Skip to main content
ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Insect Genetics and Biochemistry Research » Research » Publications at this Location » Publication #351649
Title: A precise and autonomous system for the detection of insect emergence patterns

Author
item BENNETT, MEGHAN - Arizona State University
item Rinehart, Joe
item Yocum, George
item YOCUM, IAN - University Of North Dakota

Submitted to: Journal of Visualized Experiments
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/24/2018
Publication Date: 1/9/2019
Citation: Bennett, M., Rinehart, J.P., Yocum, G.D., Yocum, I.S. 2019. A precise and autonomous system for the detection of insect emergence patterns. Journal of Visualized Experiments. 143:e58362. https://doi.org/10.3791/58362.
DOI: https://doi.org/10.3791/58362

Interpretive Summary: Experiments that require round-the-clock data collection are difficult to conduct. The strain they cause to the researchers collecting the data is just one of many logistical hurdles one encounters when running this type of experiment. This is especially true for experiments on how environmental conditions such as temperature and light affect the daily behavior patterns of organisms. While investigating the emergence patterns of pollinating insects, researchers with the USDA-ARS and North Dakota State University in Fargo, North Dakota designed an automated data collection apparatus. Using 3D printed parts, Arduino microcontrollers, and off-the-shelve electronics, the system precisely measures the time of emergence of an insect with no input from the scientist once the system is launched. This article describes the construction and use of the apparatus in detail, including the 3D printer files and programming code required for successful use. In addition to use by other researchers, we expect this apparatus to be useful to teachers while fulfilling the National Science Standards requirement of identifying ways that an organism’s pattern of behavior is related to the nature of the organism’s environment.

Technical Abstract: Existing systems to measure insect emergence patterns have limitations including that fact that they are only partially automated and that they are limited in sample size. In order to obtain precise measurement of insect emergence, it is necessary for systems to be semi-automated and able to measure large numbers of emerging insects. We addressed these issues by designing and building a system that is automated and can measure emergence of up to 1200 insects. We modified the existing “falling-ball” system using Arduino microcontrollers to automate data collection and expand the sample size through multiple data channels. Multiple data channels enable the user to not only increase their sample size, but also allows for multiple pretreatments to be ran simultaneously in a single experiment. Furthermore, we created an R script to automatically visualize the data as a bubble plot, while also calculating the median day and time of emergence. The current system was designed using 3D printing so the user can modify the system to be adjusted for different species of insects. Important questions in chronobiology and stress physiology can be answered using this precise and automated system to measure insect emergence patterns.