A new species,Sclerodermus alternatusi Yang,sp.nov.(Hymenoptera:Bethylidae),is described and illustrated.Its cerambycid host,Monochamus alternatus Hope,a severe wood borer attacking many pine trees(Pinus spp.),is also...A new species,Sclerodermus alternatusi Yang,sp.nov.(Hymenoptera:Bethylidae),is described and illustrated.Its cerambycid host,Monochamus alternatus Hope,a severe wood borer attacking many pine trees(Pinus spp.),is also a vector of pine wood nematode,Bursaphelencus xylophilus,which cause severe damages to pine forests in China.The new species is a gregarious ectoparasitoid of junior larva of M.alternatus.The number of adult wasps reared from a single host larva ranges from 6 to 45.The ratio of female to male is 20:1.The new parasitoid species has a high potential in using as a biocontrol agent for the wood borer.Diagnosis of the new species with comparisons to its related species,S.pupariae Yang&Yao and a key to known species of Sclerodermus from China is provided.展开更多
To provide pest technicians with a convenient way to recognize insects,a novel method is proposed to classify insect images by integrated region matching (IRM) and dual tree complex wavelet transform (DTCWT).The wing ...To provide pest technicians with a convenient way to recognize insects,a novel method is proposed to classify insect images by integrated region matching (IRM) and dual tree complex wavelet transform (DTCWT).The wing image of the lepidopteran insect is preprocessed to obtain the region of interest (ROI) whose position is then calibrated.The ROI is first segmented with the k-means algorithm into regions according to the color features,properties of all the segmented regions being used as a coarse level feature.The color image is then converted to a grayscale image,where DTCWT features are extracted as a fine level feature.The IRM scheme is undertaken to find K nearest neighbors (KNNs),out of which the nearest neighbor is searched by computing the Canberra distance of DTCWT features.The method was tested with a database including 100 lepidopteran insect species from 18 families and the recognition accuracy was 84.47%.For the forewing subset,a recognition accuracy of 92.38% was achieved.The results showed that the proposed method can effectively solve the problem of automatic species identification of lepidopteran specimens.展开更多
基金part of the Research Program “The Key Techniques for Control Pine Wood Nematod”“Fundamental Research Funds of Chinese Academy of Forestry (CAFYBB2021ZG001)” for supporting the present studysupported by the National Natural Science Foundation of China (32370494):Taxonomic study of braconids parasitizing important cerambycids and screening of excellent natural enemies.
文摘A new species,Sclerodermus alternatusi Yang,sp.nov.(Hymenoptera:Bethylidae),is described and illustrated.Its cerambycid host,Monochamus alternatus Hope,a severe wood borer attacking many pine trees(Pinus spp.),is also a vector of pine wood nematode,Bursaphelencus xylophilus,which cause severe damages to pine forests in China.The new species is a gregarious ectoparasitoid of junior larva of M.alternatus.The number of adult wasps reared from a single host larva ranges from 6 to 45.The ratio of female to male is 20:1.The new parasitoid species has a high potential in using as a biocontrol agent for the wood borer.Diagnosis of the new species with comparisons to its related species,S.pupariae Yang&Yao and a key to known species of Sclerodermus from China is provided.
基金Project (No.2006AA10Z211) supported by the National High-Tech Research and Development Program (863) of China
文摘To provide pest technicians with a convenient way to recognize insects,a novel method is proposed to classify insect images by integrated region matching (IRM) and dual tree complex wavelet transform (DTCWT).The wing image of the lepidopteran insect is preprocessed to obtain the region of interest (ROI) whose position is then calibrated.The ROI is first segmented with the k-means algorithm into regions according to the color features,properties of all the segmented regions being used as a coarse level feature.The color image is then converted to a grayscale image,where DTCWT features are extracted as a fine level feature.The IRM scheme is undertaken to find K nearest neighbors (KNNs),out of which the nearest neighbor is searched by computing the Canberra distance of DTCWT features.The method was tested with a database including 100 lepidopteran insect species from 18 families and the recognition accuracy was 84.47%.For the forewing subset,a recognition accuracy of 92.38% was achieved.The results showed that the proposed method can effectively solve the problem of automatic species identification of lepidopteran specimens.
