Automated assay and differential model of western honey bee (Apis mellifera) autogrooming using digital image processing

• A novel, automated honey bee grooming assay was developed and tested.
• Five honey bees were coated in baking flour, then their grooming was recorded.
• Pixel data were thresholded (flour = 0, bee = 1) and measured over 10 min.
• Honey bee grooming rate was calculated using nonlinear least-squares fit.

In animals, self-grooming is an important component of their overall hygiene because it reduces the risk of disease and parasites. The European honey bee (Apis mellifera) exhibits hygienic behavior, which refers to the ability of the members of a colony to remove diseased or dead brood from the hive. Individual grooming behavior, however, is when a bee grooms itself to remove parasites. While both behaviors are critical for the mitigation of disease, hygienic behavior is overwhelmingly more studied because, unlike grooming behavior, it has a simple bioassay to measure its phenotype. Here, we develop a novel bioassay to expedite data collection of grooming behavior by testing different honey bee genotypes (stocks). Individual worker bees from different commercial stocks were coated in baking flour, placed in an observation arena, and digitally recorded to automatically measure grooming rates. The videos were analyzed in MATLAB, and an exponential function was fit to the pixel data to calculate individual grooming rates. While bees from the different commercial stocks were not significantly different in their grooming rates, the automation of grooming measurements may facilitate future research and stock selection for this important mechanism of social immunity.

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