חיפוש מתקדם
Analyst
Salman, A., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Pomerantz, A., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, M.P. Negev, 85250, Israel
Lapidot, I., University of Avignon, CERI, LIA, Avignon, France
Moreh, R., Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
Mordechai, S., Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
Huleihel, M., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Colletotrichum coccodes (C. coccodes) is a pathogenic fungus which causes anthracnose on tomatoes and black dot disease in potatoes. It is important to differentiate among these isolates and to detect the origin of newly discovered isolates, in order to treat the disease in its early stages. However, distinguishing between isolates using common biological methods is time-consuming, and not always available. We used Fourier Transform Infra-Red (FTIR)-Attenuated Total Reflectance (ATR) spectroscopy and advanced mathematical and statistical methods to distinguish between different isolates of C. coccodes. To our knowledge, this is the first time that FTIR-ATR spectroscopy was used, combined with multivariate analysis, to classify such a large number of 15 isolates belonging to the same species. We obtained a success rate of approximately 90% which was achieved using the region 800-1775 cm-1. In addition we succeeded in determining the relative spectral similarity between different fungal isolates by developing a new algorithm. This method could be an important potential diagnostic tool in agricultural research, since it may outline the extent of the biological similarity between fungal isolates. Based on the PCA calculations, we grouped the fifteen isolates included in this study into four different degrees of similarity. © The Royal Society of Chemistry 2012.
פותח על ידי קלירמאש פתרונות בע"מ -
הספר "אוצר וולקני"
אודות
תנאי שימוש
Utilizing FTIR-ATR spectroscopy for classification and relative spectral similarity evaluation of different Colletotrichum coccodes isolates
137
Salman, A., Department of Physics, SCE-Shamoon College of Engineering, Beer-Sheva 84100, Israel
Pomerantz, A., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Tsror, L., Department of Plant Pathology, Institute of Plant Protection, Agricultural Research Organization, M.P. Negev, 85250, Israel
Lapidot, I., University of Avignon, CERI, LIA, Avignon, France
Moreh, R., Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
Mordechai, S., Department of Physics, Ben-Gurion University, Beer-Sheva 84105, Israel
Huleihel, M., Department of Virology and Developmental Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Utilizing FTIR-ATR spectroscopy for classification and relative spectral similarity evaluation of different Colletotrichum coccodes isolates
Colletotrichum coccodes (C. coccodes) is a pathogenic fungus which causes anthracnose on tomatoes and black dot disease in potatoes. It is important to differentiate among these isolates and to detect the origin of newly discovered isolates, in order to treat the disease in its early stages. However, distinguishing between isolates using common biological methods is time-consuming, and not always available. We used Fourier Transform Infra-Red (FTIR)-Attenuated Total Reflectance (ATR) spectroscopy and advanced mathematical and statistical methods to distinguish between different isolates of C. coccodes. To our knowledge, this is the first time that FTIR-ATR spectroscopy was used, combined with multivariate analysis, to classify such a large number of 15 isolates belonging to the same species. We obtained a success rate of approximately 90% which was achieved using the region 800-1775 cm-1. In addition we succeeded in determining the relative spectral similarity between different fungal isolates by developing a new algorithm. This method could be an important potential diagnostic tool in agricultural research, since it may outline the extent of the biological similarity between fungal isolates. Based on the PCA calculations, we grouped the fifteen isolates included in this study into four different degrees of similarity. © The Royal Society of Chemistry 2012.
Scientific Publication
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