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Environmentally friendly technologies for the prevention and control of crop diseases and insect pests are important to reduce the use of chemical pesticides, improve the quality of agricultural products, protect the environment, and promote sustainable development of crop production. On the basis of Internet of Things (IoT) technology, we developed a prevention and control system for crop diseases and insect pests with two main components: a plant protection device (the hardware) and an information management system (the software). To be suitable for both facility- and field-based production scenarios, we incorporated two types of plant protection devices, utilizing ozone sterilization and light-trap technologies. The devices were equipped with various sensors to realize real-time collection and monitoring of data on the crop production environment. The information management system has an IoT-based architecture and includes a mobile device app to enable remote control of the plant protection devices for intelligent management of plant protection data. The system can achieve efficient management of large-scale equipment applications and multi-device collaborative work to prevent and control pests and diseases. The developed system has operated successfully for several years in China and has been applied to cucumber, tomato, rice, and other crops. We demonstrate the effectiveness and practicality of the system in a greenhouse facility and in the field. [ABSTRACT FROM AUTHOR]

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Background: Analyses of the temporal distribution of mosquitoes are presented in statistical charts, but it is difficult to prove in statistics whether differences in peak periods exist among different years or habitats. This study aimed to investigate the application of circular statistics in determining the peak period and a comparison of differences., Methods: Surveillance of adult mosquitoes was conducted twice a month by light traps in five different habitats from March to November for 3 years (2021-2023) in Qingdao, Shandong Province, China. The Kruskal-Wallis test was performed to determine the differences in mosquito density among different years and habitats. Circular statistics and line charts were employed to determine the peak period and a comparison of differences., Results: Among a total of 14,834 adult mosquitoes comprising five mosquito species from four genera, Culex pipiens pallens was dominant and accounted for 89.6% of the specimens identified. Aedes albopictus, Armigeres subalbatus, and Anopheles sinensis made up 5.7%, 4.2%, and 0.5%, respectively. Culex tritaeniorhynchus accounted for less than 0.1%. The mean mosquito density (females/trap night) for the trapping period was 10.3 in 2021, 5.6 in 2022, and 3.6 in 2023. Among five habitats, the highest mosquito density was 8.9 in livestock sheds, followed by 6.8 in parks, 5.9 in rural dwellings, 5.5 in urban dwellings, and 5.4 in hospitals. No statistically significant differences were found among different years (H = 1.96, d.f. 2, P = 0.376) and habitats (H = 0.45, d.f. 4, P = 0.978). Overall, the peak period of mosquito activity fell in the months from June to September. The peak period among 3 years differed significantly (F (2,7022)  = 119.17, P < 0.01), but there were no statistically significant differences in peak period among different habitats (F (4,7020)  = -159.09, P > 0.05)., Conclusion: Circular statistics could be effectively combined with statistical charts to elucidate the peak period of mosquitoes and determine the differences in statistics among different years and habitats. These findings will provide valuable information for mosquito control and public health management., (© 2024. The Author(s).)

The use of light traps for controlling insect pests is restricted since they kill both pests and beneficial insects. It may be a possible to reduce the numbers of beneficial insects trapped by adjusting nightly trapping time based on differences recorded in the timing of the nocturnal flight peaks of target pests and beneficials. To test this, insects were collected hourly over night using black light traps at three locations in China from 2003 to 2005. Groups of lepidopteran and coleopteran pests were selected as the target pests that we would control by trapping and groups of beneficial predatory insects the catches of which needed to be reduced. The highest numbers of Coleoptera were caught between 20:00 and 22:00 h and of most Lepidoptera between 02:00 and 04:00 h. The hourly numbers of predatory insects caught by light traps were evenly distributed throughout the night. A model was developed to describe the relationships between the cumulative proportions of insects caught and time of night. The model accurately describes the flight activity of insects that were mainly caught before midnight, after midnight and evenly throughout a night by using different parameters for the three different insect groups. A beneficial-friendly trapping strategy was developed to reduce the numbers of beneficial insects trapped, which was based on differences in the nocturnal flight activity of pests and beneficial insects and validated by a field study in Shandong province. Results show that this trapping strategy reduced the number of beneficial insects caught by 46% and the electricity consumption by 50% compared to the traditional strategy. Thus this strategy is more beneficial-friendly than the traditional trapping strategy for controlling pests. [ABSTRACT FROM AUTHOR]