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20 April 2020 Using Digital Image Analysis to Quantify Small Arthropod Vectors
Christine Parker, Morgan Meador, Jeffrey P. Hoover
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Abstract

Quantifying arthropod vectors can be a time-consuming process. Here, we describe a technique to count large samples of small arthropods using ImageJ. ImageJ is an open source image processing software, produced by the National Institutes of Health, with a straightforward interface that has proven useful in quantifying small organisms (i.e., cells, pollen, eggs). In 2017, we deployed CDC light traps baited with carbon dioxide among seven sites to capture black flies (Diptera: Simuliidae). Samples of the captured specimens were photographed, and then quantified manually and automatically, using ImageJ. We compared the accuracy of three types of automated counts to manual counts of black flies using an information-theoretic approach. We found that changing the particle size produced counts closest to those obtained by manual counts. Even over a large range of values, from tens to thousands of flies, our automated counts were often identical to and almost always within 5% of the manual counts. When different, automated counts were usually slightly less than manual counts, and thus conservative estimates. This automated technique is simple, repeatable, requires minimal training, and can reduce the time needed to quantify small arthropods such as black flies.

© The Author(s) 2020. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Christine Parker, Morgan Meador, and Jeffrey P. Hoover "Using Digital Image Analysis to Quantify Small Arthropod Vectors," Journal of Medical Entomology 57(5), 1671-1674, (20 April 2020). https://doi.org/10.1093/jme/tjaa072
Received: 24 December 2019; Accepted: 18 March 2020; Published: 20 April 2020
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KEYWORDS
arthropod counts
automatic counts
black flies
ImageJ
Simuliidae
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