Variables selection methods in near-infrared spectroscopy

Zhang, Xiaobo; Zhao, Jiewen; Povey, M. J. W.; Holmes, Mel; Hanpin, Mao

doi:10.1016/j.aca.2010.03.048

Cited by 884 publications

(415 citation statements)

References 100 publications

(140 reference statements)

Supporting

Mentioning

397

Contrasting

Unclassified

Order By: Relevance

“…It was observed that the transmittance in several zones changes with the ethanol concentration. The plot shows the principal amplified regions of ethanol absorptions in 1600-1900 nm region related with O-H combinations (Xiaobo et al 2010) and C-H stretch first overtones (Liu et al 2008;Xiaobo et al 2010) and 2200-2300 nm related with C-H vibrations (Osborne et al 1993;Dambergs et al 2002;Cozzolino et al 2003).…”

Section: Resultsmentioning

confidence: 99%

Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds

Martelo-Vidal¹,

Vázquez²

2014

Czech J. Food Sci.

View full text Add to dashboard Cite

Martelo-Vidal M.J., Vázquez M. (2014): Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds. Czech J. Food Sci., 32: 37-47.Spectroscopy of UV-VIS-NIR combined with chemometric analyses was used as a non-destructive technique to build models for the quantitative characterisation of the main compounds of wine. The work in mixtures can give insight into how interferences affect the performance of calibrations in wines. Ethanol, glycerol, glucose, tartaric acid, malic acid, lactic acid, and acetic acid were evaluated as pure compounds and in mixtures. Different pre-treatments for the spectra and modelling strategies such as partial least squares (PLS) regression or Principal Component Regression (PCR) were evaluated. All pure compounds studied showed a good relationship between spectra and concentrations. However, interferences were observed in the mixtures and only good models for ethanol, tartaric acid, and malic acid were obtained. The best model was obtained in the NIR region for ethanol and in the UV region for tartaric acid and malic acid. The results indicate that NIR spectroscopy could be used as an alternative to conventional chemical methods for ethanol determination and UV spectroscopy for the determination of tartaric acid and malic acid.

show abstract

Section: Resultsmentioning

confidence: 99%

Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds

Martelo-Vidal¹,

Vázquez²

2014

Czech J. Food Sci.

View full text Add to dashboard Cite

show abstract

“…Several reviews of GAs and their application to chemistry-related problems have been published [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data

Cséfalvayová

Pelikán

Cigić

et al. 2010

Talanta

View full text Add to dashboard Cite

Quantitative non-destructive analysis of individual constituents of historic rag paper is crucial for its effective preservation. In this work, we examine the potentials of mid-and near-infrared spectroscopy, however, in order to fully utilise the selectivity inherent to spectroscopic multivariate measurements, genetic algorithms were used to select spectral data derived from information-rich FT-IR or UV-VIS-NIR measurements to build multivariate calibration models based on partial least squares regression, relating spectra to gelatine content in paper. A selective but laborious chromatographic method for the quantification of hydroxyproline (HYP) has been developed to provide the reference data on gelatine content. We used 9-fluorenylmethyl chloroformate (FMOC) to derivatise HYP, which was subsequently determined using reverse-phase liquid chromatographic separation and fluorimetric detection. In this process, the sample is consumed, which is why the method can only be used as a reference method.The sampling flexibility afforded by small-size field-portable spectroscopic instrumentation combined

show abstract

“…Most recently applications have been published showing that spectral region selection using suitable algorithms such as interval partial least squares (iPLS) and synergical partial least squares (siPLS) can significantly improve the performance of PLS regression techniques (Xiaobo et al, 2010;Shi et al, 2012;Piantavini et al, 2015;Silva, Flores and Parisotto, 2016). Moreover, spectral region selection containing relevant chemical information is especially important for spectra with strong band overlapping such as pharmaceutical formulations (containing active substance, impurities and excipients) (Silva et al, 2009;Piantavini et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous determination of valsartan, amlodipine besylate and hydrochlorothiazide in tablets by near infrared

Becker¹,

Foresti²,

Almeida³

et al. 2017

J App Pharm Sci

View full text Add to dashboard Cite

Interval partial least-squares calibration (iPLS) and synergical partial least-squares calibration (siPLS) methods in combination with near infrared spectroscopy coupled with integrating sphere (NIRA) have been developed for simultaneous determination of amlodipine (AML), valsartan (VAL) and hydrochlorothiazide (HCT) in raw material powder mixtures used for production commercial pharmaceutical product (tablets). Variable selection methods (iPLS and siPLS) were applied to select a spectral range that provided significant information and models with lower prediction errors. A near-infrared reflectance accessory (NIRA) was used for direct sample analysis. Spectral data were acquired between 10000 -4000 cm -1 and divided into 32 intervals. A relative standard error of prediction of 1.27% for VAL, 1.92% for HCT and 5.19% for AML was obtained after selection of better intervals by siPLS. Results shown that variable selection methods associated to NIRA is a relatively simple, free solvent and non-destructive procedure that could be applied to the simultaneous determination of AML, VAL and HCT in tablets.

show abstract

Variables selection methods in near-infrared spectroscopy

Cited by 884 publications

References 100 publications

Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds

Evaluation of ultraviolet, visible, and near infrared spectroscopy for the analysis of wine compounds

Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data

Simultaneous determination of valsartan, amlodipine besylate and hydrochlorothiazide in tablets by near infrared

Contact Info

Product

Resources

About