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Updated: May 22, 2025
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Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
Published on: November 17, 2016
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Comparative resilience and precision of digitized optical counting using ImageJ during routine mosquito (Diptera:
Ayla Faraji1, Kelsey A Fairbanks1, Ary Faraji1
1Salt Lake City Mosquito Abatement District, Salt Lake City, UT, USA.
Journal of Insect Science (Online)
|March 14, 2025
Summary
Digitized-optical counting offers a more accurate and efficient method for estimating mosquito populations compared to traditional volume or mass measurements. This approach is resilient to various sample conditions and ideal for public health surveillance programs with limited resources.
Area of Science:
- Vector-borne disease control
- Entomology
- Public health surveillance
Background:
- Integrated vector management relies heavily on effective mosquito surveillance.
- Current surveillance methods, like manual trap processing, are labor-intensive and pose capacity challenges for public health agencies.
- Estimation methods are crucial for operational decision-making in mosquito control programs.
Purpose of the Study:
- To rigorously evaluate the accuracy and resilience of different mosquito enumeration methods under operational conditions.
- To compare traditional volume and mass estimation techniques against digital image processing for high-throughput mosquito surveillance.
- To identify the most efficient and accurate method for mosquito population estimation in resource-limited settings.
Main Methods:
- Stress-testing volume, mass, and digital image processing (ImageJ) methods throughout a mosquito active season.
- Utilizing sample calibrations from early in the season and throughout.
- Testing method resilience with frozen, desiccated, aged, and excessively large trap samples, and after deviations from best practices.
Main Results:
- Volume and mass measurement methods exhibited significant errors across various conditions.
- The digitized-optical counting method demonstrated resilience to extended use without recalibration.
- Digital image processing effectively handled varying species compositions and aged or damaged samples, maintaining accuracy.
- Mass and volume methods encountered significant errors, while digital optical counting proved resilient.
Conclusions:
- Digital image processing offers a superior balance of accuracy and expediency for time-sensitive mosquito surveillance workloads.
- This method is particularly beneficial for public health programs facing logistical constraints and high-throughput demands.
- Digitized-optical counting enhances operational decision-making in mosquito control efforts.
