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Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. This estimation relies on the development of the flies found at the (death) scene and can be affected (and sometimes corrected) by external factors, such as temperature and humidity, and internal factors, such as species and sex. This study leverages infrared (IR) spectroscopy combined with machine learning models—Partial Least Squares Discriminant Analysis (PLS‐DA) and eXtreme Gradient Boosting trees Discriminant Analysis (XGBDA)—to differentiate between male and female Cochliomyia macellaria larvae, commonly found on human remains. Significant vibrational differences were detected in the infrared spectra of third instar C. macellaria larvae, with distinct peaks showing variations in relative absorbance between sexes, suggesting differences in biochemical compositions such as cuticular proteins and lipids. The application of PLS‐DA and XGBDA yielded high classification accuracies of about 94% and 96%, respectively, with female spectra consistently having higher sensitivity than males. This non‐destructive approach offers the potential to refine supplemental post‐mortem interval estimations significantly, enhancing the accuracy of forensic analyses. [ABSTRACT FROM AUTHOR]

Difficulties in the localization of bodies of homicidal or drowning victims in natural water result in their submergence for weeks if not months. Water insects and microbes drastically change the body's appearance, which significantly changes the determination of a victim's identity. DNA analysis is commonly used for identifying the decedent; however, this PCR‐based approach is time‐consuming and destructive of the evidence. Considering that nearly half of the people in the world dye their hair with a variety of permanent and semi‐permanent dyes, one can expect that confirmatory identification of dyes on the body's hair can be used to shed light on the victim's identity. A growing body of evidence suggests that surface‐enhanced Raman spectroscopy (SERS) can be used to detect and identify hair dyes. In this study, we investigated the extent to which SERS could be used to detect black and blue, permanent and semi‐permanent dyes on hair submerged in hypolimnion water for up to twelve weeks. We found that SERS enabled 100% accurate identification of analyzed dyes on hair submerged in hypolimnion water for up to 8 weeks, whereas, on average, 87% accurate identification of the hair dyes could be achieved on hair exposed for 10 weeks and 50% for hair exposed 12 weeks in hypolimnion water. We also found that the aqueous environment caused progressive fading of some dyes, whereas other dyes showed substantial spectral transformations after prolonged submergence. Finally, we found that changes in the intensity of vibrational bands of dyes could be used to predict the duration of submergence of colored hair in hypolimnion water. [ABSTRACT FROM AUTHOR]