Estimating the postmortem interval (PMI) is critical in the field of forensic science, and necrophagous insects play a significant role in this process. Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae) is a common necrophagous insect species, making its rapid and accurate identification essential. However, commonly used molecular biology methods, such as DNA barcode, still have some limitations in identifying necrophagous insects as they are often complex, time-consuming, and reliant on laboratory instruments. Therefore, in this study, we have developed an innovative detection system for the rapid and accurate identification of C. megacephala based on the Cytochrome b gene using recombinase polymerase amplification (RPA) and lateral flow dipstick (LFD) in combination. The developed RPA-LFD detection system achieved complete amplification in just 15 min at 37 °C with good sensitivity and specificity. Only 7.8 × 10⁻⁴ ng or more of target DNA fragments were required, and a positive detection rate of 100% was achieved in 18 C. megacephala samples from actual cases. In addition, the ability of the developed RPA-LFD detection system in combination with rapid DNA extraction methods to enable on-site detection was preliminarily explored. The results suggested that when the RPA-LFD detection system was combined with the grinding ddH₂O extraction method (a rapid DNA extraction method), the process from species acquisition to visualization of detection results could be completed in less than 20 min. In conclusion, this innovative RPA-LFD detection system outperforms commonly used molecular biology methods for C. megacephala identification in terms of speed, sensitivity and convenience, making it suitable for direct application at crime scenes, promising to provide important assistance in estimating PMI and expanding the impact of forensic entomological evidence.

Estimating the post-feeding developmental time of necrophagous larvae remains challenging because body size and behavior provide limited resolution after larvae cease feeding. This study integrated behavioral observation, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), chemometric regression modeling, transcriptomic analysis, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation to characterize post-feeding development in Sarcophaga peregrina (Robineau-Desvoidy) under 25 °C. The post-feeding stage began at 84.83 ± 1.34 h after larviposition and lasted 38.21 ± 2.29 h. ATR-FTIR spectra from 0, 10, 20, 30, and 40 h post-feeding larvae showed temporal changes in the 1800–900 cm⁻¹ fingerprint region, mainly involving bands associated with proteins, lipids, polysaccharides, and chitin. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and variable importance in projection (VIP) analyses identified discriminative spectral regions, while regression models further evaluated time-estimation performance. Among the models, partial least squares regression (PLS-R) showed the most balanced predictive ability, with the coefficient of determination in prediction (R²P) = 0.920 and the root mean square error of prediction (RMSEP) = 4.00 h in the prediction set. Transcriptomic analysis identified 4641 differentially expressed genes, and RT-qPCR confirmed temporal expression patterns of selected candidate genes. These molecular changes were mainly associated with cuticle/chitin remodeling, protein metabolism, and energy metabolism. Overall, ATR-FTIR combined with chemometric modeling provides a complementary biochemical approach for estimating post-feeding developmental time in S. peregrina under controlled 25 °C conditions, although validation at other temperatures is required before broader application.

Accurate postmortem interval estimation is an important issue in forensic investigations. Entomological evidence is widely used to estimate the minimum postmortem interval (PMI_min), primarily based on insect development and succession on decomposing remains. However, once adult emergence has occurred and only empty puparia remain, the applicability of conventional development-based methods becomes limited. Empty puparia, which can persist at crime scenes for extended periods, may provide time-related information based on their weathering after adult emergence. Nevertheless, for Aldrichina grahami (Aldrich, 1930) (Diptera: Calliphoridae), a forensically important necrophagous species, systematic models for empty puparia weathering remain limited. In this study, a 13-month indoor exposure experiment was conducted to characterize weathering-associated changes in empty puparia of A. grahami using metabolomic and bacterial community analyses. The results showed that lipid metabolites, particularly long-chain fatty acids such as stearic and palmitic acids, decreased consistently with weathering time. In contrast, bacterial communities showed variation over time but exhibited weaker associations with weathering time. In internal cross-validation, the metabolomics model showed lower prediction error than the bacterial community model, while decision-level integration yielded the lowest error within this dataset. These results suggest that empty puparia undergo measurable molecular changes during indoor weathering, which may assist in estimating the post-eclosion interval (PEI) and thereby provide supplementary information for PMI_min assessment in long-interval cases.