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Volumn 4, Issue 2, 2012, Pages 467-473

Multivariate calibration of near-infrared spectra by using influential variables

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION MODEL; DATA SETS; MONTE CARLO; MULTIVARIATE CALIBRATION; NEAR INFRA RED; NEAR INFRARED SPECTRA; PARTIAL LEAST SQUARES MODELS; PERFORMANCE MODEL; PLS MODELS; RESAMPLING;

EID: 84863153660     PISSN: 17599660     EISSN: 17599679     Source Type: Journal    
DOI: 10.1039/c2ay05609g     Document Type: Article
Times cited : (23)

References (48)
  • 1
    • 39849105217 scopus 로고    scopus 로고
    • Monitoring galenical process development by near infrared chemical imaging: One case study
    • DOI 10.1016/j.ejpb.2007.08.008, PII S0939641107002925
    • C. Gendrin Y. Roggo C. Spiegel C. Collet Monitoring galenical process development by near infrared chemical imaging: One case study Eur. J. Pharm. Biopharm. 2008 68 828 837 (Pubitemid 351318208)
    • (2008) European Journal of Pharmaceutics and Biopharmaceutics , vol.68 , Issue.3 , pp. 828-837
    • Gendrin, C.1    Roggo, Y.2    Spiegel, C.3    Collet, C.4
  • 2
    • 33947242024 scopus 로고    scopus 로고
    • Review: Infrared spectroscopy - Enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries
    • K. D. Shepherd M. G. Walsh Review: Infrared spectroscopy-enabling an evidence-based diagnostic surveillance approach to agricultural and environmental management in developing countries J. Near Infrared Spectrosc. 2007 15 1 19
    • (2007) J. Near Infrared Spectrosc. , vol.15 , pp. 1-19
    • Shepherd, K.D.1    Walsh, M.G.2
  • 4
  • 5
    • 71549134926 scopus 로고    scopus 로고
    • Multiblock partial least squares regression based on wavelet transform for quantitative analysis of near infrared spectra
    • M. Jing W. S. Cai X. G. Shao Multiblock partial least squares regression based on wavelet transform for quantitative analysis of near infrared spectra Chemom. Intell. Lab. Syst. 2010 100 22 27
    • (2010) Chemom. Intell. Lab. Syst. , vol.100 , pp. 22-27
    • Jing, M.1    Cai, W.S.2    Shao, X.G.3
  • 6
    • 77952548488 scopus 로고    scopus 로고
    • An improved boosting partial least squares method for near-infrared spectroscopic quantitative analysis
    • X. G. Shao X. H. Bian W. S. Cai An improved boosting partial least squares method for near-infrared spectroscopic quantitative analysis Anal. Chim. Acta 2010 666 32 37
    • (2010) Anal. Chim. Acta , vol.666 , pp. 32-37
    • Shao, X.G.1    Bian, X.H.2    Cai, W.S.3
  • 7
  • 8
    • 58149203252 scopus 로고    scopus 로고
    • Support vector machines and its applications in chemistry
    • H. D. Li Y. Z. Liang Q. S. Xu Support vector machines and its applications in chemistry Chemom. Intell. Lab. Syst. 2009 95 188 198
    • (2009) Chemom. Intell. Lab. Syst. , vol.95 , pp. 188-198
    • Li, H.D.1    Liang, Y.Z.2    Xu, Q.S.3
  • 9
    • 0000209316 scopus 로고    scopus 로고
    • Statistical analysis of NIR data: Data pretreatment
    • J. G. Sun Statistical analysis of NIR data: Data pretreatment J. Chemom. 1997 11 525 532
    • (1997) J. Chemom. , vol.11 , pp. 525-532
    • Sun, J.G.1
  • 10
    • 77957075239 scopus 로고    scopus 로고
    • Framework for explicit drift correction in multivariate calibration models
    • P. Gujral M. Amrhein B. M. Wise D. Bonvin Framework for explicit drift correction in multivariate calibration models J. Chemom. 2010 24 534 543
    • (2010) J. Chemom. , vol.24 , pp. 534-543
    • Gujral, P.1    Amrhein, M.2    Wise, B.M.3    Bonvin, D.4
  • 11
    • 3142619653 scopus 로고    scopus 로고
    • Removal of major interference sources in aqueous near-infrared spectroscopy techniques
    • DOI 10.1007/s00216-004-2569-2
