Terroir 2004 banner
IVES 9 IVES Conference Series 9 “Zonation”: interpretation and estimation of “Great zonation” (GZ) following the base methodology of “GRANDE FILIERA” (GF) (Great chain)

“Zonation”: interpretation and estimation of “Great zonation” (GZ) following the base methodology of “GRANDE FILIERA” (GF) (Great chain)

Abstract

[English version below]

Dans des travaux précédents sur le zonage, on a traité de la « Grande Filière », du « terroir », du « territoire », de la «″Terra »″ (« Terre »”), des « Petits zonages ou sub-zonages », du « Grand Zonage », de la qualité (nous en avons classifié plus de quatre-vingt-dix), des « Grands Objectifs » (GO) de l’activité vitivinicole et des moyens utilisés pour les atteindre. Dans le « GRAND ZONAGE » (GZ) nous avons précisé que pour zoner, nous partons des aspects économiques, sociaux et existentiels que représentent du bas vers le haut en filière les « GRANDS OBJECTIFS » (GO) de l’activité vitinicole et donc du zonage et non pas des aspects « techniques » tels que par exemple le sol, le climat, le modèle de vignoble et sa gestion, etc., qui représentent les « MOYENS » pour atteindre les grands objectifs cités ci-dessus (Cargnello G. 1995, 1997, 1999a-b-c-d, 200a-b et 2003a-c-d). Il faut donc souligner que les « grands objectifs » ne doivent pas être confondus, comme c’est souvent le cas dans notre secteur, avec les moyens utilisés pour atteindre ces objectifs. « Zoner » (« Grand Zonage ») en incluant aussi la lecture et l’évaluation de ce zonage, objet de ce travail, en suivant la méthodologie de base de la « GRANDE FILIERE » (GF) signifie donc, entre autre, opérer aussi bien dans la « globalité », de façon équo soutenable solidaire au niveau temps, économique et social et réalistiquement « qualitatif », aussi bien en syntonie (au mieux) avec les 54 descripteurs d’ordre technique économique social existentiel prévus dans la « Grande Filière ».
On exposera dans ce travail la lecture et l’évaluation du zonage d’après ce qui a été exposé ci-dessus. Lecture et évaluation qui à la suite des recherches conduites à l’étranger aussi a suscité un vif intérêt et nous a encouragé à intensifier ces recherches.

In previous papers on zonation we investigated: so called “GRANDE FILIERA” (GF) (“Great chain”), “terroir”, “Terra”, “Small zonations or sub-zonations”, “Great zonation”, qualities (we have classified more than ninety), economy of qualities, as well as “GREAT OBJECTIVES” (GO) of vitivinicultural activity and means utilised for its achievement.
In “GREAT ZONATION” (GZ) we have specified that in order to zonate, it is necessary to start from economic, social and existential aspects which in filiera from below to above represent “GREAT OBJECTIVES” (GO) also of vitivinicultural activity and thus of zonation, and not from “technical” aspects such as soil, climate, vineyard model and its management, etc. which represent “MEANS” for achievements of “great objectives” above mentioned (Cargnello G., 1995, 1997, 1999a-b-c-d-, 2000a-b and 2003a-c-d).
Must be therefore said again that “great objectives” shouldn’t be messed-up, as frequently happens in our branch, with means utilised for achievement of such objectives.
Consequently “Zonating” (“Great Zonation”) comprised between interpretation and estimation of zonation, following the base methodology of “Great Chain” means, among other things, to operate in “globality” and in sustainable equal mode on tempistic, economic-social and realistically “qualitative” level, also in harmony (the best) with listed descriptors.
In the present paper, zonation interpretation and estimation will be treated as explained above. Type of interpretation and estimation that after researches conducted by foreign researches have risen in importance and have stimulated us to intensify our investigations in that sense.

