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Assignment of Colletotrichum coccodes isolates into vegetative compatibility groups using infrared spectroscopy: a

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  • 1Department of Physics, SCE - Shamoon College of Engineering, Beer-Sheva 84100, Israel. ahmad@ sce.ac.il.

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Summary

Classifying Colletotrichum coccodes (C. coccodes) isolates into Vegetative Compatibility Groups (VCGs) is crucial for disease control. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) offer a rapid and effective method for this classification.

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Area of Science:

  • Plant Pathology
  • Mycology
  • Agricultural Science

Background:

  • Colletotrichum coccodes (C. coccodes) causes significant crop diseases like anthracnose in tomatoes and black dot in potatoes.
  • This pathogen is soil-borne and seed tuber-borne, posing challenges for effective disease management.
  • Classifying C. coccodes isolates into Vegetative Compatibility Groups (VCGs) is vital for understanding disease epidemiology and implementing control strategies.

Purpose of the Study:

  • To develop a rapid and efficient method for classifying Colletotrichum coccodes isolates into VCGs.
  • To differentiate between C. coccodes isolates for improved disease control at early stages.
  • To assess the utility of multivariate statistical analyses for isolate classification.

Main Methods:

  • Utilized Principal Component Analysis (PCA) for dimensionality reduction of isolate data.
  • Employed Linear Discriminant Analysis (LDA) for classification of isolates into VCGs.
  • Compared the efficacy of PCA and LDA with traditional microbiological or genetic methods.

Main Results:

  • Achieved a high success rate in assigning C. coccodes isolates to their respective VCGs using PCA and LDA.
  • Demonstrated that PCA and LDA can effectively classify isolates at the individual isolate level.
  • Showcased the potential of these statistical methods as a faster alternative to conventional techniques.

Conclusions:

  • Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) provide a successful and efficient approach for classifying Colletotrichum coccodes isolates into VCGs.
  • These methods offer a valuable tool for researchers and plant pathologists to quickly identify and manage C. coccodes populations.
  • The study highlights the importance of advanced statistical techniques in accelerating plant disease diagnostics and control efforts.