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Published on: July 24, 2015
Monitoring infestation levels using an AI-based Chironomid quantification tool (CQT) in a laboratory Xenopus laevis
Maximilian Schwarzbach1, Bastian Popper2
1Core Facility Animal Models, Biomedical Center, Medical Faculty, Ludwig-Maximilians-University Munich, Munich, Germany.
BMC Research Notes
|June 19, 2026
Summary
An AI tool accurately quantifies non-biting midge (Chironomidae) infestations in aquatic lab systems. Bacillus thuringiensis israelensis (Bti) effectively eradicated midges without harming Xenopus laevis.
Area of Science:
- Veterinary Entomology
- Laboratory Animal Science
- Aquatic Ecology
Background:
- Insect infestations, particularly non-biting midges (Chironomidae), pose significant risks in laboratory animal facilities.
- These risks include compromised animal welfare, staff hygiene concerns, and potential threats to experimental integrity.
- Effective monitoring and control of such infestations are crucial for maintaining high standards in research settings.
Purpose of the Study:
- To develop and validate an AI-assisted image analysis workflow, the Chironomid Quantification Tool (CQT-AI), for detecting and quantifying Chironomidae infestations.
- To assess the efficacy of CQT-AI in monitoring infestation dynamics and evaluating different control strategies.
- To compare the effectiveness of increased water exchange versus biological control with Bacillus thuringiensis israelensis (Bti) in managing midge populations.
Main Methods:
- Development and application of the custom AI-assisted image analysis workflow, CQT-AI.
- Implementation of CQT-AI for real-time detection and quantification of adult Chironomidae in aquatic housing systems for Xenopus laevis.
- Experimental testing of control strategies: increased water exchange and biological control using Bti.
Main Results:
- CQT-AI demonstrated reliability in detecting and quantifying Chironomidae infestation dynamics, allowing objective assessment of treatment effects within one minute.
- Increased water exchange showed moderate success in reducing infestation levels, despite causing measurable changes in water chemistry.
- Bacillus thuringiensis israelensis (Bti) treatment resulted in rapid and near-complete eradication of adult midges within six weeks, with no observed adverse effects on animal health.
Conclusions:
- The Chironomid Quantification Tool (CQT-AI) offers an efficient and objective method for monitoring insect infestation dynamics in aquatic laboratory systems.
- Bacillus thuringiensis israelensis (Bti) is a highly effective biological control agent for Chironomidae in Xenopus laevis housing systems.
- AI-assisted image analysis provides a valuable tool for evaluating pest control strategies in research environments, ensuring animal welfare and experimental validity.
