Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species

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dc.contributor.author Moore, Hannah E.
dc.contributor.author Butcher, John B.
dc.contributor.author Day, Charles R.
dc.contributor.author Drijfhout, Falko P.
dc.date.accessioned 2021-01-19T14:43:16Z
dc.date.available 2021-01-19T14:43:16Z
dc.date.issued 2017-10-08
dc.identifier.citation Moore HE, Butcher JB, Day CR, Drijfhout FP. (2017) Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species. Forensic Science International, Volume 280, November 2017, pp. 33-244 en_UK
dc.identifier.issn 0379-0738
dc.identifier.uri https://doi.org/10.1016/j.forsciint.2017.10.001
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/16201
dc.description.abstract Blowflies (Diptera: Calliphoridae) are forensically important as they are known to be one of the first to colonise human remains. The larval stage is typically used to assist a forensic entomologists with adult flies rarely used as they are difficult to age because they remain morphologically similar once they have gone through the initial transformation upon hatching. However, being able to age them is of interest and importance within the field. This study examined the cuticular hydrocarbons (CHC) of Diptera: Calliphoridae species Lucilia sericata, Calliphora vicina and Calliphora vomitoria. The CHSs were extracted from the cuticles of adult flies and analysed using Gas Chromatography-Mass Spectrometry (GC-MS). The chemical profiles were examined for the two Calliphora species at intervals of day 1, 5, 10, 20 and 30 and up to day 10 for L. sericata. The results show significant chemical changes occurring between the immature and mature adult flies over the extraction period examined in this study. With the aid of a Principal Component Analysis (PCA) and Artificial Neural Networks (ANN), samples were seen to cluster, allowing for the age to be established within the aforementioned time frames. The use of ANNs allowed for the automatic classification of novel samples with very good performance. This was a proof of concept study, which developed a method allowing to age post-emergence adults by using their chemical profiles en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject principal component analysis en_UK
dc.subject post mortem interval en_UK
dc.subject cuticular hydrocarbons en_UK
dc.subject artificial neural networks en_UK
dc.subject adult blowflies en_UK
dc.title Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species en_UK
dc.type Article en_UK
dc.identifier.cris 18783817
dc.date.freetoread 2021-01-19


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