期刊名称：Journal of Data Analysis and Information Processing
印刷版ISSN：2327-7211
电子版ISSN：2327-7203
出版年度：2013
卷号：1
期号：3
页码：30-34
DOI：10.4236/jdaip.2013.13005
出版社：Scientific Research Publishing
摘要：Short-wavelength near infrared spectroscopy (SW-NIR) is a very rapid, versatile and precise technique, which can be used in many different situations and for very types of products and chemical compounds. Extended multiplicative signal correction (EMSC) is a modification of the standard MSC pre-processing method that allows the separation of physical light scattering effects from chemical (vibrational) light absorbance effects in spectra. In this paper, the EMSC is applied and compared with first derivate, second derivate, MSC and SNV in combination of PLSR to obtain robust models in terms of accuracy and predict ability with a reduced calibration data set using SW-NIR spectra of moisture in marzipan. The Extended Multiplicative Signal Correction—EMSC and combination methods provide the best results in terms of prediction ability and calibration SW-NIR spectra of moisture in marzipan. The best classification results were obtained by Extended Multiplicative Signal Correction followed by second derivates.
关键词：EMSC; PLSR; SW-NIR; Extended Multiplicative Signal Correction; Chemometrics