    • D. Chen B. Hu X. G. Shao Q. D. Su Removal of major interference sources in aqueous near-infrared spectroscopy techniques Anal. Bioanal. Chem. 2004 379 143 148 (Pubitemid 40877634)
    • (2004) Analytical and Bioanalytical Chemistry , vol.379 , Issue.1 , pp. 143-148
    • Chen, D.1    Hu, B.2    Shao, X.3    Su, Q.4
  • 12
    • 47749116004 scopus 로고    scopus 로고
    • Outlier detection in near-infrared spectroscopic analysis by using Monte Carlo cross-validation
    • Z. C. Liu W. S. Cai X. G. Shao Outlier detection in near-infrared spectroscopic analysis by using Monte Carlo cross-validation Sci. China, Ser. B: Chem. 2008 51 751 759
    • (2008) Sci. China, Ser. B: Chem. , vol.51 , pp. 751-759
    • Liu, Z.C.1    Cai, W.S.2    Shao, X.G.3
  • 13
    • 77958073328 scopus 로고    scopus 로고
    • Detecting influential observations by cluster analysis and Monte Carlo cross-validation
    • X. H. Bian W. S. Cai X. G. Shao D. Chen E. R. Grant Detecting influential observations by cluster analysis and Monte Carlo cross-validation Analyst 2010 135 2841 2847
    • (2010) Analyst , vol.135 , pp. 2841-2847
    • Bian, X.H.1    Cai, W.S.2    Shao, X.G.3    Chen, D.4    Grant, E.R.5
  • 14
    • 70350364494 scopus 로고    scopus 로고
    • A nonlinear partial least squares algorithm using quadratic fuzzy inference system
    • A. I. Abdel-Rahman G. J. Lim A nonlinear partial least squares algorithm using quadratic fuzzy inference system J. Chemom. 2009 23 530 537
    • (2009) J. Chemom. , vol.23 , pp. 530-537
    • Abdel-Rahman, A.I.1    Lim, G.J.2
  • 16
    • 34547681617 scopus 로고    scopus 로고
    • Removing uncertain variables based on ensemble partial least squares
    • DOI 10.1016/j.aca.2007.07.023, PII S0003267007012226
    • D. Chen W. S. Cai X. G. Shao Removing uncertain variables based on ensemble partial least squares Anal. Chim. Acta 2007 598 19 26 (Pubitemid 47212060)
    • (2007) Analytica Chimica Acta , vol.598 , Issue.1 , pp. 19-26
    • Chen, D.1    Cai, W.2    Shao, X.3
  • 17
    • 70349841560 scopus 로고    scopus 로고
    • Subspace regression ensemble method based on variable clustering for near-infrared spectroscopic calibration
    • C. Tan X. Qin M. L. Li Subspace regression ensemble method based on variable clustering for near-infrared spectroscopic calibration Anal. Lett. 2009 42 1693 1710
    • (2009) Anal. Lett. , vol.42 , pp. 1693-1710
    • Tan, C.1    Qin, X.2    Li, M.L.3
  • 18
    • 49749104280 scopus 로고    scopus 로고
    • Random subspace regression ensemble for near-infrared spectroscopic calibration of tobacco samples
    • C. Tan M. L. Li X. Qin Random subspace regression ensemble for near-infrared spectroscopic calibration of tobacco samples Anal. Sci. 2008 24 647 653
    • (2008) Anal. Sci. , vol.24 , pp. 647-653
    • Tan, C.1    Li, M.L.2    Qin, X.3
  • 19
    • 0030180714 scopus 로고    scopus 로고
    • Wavelength selection for simultaneous spectroscopic analysis. Experimental and theoretical study
    • L. Xu I. Schechter Wavelength selection for simultaneous spectroscopic analysis. Experimental and theoretical study Anal. Chem. 1996 68 2392 2400
    • (1996) Anal. Chem. , vol.68 , pp. 2392-2400
    • Xu, L.1    Schechter, I.2
  • 20
    • 0003188418 scopus 로고    scopus 로고
    • Theoretical justification of wavelength selection in PLS calibration: Development of a new algorithm
    • C. H. Spiegelman M. J. McShane M. J. Goetz M. Motamedi Q. L. Yue G. L. Cote Theoretical justification of wavelength selection in PLS calibration: Development of a new algorithm Anal. Chem. 1998 70 35 44
    • (1998) Anal. Chem. , vol.70 , pp. 35-44
    • Spiegelman, C.H.1    McShane, M.J.2    Goetz, M.J.3    Motamedi, M.4    Yue, Q.L.5    Cote, G.L.6
  • 21
    • 0028902217 scopus 로고
