Next Article in Journal
eButterfly: Leveraging Massive Online Citizen Science for Butterfly Conservation
Next Article in Special Issue
Abiotic and Biotic Factors Regulating Inter-Kingdom Engagement between Insects and Microbe Activity on Vertebrate Remains
Previous Article in Journal
Estimating Density and Temperature Dependence of Juvenile Vital Rates Using a Hidden Markov Model
Previous Article in Special Issue
The Role of a PMI-Prediction Model in Evaluating Forensic Entomology Experimental Design, the Importance of Covariates, and the Utility of Response Variables for Estimating Time Since Death
Article Menu

Export Article

Open AccessFeature PaperArticle
Insects 2017, 8(2), 52;

Connecting the Dots: From an Easy Method to Computerized Species Determination

Institute of Legal Medicine, University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany
Department of Electrical Engineering and Information Technology, University of Applied Sciences Jena, Carl-Zeiss-Promenade 2, 07745 Jena, Germany
Author to whom correspondence should be addressed.
Academic Editors: David Rivers and John R. Wallace
Received: 8 March 2017 / Revised: 28 April 2017 / Accepted: 12 May 2017 / Published: 18 May 2017
(This article belongs to the Special Issue Advances in Forensic Entomology)
View Full-Text   |   Download PDF [6118 KB, uploaded 18 May 2017]   |  


Differences in growth rate of forensically important dipteran larvae make species determination an essential requisite for an accurate estimation of time since colonization of the body. Interspecific morphological similarities, however, complicate species determination. Muscle attachment site (MAS) patterns on the inside of the cuticula of fly larvae are species specific and grow proportionally with the animal. The patterns can therefore be used for species identification, as well as age estimation in forensically important dipteran larvae. Additionally, in species where determination has proven to be difficult—even when employing genetic methods—this easy and cheap method can be successfully applied. The method was validated for a number of Calliphoridae, as well as Sarcophagidae; for Piophilidae species, however, the method proved to be inapt. The aim of this article is to assess the utility of the MAS method for applications in forensic entomology. Furthermore, the authors are currently engineering automation for pattern acquisition in order to expand the scope of the method. Automation is also required for the fast and reasonable application of MAS for species determination. Using filters on digital microscope pictures and cross-correlating them within their frequency range allows for a calculation of the correlation coefficients. Such pattern recognition permits an automatic comparison of one larva with a database of MAS reference patterns in order to find the correct, or at least the most likely, species. This facilitates species determination in immature stages of forensically important flies and economizes time investment, as rearing to adult flies will no longer be required. View Full-Text
Keywords: forensic entomology; muscle attachment sites; species determination; image processing; correlation; knowledge base forensic entomology; muscle attachment sites; species determination; image processing; correlation; knowledge base

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Niederegger, S.; Döge, K.-P.; Peter, M.; Eickhölter, T.; Mall, G. Connecting the Dots: From an Easy Method to Computerized Species Determination. Insects 2017, 8, 52.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Insects EISSN 2075-4450 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top