Suchergebnisse

The salinity tolerance of plants can be improved by efficient irrigation management and salt flushing, which require a continuous and precise knowledge of the salinity in the soil or substrate. Soil sensors that measure electrical conductivity play an essential role in monitoring soil salinity. However, the correct interpretation of salinity measurements using soil sensors depends on developing appropriate salinity indexes. This work studied the potential of several salinity indexes based on the bulk EC (ECb) directly measured by soil sensors, and on pore water EC (ECw) estimated by the Hilhorst model (ECwHI). The methodology used in the experiments is based on the simultaneous use of scales and sensors, which allowed the automatic monitoring of the real salinity levels of the substrate, and the conductivity measurements made with the soil sensor. Regression studies were carried out to know how well the proposed salinity indexes explain real salinity. In general, all the indexes were suitable for estimating the relative changes in substrate salinity, as long as they met certain requirements. For example, ECwHI was seen to be a reliable salinity index when substrate moisture was high and constant. However, there was no such requirement when the ECwHI was corrected according to the current substrate water content, or when the salinity index was calculated as the average of the ECwHI values between two successive irrigation events. ECb was an efficient salinity indicator as long as the moisture content was constant, although its accuracy increased at a high moisture level. The findings led us to propose a new salinity index calculated with the slopes of the linear section of the quadratic moisture adjustment, which avoids the need for the substrate moisture content to be constant. ; This research was funded by the Ministry of Science, Innovation, and Universities of Spain, and the European Regional Development Fund, grant number RTI2018-093997-B-I00, and by the Spanish AEI (grant number PCI 2019-103608) under the PRIMA programme in the frame of the PRECIMED project. PRIMA is an Art.185 initiative supported and co-funded under Horizon 2020, the European Union's Programme for Research and Innovation