An Approach to Avoid Moisture Interference on VISNIRS Measurement of Soil Organic Carbon

Resúmen de la comunicación oral presentada en el 10th Compositional Data Analysis Workshop (CoDaWork24), held on 3-7 June 2024 en Gerona (España)

Soil organic matter content (SOM) has an important role in modulating atmospheric CO2, soil organic carbon (SOC) being the best indicator of SOM. Soilcomponents are interdependent, no single soil component varies independently of the rest. Thus, they carry only relative information, which means they have a compositional nature. VisNIRS modelling with soil reference data needs therefore specific compositional data (CoDa) methods. The soil moisture (SM) variation supposes an important handicap to VisNIRS measurement of SOC. The CoDa methods can integrate SOC prediction along with the other soil parts considered, including SM. Doing it like this, the interference of SM in measuring SOC could therefore be prevented. Here are presented results from soil compositional tests carried out within the frame of the ProbeField Project https://ejpsoil.eu/soilresearch/ probefield, granted by the EJP-Soil program, focused on proximal sensing techniques for SOC measurement. Di¿erent approaches for 6, 5, 4, 3, and 2 soil parts were assessed. The soil components considered were SOM, SM, soil inorganic carbon (SIOC), the textural fractions of clay (C) and silt (S), and the sand content which was considered in all the approaches together the rest of soil mass (R). The preliminary results provided correlation coefficients between SOC predictions and the corresponding reference values oscillating from r = 0.71 to r = 0.86. Therefore, this method to estimate SOC could be satisfactory. More research is ongoing to verify this approach within the frame of the ProbeField Project.