Discrimination of yerba mate (Ilex paraguayensis St. Hil.) samples according to their geographical origin by means of near infrared spectroscopy and multivariate analysis

Original Paper

Abstract

Near infrared reflectance (NIR) spectroscopy combined with multivariate data analysis was used to discriminate between the geographical origins of yerba mate (Ilex paraguayensis St. Hil.) samples. Samples were purchased from the local market and scanned in the NIR region (1100–2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to classify the samples based on their NIR spectra according to their geographical origin. Full cross validation was used as validation method when classification models were developed. The overall classification rates obtained were 76 and 100% using PLS-DA and LDA, respectively. The results demonstrated the usefulness of NIR spectra combined with multivariate data analysis as an objective and rapid method to classify yerba mate samples according to their geographical origin. Nevertheless, NIR spectroscopic might provide initial screening in the food chain and enable costly methods to be used more productively on suspect specimens.

Keywords

Near infrared Spectroscopy Principal component analysis Linear discriminant analysis Yerba mate Ilex paraguayensis 

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Instituto Nacional de Investigación AgropecuariaEstación Experimental INIA La EstanzuelaColoniaUruguay
  2. 2.The Australian Wine Research InstituteAdelaideAustralia

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