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Classification of phyto-pathogens using infrared spectroscopy and advanced computerized methods
Year:
2013
Authors :
Tsror, Leah
;
.
Volume :
Co-Authors:
Salman, A., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Shufan, E., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection Agricultural Research Organization, Gilat Experiment Station, M.P. Negev, 85250, Israel
Moreh, R., Department of Physics, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Huleihel, M., Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Mordechai, S., Department of Physics, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Facilitators :
From page:
14
To page:
19
(
Total pages:
6
)
Abstract:
Fungi are serious pathogens for many plants and crops, potentially causing severe economic loss. Early detection and identification of these pathogens is crucial for their timely control. Currently existing methods available for identification of fungi are time consuming, expensive and not always very specific. We used Fourier Transform InfraRed spectroscopy (FTIR) attenuated total reflectance (ATR), combined with Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA), for differentiating fungal phyto-pathogens at the isolate level. Four different fungi genera were investigated; Colletotrichum, Verticillium, Fusarium and Rhizoctoniai. Our main goal was to differentiate these fungi samples at the level of isolates, based on their infrared (IR) fingerprint absorption spectra. Based on our computerized and objective analyses, our results are in high compliance with existing biological classification methods. FTIR, combined with advanced computerized methods, provides an inexpensive and reagentfree technique that delivers accurate results on fungi classification within few minutes. FTIR may also turn out to be an important in situ and in vivo alternative diagnostic tool in agricultural. At the generic level, the identification success rate was 97.5% using five principal components (PCs), while at the isolates level the identification success rates were 97.1%, 90%, and 89%, respectively, for Verticillium dahliae, Colletotrichum coccodes, and Fusarium oxysporum.
Note:
Related Files :
FT-IR-ATR
Fungal detection
Fungal detections
fungi
Pathogens
Rhizoctonia solani
Show More
Related Content
More details
DOI :
Article number:
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
30655
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:56
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Scientific Publication
Classification of phyto-pathogens using infrared spectroscopy and advanced computerized methods
Salman, A., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Shufan, E., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection Agricultural Research Organization, Gilat Experiment Station, M.P. Negev, 85250, Israel
Moreh, R., Department of Physics, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Huleihel, M., Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Mordechai, S., Department of Physics, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Classification of phyto-pathogens using infrared spectroscopy and advanced computerized methods
Fungi are serious pathogens for many plants and crops, potentially causing severe economic loss. Early detection and identification of these pathogens is crucial for their timely control. Currently existing methods available for identification of fungi are time consuming, expensive and not always very specific. We used Fourier Transform InfraRed spectroscopy (FTIR) attenuated total reflectance (ATR), combined with Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA), for differentiating fungal phyto-pathogens at the isolate level. Four different fungi genera were investigated; Colletotrichum, Verticillium, Fusarium and Rhizoctoniai. Our main goal was to differentiate these fungi samples at the level of isolates, based on their infrared (IR) fingerprint absorption spectra. Based on our computerized and objective analyses, our results are in high compliance with existing biological classification methods. FTIR, combined with advanced computerized methods, provides an inexpensive and reagentfree technique that delivers accurate results on fungi classification within few minutes. FTIR may also turn out to be an important in situ and in vivo alternative diagnostic tool in agricultural. At the generic level, the identification success rate was 97.5% using five principal components (PCs), while at the isolates level the identification success rates were 97.1%, 90%, and 89%, respectively, for Verticillium dahliae, Colletotrichum coccodes, and Fusarium oxysporum.
Scientific Publication
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