The direct chemical analysis allows investigating samples without altering them, keeping the sample available for further analysis. For the qualitative investigation, analytical procedures like gas-chromatography, Raman microscopy, and Infra Red spectroscopy are available; however, the univariate approach is not exhaustive in the case of very complex matrices. The quantitative approach is still an open issue, due to the strong matrix effect hindering the creation of univariate calibration methods in interpolation mode. The multivariate analysis may be the solution. Three-way Principal Components Analysis (PCA) allows for comprehension of variables influencing classification. The Partial Least Squares regression (PLS) combined with Discriminant Analysis (DA) allows classifying. Multivariate standard addition calibration based on PLS coupled with Net Analyte Signal (NAS) calculation allows bypassing the matrix effect in quantitative analysis. This Chapter is focused on the issues mentioned above. Three sections will be presented: SECTION 1: three-way PCA is applied to the discrimination among bacterial species in samples analyzed as such by pyrolysis gas chromatography-mass spectrometry. Applications to timely analysis of pathogenic microbes are foreseen. SECTION 2 PLS-DA is applied to Raman spectra to discriminate adulterated beeswaxes from natural ones. This procedure may be implemented to prevent possible adulteration of bees’ products. SECTION 3 PLS-NAS is applied to ATR spectra to quantify biogenic silica in marine sediments. The new method allows to accurately study the time evolution of primary productivity in the Antarctic basins.

Chemometrics for the direct analysis of solid samples by spectroscopic and chromatographic techniques

LOCATELLI, Marcello
2017

Abstract

The direct chemical analysis allows investigating samples without altering them, keeping the sample available for further analysis. For the qualitative investigation, analytical procedures like gas-chromatography, Raman microscopy, and Infra Red spectroscopy are available; however, the univariate approach is not exhaustive in the case of very complex matrices. The quantitative approach is still an open issue, due to the strong matrix effect hindering the creation of univariate calibration methods in interpolation mode. The multivariate analysis may be the solution. Three-way Principal Components Analysis (PCA) allows for comprehension of variables influencing classification. The Partial Least Squares regression (PLS) combined with Discriminant Analysis (DA) allows classifying. Multivariate standard addition calibration based on PLS coupled with Net Analyte Signal (NAS) calculation allows bypassing the matrix effect in quantitative analysis. This Chapter is focused on the issues mentioned above. Three sections will be presented: SECTION 1: three-way PCA is applied to the discrimination among bacterial species in samples analyzed as such by pyrolysis gas chromatography-mass spectrometry. Applications to timely analysis of pathogenic microbes are foreseen. SECTION 2 PLS-DA is applied to Raman spectra to discriminate adulterated beeswaxes from natural ones. This procedure may be implemented to prevent possible adulteration of bees’ products. SECTION 3 PLS-NAS is applied to ATR spectra to quantify biogenic silica in marine sediments. The new method allows to accurately study the time evolution of primary productivity in the Antarctic basins.
File in questo prodotto:
File Dimensione Formato  
Capitolo Libro Chemometrics ISBN 978-1-53610-518-6.pdf

Solo gestori archivio

Tipologia: PDF editoriale
Dimensione 8.1 MB
Formato Adobe PDF
8.1 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/665544
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact