Sensoterra’s recent experiments on soil calibration curves
Sensoterra is working on even more efficiency by currently investing in new soil calibration curves in laboratory; with the objective to increase the number of covered soil types and provide more specific data on calibration.
Recent technological advances have been revolutionizing water management practices, such as research on crop yield, precision agriculture, and irrigation scheduling. Modern methods in agriculture involve different instruments and methods to monitor soil moisture measurement, such as in-field sensors and aerial drones imagery.
Sensoterra is a low-cost, robust and fully wireless solution providing hourly soil moisture measurements for all types of growers and crop types worldwide. Guided by Internet of Things technology (IoT), based on LoRaWAN connectivity, the collected hard-data gets stored in Sensoterra’s cloud-based server, where growers can easily access it via smartphones, desktop or API data integration.
The soil diagram consists of a tool to provide soil texture classifications - used both in the field and laboratory - to determine soil classes based on physical texture.
Soil texture diagram (soil triangle) for soil classification based percentages of sand, clay and silt.
Even though each soil type has specific characteristics on its composition: minerals, water, organic matter and air, to calibrate the most important soil types in the market will support growers with irrigation’s optimization, as soil moisture levels at the root zone can now be adequately measured.
The fact that variations among soil types properties can also affect sensors output, calibration becomes essential to achieve the best results. In general, calibration can reduce errors to more or less 1%. Moisture content of soil, in its turn, is a key factor for plant growth. Plants can readily absorb soil water, which dissolves salts and makes up soil solution, important for the supply of nutrients to growing plants.
Covering the most common soil types in the market (sandy, clay, clay-loam, saline clay and peat), Sensoterra is working on even more efficiency by currently investing in new soil calibration curves in laboratory; with the objective to increase the number of covered soil types (in soil texture diagram) and provide more specific data on calibration, as well as optimize the existing calibration curves.
A variety of soil types has been collected from the field to represent as many soil types as there are outside. During the experiment, soil moisture is measured every 15 minutes in order to provide precise data for the calibration curve settings. The higher the accuracy level, the better soil moisture sensors can indicate reality, with fewer chances for deviations.
Tests in Sensoterra's Laboratory
The experiment so far has been focusing on the repeatability of soil moisture readings for sand (with and without organic matter content), peat and saline clay soils. In addition, calibrated curves for new soil types: loamy-sand, tree soil (sand), light-clay (clay-loam), and planting soil (sand). Repeatability is extremely important in soil calibration to reduce sensors sensitivity - mostly increased in light soils as sandy textures.
Founded in 2014, Sensoterra (www.sensoterra.com) provides data-driven solutions for optimizing land and freshwater resources for agriculture, horticulture, landscaping and nature restoration. Based in Amsterdam, the company has over 5,000 sensors distributed worldwide.
Contact for more information:
Email: [email protected]
Caroline is a Soil Data Manager at Sensoterra. Previously, she worked as a laboratory analyst, responsible for data analysis of roots and soil, identifying pesticide contamination and plant accumulation. Her background is in Environmental Science, with a Masters's degree in Water & Environment from Radboud University.Get in touch