What our data tells you about installation method, how Spiio compares to TDR readings, and why rainfall doesn't always immediately change your numbers.
Spiio™ soil sensors continuously monitor moisture, temperature, and salinity at rootzone depth. This article explains what our internal trial data shows about how installation method affects your readings, why Spiio numbers may differ from a TDR meter, and how rainfall and irrigation relate to what your sensors report.
The trial was conducted on a bermudagrass fairway in a native-soil, sandy loam environment. Results should be considered within the context of these trial conditions.
Data was sourced from an internal Spiio installation trial (Protocol Spiio123, April 2026) conducted by the Syngenta Digital Data Science team.
Does Installation Method Affect My Sensor Data?
When a Spiio sensor is installed at the correct depth and orientation, the physical installation method does not significantly affect moisture, temperature, or salinity readings.
In a controlled field trial, Spiio sensors were installed using multiple installation methods and monitored over an extended period. Soil moisture, soil temperature, and soil salinity were analyzed to determine whether the physical method used to place the sensor in the ground changed the data.
Key findings across all three measurements:
Installation method had no statistically significant effect on moisture, temperature, or salinity readings.
The factor that drove differences in readings was time of year, month, and season, rather than the physical installation method.
What this means for you: sensors installed using slightly different methods, such as hand-pressed or machine-assisted installatio, can still provide valid and comparable data.
However, installation method and sensor positioning are not the same thing. Correct sensor depth and horizontal orientation still matter for accurate data collection. Always follow the recommended Spiio installation procedure when placing a sensor.
Why Do My Spiio Readings Look Different from My TDR?
Spiio sensors and TDR meters measure soil moisture differently. This is expected and is not a sign that something is wrong.
In the same trial, Spiio sensor data was compared directly with TDR 350 handheld meter readings taken at matched timepoints. The results showed a consistent pattern:
Spiio sensors reported an average moisture reading approximately 11% higher than the TDR 350.
Spiio readings showed less variability over time, while TDR readings showed more variability from measurement to measurement.
This difference was consistent across installation methods and was not caused by how the sensor was physically installed.
Why the difference?
Spiio sensors and TDR meters use different technologies and measurement approaches to estimate soil moisture. They are not interchangeable instruments, and their absolute values are not expected to match.
The value of a Spiio sensor is in trending and consistency, tracking how your rootzone changes over time at a specific location, rather than matching an individual spot-check reading from a handheld meter.
Use your TDR for validation spot-checks and GreenCast Connect to monitor the directional trends that support your management decisions.
Practical guidance:
Don't set thresholds based solely on your TDR readings and expect Spiio to reach the same values. Establish thresholds using Spiio data alongside what you observe on the turf.
Use Data Explorer to compare sensor readings over time and establish a baseline for each location.
If you consistently see a difference between a Spiio reading and your TDR, that difference can become useful reference information for that specific area.
Why Doesn't Rainfall Always Spike My Moisture Readings?
Water from rainfall or irrigation does not always immediately reach the sensor location due to surface water movement influenced by topography or varying infiltration rates.
The trial examined whether daily precipitation correlated with changes in Spiio soil moisture and salinity readings. Overall, precipitation had a weak influence on sensor readings.
Several factors can explain this:
Rainfall amount: Light rain events, (less than 0.5 inches) may not result in a noticeable change at the sensor location. More significant rain events of 0.5 inches or greater are more likely to influence rootzone conditions.
Water movement and infiltration: Water from rainfall or irrigation may move differently through the soil depending on topography, drainage, soil characteristics, and infiltration rates. As a result, water applied at the surface may not immediately reach the sensor location.
Seasonal context: Season had a stronger influence on salinity readings than rainfall alone. Fall and winter showed the strongest relationship between precipitation and salinity, consistent with leaching behavior during cooler, wetter conditions.
Small rain events don't always equal rootzone change: A brief passing shower may produce little or no noticeable response in your sensor data, while larger events and irrigation that reach the sensor location are more likely to appear in the trend.
If you see little or no movement in your moisture readings after rainfall or irrigation, consider the amount of water received, how water moves through that particular area, and whether it was sufficient to affect conditions at the sensor location.
Summary
Installation method: The physical method used to install the sensor does not significantly affect moisture, temperature, or salinity readings. However, correct sensor depth and horizontal orientation still matter for accurate data collection. Season and time of year were the dominant drivers of differences observed in the trial.
Spiio vs. TDR: Spiio read approximately 11% higher than a TDR 350 in the trial. This is expected. Use Spiio for continuous trending and TDR measurements for spot validation.
Rainfall: Light rain events of less than 0.5 inches may not noticeably affect sensor readings. Larger events of 0.5 inches or greater are more likely to influence rootzone conditions, but water movement, infiltration, topography, and seasonal conditions also affect the sensor response.
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