Identification of fungal phytopathogens using Fourier transform infrared-attenuated total reflection spectroscopy and advanced statistical methods

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

doi:doi:10.1117/1.JBO.17.1.017002

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Journal of Biomedical Optics / Volume 17 / Issue 1 / Research Papers: Sensing

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Identification of fungal phytopathogens using Fourier transform infrared-attenuated total reflection spectroscopy and advanced statistical methods

J. Biomed. Opt. 17, 017002 (Feb 06, 2012); http://dx.doi.org/10.1117/1.JBO.17.1.017002

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Abstract

References (57)

Ahmad Salman and Elad Shufan

SCE-Sami Shamoon College of Engineering, Department of Physics, Beer-Sheva 84100, Israel

Itshak Lapidot

SCE-Sami Shamoon College of Engineering, Department of Electrical and Electronics Engineering, Beer-Sheva 84100, Israel

Ami Pomerantz and Mahmoud Huleihel

Ben-Gurion University of the Negev, Department of Virology and Developmental Genetics, Faculty of Health Sciences, Beer-Sheva 84105, Israel

Leah Tsror

Institute of Plant Protection, Department of Plant Pathology, Agricultural Research Organization, Gilat Experiment Station, M.P. Negev, 85250, Israel

Raymond Moreh and Shaul Mordechai

Ben-Gurion University, Department of Physics, Beer-Sheva 84105, Israel

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.

History

Received Sep 13, 2011
Accepted Nov 04, 2011
Revised Nov 02, 2011
Published online Feb 06, 2012

Digital Object Identifier

http://dx.doi.org/10.1117/1.JBO.17.1.017002

Citation

Ahmad Salman, Itshak Lapidot, Ami Pomerantz, Leah Tsror, Elad Shufan, Raymond Moreh, Shaul Mordechai and Mahmoud Huleihel, "Identification of fungal phytopathogens using Fourier transform infrared-attenuated total reflection spectroscopy and advanced statistical methods", J. Biomed. Opt. 17, 017002 (Feb 06, 2012); http://dx.doi.org/10.1117/1.JBO.17.1.017002