title: Background correction in near-infrared spectra of plant extracts by orthogonal signal correction.
abstract: In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.
authors.affiliation: Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310027, China.
authors.forename: Hai-bin
authors.initials: HB
authors.lastname: Qu
authors.forename: Dan-lin
authors.initials: DL
authors.lastname: Ou
authors.forename: Yi-yu
authors.initials: YY
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D039323:Coptis / Q000737:chemistry*; D008956:Models, Chemical; D015233:Models, Statistical; D015999:Multivariate Analysis; D010936:Plant Extracts / Q000032:analysis* / Q000737:chemistry*; D025341:Principal Component Analysis; D013055:Spectrophotometry, Infrared / Q000379:methods*
chemical_list: D010936:Plant Extracts