    • Comparison of multivariate methods based on latent vectors and methods based on wavelength selection for the analysis of near-infrared spectroscopic data
    • D. Jouan-Rimbaud B. Walczak D. L. Massart I. R. Last K. A. Prebble Comparison of multivariate methods based on latent vectors and methods based on wavelength selection for the analysis of near-infrared spectroscopic data Anal. Chim. Acta 1995 304 285 295
    • (1995) Anal. Chim. Acta , vol.304 , pp. 285-295
    • Jouan-Rimbaud, D.1    Walczak, B.2    Massart, D.L.3    Last, I.R.4    Prebble, K.A.5
  • 22
    • 0345019845 scopus 로고    scopus 로고
    • Genetic algorithms applied to feature selection in PLS regression: How and when to use them
    • DOI 10.1016/S0169-7439(98)00051-3, PII S0169743998000513
    • R. Leardi A. Lupianez Gonzalez Genetic algorithms applied to feature selection in PLS regression: how and when to use them Chemom. Intell. Lab. Syst. 1998 41 195 207 (Pubitemid 28348346)
    • (1998) Chemometrics and Intelligent Laboratory Systems , vol.41 , Issue.2 , pp. 195-207
    • Leardi, R.1    Lupianez Gonzalez, A.2
  • 23
    • 47749115372 scopus 로고    scopus 로고
    • Genetic-algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: Application on ascorbic acid and uric acid mixture
    • H. Khajehsharifi E. Pourbasheer Genetic-algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: Application on ascorbic acid and uric acid mixture J. Chin. Chem. Soc. 2008 55 163 170
    • (2008) J. Chin. Chem. Soc. , vol.55 , pp. 163-170
    • Khajehsharifi, H.1    Pourbasheer, E.2
  • 24
    • 77049095825 scopus 로고    scopus 로고
    • Selection of individual variables versus intervals of variables in PLSR
    • M. Shariati-Rad M. Hasani Selection of individual variables versus intervals of variables in PLSR J. Chemometr 2010 24 45 56
    • (2010) J. Chemometr , vol.24 , pp. 45-56
    • Shariati-Rad, M.1    Hasani, M.2
  • 25
    • 0024738079 scopus 로고
    • Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry
    • J. H. Kalivas N. Roberts J. M. Sutter Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry Anal. Chem. 1989 61 2024 2030 (Pubitemid 20608746)
    • (1989) Analytical Chemistry , vol.61 , Issue.18 , pp. 2024-2030
    • Kalivas John, H.1    Roberts Nancy2    Sutter Jon, M.3
  • 26
    • 0343134566 scopus 로고    scopus 로고
    • Development of robust calibration models in near infra-red spectrometric applications
    • DOI 10.1016/S0003-2670(00)00718-2, PII S0003267000007182
    • H. Swierenga F. Wulfert O. E. de Noord A. P. de Weijer A. K. Smilde L. M. C. Buydens Development of robust calibration models in near infrared spectrometric applications Anal. Chim. Acta 2000 411 121 135 (Pubitemid 30169237)
    • (2000) Analytica Chimica Acta , vol.411 , Issue.1-2 , pp. 121-135
    • Swierenga, H.1    Wulfert, F.2    De Noord, O.E.3    De Weijer, A.P.4    Smilde, A.K.5    Buydens, L.M.C.6
  • 27
    • 10044248675 scopus 로고    scopus 로고
    • Optimized partition of minimum spanning Tree for piecewise modeling by particle swarm algorithm. QSAR Studies of antagonism of angiotensin II antagonists
    • Q. Shen J. H. Jiang C. X. Jiao S. Y. Huan G. L. Shen R. Q. Yu Optimized partition of minimum spanning Tree for piecewise modeling by particle swarm algorithm. QSAR Studies of antagonism of angiotensin II antagonists J. Chem. Inf. Model. 2004 44 2027 2031
    • (2004) J. Chem. Inf. Model. , vol.44 , pp. 2027-2031
    • Shen, Q.1    Jiang, J.H.2    Jiao, C.X.3    Huan, S.Y.4    Shen, G.L.5    Yu, R.Q.6
  • 28
    • 75749121783 scopus 로고    scopus 로고
    • Variable-weighted least-squares support vector machine for multivariate spectral analysis
    • H. Y. Zou H. L. Wu H. Y. Fu L. J. Tang L. Xu J. F. Nie R. Q. Yu Variable-weighted least-squares support vector machine for multivariate spectral analysis Talanta 2010 80 1698 1701
