Precision viticulture
Drones, satellite images, sensors...
L'precision agriculture can be defined as"all the strategies, practices and equipment that use electronic information systems or other technologies to collect, process and analyse spatio-temporal data in order to improve the sustainability, efficiency and productivity of farms".[1].
This portal describes the actual and potential applications of these technologies to viticulture.
Data acquisition
Precisionviticulture is a discipline that has been developing in France since 2000.[2]Its aim is to optimise the operation of a farm by analysing a large amount of data. This data can be of different kinds, and collected from various devices :
Types of data and applications to viticulture
- Stages of plant development : all the sensors used to complement human observations and analyses of plant material. These include monitoring vigour, leaf area, flowering, berry sugar levels, sap flow, number of shoots and their nutrient content (etc.) using various devices.
- Pathogen alerts : some technologies aim to detect sources of contamination by cryptogams(mildew, powdery mildew, botrytis, etc.) or wood diseases at plot level. Or on a larger scale, for example modelling the movement of leafhopper populations responsible for flavescence dorée.
- Meteorological data : this is the type of data for which there are currently the most technologies available, either for recording weather conditions at plot level (humidity, temperature, anemometry, rainfall, etc.), or for estimating future trends on a larger scale and thus planning interventions.
Sensor support and types of acquisition
All these data are collected from different sensors, and can be classified into two categories[2] :
Remote sensing
Remote sensing consists of recovering data, as listed above, from a distance, generally by satellite or aerial (UAV) observation. Today, it is mainly used to provide an image at a given moment of the state of the vineyard (weather, pathogens, plants). This aerial image is the result of a large aggregation of data, and generally takes the form of a graph called NDVI (Normalized Difference Vegetation Index).
Proxy-detection
Proxy-detection, on the other hand, covers all the data acquisition devices operating within the plot. These can be fixed, such as weather platforms or sap flow sensors, or removable and 'mounted' on a tractor/straddle to scan the entire plot.
Automation of operations
Precision farming (and its application to winegrowing) is a fast-developing discipline, and a number of projects are being launched toacquire data andautomate operations.
These include robotic mowers, self-guided straddle carriers, drone spraying in non-mechanisable plots, spray adjusters, etc. [3][4]
To find out more
Read the report on the Vitinnov technical day at Bordeaux Science Agro, Viticulture de précision : les capteurs à la loupe. Click here.
Articles dans cette thématique
References
- ↑ Lowenberg-DeBoer, J.M. and Erickson, B., Agronomy journal, Setting the record straight on precision agriculture adoption, 2019. https://hau.repository.guildhe.ac.uk/id/eprint/17408/
- ↑ 2.0 2.1 Saias F., Generation winemakers, precision viticulture : fiction ? 2018. https://generationvignerons.com/viticulture-de-precision-fiction-ou-realite/?cn-reloaded=1
- ↑ Loriette J., AgroTIC, La viticulture de précision : état des lieux et outils d'avenir, 2019. https://www.agrotic.org/veille/la-viticulture-de-precision-etat-des-lieux-et-outils-davenir/
- ↑ IFV Occitanie, Viticulture de recision : nos recherches, https://www.vignevin-occitanie.com/nos-recherches-2/viticulture-de-precision/
