Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex.

Journal: Parasites & vectors
Published Date: Jun 10, 2025

Abstract

BACKGROUND: Mosquito-borne diseases, such as malaria, dengue, and Zika, continue to pose significant threats to global health, resulting in millions of cases and thousands of deaths each year. Notably, only older mosquitoes can transmit these diseases. Therefore, accurate age estimation of mosquitoes is vital for targeted interventions and risk assessments. However, traditional methods, such as tracheole morphology analysis, are labor-intensive and have limited scalability. Surface-enhanced Raman spectroscopy (SERS), when coupled with artificial neural networks (ANNs), offers a robust and flexible alternative, facilitating accurate and efficient mosquito age determination even in diverse and complex environmental conditions.

Authors

  • Zili Gao
    Department of Food Science, University of Massachusetts, Amherst, MA, 01003, USA.
  • Yuzhen Zhang
  • Laura C Harrington
    Department of Entomology, Cornell University, Ithaca, NY, 14853, USA.
  • Courtney C Murdock
    Department of Entomology, Cornell University, Ithaca, NY, 14853, USA.
  • Elisabeth Martin
    Department of Entomology, Cornell University, Ithaca, NY, 14853, USA.
  • Dalton Manbeck-Mosig
    School of Veterinary Medicine, University of California Davis, Davis, CA, 95616, USA.
  • Steve Vetrone
    Greater Los Angeles County Vector Control District, Santa Fe Springs, CA, 90670, USA.
  • Nicolas Tremblay
    Greater Los Angeles County Vector Control District, Santa Fe Springs, CA, 90670, USA.
  • Christopher M Barker
    School of Veterinary Medicine, University of California Davis, Davis, CA, 95616, USA.
  • John M Clark
    ORISE Fellow, U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory.
  • Lili He
    Department of Food Science, University of Massachusetts Amherst, United States of America. Electronic address: lilihe@foodsci.umass.edu.
  • Wei Zhu
    The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine Guangzhou 510120 China zhuwei9201@163.com.

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