    • (2010) Talanta , vol.80 , pp. 1698-1701
    • Zou, H.Y.1    Wu, H.L.2    Fu, H.Y.3    Tang, L.J.4    Xu, L.5    Nie, J.F.6    Yu, R.Q.7
  • 30
    • 67650369751 scopus 로고    scopus 로고
    • Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration
    • H. D. Li Y. Z. Liang Q. S. Xu D. S. Cao Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration Anal. Chim. Acta 2009 648 77 84
    • (2009) Anal. Chim. Acta , vol.648 , pp. 77-84
    • Li, H.D.1    Liang, Y.Z.2    Xu, Q.S.3    Cao, D.S.4
  • 31
    • 38949151681 scopus 로고    scopus 로고
    • Computational science: A hard statistical view
    • DOI 10.1038/451639a, PII 451639A
    • B. Selman Computational science: A hard statistical view Nature 2008 451 639 640 (Pubitemid 351220550)
    • (2008) Nature , vol.451 , Issue.7179 , pp. 639-640
    • Selman, B.1
  • 33
    • 14644389629 scopus 로고    scopus 로고
    • A method for near-infrared spectral calibration of complex plant samples with wavelet transform and elimination of uninformative variables
    • DOI 10.1007/s00216-003-2397-9
    • X. G. Shao F. Wang D. Chen Q. D. Su A method for near-infrared spectral calibration of complex plant samples with wavelet transform and elimination of uninformative variables Anal. Bioanal. Chem. 2004 378 1382 1387 (Pubitemid 40877740)
    • (2004) Analytical and Bioanalytical Chemistry , vol.378 , Issue.5 , pp. 1382-1387
    • Shao, X.1    Wang, F.2    Chen, D.3    Su, Q.4
  • 34
    • 38149087476 scopus 로고    scopus 로고
    • A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra
    • W. S. Cai Y. K. Li X. G. Shao A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra Chemom. Intell. Lab. Syst. 2008 90 188 194
    • (2008) Chemom. Intell. Lab. Syst. , vol.90 , pp. 188-194
    • Cai, W.S.1    Li, Y.K.2    Shao, X.G.3
  • 35
    • 65649132723 scopus 로고    scopus 로고
    • A wavelength selection method based on randomization test for near-infrared spectral analysis
    • H. Xu Z. C. Liu W. S. Cai X. G. Shao A wavelength selection method based on randomization test for near-infrared spectral analysis Chemom. Intell. Lab. Syst. 2009 97 189 193
    • (2009) Chemom. Intell. Lab. Syst. , vol.97 , pp. 189-193
    • Xu, H.1    Liu, Z.C.2    Cai, W.S.3    Shao, X.G.4
  • 36
    • 56949090101 scopus 로고    scopus 로고
    • Bayesian linear regression and variable selection for spectroscopic calibration
    • T. Chen E. Martin Bayesian linear regression and variable selection for spectroscopic calibration Anal. Chim. Acta 2009 631 13 21
    • (2009) Anal. Chim. Acta , vol.631 , pp. 13-21
    • Chen, T.1    Martin, E.2
  • 37
    • 0033636234 scopus 로고    scopus 로고
    • Modified Jack-knife estimation of parameter uncertainty in bilinear modeling by partial least squares regress (PLSR)
    • H. Martens M. Martens Modified Jack-knife estimation of parameter uncertainty in bilinear modeling by partial least squares regress (PLSR) Food Qual. Preference 2000 11 5 16
    • (2000) Food Qual. Preference , vol.11 , pp. 5-16
    • Martens, H.1    Martens, M.2
  • 38
    • 0033905297 scopus 로고    scopus 로고
    • Interval partial least-squares regression (iPLS): A comparative chemometric study with an example from near-infrared spectroscopy
    • L. Norgaard A. Saudland J. Wagner J. P. Nielsen L. Munck S. B. Engelsen Interval partial least-squares regression (iPLS): A comparative chemometric study with an example from near-infrared spectroscopy Appl. Spectrosc. 2000 54 413 419 (Pubitemid 30585546)
    • (2000) Applied Spectroscopy , vol.54 , Issue.3 , pp. 413-419
    • Norgaard, L.1    Saudland, A.2    Wagner, J.3    Nielsen, J.P.4    Munck, L.5    Engelsen, S.B.6
  • 39
    • 18844432760 scopus 로고    scopus 로고
    • Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions
    • DOI 10.1002/cem.893
    • R. Leardi L. Norgaard Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions J. Chemom. 2004 18 486 497 (Pubitemid 40688862)
    • (2004) Journal of Chemometrics , vol.18 , Issue.11 , pp. 486-497
    • Leardl, R.1    Norgaard, L.2
  • 40
    • 0037099131 scopus 로고    scopus 로고
    • Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data
    • DOI 10.1021/ac011177u
    • J. H. Jiang R. J. Berry H. W. Siessler Y. Ozaki Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data Anal. Chem. 2002 74 3555 3565 (Pubitemid 34764967)
    • (2002) Analytical Chemistry , vol.74 , Issue.14 , pp. 3555-3565
    • Jiang, J.-H.1    James, R.2    Siesler, B.H.W.3    Ozaki, Y.4
  • 41
    • 0027530250 scopus 로고
    • SIMPLS: An alternative approach to partial least squares regression
    • S. De Jong SIMPLS: an alternative approach to partial least squares regression Chemom. Intell. Lab. Syst. 1993 18 251 263
    • (1993) Chemom. Intell. Lab. Syst. , vol.18 , pp. 251-263
    • De Jong, S.1
  • 43
    • 0028820823 scopus 로고
    • Related versions of the multiplicative scatter correction method for preprocessing spectroscopic data
    • I. S. Helland T. Naes T. Isaksson Related versions of the multiplicative scatter correction method for preprocessing spectroscopic data Chemometr. Intell. Lab. Syst 1995 29 233 241
    • (1995) Chemometr. Intell. Lab. Syst , vol.29 , pp. 233-241
    • Helland, I.S.1    Naes, T.2    Isaksson, T.3
  • 44
    • 0037314976 scopus 로고    scopus 로고
    • Light scattering and light absorbance separated by extended multiplicative signal correction. Application to near-infrared transmission analysis of powder mixtures
    • DOI 10.1021/ac020194w
    • H. Martens J. P. Nielsen S. B. Engelsen Light scattering and light absorbance separated by extended multiplicative signal correction. Application to near-infrared transmission analysis of powder mixture Anal. Chem. 2003 75 394 404 (Pubitemid 36176708)
    • (2003) Analytical Chemistry , vol.75 , Issue.3 , pp. 394-404
    • Martens, H.1    Nielsen, J.P.2    Engelsen, S.B.3
  • 45
    • 84894887900 scopus 로고
    • Computer aided design of experiments
    • R. W. Kennard L. A. Stone Computer aided design of experiments Technometrics 1969 11 137 148
    • (1969) Technometrics , vol.11 , pp. 137-148
    • Kennard, R.W.1    Stone, L.A.2
  • 46
    • 0002656714 scopus 로고
    • Selection of optimal regression models via cross-validation
    • D. W. Osten Selection of optimal regression models via cross-validation J. Chemom. 1988 2 39 48
    • (1988) J. Chemom. , vol.2 , pp. 39-48
    • Osten, D.W.1
  • 47
    • 67650214895 scopus 로고    scopus 로고
    • A practical approach for near infrared spectral quantitative analysis of complex samples using partial least squares modeling
    • Z. C. Liu X. Ma Y. D. Wen Y. Wang W. S. Cai X. G. Shao A practical approach for near infrared spectral quantitative analysis of complex samples using partial least squares modeling Sci. China, Ser. B: Chem. 2009 52 1021 1027
    • (2009) Sci. China, Ser. B: Chem. , vol.52 , pp. 1021-1027
    • Liu, Z.C.1    Ma, X.2    Wen, Y.D.3    Wang, Y.4    Cai, W.S.5    Shao, X.G.6
  • 48
    • 0037191154 scopus 로고    scopus 로고
    • Model selection for partial least squares regression
    • DOI 10.1016/S0169-7439(02)00051-5, PII S0169743902000515
    • B. Li J. Morris E. B. Martin Model selection for partial least squares regression Chemom. Intell. Lab. Syst. 2002 64 79 89 (Pubitemid 35304561)
    • (2002) Chemometrics and Intelligent Laboratory Systems , vol.64 , Issue.1 , pp. 79-89
    • Li, B.1    Morris, J.2    Martin, E.B.3


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