IXe Congrès International des Terroirs vitivinicoles 2012 / IXe International Terroirs Congress 2012
entre Damery et Rueil. Rapport destiné au Comité
Interprofessionnel du Vin de Champagne (CIVC),
1993, 23 p.
6. F. SIMON, 2000. Les glissements de terrain
affectant le versant nord de la vallée de la Marne entre
Ambonnay et Barzy : synthèse. Mémoire de DEA,
Géographie, Université de Reims Champagne-Ardenne
et Université des Sciences et Technologies de Lille,
262 p.
7. P. LAVILLE, D. RAMBAUD, avec la collaboration
de J.N. HATRIVAL, P. MORFAUX, J.C. PINTE,
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Rapport destiné au Comité Interprofessionnel du Vin
de Champagne (CIVC), BRGM/RR-36789 CHA 4S
93, 55 p.
8. N. BOLLOT, 2010. Étude de la circulation de l’eau
dans les glissements de terrain : exemple du secteur de
Montchenot (Marne–France), mémoire du Master
DDMNA, Géographie, Université de Reims
Champagne-Ardenne, 134 p.
Soil-plant water status and wine quality:
an physically based approach to terroir analysis
Antonello BONFANTE1,*, Rossella ALBRIZIO1, Angelo BASILE1, Roberta BUONOMO1,
Roberto DE MASCELLIS1, Arturo ERBAGGIO2, Angelita GAMBUTI2, Pasquale GIORIO1,
Gianpiero GUIDA1, Caterina IANNINI3, Piero MANNA4, Luigi MOIO2, Fabio TERRIBILE4
1
National Research Council of Italy (CNR) – Institute for Mediterranean Agricultural and Forestry Systems (ISAFOM),
Ercolano (NA), Italy
2
University of Naples Federico II – Department of food science, Portici (NA), Italy
3
Department S.T.A.A.M. University of Molise
4
University of Naples Federico II, Department of Soil, Plant, Environment and Animal Production Sciences, Portici
(NA), Italy
* Corresp. author : Bonfante, Telephone +390817717325, Fax +390817718045, Email : [email protected]
ABSTRACT
The ZOViSA Project (Viticultural zoning at farm scale) tests a new physically oriented approach to terroir analysis,
strongly rooted on hydropedology and aiming to achieve a better use of environmental features with respect to plant
requirement and wine production. The physics of our approach is defined by the use of soil-plant-atmosphere simulation
models which apply physically-based equations to describe the soil hydrological processes and solve soil-plant water
status.
The project is conducted in two farms of southern Italy (Del Monte-Ponte(BN) and Quintodecimo-Mirabella Eclano
(AV)) located in the Campania region and devoted to quality wines production (Aglianico and Falanghina DOC). In
one site (Quintodecimo farm) the soil spatial distribution was recognized; then the soil-plant water status was monitored
in two experimental plots from two different soils. Daily soil water variables (through TDR probes and tensiometers),
crop development (biometric and physiological parameters) and daily climate variables (temperature, solar radiation,
rainfall, wind) were monitored.
The SWAP model was calibrated and applied in the two experimental plots to estimate soil-plant water status in
different crop phenological stages. The effects of crop water status on crop response and wine quality was evaluated in
two different pedo-systems, comparing the crop water stress index with both: crop physiological measurement (leaf gas
exchange, chlorophyll-a fluorescence, leaf water potential, chlorophyll content, LAI measurement), grape bounches
measurement (berry weight, sugar content, titrable acidity, etc.) and wine quality (aromatic response). Finally a
preliminary "spatial application" of the model was carried out and different terroirs defined.
Keywords: Terroir, SWAP model, CWSI.
1 INTRODUCTION
The concept of terroir is known to be very complex [1].
Basically its implementation [2] aims to classify the
landscape (mainly climate and soil) studying its
interaction with vineyard and wine quality.
This methodology indeed enabled many positive
results, but also showed some important limitations to
be mainly related to its strongly empirical base. In
other words the terroir is a sort of “black box” in which
the quantitative linkage between climate–soil–plant
and wine is empirically described and not analysed in
its mechanics.
Recently some changing are occurring and the spatial
analysis of terroirs has improved incorporating solar
radiation and bioclimatic indexes [3]. Most importantly
Bonfante et al. [4] showed that terroir analysis can be
further profitable integrated combining high quality
GIS with water balance simulation modelling for
addressing the key and very complex feature of soilplant water stress. Despite these positive results a
proper quantification of the connection, at the
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IXe Congrès International des Terroirs vitivinicoles 2012 / IXe International Terroirs Congress 2012
landscape scale, between the key soil landscape
features “plant-soil water stress” and vineyard status
and grape wine quality is still lacking.
In this perspective, the ultimate aim of this paper is
then to prove that the use of a physically based
approach to terroir is very robust and enables to
effectively separate different pedoenvironments on the
base of their water stress. This general aim is
performed by quantifying, at the landscape scale, how
water stress affect plant growth, grape quality and wine
quality. This was done on an experimental landscape
site characterised by soil varying in their ability to
induce differential plant-soil water stress under the
same climatic conditions.
water vapor, leaf water potential, fluorimetric
measurements, leaf area, chlorophyll content).
