Gengwang Hu, Zhengyang Zhu, Zijian Chen, Fan Cao, Xinggong Liang, Run Chen, Yudong Qin, Qi Liao, Wei Sun, Yu Wang, Qinru Sun, Zhenyuan Wang
Insect exuviae are physical records of insect molting events, which can provide valuable clues regarding insect developmental timing and physiological status. They are frequently encountered and sometimes the sole insect evidence at a crime scene. However, fragmentation poses a significant limitation to their practical application, potentially shifting the advantage towards physicochemical characterization methods over traditional morphological analysis. This study presents a systematic characterization of exuviae from seven major necrophagous insect taxa using Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDS), Thermogravimetric Analysis (TGA), Gas Chromatography-Mass Spectrometry (GC-MS), Raman Spectroscopy, and Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy coupled with chemometrics. These multispectroscopic methods provided comprehensive information on morphology, elemental distribution, thermal stability, molecular structures, and cuticular hydrocarbon profiles. Comparative analysis enabled successful interspecies discrimination of exuviae and intraspecies differentiation based on larval food sources across multiple methods. ATR-FTIR spectroscopy combined with Support Vector Machine (SVM) demonstrated superior performance for species identification compared to Random Forest (RF) and Partial Least Squares Discriminant Analysis (PLS-DA), achieving 100% training set accuracy and 99.38% test set accuracy. The observed similarity in physicochemical properties among exuviae from closely related species indicates a primary dependence on taxonomy and further validates the reliability of our dataset. This work introduces several promising new methods for discriminating necrophagous insect exuviae, providing fundamental data and standard references for their forensic application, particularly in minimum post-mortem interval (mPMI) estimation. Future efforts should focus on expanding the database to encompass species-level identification.