Age estimation of Calliphorida (Diptera: Calliphoridae) larvae using cuticular hydrocarbon analysis and Artificial Neural Networks Hannah E. Moorea*, John B. Butcherb, Craig D. Adama, Charles R. Dayc, Falko P. Drijfhouta aSchool of Physical and Geographical Sciences, Keele University, Staffordshire, ST5 5BG, UK bSchool of Life Sciences, Keele University, Staffordshire, ST5 5BG, UK cSchool of Computing and Mathematics, Keele University, Staffordshire, ST5 5BG, UK *corresponding author:
[email protected] An ageing technique of forensically important larvae using cuticular hydrocarbons Analysed using Gas Chromatography – Mass Spectrometry Statistically analysed using Principal Component Analysis and Artificial Neural Networks Successfully age larvae of Calliphora vicina and Calliphora vomitoria 1 2 3 4 5 Age estimation of Calliphorida (Diptera: Calliphoridae) larvae 6 using cuticular hydrocarbon analysis and Artificial Neural 7 Networks 8 Abstract 9 Cuticular hydrocarbons were extracted daily from the larvae of two closely related blowflies 10 Calliphora vicina and Calliphora vomitoria (Diptera:Calliphoridae). The hydrocarbons were then 11 analysed using Gas Chromatography-Mass Spectrometry (GC-MS), with the aim of observing 12 changes within their chemical profiles in order to determine the larval age. The hydrocarbons were 13 examined daily for each species from 1 day old larvae until pupariation. The results show significant 14 chemical changes occurring from the younger larvae to the post-feeding larvae. With the aid of a 15 multivariate statistical method (Principal Component Analysis and Artificial Neural Networks), 16 samples were clustered and classified, allowing for the larval age to be established. Results from this 17 study allowed larvae to be aged to the day with at worst, 87% accuracy, which suggests there is great 18 potential for the use of cuticular hydrocarbons present on larvae to give an indication of their age and 19 hence potentially a valuable tool for minimum PMI estimations.