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A Precise and Autonomous System for the Detection of Insect Emergence Patterns.
Bennett, Meghan M; Rinehart, Joseph P; Yocum, George D; Yocum, Ian.
Afiliación
  • Bennett MM; Department of Biological Sciences, North Dakota State University; School of Life Sciences, Arizona State University; mbenne15@asu.edu.
  • Rinehart JP; Red River Valley Agricultural Research Center, USDA-ARS.
  • Yocum GD; Red River Valley Agricultural Research Center, USDA-ARS.
  • Yocum I; Red River Valley Agricultural Research Center, USDA-ARS.
J Vis Exp ; (143)2019 01 09.
Article en En | MEDLINE | ID: mdl-30688298
ABSTRACT
Existing systems to measure insect emergence patterns have limitations; they are only partially automated and are limited in the maximum number of emerging insects they can detect. 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 treatments to be run 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. The goal of this protocol is to investigate important questions in chronobiology and stress physiology, using this precise and automated system to measure insect emergence patterns.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Insectos Tipo de estudio: Diagnostic_studies / Guideline Límite: Animals Idioma: En Revista: J Vis Exp Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Insectos Tipo de estudio: Diagnostic_studies / Guideline Límite: Animals Idioma: En Revista: J Vis Exp Año: 2019 Tipo del documento: Article