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Trap placement and attractant choice affect capture and create sex and parity biases in collections of the biting midge, Culicoides sonorensis.

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Estimating Culicoides sonorensis biting midge abundance using digital image analysis.

C J Osborne1, C E Mayo, B A Mullens

  • 1Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California Davis, Davis, CA, U.S.A.

Medical and Veterinary Entomology
|May 10, 2014
PubMed
Summary

ImageJ software offers a reliable, automated method for counting Culicoides sonorensis midges. This tool also enables accurate and efficient parity analysis, significantly aiding arbovirus vector surveillance efforts.

Keywords:
Culicoides sonorensisImageJdigital image analysis

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Area of Science:

  • Veterinary Entomology
  • Medical Entomology
  • Image Analysis Software

Background:

  • Culicoides sonorensis is a significant vector of ruminant arboviruses in California.
  • Current surveillance methods for Culicoides spp. are labor-intensive and time-consuming.
  • ImageJ software has proven utility in other insect abundance estimations.

Purpose of the Study:

  • To evaluate ImageJ's effectiveness for gross trap enumeration of Culicoides sonorensis.
  • To assess ImageJ's capability for parity analysis in Culicoides sonorensis.
  • To compare ImageJ-based methods with traditional visual sorting techniques.

Main Methods:

  • Utilized ImageJ software for automated counting of Culicoides sonorensis specimens.
  • Employed ImageJ for parity determination in Culicoides sonorensis.
  • Compared ImageJ results against manual enumeration and parity assessment using a dissecting microscope.

Main Results:

  • Automated counting with ImageJ provides a reliable approximation of midge numbers under specific conditions.
  • ImageJ facilitates accurate and time-efficient parity analysis compared to manual sorting.
  • The software demonstrates potential for expediting Culicoides sonorensis surveillance.

Conclusions:

  • ImageJ is a promising tool for enhancing the efficiency and accuracy of Culicoides sonorensis surveillance.
  • The developed ImageJ methods may be applicable to other insect surveillance programs.
  • Automated image analysis can significantly reduce the time and effort required for vector entomology studies.