Integration of Soil Electrical Conductivity and Indices Obtained through Satellite Imagery for Differential Management of Pasture Fertilization

Abstract

Dryland pastures in the Alentejo region, located in the south of Portugal, normally occupy soils that have low fertility but, simultaneously, important spatial variability. Rational application of fertilizers requires knowledge of spatial variability of soil characteristics and crop response, which reinforces the interest of technologies that facilitates the identification of homogeneous management zones (HMZ). In this work, a pasture field of about 25 ha, integrated in the Montado mixed ecosystem (agro-silvo-pastoral), was monitored. Surveys of apparent soil electrical conductivity (ECa) were carried out in November 2017 and October 2018 with a Veris 2000 XA contact sensor. A total of 24 sampling points (30 × 30 m) were established in tree-free zones to allow readings of normalized difference vegetation index (NDVI) and normalized difference water index (NDWI). Historical time series of these indices were obtained from satellite imagery (Sentinel-2) in winter and spring 2017 and 2018. Three zones with different potential productivity were defined based on the results obtained in terms of spatial variability and temporal stability of the measured parameters. These are the basis for the elaboration of differentiated prescription maps of fertilizers with variable application rate technology, taking into account the variability of soil characteristics and pasture development, contributing to the sustainability of this ecosystem.

Remote and Proximal Sensing Techniques for Site-Specific Irrigation Management in the Olive Orchard

“…Cluster analysis of maps obtained both by soil survey, such as proximal soil sensing, and by plant water status, such as NDVI, allowed to identify functional homogeneous zones (fHZs), corresponding to areas where soil and plant performance showed limited variability [37,38]. Soil and crop indices have been mainly tested in vineyards in experiments focused on zoning and precision irrigation management [19,[38][39][40][41][42] while few studies have been conducted in orchards [43][44][45]. To our knowledge, there is only one study in which the use of proximal and remote sensing techniques was used to separate management zones within an irrigated olive orchard [46].…”

Improved Soil Moisture and Electrical Conductivity Prediction of Citrus Orchards Based on IoT Using Deep Bidirectional LSTM

“…It can be seen that the prediction performance of the two models on SEC was not as good as that of SM because of the lower SM and SEC. SEC is a complex factor [46] affected by soil nutrients, salinity, soil fertilization, organic matter content, and other parameters [47]. Figures 14 and 16 show that the five nodes of orchard SEC were mainly in the range of (6, 60) μS•cm −1 .…”

Climate Changes Challenges to the Management of Mediterranean Montado Ecosystem: Perspectives for Use of Precision Agriculture Technologies

“…Over the next years, variable-rate application of inputs will be carried out, decreasing fertilization in the less productive areas (low EC a ) and minimizing the application of chemical substances as a strategy to develop a more cost-effective field management, including less use of agricultural machinery [44]. A recent example of these applications was presented by Serrano et al [20], with an integrated approach using spatial variability and temporal stability of EC a and indices obtained by remote sensing to delineate management zones with differential fertilizer prescription.…”