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基于翅膀图像实现丽蝇的自动识别

Towards the automated identification of Chrysomya blow flies from wing images.

作者信息

Macleod N, Hall M J R, Wardhana A H

机构信息

Department of Earth Sciences, Natural History Museum, London, U.K.

Department of Life Sciences, Natural History Museum, London, U.K.

出版信息

Med Vet Entomol. 2018 Sep;32(3):323-333. doi: 10.1111/mve.12302. Epub 2018 Apr 15.

Abstract

The Old World screwworm fly (OWSF), Chrysomya bezziana (Diptera: Calliphoridae), is an important agent of traumatic myiasis and, as such, a major human and animal health problem. In the implementation of OWSF control operations, it is important to determine the geographical origins of such disease-causing species in order to establish whether they derive from endemic or invading populations. Gross morphological and molecular studies have demonstrated the existence of two distinct lineages of this species, one African and the other Asian. Wing morphometry is known to be of substantial assistance in identifying the geographical origin of individuals because it provides diagnostic markers that complement molecular diagnostics. However, placement of the landmarks used in traditional geometric morphometric analysis can be time-consuming and subject to error caused by operator subjectivity. Here we report results of an image-based approach to geometric morphometric analysis for delivering wing-based identifications. Our results indicate that this approach can produce identifications that are practically indistinguishable from more traditional landmark-based results. In addition, we demonstrate that the direct analysis of digital wing images can be used to discriminate between three Chrysomya species of veterinary and forensic importance and between C. bezziana genders.

摘要

旧大陆螺旋蝇(OWSF),即致倦库蚊(双翅目:丽蝇科),是创伤性蝇蛆病的重要病原体,因此也是人类和动物健康的主要问题。在实施旧大陆螺旋蝇控制行动时,确定此类致病物种的地理起源非常重要,以便确定它们是源自地方种群还是入侵种群。宏观形态学和分子研究表明,该物种存在两个不同的谱系,一个是非洲谱系,另一个是亚洲谱系。已知翅形态测量在识别个体的地理起源方面有很大帮助,因为它提供了补充分子诊断的诊断标记。然而,传统几何形态分析中使用的地标放置可能很耗时,并且容易受到操作员主观性导致的误差影响。在这里,我们报告了一种基于图像的几何形态分析方法用于基于翅的识别的结果。我们的结果表明,这种方法产生的识别结果与更传统的基于地标的结果几乎没有区别。此外,我们证明数字翅图像的直接分析可用于区分三种具有兽医和法医重要性的库蚊物种以及致倦库蚊的性别。

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