Reliable determination of mosquito age and reproductive status is critical for understanding disease transmission dynamics and evaluating vector control strategies. In this study, we investigated the use of mid-infrared (MIR) spectroscopy combined with multivariate statistical models to predict the gonotrophic state (parity) and chronological age of Aedes triseriatus. Using a reflectance sampling geometry, we acquired IR spectra from the hind tibiae of Ae. triseriatus females to assess gonotrophic status. Spectral data in the 1800-650 cm-1 range were normalized and subjected to second-derivative transformation to minimize baseline variation. Partial least squares discriminant analysis (PLS-DA) was used to classify mosquitoes as parous or nulliparous based on their IR spectra, achieving clear separation between groups in the validation set. The model demonstrated 97% (95% CI: 92%-99%) classification accuracy, with a positive predictive value of 97% (95% CI: 88%-100%) and a negative predictive value of 97% (95% CI: 91%-99%), indicating robust statistical differentiation based on gonotrophic status. Using female Ae. triseriatus aged from 2 to 35 days old we assessed the ability of MIR to predict age. Partial least squares regression (PLS-R) yielded a strong correlation (R = 0.96) between spectral data and mosquito age. Statistical testing (ANOVA, Tukey's HSD) revealed that the model could not reliably distinguish between mosquitoes aged 2 and 7 days but could reliably distinguish Ae. triseriatus ≤ 7 days (1 week) old from those 2-5 weeks of age at the 95% confidence level. Collectively, these findings demonstrate that MIR spectroscopy, coupled with chemometric modeling (PLS analyses), provides a rapid and reproducible method for determining reproductive status and age in Ae. triseriatus. The methods reported here may improve La Crosse virus transmission risk assessments and better refine our understanding of enzootic maintenance and human spillover.
Huffman et al. (Fri,) studied this question.