DOI:

Publication date: January 12, 2022

Issue: Terroir 2004

Type: Article

Authors

Giovanni Cargnello (Collaboration de Luciano Pezza)

Directeur SOC Tecniche Colturali – Istituto Sperimentale per la Viticoltura – Via E. De Nicola, 41 – 31015 Conegliano (TV) Italy

Contact the author

Keywords

Zonage, grand zonage, petit zonage vitivinicole, terre, territoire, terroir, qualité, grande filière
zoning, great zonation, little zonation, interpretation, estimation, quality, land, great chain

Tags

IVES Conference Series | Terroir 2004

Citation

Related articles…

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Is wine terroir a valid concept under a changing climate?

The OIV[i] defines terroir as a concept referring to an area in which collective knowledge of the interactions between the physical and biological environment (soil, topography, climate, landscape characteristics and biodiversity features) and vitivinicultural practices develops, providing distinctive wine characteristics. Those are perceptible in the taste of wine, which drives consumer preference and, therefore, wine’s value in the marketplace. Geographical indications (GI) are recognized regulatory constructs formalizing and protecting the nexus between wine taste and the terroir generating it. Despite considering updates, GIs do not consider the nexus as a dynamic one and do not anticipate change, namely of climate. Being climate a fundamental feature of terroir, it strongly impacts wine characteristics, such as taste. According to IPCC[ii], many widespread, rapid and unprecedented changes of climate occurred, some being irreversible over hundreds to thousands of years. Climatic shifts and atmospheric-driven extreme events have been widely reported worldwide. Recent climatic trends are projected to strengthen in upcoming decades, whereas extremes are expected to increase in frequency and intensity, forcing wines away from GI definitions. Geographical shifts of viticultural suitability are projected, often moving into regions and countries different from current ones. Some authors propose adaptation in viticulture, winemaking and product innovation. We show evidence of climate changing wine characteristics in the Douro valley, home of 270-year-old Port GI. We discuss herein resist or adapt stances for when climate changes the nexus between terroir and wine characteristics. Using the MED-GOLD[iii] dashboard, a tool allowing for easy visual navigation of past and future climates, we demonstrate how policymakers can identify future moments, throughout the 21st century under different emission scenarios, when GI specifications will likely need updates (e.g., boundaries, varieties) to reduce climate-change impacts.

Mapping and tracking canopy size with VitiCanopy

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

Characterization of variety-specific changes in bulk stomatal conductance in response to changes in atmospheric demand and drought stress

In wine growing regions around the world, climate change has the potential to affect vine transpiration and overall vineyard water use due to related changes in atmospheric demand and soil water deficits. Grapevines control their transpiration in response to a changing environment by regulating conductance of water through the soil-plant-atmosphere continuum. Most vineyard water use models currently estimate vine transpiration by applying generic crop coefficients to estimates of reference evapotranspiration, but this does not account for changes in vine conductance associated with water stress, nor differences thought to exist between varieties. The response of bulk stomatal conductance to daily weather variability and seasonal drought stress was studied on Cabernet-Sauvignon, Merlot, Tempranillo, Ugni blanc, and Semillon vines in a non-irrigated vineyard in Bordeaux France. Whole vine sap flow, temperature and humidity in the vine canopy, and net radiation absorbed by the vine canopy were measured on 15-minute intervals from early July through mid-September 2020, together with periodic measurement of leaf area, canopy porosity, and predawn leaf water potential. From this data, bulk stomatal conductance was calculated on 15-minute intervals, and multiple regression analysis was performed to identify key variables and their relative effect on conductance. Attention was focused on addressing multicollinearity and time-dependency in the explanatory variables and developing regression models that were readily interpretable. Variability of vapor pressure deficit over the day, and predawn water potential over the season explained much of the variability in conductance, with relative differences in response coefficients observed across the five varieties. By characterizing this conductance response, the dynamics of vine transpiration can be better parameterized in vineyard water use modeling of current and future climate scenarios.