Identification of fungal phytopathogens using Fourier transform infraredattenuated total reflection spectroscopy and advanced statistical methods

Ahmad Salman, Itshak Lapidot, Ami Pomerantz, Leah Tsror, Elad Shufan, Raymond Moreh, Shaul Mordechai, Mahmoud Huleihel

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The early diagnosis of phytopathogens is of a great importance; it could save large economical losses due to crops damaged by fungal diseases, and prevent unnecessary soil fumigation or the use of fungicides and bactericides and thus prevent considerable environmental pollution. In this study, 18 isolates of three different fungi genera were investigated; six isolates of Colletotrichum coccodes, six isolates of Verticillium dahliae and six isolates of Fusarium oxysporum. Our main goal was to differentiate these fungi samples on the level of isolates, based on their infrared absorption spectra obtained using the Fourier transform infrared-attenuated total reflection (FTIR-ATR) sampling technique. Advanced statistical and mathematical methods: principal component analysis (PCA), linear discriminant analysis (LDA), and k-means were applied to the spectra after manipulation. Our results showed significant spectral differences between the various fungi genera examined. The use of k-means enabled classification between the genera with a 94.5% accuracy, whereas the use of PCA [3 principal components (PCs)] and LDA has achieved a 99.7% success rate. However, on the level of isolates, the best differentiation results were obtained using PCA (9 PCs) and LDA for the lower wavenumber region (800-1775 cm-1), with identification success rates of 87%, 85.5%, and 94.5% for Colletotrichum, Fusarium, and Verticillium strains, respectively.

Original languageEnglish
Article number017002
JournalJournal of Biomedical Optics
Volume17
Issue number1
DOIs
StatePublished - 1 Jan 2012

Keywords

  • Colletotrichum coccodes
  • Fourier transform infrared-attenuated total reflection
  • Fungal detection
  • Fusarium oxysporum
  • Linear discriminant analysis
  • Principal component analysis
  • Verticillium dahliae

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Biomedical Engineering

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