Terroir 2006 banner
IVES 9 IVES Conference Series 9 New technologies to characterize spatial variability in viticulture

New technologies to characterize spatial variability in viticulture

Abstract

Measurements of parameters spatialy positionned, with on line sensors mounted on classical machinery or airborne imagery is no more a problem in viticulture. In a short time, high resolution data dedicated to the assessment of the vine characteristics, the soil, the harvest, etc. will become a reality. This information sources will allow the wine grower to have a spatial accurate knowledge of the vineyard and its variability. Such an accuracy in monitoring the production system was never achieved until now. This paper makes a brief overview of the tools and methods already released or under development to assess the vineyard variability of the main parameters. This work makes also an overview of the main references in vineyard variability. It presents the main results observed on yield, sugar, TTA, etc. within field variability. For each of these parameters clues on magnitude of variation and coefficient of variation observed at a within field scale are given. Assessing the within field variability can lead the wine grower to take advantage of this variability by adopting site specific management practices. In that case, information of the spatial structure of the variation is of importance since it gives an idea of how a site specific management is opportune on each field. This work will present the main results obtained in spatial structure assessment in viticulture (focusing on yield). Finally, one of the keypoint in viticulture is the assessment of the plant water restriction and its variability whether over the time or over the space. This work presents main experimental results dedicated to the assessment of the within field variability of the plant water status and its link with harvest quality.

DOI:

Publication date: January 11, 2022

Issue: Terroir 2006

Type: Article

Authors

B. TISSEYRE (1), J. TAYLOR (2) and OJEDA H. (3)

(1) UMR Itap, ENSA. Montpellier, bât. 21, 2 place Viala, 34060 Montpellier, France
(2) Australian Centre for Precision Agriculture, University of Sydney, Australia
(3) UMR SPO, INRA,station expérimentale de Pech Rouge, 11000 Gruissan, France

Contact the author

Keywords

grapevine, spatial variability, precision viticulture, temporal stability, water restriction

Tags

IVES Conference Series | Terroir 2006

Citation

Related articles…

Can the satellite image resolution be improved to support precision agriculture in the vineyard through vegetation indices?

Aim: This study aims to show the application of a new methodological approach to improve the resolution of Sentinel-2A images and derived vegetation indices through the results from different vineyards. 

Evolution of chemical pattern related to Valpolicella aroma ‘terroir’ during bottle aging

Valpolicella is a famous Italian wine-producing region. Wines produced in its different sub-regions are believed to be aromatically different, as confirmed by recent studies in our laboratory. Aging is a very common practice in Valpolicella and it is required by the appellation regulation for periods up to four years require wines. The aim of this study was to investigate the evolution, during aging, of volatile chemical composition of Valpolicella wines obtained from grapes harvested in different sub-regions during different vintages.

Potential deacidifying role of a commercial chitosan: impact on pH, titratable acidity, and organic acids in model solutions and white wine

Chitin is the main structural component of a large number of organisms (i.e., mollusks, insects, crustaceans, fungi, algae), and marine invertebrates including crabs and shrimps.

Strategies for sample preparation and data handling in GC-MS wine applications

It is often said that wine is a complex matrix and the chemical analysis of wine with the thousands of compounds detected and often measured is proof. New technologies can assist not only in separating and identifying wine compounds, but also in providing information about the sample as a whole. Information-rich techniques can offer a fingerprint of a sample (untargeted analysis), a comprehensive view of its chemical composition. Applying statistical analysis directly to the raw data can significantly reduce the number of compounds to be identified to the ones relevant to a particular scientific question. More data can equal more information, but also more noise for the subsequent statistical handling.