甜菜夜蛾智能性诱监测效能评价及其温度预测模型OA

To address the limitations of traditional manual pest monitoring,such as data latency,high labor costs,and lack of data standardization,this study aimed to evaluate the performance of the AIM intelligent monitoring system.A year-round comparative experiment between the AIM intelligent monitoring device and conventional general-purpose sex pheromone traps was conducted in the main vegetable production area of Jinning,Kunming,in 2025.The study sys-tematically analyzed differences in population dynamics monitoring,trapping sensitivity,and operating costs.Using SPSS software,a multivariate linear regression model incorporating monthly mean temperature,rainfall,and relative humidity was constructed.The weights of these factors were evaluated using standardized coefficients,and a linear regression prediction model based on the temperature factor was subsequently established.(1)Monitoring Efficacy:The AIM in-telligent monitor trapped a total of 781 Spodoptera exigua individuals throughout the year,significantly exceeding the 462 individuals caught by conventional traps,representing a 69.05％increase in trapping efficacy.The device demon-strated a particularly significant advantage in monitoring sensitivity during periods of low temperature and low popula-tion density.(2)Model Analysis:Multivariate regression analysis indicated that the trap catches of the AIM intelligent monitor were primarily positively driven by temperature(standardized coefficient β=0.775),while the effects of humidity(β=0.033)and rainfall(β=0.060)were minimal and insignificant(P>0.800).This confirms the device's excellent re-silience to environmental interference.In contrast,conventional traps exhibited a distinct negative sensitivity to humidity(β=-0.294).Considering both scientific rigor and practical applicability,the final single-factor temperature prediction model determined was y=2.69x+20.97(R2=0.696),which is sufficient to explain the primary characteristics of population fluctuations.(3)Economic Benefits:Although the intelligent monitoring system requires a higher initial investment,the substantial savings in labor costs resulted in a 15.39％reduction in the average annual comprehensive operating cost compared to traditional manual monitoring.The AIM intelligent monitoring device achieves real-time and precise data acquisition while offering significant advantages in cost reduction and efficiency improvement.The constructed tempera-ture-based prediction model provides a scientific basis for the early warning and precise control of S.exigua in the local region.