[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelli...[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelligent insect sexual attraction monitoring system,manual survey and traditional pest monitoring tool were compared and analyzed,and the application effect of guiding field pest control was investigated.[Results]The statistical data of intelligent insect sexual attraction monitoring system were highly consistent with that of manual survey,and were consistent with that of traditional pest monitoring tool,which had good effect in guiding field control.[Conclusions]The monitoring data of intelligent insect sexual attraction monitoring system are accurate,efficient,real-time and practical.It can solve the problem of high monitoring intensity for the monitoring personnel and conform to the development direction of modern agriculture.展开更多
[Objectives]To assess the effectiveness of the intelligent small insect monitoring and forecasting system developed by Zhejiang Top Cloud-Agri Technology Co.,Ltd.in monitoring,providing early warnings,and identifying ...[Objectives]To assess the effectiveness of the intelligent small insect monitoring and forecasting system developed by Zhejiang Top Cloud-Agri Technology Co.,Ltd.in monitoring,providing early warnings,and identifying rice planthoppers.[Methods]In 2024,an experiment involving the automatic identification and counting of rice planthoppers was conducted using the intelligent small insect monitoring and forecasting system in the rice production demonstration area of Qingxichang Sub-district,Xiushan Autonomous County,Chongqing City.The results obtained were subsequently compared and analyzed against those derived from manual identification.[Results]The intelligent small insect monitoring and forecasting system achieved recognition accuracy rates of 95.14%,94.25%,and 97.78% for Nilaparvata lugens,Sogatella furcifera,and Laodelphax striatellus,respectively,resulting in an average accuracy rate of 95.72%.The outcomes derived from automatic recognition closely corresponded with those obtained through manual identification.[Conclusions]This research provides a reference for the optimization of the intelligent small insect monitoring and forecasting system.展开更多
文摘[Objectives]The paper was to verify and explore the application effect of intelligent insect sexual attraction monitoring system.[Methods]The data of Helicoverpa armigera and Spodoptera frugiperda monitored by intelligent insect sexual attraction monitoring system,manual survey and traditional pest monitoring tool were compared and analyzed,and the application effect of guiding field pest control was investigated.[Results]The statistical data of intelligent insect sexual attraction monitoring system were highly consistent with that of manual survey,and were consistent with that of traditional pest monitoring tool,which had good effect in guiding field control.[Conclusions]The monitoring data of intelligent insect sexual attraction monitoring system are accurate,efficient,real-time and practical.It can solve the problem of high monitoring intensity for the monitoring personnel and conform to the development direction of modern agriculture.
文摘[Objectives]To assess the effectiveness of the intelligent small insect monitoring and forecasting system developed by Zhejiang Top Cloud-Agri Technology Co.,Ltd.in monitoring,providing early warnings,and identifying rice planthoppers.[Methods]In 2024,an experiment involving the automatic identification and counting of rice planthoppers was conducted using the intelligent small insect monitoring and forecasting system in the rice production demonstration area of Qingxichang Sub-district,Xiushan Autonomous County,Chongqing City.The results obtained were subsequently compared and analyzed against those derived from manual identification.[Results]The intelligent small insect monitoring and forecasting system achieved recognition accuracy rates of 95.14%,94.25%,and 97.78% for Nilaparvata lugens,Sogatella furcifera,and Laodelphax striatellus,respectively,resulting in an average accuracy rate of 95.72%.The outcomes derived from automatic recognition closely corresponded with those obtained through manual identification.[Conclusions]This research provides a reference for the optimization of the intelligent small insect monitoring and forecasting system.
