Design of multi-channel data acquisition and processing model and optimization of moisture sensor buried position

Abstract: With soil moisture sensors being widely used in precision irrigation, soil moisture is measured with soil moisture sensor to guide irrigation, as well as to improve water use efficiency and yield of crops. But because of the complexity of soil moisture sensor principle and soil composition, it will lead to the larger error between the measured and the actual value when using soil moisture sensor. In addition, soil moisture sensor has higher price. Therefore more sensors buried will increase the cost of irrigation system, and influence the popularization of irrigation system. So it is important to study the water status of the whole field with fewer sensors. The studies aiming at the soil moisture sensor laying position are mainly focused on buried depth, but there are few experimental studies of combining embedment width and depth. In this paper, the multi-channel data acquisition and monitoring system is designed, and the laying deepness and wideness of moisture sensors is studied in the cucumber drip irrigating field of the greenhouse in Ningxia. In addition, the calibration model of soil moisture sensor is also researched. Firstly, the calibration model of MP406 soil moisture sensor (made in Australia) is studied; thus the quadratic curve fitting of the experimental sensor calibration is got by the least squares method, and the calibration model for soil moisture sensor in Ningxia area is established. The errors between the fitting values and the measured values are calculated, in which the maximum error is 2.33%, and the correlation coefficient (r) is 0.9906. Then the multi-channel automatic data acquisition and monitoring system is designed and realized. The system is made up of 5 parts, including sensors (2 groups, 9 sensors each group), data acquisition devices (master data acquisition device and extended data acquisition device), GPRS (general packet radio service) wireless transmission module, remote PC terminal and remote mobile phone terminal. Data of 18 moisture sensors of different experimental treatments can be obtained at the same time, and moisture data can be downloaded and monitored from remote PC terminal in no time. During the irrigation process, when soil under treatment reaches the irrigation upper or lower limit, the system can notify the user's mobile phone via short message service (SMS), and users can also send SMS commands to control one or more treatments to start or stop irrigation. The data of irrigation, cucumber production and water use efficiency under different treatments are recorded. From the analyses of water use efficiency and cucumber production, T4 treatment (horizontal distance from drop head is 10 cm and embedding depth is 10 cm) is the best irrigation treatment. Regression analysis and examination is conducted on adjacent soil layers with burying sensors in 3 growing stages of cucumber, and the results show that it is feasible and effective to use moisture content values of T4 treatment to calculate moisture content values of T3 treatment (horizontal distance from drop head is 10 cm and embedding depth is 20 cm) in the flowering and fruit period. From the difference coefficient and correlation coefficient of the moisture sensor data, it is concluded that the best burying position of the moisture sensor in the cucumber drip irrigating field of the greenhouse in Ningxia is that the vertical distance from the drop hole is 10 cm, and the horizontal distance from the drop hole is 10 cm. It can achieve low cost drip irrigation intelligent control. This research method provides a reference for determining the buried depth and width of soil moisture sensors.