Accurate recognition of the reproductive development status and prediction of oviposition fecundity in Spodoptera frugiperda(Lepidoptera:Noctuidae)based on computer vision

作     者：LÜChun-yang GE Shi-shuai HE Wei ZHANG Hao-wen YANG Xian-ming CHU Bo WU Kong-ming Lü Chun-yang;GE Shi-shuai;HE Wei;ZHANG Hao-wen;YANG Xian-ming;CHU Bo;WU Kong-ming

作者机构：Key Laboratory of Agricultural Information Service TechnologyMinistry of Agriculture and Rural AffairsAgricultural Information InstituteChinese Academy of Agricultural SciencesBeijing 100081P.R.China State Key Laboratory for Biology of Plant Diseases and Insect PestsInstitute of Plant ProtectionChinese Academy of Agricultural SciencesBeijing 100193P.R.China State Key Laboratory of Ecological Pest Control for Fujian and Taiwan CropsInstitute of Applied EcologyFujian Agriculture and Forestry UniversityFuzhou 350002P.R.China College of Plant ProtectionHenan Agricultural UniversityZhengzhou 450002P.R.China 

出 版 物：《Journal of Integrative Agriculture》 (农业科学学报（英文版）)

年 卷 期：2023年第22卷第7期

页      面：2173-2187页

核心收录：

学科分类：08[工学] 09[农学] 080203[工学-机械设计及理论] 0904[农学-植物保护] 0901[农学-作物学] 0802[工学-机械工程] 090402[农学-农业昆虫与害虫防治] 

基　　金：supported by the National Natural Science Foundation of China(31727901) the National Key R&D Program of China(2021YFD1400702) the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences 

主　　题：Spodoptera frugiperda computer vision ovary testis WeChat applet 

摘      要：Spodoptera frugiperda(Lepidoptera:Noctuidae)is an important migratory agricultural pest worldwide,which has invaded many countries in the Old World since 2016 and now poses a serious threat to world food *** present monitoring and early warning strategies for the fall army worm(FAW)mainly focus on adult population density,but lack an information technology platform for precisely forecasting the reproductive dynamics of the *** this study,to identify the developmental status of the adults,we first utilized female ovarian images to extract and screen five features combined with the support vector machine(SVM)classifier and employed male testes images to obtain the testis circular ***,we established models for the relationship between oviposition dynamics and the developmental time of adult reproductive organs using laboratory *** results show that the accuracy of female ovary development stage determination reached 91%.The mean standard error(MSE)between the actual and predicted values of the ovarian developmental time was 0.2431,and the mean error rate between the actual and predicted values of the daily oviposition quantity was 12.38%.The error rate for the recognition of testis diameter was 3.25%,and the predicted and actual values of the testis developmental time in males had an MSE of 0.7734.A WeChat applet for identifying the reproductive developmental state and predicting reproduction of *** was developed by integrating the above research results,and it is now available for use by anyone involved in plant *** study developed an automated method for accurately forecasting the reproductive dynamics of *** populations,which can be helpful for the construction of a population monitoring and early warning system for use by both professional experts and local people at the county level.