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Detection of Fusarium oxysporum fungal isolates using ATR spectroscopy -2013
Year:
2013
Authors :
צרור, לאה
;
.
Volume :
7
Co-Authors:
Salman, A., Department of Physics, SCE, Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel
Lapidot, I., Department of Electrical and Electronics Engineering, SCE, Sami Shamoon College of Engineering, Ashdod, Israel
Pomerantz, A., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, Israel
Hammody, Z., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Moreh, R., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Huleihel, M., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
Mordechai, S., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Facilitators :
From page:
47
To page:
51
(
Total pages:
5
)
Abstract:
Fungi are considered as serious pathogens for many plants, potentially causing severe economic damage. Early detection and identification of these pathogens is crucial for their timely control. The methods available for identification of fungi are time consuming and not always very specific. In this study, the potential of FTIR-ATR spectroscopy was examined together with advanced mathematical principle component analysis (PCA) and statistical linear discriminant analysis (LDA) to differentiate among 10 isolates of Fusarium oxysporum. The results are encouraging and indicate that FTIR-ATR can successfully detect different isolates of Fusarium oxysporum. Based on PCA and LDA calculations in the region 850-1775 cm-1 with 16 PCs, the different strains from the same fungal genus could be classified with 75.3 and 69.5% success rates using the 'leave one out' method and '20-80% algorithm' respectively. © 2013 The Authors.
Note:
Related Files :
FTIR-ATR
Fungal detection
Fusarium
LDA
PCA
עוד תגיות
תוכן קשור
More details
DOI :
10.3233/978-1-61499-184-7-047
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
23056
Last updated date:
02/03/2022 17:27
Creation date:
16/04/2018 23:56
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Scientific Publication
Detection of Fusarium oxysporum fungal isolates using ATR spectroscopy -2013
7
Salman, A., Department of Physics, SCE, Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel
Lapidot, I., Department of Electrical and Electronics Engineering, SCE, Sami Shamoon College of Engineering, Ashdod, Israel
Pomerantz, A., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, Israel
Hammody, Z., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Moreh, R., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Huleihel, M., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
Mordechai, S., Department of Physics, Ben-Gurion University, Beer-Sheva, Israel
Detection of Fusarium oxysporum fungal isolates using ATR spectroscopy
Fungi are considered as serious pathogens for many plants, potentially causing severe economic damage. Early detection and identification of these pathogens is crucial for their timely control. The methods available for identification of fungi are time consuming and not always very specific. In this study, the potential of FTIR-ATR spectroscopy was examined together with advanced mathematical principle component analysis (PCA) and statistical linear discriminant analysis (LDA) to differentiate among 10 isolates of Fusarium oxysporum. The results are encouraging and indicate that FTIR-ATR can successfully detect different isolates of Fusarium oxysporum. Based on PCA and LDA calculations in the region 850-1775 cm-1 with 16 PCs, the different strains from the same fungal genus could be classified with 75.3 and 69.5% success rates using the 'leave one out' method and '20-80% algorithm' respectively. © 2013 The Authors.
Scientific Publication
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