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A method for near-infrared spectral calibration of complex plant samples with wavelet transform and elimination of uninformative variables

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Abstract

An algorithm is proposed for extracting relevant information from near-infrared (NIR) spectra for multivariate calibration of routine components in complex plant samples. The algorithm is a combination of wavelet transform (WT) data compression and a procedure for uninformative variable elimination (UVE). After compression of the NIR spectra by WT, the UVE approach is used to eliminate the irrelevant wavelet coefficients. Finally, a calibration model is built from the retained wavelet coefficients to enable prediction. Because irrelevant information can be removed from the spectra used for multivariate calibration, the model based on the extracted relevant features is better than those obtained with full-spectrum data. Both prediction precision and calculation speed are improved.

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Acknowledgement

This study is supported by the National Natural Science Foundation of China (No. 29975027) and State Tobacco Monopoly Administration Bureau of China (No. 110200101042)

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Authors and Affiliations

  1. Department of Chemistry, University of Science and Technology of China, 230026, Hefei, Anhui, People’s Republic of China

    Xueguang Shao, Fang Wang, Da Chen & Qingde Su

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  1. Xueguang Shao
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  2. Fang Wang
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  3. Da Chen
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  4. Qingde Su
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Correspondence to Xueguang Shao.

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Shao, X., Wang, F., Chen, D. et al. A method for near-infrared spectral calibration of complex plant samples with wavelet transform and elimination of uninformative variables. Anal Bioanal Chem 378, 1382–1387 (2004). https://doi.org/10.1007/s00216-003-2397-9

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  • DOI: https://doi.org/10.1007/s00216-003-2397-9

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