Efficient Discrimination of Some Moss Species by Fourier Transform Infrared Spectroscopy and Chemometrics

Zhen Cao,Yongying Liu,Jiancheng Zhao

doi:10.1155/2014/191796

Abstract

Fourier transform infrared spectroscopy (FTIR) technique was used to classify 16 species from three moss families (Mielichhoferiaceae, Bryaceae, and Mniaceae). The FTIR spectra ranging from 4000 cm−1to 400 cm−1of the 16 species were obtained. To group the spectra according to their spectral similarity in a dendrogram, cluster analysis and principal component analysis (PCA) were performed. Cluster analysis combined with PCA was used to give a rough result of classification among the moss samples. However, some species belonging to the same genus exhibited very similar chemical components and similar FTIR spectra. Fourier self-deconvolution (FSD) was used to enhance the differences of the spectra. Discrete wavelet transform (DWT) was used to decompose the FTIR spectra ofMnium laevinerveandM. spinosum. Three scales were selected as the feature extracting space in the DWT domain. Results showed that FTIR spectroscopy combined with DWT was suitable for distinguishing different species of the same genus.

Highlights

Mosses are perennial plants, typically 1 cm to 10 cm tall, usually occur in large tufts, and concentrate in groups
Results of the present analysis show that Fourier transform infrared spectroscopy (FTIR) spectroscopy in combination with principal component analysis (PCA) and cluster analyses can be used to discriminate the genera in Mielichhoferiaceae, Bryaceae, and Mniaceae
Recent studies based on molecular data indicated that genus Pohlia belongs to the family Mniaceae [41]

Summary

Introduction

Typically 1 cm to 10 cm tall, usually occur in large tufts, and concentrate in groups. The FTIR spectra of some species in families Mielichhoferiaceae, Bryaceae, and Mniaceae were similar. WT is useful for the compression of digital image files, noise reduction, and pattern recognition It provides a time-frequency representation of the signal. The present study aimed to evaluate the potential use of FTIR spectroscopy combined with cluster analysis and PCA technique for the discrimination of 16 moss species. DWT possesses compact support in both time and frequency domains [27] It is a signal-processing tool that is used in many engineering, scientific, and mathematical applications. The DWT is computed by successive low-pass and high-pass filtering of the discrete time-domain signal. This computation is called the Mallat algorithm or Mallat-tree decomposition. The time resolution becomes arbitrarily good at high frequencies, whereas the frequency resolution becomes arbitrarily good at low frequencies [29]

Materials and Methods

Validation of the Method

Conclusion