According to United Nations [1] the worldwide population is expected to reach 11 billion people by the end of the century. Such a forecast sets an unprecedented demand for, among others, food and water resources. The food demand, for at least a few decades ahead, is expected to be fulfilled by agriculture that is currently (and so will be for a while) the world’s largest food industry. Agriculture, as it is now, enormously impacts the planet resources and life as it relies on chemical pesticides and fertilizers to maintain the crops fields. The chemical compounds in pesticides and fertilizers contaminate water, soil and water, contribute to lose biodiversity and, on a not-so-long-term can lead to pest resistance. Not to mention the impact of such compounds on human health.
On the other hand, the (unnecessarily) massive use of pesticides and fertilizers is often adopted to make agriculture financially sustainable for farmers. Precision farming technologies can contribute to balance environmental and financial sustainability in agriculture. Precision farming is a farm management approach that builds the decision-making process (e.g., watering, pesticides spraying and fertilizers application) upon observations (from on-field measurements) and a crop knowledge-base. Such technologies can effectively contribute to decrease the use of polluting pesticides and fertilizers and minimized the amount of used water.
The objective of this project is to harness the capabilities of autonomous systems to monitor crops fields and either decide, or alternatively provide support to farmers’ decision, of, for example, spraying pesticides or water specific crop areas, selectively applying fertilizers thus avoiding massive use of polluting compounds. The project will adopt a combination of ground and aerial robots to collect information from the crop field ranging from parasites footprints, crop stress status from imaging spectroscopy [2]. The project results will be validated in an experimental farm by using mobile ground robots and aerial drones.
Apply at http://dausy.poliba.it/phd/application/
Contact: falcone at unimore.it
[1] United Nations Population Fund, “State of World Population 2024”, April 2024, DOI: https://doi.org/10.18356/9789213589526
[2] Gerrit Polder, J. Anja Dieleman, Selwin Hageraats, Esther Meinen, “Imaging spectroscopy for monitoring the crop status of tomato plants”, Computers and Electronics in Agriculture, 2024, https://doi.org/10.1016/j.compag.2023.108504.
