CORDIS - EU research results

Low-cost multispectral camera for Precision Farming Application

Project description

Multispectral camera takes small-scale farms into the digital age

Small-scale farms, which make up two thirds of EU agriculture, need to adopt digital technology to carry out more efficient and resource-friendly sustainable practices. However, the current uptake of this technology is relatively low, mainly due to the high initial cost of the necessary equipment. The EU-funded MCAPEFA project will enable small farms to access digital technology by developing a low-cost multispectral camera that can be mounted on a drone, allowing several farms to be monitored during a single growing season. The data acquired will be used to classify the condition of plants, and a designed decision support system will suggest appropriate agricultural activity in the field. Hence, MCAPEFA will help provide infrastructure for the wider adoption of precision farming to maximise quality and yields.


The main goal of this proposal is improving the adoption of precision farming in small farms. Small farms share 67% of all farms in the EU, and small farmers need to adopt digital technology to get efficient and resource-friendly sustainable farming. Unfortunately, adoption of that technology is relatively low, especially with small filed sizes, due to large initial cost of necessary equipment. This research will overcome the financial barrier with the development of a new low-cost multispectral camera. The main hypothesis is that, contrary to the common commercial solution, the multispectral camera can be achieved using combinations of camera's spectral response and spectral response of the triple-band filter. This idea is a new approach to multispectral imaging. Designed low-cost multispectral camera together will thermal imaginer will be mounted on a drone and a few farms will be monitored during one agricultural season. Acquired data will be the basis for developing an algorithm for classifying the state of the plants. After classification, a designed decision support system will
suggest appropriate agricultural activity in the field. All previous results will be unified in smartphone applications with a friendly user interface. This research will provide infrastructure for wider adoption of precision farming, which is crucial for maximizing production and quality, the efficiency of nitrogen use and minimizing environmental pollution, especially due to nitrate contamination of drinking water and aquatic ecosystems.


Net EU contribution
€ 183 473,28
38122 Trento

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Nord-Est Provincia Autonoma di Trento Trento
Activity type
Higher or Secondary Education Establishments
Total cost
€ 183 473,28