJ-EW-STS-069)
WOS研究方向Spectroscopy
WOS类目Spectroscopy
WOS记录号WOS:000407256200028
引用统计
文献类型期刊论文
条目标识符http://ir.hfcas.ac.cn:8080/handle/334002/33604
专题中科院合肥智能机械研究所
作者单位1.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
推荐引用方式
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.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Lin, Z. D.]的文章
[Wang, Y. B.]的文章
[Wang, R. J.]的文章
百度学术
百度学术中相似的文章
[Lin, Z. D.]的文章
[Wang, Y. B.]的文章
[Wang, R. J.]的文章
必应学术
必应学术中相似的文章
[Lin, Z. D.]的文章
[Wang, Y. B.]的文章
[Wang, R. J.]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。