AgroICT & Precision Agriculture
The overall aim of the research group is to develop a competitive leading research in the field of equipment development to increase the productive efficiency and reduce the environmental impact in the field of agriculture. For this purpose, we take part of research projects at the National and International levels and we do also have projects with the industry. Researchers come from various fields and two institutions, so that knowledge and application areas covered are complementary. Researchers at the University of Lleida provide knowledge related to the application of sensors in agriculture, data acquisition and interpretation, using geostatistical analysis models, the automation and the development of variable rate technologies in agricultural machinery, implementation of GPS systems, and modelling and designing systems to support decision making. Researchers from the Centre for Agricultural Mechanization provide knowledge related to the application of pesticides in fruit and field crops and established a relationship with agribusiness equipment and machinery. This composition facilitates the multidisciplinary approach needed for research and development of new technologies in agriculture. Some of the specific research activities developed during the reporting year included
– Electronic characterization of vegetation (phenotyping): geometry and structure of tree crops; detection and classification of weeds; developing of new sensing systems.
– Geostatistical analysis and mapping of variables at a field level: spatial analysis of agricultural data; measurements and mapping of soil ECa; yield mapping in vineyards and tree crops; remote sensing and analysis of spatial variability of yield and quality parameters; leaf area index mapping by using terrestrial laser scanners; pest spatial distribution mapping for control and management.
– Dose adjustment and decision support system on plant protection products application.
– Drift detection of plant protection products by means of LIDAR sensors and ISO classical methods. – Development of autonomous vehicles for field sampling.