Mosquito surveillance for vector-borne disease management relies on traditional morphological and molecular techniques, which are tedious, time-consuming, and costly. The present study describes a simple and efficient recording device that analyzes mosquito sound to estimate species composition, male-female ratio, fed-unfed status, and harmonic convergence interaction using fundamental frequency (F0) bandwidth, harmonics, amplitude, and combinations of these parameters. The study examined a total of 19 mosquito species, including 3 species of Aedes, 7 species of Anopheles, 1 species of Armigeres, 5 species of Culex, 1 species of Hulecoetomyia, and 2 species of Mansonia. Among them, the F0 ranges between 269.09 ± 2.96 Hz (Anopheles culiciformis) to 567.51 ± 3.82 Hz (Aedes vittatus) and the harmonic band (hb) number ranges from 5 (An. culiciformis) to 12 (Ae. albopictus). In terms of species identification, the success rate was 95.32 % with F0, 84.79 % with F0-bandwidth, 84.79 % with harmonic band (hb) diversity, and 49.7 % with amplitude (dB). The species identification rate has gone up to 96.50 % and 97.66 % with the ratio and multiplication of F0 and hb, respectively. This is because of the matrices that combine multiple sound attributes. Comparatively, combinations of the amplitude of the F0 and the higher harmonic frequency band were non-significant for species identification (60.82 %). The fed females have shown a considerable increase in F0 in comparison to the unfed. The males of all the species possessed significantly higher frequencies with respect to the females. Interestingly, the presence of male-female of Ae. vittatus together showed harmonic convergence between the 2nd and 3rd harmonic bands. In conclusion, the sound-based technology is simple, precise, and cost-effective and provides better resolution for species, sex, and fed-unfed status detection in comparison to conventional methods. Real-time surveillance of mosquitoes could potentially utilize this technology.
Keywords: E-surveillance; Harmonic convergence; Mosquito sound; Real-time species identification; Vectors.
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