Design and experiment of trapping and monitoring device for adult bactrocera dorsalis(hendel)

Bactrocera Dorsalis (Hendel) are invasive pests that occur frequently. They can cause serious harm to fruit trees' growth and have been ranked as an important quarantine object in many countries and regions. The regular manual survey used as the routine predicting method for Bactrocera Dorsalis (Hendel) cannot meet the requirement for real-time monitoring and warning of the adult pests in orchards. With the development of science and technologies, the method of the automatic machine monitoring for pests has been studied including detection of sound characteristics, radar monitoring, machine vision and spectral monitoring. Since the occurrence of Bactrocera Dorsalis (Hendel) is characteristics by randomness, migratory and hiding, the direct use of monitoring techniques above in combination with the traditional method may cause some problems such as timing, processing and costs in monitoring pests. Therefore, this study developed a trapping and monitoring device for detecting Bactrocera Dorsalis (Hendel) pests' quantity to tackle the problems above. Biological characteristics of the pests were analyzed. The numbers of pests were detected based on photo-electricity technology. The developed device was composed of a baffle, pest tunnels, detection area and a pest jar. A relevant signal detection module contained infrared photoelectric matching circuits, voltage followers, differential amplifiers and hysteresis comparators. Performance test of the device showed that there was significant (P<0.05) difference in the voltages detected from the device with shadowing and that without shadowing. The average voltages output from the device with shadowing and that without shadowing were 3.923 V and 3.883 V, respectively. The voltage output worked in a linear area. No significant difference (P>0.05) was found in the voltage outputs from the devices with different colors (black, white and blue) designed for its tunnel wall. The measuring errors caused by different detection positions could be ignored since the F test for voltage outputs from different positions produced P value greater than 0.05. Furthermore, the detection reliability of the device was validated in a Bactrocera Dorsalis (Hendel) pests' quantity monitoring experiment during peak seasons. The results showed the detection error of the developed device ranged from 3% to 8%. It could provide real-time and automatic detection for the pests and meet the requirements of monitoring Bactrocera Dorsalis (Hendel) in orchards.