Age estimation of Calliphora (Diptera: Calliphoridae) larvae using cuticular hydrocarbon analysis and Artificial Neural Networks.

Cuticular hydrocarbons were extracted daily from the larvae of two closely related blowflies Calliphora vicina and Calliphora vomitoria (Diptera: Calliphoridae). The hydrocarbons were then analysed using Gas Chromatography-Mass Spectrometry (GC-MS), with the aim of observing changes within their chemical profiles in order to determine the larval age. The hydrocarbons were examined daily for each species from 1day old larvae until pupariation. The results show significant chemical changes occurring from the younger larvae to the post-feeding larvae. With the aid of a multivariate statistical method (Principal Component Analysis and Artificial Neural Networks), samples were clustered and classified, allowing for the larval age to be established. Results from this study allowed larvae to be aged to the day with at worst, 87% accuracy, which suggests there is great potential for the use of cuticular hydrocarbons present on larvae to give an indication of their age and hence potentially a valuable tool for minimum PMI estimations.