MUSELY

Development of a MUlti-SEnsor remote sensing approach from drone to earLY detect plant diseases: A tool for sustainable agriculture and food security.

The project MUSELY aims at integrating imaging spectroscopy, Solar-Induced Fluorescence (SIF), thermal-infrared (TIR) and LiDAR remote sensing (RS) to develop novel multi-sensor methods to identify and quantify plant diseases. MUSELY will focus on Fusarium Head Blight of wheat and Fusarium wilt of Tomato, i.e., two major plant diseases characterized by different pathogenic mechanisms and symptoms. MUSELY approaches the study by means of a small–scale controlled experiment and multi-sensor RS observations from Unmanned Airborne Vehicles (UAV). The RS measurements are complemented by leaf level hyperspectral measurements (to disentangle the leaf-canopy radiation transport) and by key physiological measurements. Two field experiments (one for each plant disease) will be run in the first year of MUSELY, and repeated in the second one, in order to develop novel RS approaches in plots where are grown cultivars with different disease susceptibility, subjected to different pathogen infections and treatments with conventional agrochemical and bio-control agents. Remote sensing spectral measurements will be collected at different spatial and temporal scales, to combine continuous ground-based hyperspectral and SIF data (temporal monitoring, every 5 min) with UAV-based RS imagery collected routinely over the entire experimental field.