Abstract

Egg-laying preferences of mosquitoes can reveal key neurosensory mechanisms informing the decision-making process for this critical behavior. A single blood meal results in a gravid female Aedes aegypti mosquito laying more than 100 eggs. Therefore, egg counting represents a potentially time-consuming and laborious component to behavioral assays, such as those that measure oviposition preference or fecundity. Automated algorithms that count eggs from images can dramatically reduce the time required for this step of data processing and analysis and increase reproducibility associated with having multiple human observers count the eggs. Here, we present two distinct approaches for counting melanized Ae. aegypti eggs laid on white filter paper.

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