Development of calibration equations for capacitance sensors to measure soil water content using an IoT-based network
| dc.contributor.author | Santhanam, Prabakaran | |
| dc.contributor.examiningcommittee | Morrison, Jason (Biosystems Engineering) | en_US |
| dc.contributor.examiningcommittee | Bridges, Gregory (Electrical and Computer Engineering) | en_US |
| dc.contributor.supervisor | Ramanathan, Sri Ranjan | |
| dc.date.accessioned | 2023-01-09T16:34:01Z | |
| dc.date.available | 2023-01-09T16:34:01Z | |
| dc.date.copyright | 2023-01-04 | |
| dc.date.issued | 2023-01-04 | |
| dc.date.submitted | 2023-01-04T21:19:19Z | en_US |
| dc.degree.discipline | Biosystems Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Soil Water Content (SWC) plays a vital role in agriculture. Knowledge of SWC helps the farmers understand the crop’s water requirement and achieve a better yield. Due to commercialization, well-developed sensors are expensive for large-scale agriculture. There is a need for low-cost soil sensors to measure SWC precisely with spatial and temporal resolution. Low-cost soil sensors like SEN0193 needed to be calibrated and validated using the gravimetric method to obtain SWC. The SEN0193 sensors were integrated with the raspberry-pi stand-alone system, with mini-controllers (Arduino) to log the data from the sensors. The SEN0193 sensors were tested under a controlled environment with target VWC samples (Sand: 10, 20, 25, 30%, Loam: 10, 20, 30, 40, 50%, Clay: 10, 20, 30, 40%) prepared in the laboratory. The calibration equations were developed and validated both under laboratory and field conditions to find out the accuracy and precision. The SEN193 sensors demonstrated poor precision on fine particle-sized soils such as loam (0.003 m3/m3) and clay (0.003 m3/m3) and moderate precision on sand (0.002 m3/m3). Validation of sensors at different depths of 20 cm and 40 cm during the field study proved that the surface contact of the sensor with soil was affected by the air gap. Each sensor provided a different precision, which confirms the SEN0193 sensor’s fragile nature. A comparison of TEROS T10 sensors with SEN0193 sensors showed that the T10 sensors work with better accuracy and precision. Monitoring the airgap is, a better installation method with careful handling of the SEN0193 sensor could increase its performance. A water uptake pattern study of the canola root zone was conducted using the SEN0193 sensor at the Winkler site. Rainfall and the presence of crops influenced the upward groundwater flux. The shallow groundwater table with saline content adversely affects the crop. Using the sub-surface drainage system to remove the excess water will help the crop to attain a higher yield by limiting the upward flux of saline groundwater. | en_US |
| dc.description.note | February 2023 | en_US |
| dc.description.sponsorship | BELLMTS IoT grants | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/37072 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Soil water content, | en_US |
| dc.subject | IoT | en_US |
| dc.subject | Soil moisture sensors | en_US |
| dc.subject | Root water uptake pattern | en_US |
| dc.title | Development of calibration equations for capacitance sensors to measure soil water content using an IoT-based network | en_US |
| dc.type | master thesis | en_US |
| local.subject.manitoba | yes | en_US |
| oaire.awardTitle | Graduate Research Assistant | en_US |
| project.funder.identifier | NSERC: https://doi.org/10.13039/501100000038 | en_US |
| project.funder.name | National Sciences and Engineering Research Council of Canada | en_US |