Author： Dupuy Nathalie Huvenne Jean Pierre Duponchel Ludovic Legrand Pierre
Publisher： Society for Applied Spectroscopy
ISSN： 0003-7028
Source： Applied Spectroscopy, Vol.49, Iss.5, 1995-05, pp. : 580-585
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
Principal component analysis (PCA) of infrared spectra has been used as a classification method for the green beans of coffee from various origin. Before spectral acquisition, sampling methods were tested for 45 samples, and we chose dry extract of water-soluble compounds on SiCaF2 supports. After PCA of the first derivatized spectra, the first four loadings were examined. The scores of the second principal component appear to be directly correlated by their sign to the species arabica or robusta. This result allows an easy classification. In the same way, the pigmentation is well characterized into two groups on the scattergram of the samples with respect to the PC1 and PC3 components. Another feature of this method is that the analysis of the spectral data in terms of residual variance separate components which are correlated with properties. This approach provides assistance in the interpretation of infrared spectra of complex mixtures.
Related content
Access to resources
Recommend
Multicomponent Analysis of FT-IR Spectra
By Saarinen Pekka Kauppinen Jyrki
Applied Spectroscopy, Vol. 45, Iss. 6, 1991-07 ,pp. :
Polymers Research Journal, Vol. , Iss. , 2016-10 ,pp. :