Identificator: A web-based tool for visual plant disease identification, a proof of concept with a case study on strawberry

Ilaria Pertot, Tsvi Kuflik, Igor Gordon, Stanley Freeman, Yigal Elad

Research output: Contribution to journalArticlepeer-review


Identificator is a web-based tool used to help non experts in identifying plant diseases, based on the selection of pictures and/or short text descriptions (when no suitable images exist) representing the symptoms on a specific sample of plant organs. The system is based on a multi-access key of identification and specifically on the selection of pictures by the user and can be used remotely from a desktop as well as from a smart phone or personal digital assistant. The system was developed following a simple approach: visual identification where images and/or short descriptions are used to uniquely identify diseases when possible and suggest refining the visual identification process in cases of ambiguous identification. It has been designed in a way that allows easy definition of additional diseases by uploading the correct images and defining the identification rules and diseases. In this way the system may aid growers in identifying various diseases when using the system remotely while the system is developed and maintained centrally. This approach may ease the process of manual visual disease identification until machine vision technology is mature enough to perform this task automatically. We tested the system for visual identification of strawberry diseases using a computer and samples of infected plants. The evaluation showed that it is effective and accurate in enabling its users to identify strawberry diseases.

Original languageEnglish
Pages (from-to)144-154
Number of pages11
JournalComputers and Electronics in Agriculture
StatePublished - Jun 2012

Bibliographical note

Funding Information:
The authors wish to thank Sharon Bentov for the high quality photographs from the iPhone showing the Identificator on a mobile device and Andrea Frizzi for technical support. The research was partially funded by the project ENVIROCHANGE, Autonomous Province of Trento (Italy), Call for proposal Major Projects 2006.


  • Disease identification
  • Multi-access key
  • Plant disease
  • Plant pathogen
  • Web-based system

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture


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