Precision agriculture, the new agricultural techniques, promote the use of sensors to capture, process and convert georeferenced data into useful information for decision-making. One EU target is to achieve sustainable use of pesticides by reducing their impact on human health and the environment through non-chemical alternatives.
The aim of the project is to design and construct a preindustrial prototype with the development of algorithms based on hyperspectral models and machine learning to adapt the algorithm to the recognition of other small insects that affect (citric) fruit crops, such as red scale (Aonidiella Aurantii), the most harmful pest for citric fruits.
The new system can be used to obtain images of georeferenced traps and provide automatic counts of the development of infestations in almost real-time. It identifies the type of insect associated with the infestation, based on its properties. The system will help the farmer to respond in the best way to infestations that involve very small insects, with maximum protection and zero waste.
This project is supported by companies and clusters in the agricultural sector and has been cofunded by the European Union through the European Regional Development Funds (ERDF). It is supported by the Secretariat for Universities and Research of the Government of Catalonia’s Ministry of Business and Knowledge.