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Schott, Matthias ; Klein, Birgit ; Vilcinskas, Andreas:
Detection of Illicit Drugs by Trained Honeybees (Apis mellifera).
In: PLoS One.
Bd. 10
(2015)
Heft 6
.
- No. e0128528.
ISSN 1932-6203
DOI: https://doi.org/10.1371/journal.pone.0128528
Abstract
Illegal drugs exacerbate global social challenges such as substance addiction, mental health issues and violent crime. Police and customs officials often rely on specially-trained sniffer dogs, which act as sensitive biological detectors to find concealed illegal drugs. However, the dog “alert” is no longer sufficient evidence to allow a search without a warrant or additional probable cause because cannabis has been legalized in two US states and is decriminalized in many others. Retraining dogs to recognize a narrower spectrum of drugs is difficult and training new dogs is time consuming, yet there are no analytical devices with the portability and sensitivity necessary to detect substance-specific chemical signatures. This means there is currently no substitute for sniffer dogs. Here we describe an insect screening procedure showing that the western honeybee (Apis mellifera) can sense volatiles associated with pure samples of heroin and cocaine. We developed a portable electroantennographic device for the on-site measurement of volatile perception by these insects, and found a positive correlation between honeybee antennal responses and the concentration of specific drugs in test samples. Furthermore, we tested the ability of honeybees to learn the scent of heroin and trained them to show a reliable behavioral response in the presence of a highly-diluted scent of pure heroin. Trained honeybees could therefore be used to complement or replace the role of sniffer dogs as part of an automated drug detection system. Insects are highly sensitive to volatile compounds and provide an untapped resource for the development of biosensors. Automated conditioning as presented in this study could be developed as a platform for the practical detection of illicit drugs using insect-based sensors.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Biologie > Lehrstuhl Tierökologie I > Lehrstuhl Tierökologie I - Univ.-Prof. Dr. Christian Laforsch Fakultäten Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Biologie Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Biologie > Lehrstuhl Tierökologie I |
| Titel an der UBT entstanden: | Nein |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie 500 Naturwissenschaften und Mathematik > 590 Tiere (Zoologie) |
| Eingestellt am: | 16 Apr 2020 07:40 |
| Letzte Änderung: | 01 Sep 2022 09:46 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/54932 |