Toward an Automated Identification of Anastrepha Fruit Flies in the fraterculus group (Diptera, Tephritidae)

• Published in: Neotropical entomology Vol. 45; no. 5; pp. 554 - 558
• Main Authors: Perre, P, Faria, F A, Jorge, L R, Rocha, A, Torres, R S, Souza-Filho, M F, Lewinsohn, T M, Zucchi, R A
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-10-2016
• Subjects: Agriculture; Animals; Biomedical and Life Sciences; Drosophila; Entomology; Life Sciences; Morphology and Physiology; Systematics; Tephritidae - anatomy & histology; Tephritidae - classification; Wings, Animal; Identification; taxonomy; machine learning; image analysis
• DOI: 10.1007/s13744-016-0403-0
• EISSN: 1678-8052
• ISSN: 1519-566X

In this study, we assess image analysis techniques as automatic identifiers of three
Anastrepha
species of quarantine importance,
Anastrepha fraterculus
(Wiedemann),
Anastrepha obliqua
(Macquart), and
Anastrepha sororcula
Zucchi, based on wing and aculeus images. The right wing and aculeus of 100 individuals of each species were mounted on microscope slides, and images were captured with a stereomicroscope and light microscope. For wing image analysis, we used the color descriptor
Local Color Histogram
; for aculei, we used the contour descriptor
Edge Orientation Autocorrelogram
. A
Support Vector Machine
classifier was used in the final stage of wing and aculeus classification. Very accurate species identifications were obtained based on wing and aculeus images, with average accuracies of 94 and 95%, respectively. These results are comparable to previous identification results based on morphometric techniques and to the results achieved by experienced entomologists. Wing and aculeus images produced equally accurate classifications, greatly facilitating the identification of these species. The proposed technique is therefore a promising option for separating these three closely related species in the
fraterculus
group.