The fall armyworm(FAW),Spodoptera frugiperda,has colonized and caused consistent damage in the Eastern hemisphere.The identification of various FAW strains is essential for developing precise prevention and control me...The fall armyworm(FAW),Spodoptera frugiperda,has colonized and caused consistent damage in the Eastern hemisphere.The identification of various FAW strains is essential for developing precise prevention and control measures.The triosephosphate isomerase(Tpi)gene is recognized as an effective marker closely linked to FAW subpopulations.However,most current studies primarily focus on the comparison of variations in specific gene sites of this gene.In this study,we conducted full-length sequencing of the Tpi genes from 5 representative FAW groups.Our findings revealed that the Tpi genes varied in length from 1220 to 1420 bp,with the primary variation occurring within 4 introns.Notably,the exon lengths remained consistent,at 747 bp,with 37 observed base variations;however,no amino acid variations were detected.Through sequence alignment,we identified 8 stable variation sites that can be used to distinguish FAW strains in the Eastern hemisphere.Additionally,we performed strain identification on 1569 FAW samples collected from 19 provinces in China between 2020 and 2021.The extensive analysis indicated the absence of the rice strain in the samples.Instead,we only detected the presence of the corn strain and the Zambia strain,with the Zambia strain being distributed in a very low proportion(3.44%).Furthermore,the corn strain could be further categorized into 2 subgroups.This comprehensive study provides a valuable reference for enhancing our understanding of FAW population differentiation and for improving monitoring and early warning efforts.展开更多
Similarity measure has long played a critical role and attracted great interest in various areas such as pattern recognition and machine perception.Nevertheless,there remains the issue of developing an efficient two-d...Similarity measure has long played a critical role and attracted great interest in various areas such as pattern recognition and machine perception.Nevertheless,there remains the issue of developing an efficient two-dimensional(2D)robust similarity measure method for images.Inspired by the properties of subspace,we develop an effective 2D image similarity measure technique,named transformation similarity measure(TSM),for robust face recognition.Specifically,the TSM method robustly determines the similarity between two well-aligned frontal facial images while weakening interference in the face recognition by linear transformation and singular value decomposition.We present the mathematical features and some odds to reveal the feasible and robust measure mechanism of TSM.The performance of the TSM method,combined with the nearest neighbor rule,is evaluated in face recognition under different challenges.Experimental results clearly show the advantages of the TSM method in terms of accuracy and robustness.展开更多
基金supported by Shenzhen Natural Science Foundation(JCYJ20200109150629266)the National Natural Science Foundation of China(32302352 and 32372546)+1 种基金Sci-Tech Innovation 2030 Agenda(2022ZD04021)Shenzhen Science and Technology Program(KQTD20180411143628272).
文摘The fall armyworm(FAW),Spodoptera frugiperda,has colonized and caused consistent damage in the Eastern hemisphere.The identification of various FAW strains is essential for developing precise prevention and control measures.The triosephosphate isomerase(Tpi)gene is recognized as an effective marker closely linked to FAW subpopulations.However,most current studies primarily focus on the comparison of variations in specific gene sites of this gene.In this study,we conducted full-length sequencing of the Tpi genes from 5 representative FAW groups.Our findings revealed that the Tpi genes varied in length from 1220 to 1420 bp,with the primary variation occurring within 4 introns.Notably,the exon lengths remained consistent,at 747 bp,with 37 observed base variations;however,no amino acid variations were detected.Through sequence alignment,we identified 8 stable variation sites that can be used to distinguish FAW strains in the Eastern hemisphere.Additionally,we performed strain identification on 1569 FAW samples collected from 19 provinces in China between 2020 and 2021.The extensive analysis indicated the absence of the rice strain in the samples.Instead,we only detected the presence of the corn strain and the Zambia strain,with the Zambia strain being distributed in a very low proportion(3.44%).Furthermore,the corn strain could be further categorized into 2 subgroups.This comprehensive study provides a valuable reference for enhancing our understanding of FAW population differentiation and for improving monitoring and early warning efforts.
基金Project supported by the National Natural Science Foundation of China(No.61873106)the Natural Science Foundation of Jiangsu Province,China(No.BK20171264)+5 种基金the Jiangsu Qing Lan Project to Cultivate Middle-Aged and Young Science Leaders,China,the Jiangsu Six Talent Peak Project,China(Nos.XYDXX-047 and XYDXX-140)the University Science Research General Research General Project of Jiangsu Province,China(Nos.18KJB520005 and 19KJB520004)the Innovation Fund Project for Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education,China(No.JYB201609)the Lianyungang Hai Yan Plan,China(Nos.2018-ZD-003,2018-QD-001,and 2018-QD-012)the Science and Technology Project of Lianyungang Hightech Zone,China(Nos.ZD201910 and ZD201912)and the Natural Science Foundation Project of Huaihai Institute of Technology,China(No.Z2017005)。
文摘Similarity measure has long played a critical role and attracted great interest in various areas such as pattern recognition and machine perception.Nevertheless,there remains the issue of developing an efficient two-dimensional(2D)robust similarity measure method for images.Inspired by the properties of subspace,we develop an effective 2D image similarity measure technique,named transformation similarity measure(TSM),for robust face recognition.Specifically,the TSM method robustly determines the similarity between two well-aligned frontal facial images while weakening interference in the face recognition by linear transformation and singular value decomposition.We present the mathematical features and some odds to reveal the feasible and robust measure mechanism of TSM.The performance of the TSM method,combined with the nearest neighbor rule,is evaluated in face recognition under different challenges.Experimental results clearly show the advantages of the TSM method in terms of accuracy and robustness.
