Identification of medically and forensically relevant flies using a decision treelearning method.

Blow flies, flesh flies, and house flies can provide excellent evidence for forensic entomologists and are also essential to the fields of public health, medicine, and animal health. In all questions, the correct identification of fly species is an important initial step. The usual methods based on morphology or even molecular approaches can reach their limits here, especially when dealing with larger numbers of specimens. Since machine learning already plays a major role in many areas of daily life, such as education, business, industry, science, and medicine, applications for the classification of insects have been reported. Here, we applied the decision tree method with wing morphometric data to construct a model for discriminating flies of three families [Calliphoridae, Sarcophagidae, Muscidae] and seven species [Chrysomya megacephala (Fabricius), Chrysomya rufifacies (Macquart), Chrysomya (Ceylonomyia) nigripes Aubertin, Lucilia cuprina (Wiedemann), Hemipyrellia ligurriens (Wiedemann), Musca domestica Linneaus, and Parasarcophaga (Liosarcophaga) dux Thomson]. One hundred percent overall accuracy was obtained at a family level, followed by 83.33% at a species level. The results of this study suggest that non-experts might utilize this identification tool. However, more species and also samples per specimens should be studied to create a model that can be applied to the different fly species in Thailand.

Identification of medically and forensically relevant flies using a decision treelearning method

@#Blow flies, flesh flies, and house flies can provide excellent evidence for forensic entomologists and are also essential to the fields of public health, medicine, and animal health. In all questions, the correct identification of fly species is an important initial step. The usual methods based on morphology or even molecular approaches can reach their limits here, especially when dealing with larger numbers of specimens. Since machine learning already plays a major role in many areas of daily life, such as education, business, industry, science, and medicine, applications for the classification of insects have been reported. Here, we applied the decision tree method with wing morphometric data to construct a model for discriminating flies of three families [Calliphoridae, Sarcophagidae, Muscidae] and seven species [Chrysomya megacephala (Fabricius), Chrysomya rufifacies (Macquart), Chrysomya (Ceylonomyia) nigripes Aubertin, Lucilia cuprina (Wiedemann), Hemipyrellia ligurriens (Wiedemann), Musca domestica Linneaus, and Parasarcophaga (Liosarcophaga) dux Thomson]. One hundred percent overall accuracy was obtained at a family level, followed by 83.33% at a species level. The results of this study suggest that non-experts might utilize this identification tool. However, more species and also samples per specimens should be studied to create a model that can be applied to the different fly species in Thailand.

Orbital ophthalmomyiasis caused by Chrysomya bezziana in Thailand.

Orbital ophthalmomyiasis occurs infrequently in Thailand. Herein, we report a case in Chiang Mai, Thailand, of orbital ophthalmomyiasis due to larvae of the blow fly Chrysomya bezziana (Diptera: Calliphoridae). A 94-year-old woman was admitted to Maharaj Nakorn Chiang Mai Hospital, Chiang Mai, Thailand, with a swollen and ulcerated right upper eyelid. The lesion in the eyelid had multiple holes around the ulcer site; bleeding was accompanied by pus and necrotic tissue - the site was filled with dipteran larvae. Eleven larvae were removed from the patient, of which five were killed for microscopic examination and six were reared in the laboratory under ambient temperature and natural relative humidity until they metamorphose into adult. Five third instars and one adult were morphologically identified as C. bezziana. The predisposing factors were probably chronic immobility, inability of the patient to perform daily activities, and presumably neglected and/or poor personal hygiene. To our knowledge, this case represents the first reported case of orbital ophthalmomyiasis caused by C. bezziana in Thailand.

Ontogenensis and developmental rate of the blow fly, Hypopygiopsis tumrasvini Kurahashi (Diptera: Calliphoridae).

Blow flies of the genus Hypopygiopsis are considered forensically important. In Thailand, four Hypopygiopsis species coexist, i.e., Hypopygiopsis fumipennis, Hypopygiopsis infumata, Hypopygiopsis violacea and Hypopygiopsis tumrasvini. In this study, the ontogeny and developmental rate of H. tumrasvini eggs, larvae and pupae were determined in the laboratory chamber reared at 25.0 ± 2.0°C and 80.0 ± 5.0% RH. Larvae emerged from eggs 10-12 h after deposition. Mean length of the first, second, third (feeding phase), third (post-feeding phase) instars and puparia were 3.5 ± 1.1, 7.2 ± 1.1, 13.5 ± 1.8, 12.5 ± 0.5 and 9.0 ± 0.7 mm, respectively. The median development time for first, second, third instar (feeding phase), third instar (post-feeding phase) and pupariation period was 8 h, 10 h, 34 h, 22 d and 9-10 d, respectively. Developmental curve of the larval length indicated the rapid progression from 0 until 40 h from the first instar until the feeding third instar. Video recording of pupariation revealed the development of pupal respiratory horn beneath the larval integument at 27.0 h; whereas it protruded through the orifice of the integument at 27.5 h.