文献类型： 外文期刊

第一作者： Gao, Xu-Yuan

作者： Gao, Xu-Yuan;Long, Xiu-Zhen;Zeng, Xian-Ru;Liu, Ji-Min;Wei, De-Wei;Yu, Yong-Hao;Gao, Xu-Yuan

作者机构：

关键词： Austrosimulium tillyardianum; instar determination method; adaptive bivariate kernel smoothing estimation; instar identification

期刊名称：ECOLOGICAL ENTOMOLOGY （ 影响因子：2.465； 五年影响因子：2.604 ）

ISSN： 0307-6946

年卷期： 2018 年 43 卷 4 期

页码：

收录情况： SCI

摘要： 1. In insects, instar determination is generally based on the frequency distribution of sclerotised body part measurements. Commonly used univariate methods, such as histograms and univariate kernel smoothing, are not sufficient to reflect the distribution of the measurements, because development of sclerotised body parts is multidimensional. 2. This study used an adaptive bivariate kernel smoothing method, based on 10 pairs of separating variables, to differentiate instars of Austrosimulium tillyardianum (Diptera: Simuliidae) larvae in two-dimensional space. A variable bandwidth matrix was used and separation lines between instars were defined. Using the Crosby growth ratio, Brooks' rule and the new standard recently proposed, larvae were separated into nine instars. It was found that, using the bivariate kernel smoothing method, the clustering accuracy and determination of separation lines as instar class limits were higher than those associated with the univariate kernel smoothing method. With the exceptions of the paired separating variables, head capsule length and antennal segment 3 length (AS3L), the mean probabilities of correct classifications was >85%. The pair of separating variables that yielded the greatest classification accuracy comprised mandible length (ML) and AS3L, which had mean probabilities of 0.8984. The clustering accuracy was higher for early- and late-instar larvae, but lower for instars 6 and 7. The adaptive bivariate kernel smoothing method was better than univariate methods for instar determination, especially in the detection of divisions between instars and identification of a larval instar.

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