Data belonging with MSc thesis "Capturing soil health variability in Mediterranean olive orchards: an integrated sensing-based approach"

Dataset

Description

Understanding variability of soil parameters at field level is key to develop adaptive management plans for land managers and enhance soil health and functioning.
This is particularly difficult in Mediterranean olive orchards, where heterogeneity is driven both by landscape factors and row-interrow differences which create variations in microclimate and management. This study investigates the within-field variability of key soil health indicators (pH, Soil Organic Matter (SOM), Cation Exchange Capacity (CEC), biomass of key microbial groups and fungi:bacteria ratio) across two contrasting olive orchard systems (extensive and intensive).
Linear Mixed Effects Models (LMEM) were employed to analyse the contributions of topographical and management (row-interrow) factors to soil variability.
Mid-infrared (MIR) spectroscopy was also evaluated as tool to integrate traditional lab measurements in the assessment of variability of soil chemical and biological indicators and integrated it with a European-wide spectr
Date made available2024
PublisherWageningen University
Date of data production2024
Geographical coverageSouthern Europe

Keywords

  • Soil health indicator
  • Spatial soil information
  • Spatial variability

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