Objectives
To obtain good wines it is necessary to produce grapes of a uniform quality. This greatly determines wine growers` profit, and thus it is very important for them to assess the optimal grape ripening state and the vine development state along the season. Current methods are based on visual assessment or testing randomly sampled grapes. There are more accurate ways, such as using remote sensing data from satellites or drones; however, they do not provide sufficient resolution to evaluate the ripening and development state at plant level. Sensors can be mounted on robots which can scout the vineyard and collect data very close to the plant, improving their resolution. The Vinescout robot is being developed to provide accurate information to wine growers so that they can take better decisions on how to manage their vineyard, so as to obtain a better quality product and make an optimal use of inputs.
Objectives
N/A
Additional information
Wine is a very important product in the European agricultural sector. To obtain good wines with high added value, it is essential to harvest grapes with a uniform, high quality. In order to achieve this, the vines need to be monitored to assess the optimal growth and ripening state for harvesting. So far, the available monitoring methods were visual observation or random sampling of individual grapes. These methods do not provide completely reliable information on the crop. There are more accurate methods such as using multispectral sensors mounted on drones or airplanes. However, the low resolutions of the data obtained in this way limits their usefulness for wine growers.
The vinescout robot is the evolution of Vinerobot which was created to tackle the aforementioned problems. As the robot collects the data in the field, It provides higher resolution images taken at less than one meter from which more accurate information can be gathered. The robot scouts the vineyard and takes data autonomously. It is equipped with a GPS, a camera and sensors which take canopy temperature and geo-referenced multispectral information of the vines. The data are processed by an onboard computer which produces mapas on canopy temperatura and growth state by computing various indices. These data are transferred to the wine grower who can constantly monitor the needs and status of the vineyard and take decisions on the best moment to irrigate, apply treatments or harvest the grapes. Vinescout runs on electrical power drawn from lithium batteries and solar panels, which increase its autonomy and make it energy efficient.
Project details
- Main funding source
- Horizon 2020 (EU Research and Innovation Programme)
- Project acronym
- VINESCOUT
- Agricultural sectors
- Viticulture
€ 2 125 081,25
Total budget
Total contributions including EU funding.
€ 1 741 225,63
EU contribution
Any type of EU funding.
Contacts
Project coordinator
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Universitat Politecnica de Valencia
Project coordinator
Project partners
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Universidad de La Rioja
Project partner
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SUNDANCE MULTIPROCESSOR TECHNOLOGY LTD
Project partner
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WALL-YE SARL
Project partner
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SYMINGTON - VINHOS SA
Project partner