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ApeX-Vigne: experiences in monitoring vine water status from within-field to regional scales using crowdsourcing data from a free mobile phone application.
- Source :
-
Precision Agriculture . Apr2021, Vol. 22 Issue 2, p608-626. 19p. - Publication Year :
- 2021
-
Abstract
- Monitoring vine water status is a major issue for vineyard management because water constraints impact both the quality and the quantity of the harvest. Existing methods are often costly and complex to implement. ApeX-Vigne is a free mobile application developed to facilitate the collection and geolocation of 50 vine apex observations to characterise vine shoot growth and classify it into 3 growth categories. The application also provides the user with a simple estimate of vine water status based on shoot growth. This paper presents the results obtained over two seasons (2019 and 2020) after the launch of the Apex-Vigne application and its use over a large wine producing region in the south of France. An existing method was adapted for evaluating the interest of the application based on the number of installations and uninstallations. The results showed that the application had more than 1200 downloads and 6000 observations made in the 2020 season. Examples from the commercially collected data showed that ApeX-Vigne can be used as a tool for characterizing water stress at within-field and inter-field scales. Finally, it was also demonstrated that by enabling the massive and centralized collection of spatial field and within-field scale observations of shoot growth, the ApeX-Vigne data was able to characterise the spatial structure of vine water status at the regional scale. Access to this new source of information offers opportunities for the management of water resources at a regional scale as well as for site- and vineyard-specific management. These results also raised new research questions on the joint use of this new source of spatial data with other sources of high spatial resolution information. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13852256
- Volume :
- 22
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Precision Agriculture
- Publication Type :
- Academic Journal
- Accession number :
- 149762437
- Full Text :
- https://doi.org/10.1007/s11119-021-09797-9