Rapid and non-destructive identification of Anopheles gambiae and Anopheles arabiensis mosquito species using Raman spectroscopy via machine learning classification models

Rapid and non-destructive identification of Anopheles gambiae and Anopheles arabiensis mosquito species using Raman spectroscopy via machine learning classification models

Abstract Background Identification of malaria vectors is an important exercise that can result in the deployment of targeted control measures and monitoring the susceptibility of the vectors to control strategies. Although known to possess distinct biting behaviours and habitats, the African malaria...

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Bibliographic Details
Main Authors: Dickson L. Omucheni, Kenneth A. Kaduki, Wolfgang R. Mukabana
Format: Article
Language:English
Published: BMC 2023-11-01
Series:Malaria Journal
Subjects:
Raman spectroscopy
Machine learning
Discriminant Analysis
Support Vector Machine
Logistic Regression
Melanin
Online Access:https://doi.org/10.1186/s12936-023-04777-y

Internet

https://doi.org/10.1186/s12936-023-04777-y

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