The main objective of this project is to combine high spatio-temporal resolution remote sensing with state-of-the-art crop microbiome analysis and machine learning models to improve or reinforce some of our current procedures and create a predictive model of soil resilience to climate change impacts and management intensity in agricultural soils. To achieve this, the following specific objectives have been defined:

1. To develop a predictive model of soil resilience and soil health based on the characterization of the influence of environmental conditions and agricultural management intensity on soil abiotic properties and the structure, composition, diversity and functionality of the soil microbiome.

2. To develop a system of crop soil microbiome sampling strategies using high-resolution remote sensing techniques.

3. To understand the real effect of the presence of pathogenic microorganisms on crop productivity and design a pest risk mapping system combining remote sensing, microbiome sequencing, and Artificial Intelligence techniques.