Tools
Tools
Pazmiño-Betancourth, Mauro, Casas Gómez-Uribarri, Ivan, Mondragon-Shem, Karina, Babayan, Simon A, Baldini, Francesco and Haines, Lee 
ORCID: https://orcid.org/0000-0001-8821-6479
(2024)
'Advancing age grading techniques for Glossina morsitans morsitans, vectors of african trypanosomiasis, through mid-infrared spectroscopy and machine learning'. Biology Methods & Protocols, Vol 9, Issue 1.
|
Text
bpae058 (1).pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
Tsetse are the insects responsible for transmitting African trypanosomes, which cause sleeping sickness in humans and animal trypanosomiasis in wildlife and livestock. Knowing the age of these flies is important when assessing the effectiveness of vector control programs and modelling disease risk. Current methods to assess fly age are, however, labour-intensive, slow, and often inaccurate as skilled personnel are in short supply. Mid-infrared spectroscopy (MIRS), a fast and cost-effective tool to accurately estimate several biological traits of insects, offers a promising alternative. This is achieved by characterising the biochemical composition of the insect cuticle using infrared light coupled with machine learning algorithms to estimate the traits of interest.
We tested the performance of MIRS in estimating tsetse sex and age for the first-time using spectra obtained from their cuticle. We used 541 insectary-reared Glossina m. morsitans of two different age groups for males (5 and 7 weeks) and three age groups for females (3 days, 5 weeks, and 7 weeks). Spectra were collected from the head, thorax, and abdomen of each sample. Machine learning models differentiated between male and female flies with a 96% accuracy and predicted the age group with 94% and 87% accuracy for males and females, respectively. The key infrared regions important for discriminating sex and age classification were characteristic of lipid and protein content. Our results support the use of MIRS as a rapid and accurate way to identify tsetse sex and age with minimal pre-processing. Further validation using wild-caught tsetse could pave the way for this technique to be implemented as a routine surveillance tool in vector control programmes.
| Item Type: | Article |
|---|---|
| Subjects: | QW Microbiology and Immunology > Viruses > QW 162 Insect viruses WC Communicable Diseases > Tropical and Parasitic Diseases > WC 695 Parasitic diseases (General) WC Communicable Diseases > Tropical and Parasitic Diseases > WC 705 Trypanosomiasis WD Disorders of Systemic, Metabolic or Environmental Origin, etc > Animal Poisons > WD 430 Insects |
| Faculty: Department: | Biological Sciences > Vector Biology Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1093/biomethods/bpae058 |
| SWORD Depositor: | JISC Pubrouter |
| Depositing User: | JISC Pubrouter |
| Date Deposited: | 12 Sep 2024 10:10 |
| Last Modified: | 10 Oct 2024 11:43 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/25219 |
Statistics
Actions (login required)
 |
Edit Item |