[Discrimination of bamboo using FTIR spectroscopy and statistical analysis]

Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Dec;33(12):3221-5.
[Article in Chinese]

Abstract

Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to identify and classify bamboo leaves. FTIR spectra of fifty-four bamboo leaf samples belonging to six species were obtained. The results showed that the infrared spectra of bamboo leaves were similar, and mainly composed of the bands of polysaccharides, protein and lipids. The original spectra exhibit minor differences in the region of 1800-700cm-1. The second derivative spectra show apparent differences in the same region. Principal component analysis and hierarchical cluster analysis were performed on the second derivative infrared spectra in the range from 1800 to 700 cm-1. The leaf samples were separated into 6 groups with accuracy of 98% with the first three principal components, and with 100% accuracy according to the third and fourth principal components. Hierarchical cluster analysis can correctly cluster the bamboo leaf samples. It is proved that Fourier transform infrared spectroscopy combined with PCA and HCA could be used to discriminate bamboo at species level with only a tiny leaf sample.

MeSH terms

  • Bambusa / classification*
  • Cluster Analysis
  • Plant Leaves / classification*
  • Principal Component Analysis
  • Spectroscopy, Fourier Transform Infrared*