An adaptive bivariate kernel smoothing method for determining instars of Austrosimulium tillyardianum (Diptera: Simuliidae) larvae |
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Authors: | Guan‐Jun Cen Xu‐Yuan Gao Xiu‐Zhen Long Xian‐Ru Zeng Ji‐Min Liu De‐Wei Wei Yong‐Hao Yu |
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Affiliation: | 1. Department of Applied Mathematics, College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China;2. Guangxi Key Laboratory of Biology for Crop Diseases and Insect Pests/Institute of Plant Protection, Guangxi Academy of Agricultural Sciences, Nanning, China;3. College of Agriculture, South China Agricultural University, Guangzhou, China |
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Abstract: | 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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Keywords: | Austrosimulium tillyardianum instar determination method adaptive bivariate kernel smoothing estimation instar identification |
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