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

Abstract

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.

Application of Spatio-Temporal Context and Convolution Neural Network (CNN) in Grooming Behavior of Bactrocera minax (Diptera: Trypetidae) Detection and Statistics

“…Identification of fruit fly adult species based on machine vision [ 43 ] or the method of identifying and counting other insects [ 44 , 45 , 46 ] is mature and has practical applications. At present, using the popular deep learning object detection algorithm, as yolo [ 47 , 48 ] and maskRCNN [ 49 , 50 ] identification can also achieve better results.…”

Muscle attachment site patterns for species determination in West Palaearctic Wohlfahrtia (Diptera: Sarcophagidae) of medical and veterinary importance

“…For further improvement of the MAS method for species determination in dipteran larvae, the first steps into computerization were conducted in a previous study 28 . This approach will reduce researcher bias and facilitate the method.…”