Scoring thermal limits in small insects using open-source, computer-Assisted motion detection

Fernan R. Perez-Galvez, Sophia Zhou, Annabelle C. Wilson, Catherine L. Cornwell, David N. Awde, Nicholas M. Teets

Research output: Contribution to journalArticlepeer-review


Scoring thermal tolerance traits live or with recorded video can be time consuming and susceptible to observer bias, and as with many physiological measurements, there can be trade-offs between accuracy and throughput. Recent studies show that automated particle tracking is a viable alternative to manually scoring videos, although some of the software options are proprietary and costly. In this study, we present a novel strategy for automated scoring of thermal tolerance videos by inferring motor activity with motion detection using an open-source Python command line application called DIME (detector of insect motion endpoint). We apply our strategy to both dynamic and static thermal tolerance assays, and our results indicate that DIME can accurately measure thermal acclimation responses, generally agrees with visual estimates of thermal limits, and can significantly increase throughput over manual methods. KEY WORDS: Automatic scoring, Thermal limits, Bioassay, Automated particle tracking, Motor performance.

Original languageEnglish
Article numberjeb246548
JournalJournal of Experimental Biology
Issue number22
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 Company of Biologists Ltd. All rights reserved.

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Physiology
  • Aquatic Science
  • Animal Science and Zoology
  • Molecular Biology
  • Insect Science


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