Context and objectives
Sugarbeet field phenotyping with high accuracy and reliability for assessment of resistant sugarbeet to biotic stresses is required but lacking. The small dimensions of breeding trial plots and the need for frequent revisits hamper the use of airborne images, especially with UAVs, able to deliver assessments at a very high spatial resolution pixel size with a very flexible temporal resolution. High-resolution hyperspectral remote sensing imagery is described to be appropriate to produce optical indices related to the crops health status. This project aims at applying the UAVs potential for the quantitative assessment of a specific plant trait (disease resistance against Powdery Mildew ‘PM’) within breeding trial plots.
Expected scientific results
Evaluation of different sensors and platforms combinations and selection of the most suitable one for PM detection and quantification. Development of a data acquisition and processing methodology for the assessment of the resistance to PM for sugar beet breeding trials using UAV imaging, and validation of the produced algorithm.
Expected products and services
This project is expected to deliver a rapid operator-independent tool to assess in a standardized way diseases at the breeding trial plot level.
Breeding companies and institutions. Companies involved in fungicide treatment screening (at field level) or in disease/fungicide application forecast. Agricultural research centres, crop phenotyping companies, agricultural UAV companies, agricultural remote sensing sector, agricultural sensor and robotics companies.