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Updated: Jun 11, 2025

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iPhyDSDB: Phytoplasma Disease and Symptom Database.

Wei Wei1, Jonathan Shao2, Yan Zhao1

  • 1Molecular Plant Pathology Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA.

Biology
|September 28, 2024
PubMed
Summary

A new Phytoplasma Disease Symptom Database (iPhyDSDB) aids farmers and researchers in identifying plant diseases caused by phytoplasmas. This resource enhances early detection and management of these significant agricultural threats.

Keywords:
NCBI nucleotide databaseadvanced search functionalitydisease diagnosisimage-based AI detectionsymptom recognition

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Area of Science:

  • Plant Pathology
  • Bacteriology
  • Bioinformatics

Background:

  • Phytoplasmas are intracellular bacteria causing significant economic losses in agriculture.
  • Early and rapid diagnosis of phytoplasma infections is critical for disease management.
  • Symptom recognition by farmers is key for early detection.

Purpose of the Study:

  • To develop a comprehensive Phytoplasma Disease Symptom Database (iPhyDSDB).
  • To create a web-based interface for easy access to phytoplasma infection information.
  • To aid farmers, growers, and researchers in diagnosing phytoplasma-related plant diseases.

Main Methods:

  • Retrieved ~35,000 phytoplasma sequence entries from NCBI.
  • Gathered information on 945 plant species associated with phytoplasma infections.
  • Manually curated links to symptomatic images and developed a web interface using MySQL and PHP.

Main Results:

  • Established the Phytoplasma Disease Symptom Database (iPhyDSDB).
  • Included curated links to symptomatic images and descriptive symptom definitions.
  • Implemented advanced search functionality based on plant host and symptom type.

Conclusions:

  • iPhyDSDB provides a valuable resource for identifying and diagnosing phytoplasma infections.
  • The database enhances understanding and management of phytoplasma diseases.
  • Facilitates efficient information retrieval for various agricultural stakeholders.