Journal
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
Volume 163, Issue -, Pages 20-27Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2016.03.017
Keywords
Multivariate calibration; Near infrared spectroscopy; Spectral pretreatment; Robustness
Categories
Funding
- National Natural Science Foundation of China [81303218]
- Ministry of Education of China [20130013120006]
- Beijing Nova Program of China [xx2016050]
- Science Fund for Distinguished Young Scholars in BUCM [2015-JYB-XYQ-003]
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In multivariate calibration, the optimization of pretreatment methods is usually according to the prediction error and there is a lack of robustness evaluation. This study investigated the robustness of pretreatment methods by adding different simulate noises to validation dataset, calibration and validation datasets, respectively. The root mean squared error of prediction (RMSEP) and multivariate detection limits (MDL) were simultaneously calculated to assess the robustness of different pretreatment methods. The result with two different near-infrared (NIR) datasets illustrated that Multiplicative Scatter Correction (MSC) and Standard normal variate (SNV) were substantially more robust to additive noise with smaller REMSP and MDL value. (C) 2016 Elsevier B.V. All rights reserved.
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