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Eggsplorer: a rapid plant-insect resistance determination tool using an automated whitefly egg quantification

Micha Gracianna Devi1, Dan Jeric Arcega Rustia2, Lize Braat3

  • 1Plant Breeding, Wageningen University & Research, Po Box 384, 6700 AJ, Wageningen, The Netherlands. micha.devi@wur.nl.

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|May 20, 2023
PubMed
Summary

This study introduces Eggsplorer, an automated tool for rapidly quantifying whitefly eggs. This method significantly speeds up plant insect resistance assessments, saving time and resources in agricultural research.

Keywords:
BioassayDeep learningInsect egg quantificationPlant insect resistanceRapid phenotypingWhitefly

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Area of Science:

  • Agricultural Science
  • Entomology
  • Plant Pathology

Background:

  • Evaluating plant resistance to insects often involves manual quantification of insect eggs, a laborious process.
  • Whiteflies are significant agricultural pests, acting as vectors for viral diseases, necessitating efficient study methods.

Purpose of the Study:

  • To develop and validate a novel automated tool for the rapid quantification of whitefly eggs.
  • To accelerate the determination of plant resistance and susceptibility to whiteflies.

Main Methods:

  • Collected leaf images featuring whitefly eggs using commercial and custom imaging systems.
  • Trained a deep learning-based object detection model on the collected images.
  • Integrated the model into an automated quantification algorithm deployed as the Eggsplorer web application.

Main Results:

  • The automated algorithm achieved high accuracy (0.94) and an R-squared value of 0.99 in counting whitefly eggs.
  • Demonstrated a low counting error of ±3 eggs compared to manual counts.
  • Results from automated counts were comparable to manual counts for determining plant resistance.

Conclusions:

  • This work presents the first comprehensive method for automated whitefly egg quantification.
  • The Eggsplorer tool offers a fast and efficient solution for assessing plant insect resistance.
  • The automated approach saves significant time and human resources in agricultural research.