Centre for Sensors, Instruments and Systems Development

Universitat Politècnica de Catalunya

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07/28/2020
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Automatic Hyperspectral Pest Counter

Agriculture in the 21st century faces multiple challenges: it has to produce more food to feed a growing population with a smaller rural labour force, adopt more efficient and sustainable production methods and adapt to climate change. In particular, preventing the development of pests in crops is an essential and difficult task in agricultural production, even more since the last EU regulations that aim to achieve a sustainable use of pesticides by reducing their impact on human health and the environment through alternative non-chemical approaches. Precision agriculture, which is nothing more than the consequence of the landing of new technologies in agriculture, promotes the use of sensors that allow georeferenced data acquisition, processing and conversion into information useful for decision making. Nevertheless, most of the current pest control systems are based on periodic manual readings and counts of traps spread over the crops, which are adhesive sheets that often include pheromones to attract certain species of insects.

The development of the AUTOMATIC HYPERSPECTRAL PEST COUNTER will promote an automated, environmental friendly strategy based on photonics that permits the farmer to get the maximum performance against plagues involving miniature insects with the maximum protection and lack of residue. The new system will permit to obtain images of georeferenced traps, and provide close to real-time counts of pest occurrences in near real time. The system will discriminate the type of insect on the basis of its features, and efficient algorithms based on machine learning to process huge amounts of data collected will also be used. The system will be firstly optimized for the detection of red scales that affect citrus crops, sector in which Spain reports 25% approximately of the total of the production of the European Union.

The project harvests on previous projects for the application described, and has the explicit support of companies and clusters in the agricultural sector.

This project has been funded with the support of the Secretariat of Universities and Research of the Department of Enterprise and Knowledge of the Generalitat de Catalunya and has also been co-financed by the European Union through the European Regional Development Fund (ERDF).
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