Utilização de sensores capacitivos no monitoramento e manejo da irrigação da cultura do melão

Abstract

Irrigation management seeks to restore with maximum degree of precision the water that was lost, either by evaporation or transpiration, seeking to restore to an optimal level for the healthy development of the plant. Thus, it seeks to mitigate the waste of water resources and optimize the productive potential of the plant. In the melon crop, adequate irrigation is one of the agricultural practices that have the greatest impact on fruit development, productivity and quality. Therefore, it is necessary equipments and techniques capable of determining how much, when and how to irrigate, observing the conditions of the plant, soil and environment. Considering the importance of the sensors for efficient irrigation management, the objective of the present work was the recommendation of capacitive sensors to evaluate the soil moisture in porous media, through the following steps: i) Characterization of the capacitive humidity sensor; ii) Correlation of the sensor parameters with the demands of the plant; iii) Remote monitoring of field cropping. Thus, real-time data collection is combined with efficient techniques for remote monitoring, essential for agile decision making. The present study was implemented at the Agricultural Electronics and Mechanics Laboratory (LEMA), at the Agricultural Engineering Department (DENA) of the Agricultural Sciences Center (CCA) of the Federal University of Ceará (UFC), Campus do Pici. This way we used Arduino Uno, ESP 8266, Solenoid Valves, Centrifugal Pumps, Relays, Reservoirs; Source + Transformer and Bridges H. Thus, with the possession of these items, the control and data acquisition system was developed, the Arduino UNO model plate was used as hardware. To enable remote access, either for control or request data, a Wi-Fi ESP 8266 module connected to the Arduino was used. The calibration test was conducted in a PVC tube with the sensor inserted along the soil forming blocks, under which it was inserted up to 24 cm deep from the lower limit of the cylinder. In this calibration, 10 kg of dry, aerated, sieved and sieved soil were added in order to know its overall density. Using the Google Drive, "Google Spreads" and "Script to Google Apps" tools, it was possible for NodeMCU to send the data to a host, which captured the information posted in the script and fed an online spreadsheet. The codes for NodeMCU and Arduino were written and recorded using Arduino's own integrated development environment (IDE). Two (02) field sensors, chosen at random, were continuously monitored. The sensor plate was in the depths of 5 - 15 cm and 20 - 30 cm and were requested and stored data every 25 seconds, from September 27, 2018 until November 5, 2018. The other sensors were monitored with some readings throughout the day, aiming to monitor the variation generated by irrigation. The readings obtained were consistent with those expected in the literature, as well as satisfactory in the determination of the irrigation start and stop points.