Near infrared spectroscopy supported by multivariate data analysis and GC-MS for discrimination and classification of different species in Achillea genus

Abstract

This study evaluated the use of near infrared spectroscopy (NIRS) for discriminating and classifying traditional medicinal plants. Achillea millefolium and three of its related species, namely, A. clypeolata, A. collina and A. nobilis were chosen as sample material because they are well known in the field of traditional medicine. The present study was subdivided into following sections: 1.) Discrimination of A. millefolium flowers and leaves by using NIRS and gas chromatography hyphenated to mass spectrometry (GC-MS) as reference method. 2.) Classification of differently treated A. millefolium samples by principal component analysis (PCA). 3.) Classification of four Achillea species by PCA. The results showed that NIRS is suitable to discriminate between different A. millefolium parts (e.g., flowers and leaves), as well as between different sample preparation techniques (e.g. air-dried, oven-dried). Furthermore, the established NIRS method proved great potential for classification of related Achillea species. This approach allowed the clustering by NIRS according to the individual ingredient patterns, applying GC-MS as a reference method for calibration. This developed NIRS method proved to be rapid and nondestructive technique for identification, discrimination and classification of traditional medicinal materials.