AI Article Synopsis

  • * Researchers analyzed the chemical profiles of these puparium using advanced techniques to identify 49 hydrocarbons, which help track how they change over time.
  • * They used three different predictive models, finding that the artificial neural network model had the best accuracy for estimating the weathering time, contributing useful insights for forensic investigations related to postmortem intervals.

Article Abstract

Empty puparium are frequently collected at crime scenes and may provide valuable evidence in cases with a long postmortem interval (PMI). Here, we collected the puparium of (Diptera: Sarcophagidae) (Robineau-Desvoidy, 1830) for 120 days at three temperatures (10 °C, 25 °C, and 40 °C) with the aim to estimate the weathering time of empty puparium. The CHC profiles were analyzed by gas chromatography-mass spectrometry (GC-MS). The partial least squares (PLS), support vector regression (SVR), and artificial neural network (ANN) models were used to estimate the weathering time. This identified 49 CHCs with a carbon chain length between 10 and 33 in empty puparium. The three models demonstrate that the variation tendency of hydrocarbon could be used to estimate the weathering time, while the ANN models show the best predictive ability among these three models. This work indicated that puparial hydrocarbon weathering has certain regularity with weathering time and can gain insight into estimating PMI in forensic investigations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502838PMC
http://dx.doi.org/10.3390/insects13090808DOI Listing

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