I4S - Integrated System for Site-Specific Soil Fertility Management

Photo: Rumposch/ATB


This page provides a brief summary of the project results in Phase 1 to 3

Preliminary results from Phase 1 (2015 - 2017)

In the first phase of the project, several sensors were successfully tested in laboratory and calibrated. The sensors that showed the best results at laboratory scale, as the Geoelectrics, the Vis-NIR-Spectrometer, Gamma-Spectrometer and ion-selective electrodes were successively integrated in a mobile multi-sensor platform for topsoil mapping (RapidMapper).

Sensor-based soil maps were integrated into soil-process models (Hermes and Daisy) to simulate soil water and nitrogen dynamics and predict crop growth and yield in higher spatial resolution.

Preliminary results from Phase 2 (2018 - 2021)

In the second phase of the project the capacity of the sensors to give useful and meaningful information about the agricultural soils was further analysed:

  • NO3 content can be correctly measured in field through ion-selective electrodes (expensive and fragile) and colorimetric methods (more complex, but drift-free and less expensive in the long run).
  • Plant-available PO4 can be predicted both by total P from X-ray fluorescence and LIBS, but X-ray fluorescence showed to be a more precise and robust alternative.
  • Raman spectroscopy has to be adapted to the soil analysis, due to interference of the Raman signals by ambient light and by fluorescence from clays and soil organic matter. To overcome this issue, the shifted excitation Raman difference spectroscopy (SERDS) approach was chosen to effectively separate Raman signals from such interference. SERDS is able to discriminate many important molecular compounds, including PO4 species and also to quantify concentrations. Within the I4S project was built the world’s first portable SERDS system dedicated to soil sensing.
  • I4S RapidMapper soil sensor platform was further implemented with other sensors and deployed in two field campaigns.
  • In cooperation with the pH-BB project it was demonstrated that base neutrali­zation capacity and liming requirements can be estimated from soil sensor data. This was possible with lab MIR spectroscopy and with in situ pH potentiometry, electrical conductivity (EC) and Vis-NIR spectroscopy.
  • The new HERMES version with enhanced speed and improved compatibility for integration into the Decision Support System (DSS) is ready to function and is currently being tested. It was also integrated with the Sulphate module and implemented with irrigation recommendations.

Expected results from Phase 3 (2022 - 2025)

The influence of the sampling date, pre-crop and period after harvest is very important for the prediction of plant-available P, K and other nutrients. To better understand these interactions and to develop specific recommendations for a sampling protocol, will be set up a systematic sampling campaign and supporting lab experiments under controlled conditions. In the third phase of the project will be also studied other soil properties and the cross-influence of the soil moisture. As a prerequisite for successful measurements on the mobile platform (RapidMapper), extensive field measurements will be carried out on different test fields.

Due to the importance of knowing subsoil characteristics to better determine the topsoil properties, a platform for soil profile analysis (RapidProfiler) will be also developed. However, since the Profiler is a quite elaborated system and there might be many situations where only surface data are available, subsoil information will be also additionally derived from surface sensor data and multiple-year spatial yield patterns with inverse modeling approaches. All these information will be used to further improve the DSS.

Since the yield maps from harvesting combines are sometimes of very poor quality or even lacking due to technical problems or operation errors, in this phase of the project we will also try to give an answer to the question “how to map yield over large areas more reliably?”. Due to their continuously improving spatial resolution and availability, satellite imagery might be a time and cost saving alternative, which we will further investigated.