论文部分内容阅读
Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.
Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed. The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared (FTIR) spectroscopy. in this study, FTIR-attenuated total reflectance (ATR) spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants. Mixtures of mycelia and spores from 27fungal different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements. The FTIR-ATR spectra ranging from 4 000 to 400 cm -1 were obtained. To classify the FTIRATR spectra, cluster analysis was compared with canonical vitiate analysis (CVA) in the spectral regions of 3 050-2 800 and 1 800-900 cm-1. Results showed that the i dentification accuracies achieved 97.53% and 99.18% for the cluster analysis and CVA analysis, respectively, demonstrating the high potential of this technique for fungal strain identification.