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ARS Home » Pacific West Area » Tucson, Arizona » Honey Bee Research » Research » Publications at this Location » Publication #353924

Research Project: Determining the Impacts of Pesticide- and Nutrition-Induced Stress on Honey Bee Colony Growth and Survival

Location: Honey Bee Research

Title: The development of honey bee colonies assessed using a new semi-automated brood counting method: CombCount

Author
item Colin, Theotime - Macquarie University
item Bruce, Jake - Queensland University - Australia
item Meikle, William
item Barron, Andrew - Macquarie University

Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/2/2018
Publication Date: 10/16/2018
Citation: Colin, T., Bruce, J., Meikle, W.G., Barron, A. 2018. The development of honey bee colonies assessed using a new semi-automated brood counting method: CombCount. PLoS One. https://doi.org/10.1371/journal.pone.0205816.
DOI: https://doi.org/10.1371/journal.pone.0205816

Interpretive Summary: Estimating how much brood (baby bees) is in a bee colony is usually done one of two ways: either the researcher visually estimates the brood, or the researcher takes a picture of each frame of comb and then analyses the photographs. The problem with the first method is that it is subjective, not very precise or accurate, and there is no permanent record. The problem with the second method is that after taking the photo, the researcher then must measure the size of the brood patch. That is typically done using software to outline the patch or even count the individual comb cells with larval bees. A faster and more reliable way might be to let a computer do the measuring. This paper presents computer code that can be used to measure brood, and tests the code by having several workers analyse the photos using both the older method and the new code. The computer code saved lots of time and was at least as accurate and precise as any the other image analysis method.

Technical Abstract: Precise, objective data on brood and honey levels in honey bee colonies can be obtained through the analysis of hive frame photographs. However, accurate analysis of all the frame photographs from medium- to large-scale experiments is time-consuming. This limits the number of hives than can be practically included in honeybee studies. Faster estimation methods exist but they significantly decrease the precision and can only be used at the cost of a larger sample size. To resolve this issue, we created ‘CombCount’ a python program that automatically detects uncapped cells to speed up measurements of capped brood and capped honey on photos of frames. CombCount does not require programming skills, it was designed to facilitate colony-level research in honeybees and to provide a fast, free, and accurate alternative to older methods based on visual estimations. Six observers measured the same photos of thirty different frames both with CombCount and by manually detouring the entire capped areas with ImageJ. The results obtained were highly similar between both the observers and the two methods, but measurements with CombCount were 3.2 times faster than with ImageJ (4 and 13 min per side of the frame, respectively). Combcount was used to measure the proportions of brood and honey on each frame of 16 hives over a year as they developed from packages to full-size colonies over about 30 days. Our data describe the formation of brood and honey stores during the establishment of a new colony.