Abstract
Sample selection is often used to improve the cost-effectiveness of near-infrared (NIR) spectral analysis. When raw NIR spectra are used, however, it is not easy to select appropriate samples, because of background interference and noise. In this paper, a novel adaptive strategy based on selection of representative NIR spectra in the continuous wavelet transform (CWT) domain is described. After pretreatment with the CWT, an extension of the Kennard–Stone (EKS) algorithm was used to adaptively select the most representative NIR spectra, which were then submitted to expensive chemical measurement and multivariate calibration. With the samples selected, a PLS model was finally built for prediction. It is of great interest to find that selection of representative samples in the CWT domain, rather than raw spectra, not only effectively eliminates background interference and noise but also further reduces the number of samples required for a good calibration, resulting in a high-quality regression model that is similar to the model obtained by use of all the samples. The results indicate that the proposed method can effectively enhance the cost-effectiveness of NIR spectral analysis. The strategy proposed here can also be applied to different analytical data for multivariate calibration.
Similar content being viewed by others
References
Golic M, Walsh K, Lawson P (2003) Appl Spectrosc 57:139–145
Chen D, Wang F, Shao XG, Su QD (2003) Analyst 128:1200–1203
Luypaert J, Zhang MH, Massart DL (2003) Anal Chim Acta 478:303–312
Boschetti CE, Olivieri AC (2001) J Near Infrared Spectrosc 9:245–254
Breitkreitz MC, Raimundo IM Jr, Rohwedder JJR, Pasquini C, Dantas-Filho HA, José GE, Araújo MCU (2003) Analyst 128:1204–1207
Walsh KB, Golic M, Greensill CV (2004) J Near Infrared Spectrosc 12:141–148
Olivieri AC, Faber NKM, Ferré J, Boque R, Kalivas JH, Mark H (2006) Pure Appl Chem 78:633–661
Chen D, Shao XG, Hu B, Su QD (2004) Anal Chim Acta 511:37–45
Chen D, Hu B, Shao XG, Su QD (2005) Anal Bioanal Chem 381:795–805
Puchwein G (1988) Anal Chem 60:569–573
Jouan-Rimbaud D, Massart DL, Saby CA, Puel C (1997) Anal Chim Acta 350:149–161
Goicoechea HC, Olivieri AC (2001) Analyst 126:1105–1112
Wu W, Walczak B, Massart DL, Heuerding S, Erni F, Last IR, Prebble KA (1996) Chemometr Intell Lab Syst 33:35–46
Zhou ZH, Wu JX, Tang W (2002) Artif Intell 137:239–263
Ferré J, Rius FX (1996) Anal Chem 68:1565–1571
Ferré J, Rius FX (1997) Trends Anal Chem 16:70–73
Dantas-Filho HA, Galvão RKH, Araújo MCU, da Silva EC, Saldanha TCB, José GE, Pasquini C, Raimundo IM Jr, Rohwedder JJR (2004) Chemometr Intell Lab Syst 72:83–91
Kennard RW, Stone LA (1969) Technometrics 11:137–148
Daszykowski M, Walczak B, Massart DL (2002) Anal Chim Acta 468:91–103
Fedorov VV (1972) In: Studden WJ, Klimko EM (eds) Theory of optimal experiments. Academic Press, New York
Rius A, Callao MP, Ferré J, Rius FX (1997) Anal Chim Acta 337:287–296
Bouveresse E, Hartmann C, Massart DL, Last IR, Prebble KA (1996) Anal Chem 68:982–990
deGroot PJ, Postma GJ, Melssen WJ, Buydens LMC (1999) Anal Chim Acta 392:67–75
Galvão RKH, Araújo MCU, José GE, Pontes MJC, Saldanha TCB (2005) Talanta 67:736–740
Gorry PA (1990) Anal Chem 62:570–573
Chen D, Hu B, Shao XG, Su QD (2004) Analyst 129:664–669
Shao XG, Leung AKM, Chau FT (2003) Accounts Chem Res 36:276–283
Chen D, Hu B, Shao XG, Su QD (2004) Anal Bioanal Chem 379:143–148
Mittermary CR, Tan HW, Brown SD (2001) Appl Spectrosc 55:827–833
Ma CX, Shao XG (2004) J Chem Inf Comput Sci 44:907–911
Shao XG, Pang CY, Su QD (2000) Fresenius J Anal Chem 367:525–529
Lin J (1998) Appl Spectrosc 52:1591–1596
Fearn T (1996) NIR news 7:5–6
Acknowledgement
This study is supported by National Natural Science Foundation (Nos 20325517 and 20575031), the Ph.D. Programs Foundation of the Ministry of Education (MOE) of China (No. 20050055001), and the Teaching and Research Award Program for Outstanding Young Teachers (TRAPOYT) in High Education Institutions of the MOE of China.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, D., Cai, W. & Shao, X. An adaptive strategy for selecting representative calibration samples in the continuous wavelet domain for near-infrared spectral analysis. Anal Bioanal Chem 387, 1041–1048 (2007). https://doi.org/10.1007/s00216-006-0967-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00216-006-0967-3