Chemical and physical analysis of musts (pH, total
acidity, sugars, total polyphenols, color, total
antocians), microvinification and analysis of wines
were also performed.
In particular, the Leaf water potential (LWP) was
measured by the pressure chamber type Scholander
(SAP II Soil moisture equipment, model 3115)
2.4 Crop Water Stress Index (CWSI)
The CWSI is defined as the ratio of Tr/Tp, where Tr is
the daily actual water uptake and Tp is daily potential
transpiration [7]. It was determined applying the
Richards based hydrological simulation model SWAP
[8]. Crop-specific input data and model parameters
comes from both field/lab measurements and literature
data.
2 MATERIALSAND METHODS
The project takes place in two farms localized in
southern Italy, Campania region, namely Del Monte
and Quintodecimo farms, belonging respectively in the
provinces of Benevento and Avellino. The farms are
oriented to the high quality wines production,
principally Falanghina and Aglianico cultivars (AOC).
The present work aims to illustrate the early results
obtained during the first year of activities realized
specifically in the Quintodecimo farm.
2.1 Study Area
The study area is located in the town of Mirabella
Eclano (AV) about 370 meters of altitude. The
vineyard studied (Aglianico cultivar– standard clone
population, planted in the year 2000 on 1103 Paulsen
rootstocks, espalier system,cordon spur pruning, 5000
units per hectare) is placed along a slope of 90 m
length with 11% slope gradient.
2.2 Soil measurements
To evaluate the apparent electrical conductivity has
been used the EM38DD equipment (Geonics Limited).
The depth of investigation was 1.5 m in VDM (Vertical
Dipole Mode) position and 0.75 m for the HDM
(Horizontal Dipole Mode) position.
The soil profiles were described according to Gardin et
al. [5]. Chemical analyseswere performedaccording to
the official methods of the Italian Ministry of
Agriculture and Forestry. The grain size distribuition
(GSD) was determined with a laser granulometer
(Marvel Mastersizer 2000).
Undisturbed soil samples were collected in each
horizon and in laboratory,water retention curve by
tension table and Richard chamber, saturated hydraulic
conductivity bythe falling head method and hydraulic
conductivity curvesby the Wind’s method were
measured [6]. Field water content at different depths
was measured by the time-domain reflectometry (TDR)
method.
Figure 1. Apparent soil electrical conductivity
(ECa) measured at 1.5 m in the vertical dipole
mode (VDM) and the location of soil profiles.
3 RESULTS AND DISCUSSION
The spatial measurements of apparent electrical
conductivity (VDM and HDM) obtained with EM38
instrument were interpolated through ordinary kriging
applying the exponential model to the experimental
semivariogram.The maps (VDM shown in Fig.1),
allow to plan the pedological survey and refining the
borders of soil map units.Accordingly, two different
areas were identified and six soil profiles were
described and sampled for chemical and physical
characterization.Two main soil types were identified
both having a clay loam texture, Typic Calciustepts
mixed mesic, (P1,P2,P3) and Typic Haplustepts mixed
mesic (P4,P6,P7), corresponding respectively to
upslope and downslope sites.
Two representatives soil profiles (P1 and P4) were
analysed for planning the experimental plots, namely
upslope (P1) and downslope (P4): Here phenological
and physiological grapevine data were collected on 27
plants.
Despite the experimental plots had the same cultivar
(Aglianico), the same rootstocks (1103P) and the same
management, the crop responses in terms of biomass
2.3
Crop
measurements
and
must/wine
characteristics
The monitoring was conducted by the vegetative
growth until the harvest on a weekly or biweekly base,
in relation to the measured variable and the
physiological crop stage (biometric measurements,
photosynthetic assimilation, stomatal conductance to
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IXe Congrès International des Terroirs vitivinicoles 2012 / IXe International Terroirs Congress 2012
development and must quality was very different. At
the harvest time, the sugar of must was 23.4 °Brix in
the upslope site and 21.3°Brix in the downslope site
despite a unique cumulative value of Amerine
&Winkler index (2064 GDD).
Plants of the downslope site have shown a major vigor
compared to those of upslope site. At the fruit thinning,
14.6 bunches/plant versus 8.7 of upslope site were
measured. Despite a very similar number of
bunches/plant (4.8 and 4.2 bunches/plant for
downslope and upslope respectively), at the harvest
time the plant production of the downslope site was
1.81 (± 0.29) kg compared to 0.97 (± 0.36) kg of the
upslope.
The monitoring of soil-plant and atmosphere system of
vineyards has allowed the proper use of SWAP model
to estimate the daily crop water stress index (CWSI). In
the table 1for the crop development phases (shoot
growth, flowering, berry formation and berry ripening)
in both experimental sites (P1 and P4)the average
values of CWSI and the measured leaf water potential
(LWP) were reported. The crop water stress was higher
in P1 from the shoot growth until the berry formation
and quite similar to that one of P4 during the berry
ripening. The berry formation represents the
phenological phase where the CWSI were very
different. The CWSI obtained from the simulation
model is in agreement with the LWP measured in field
in both sites (R Pearson = - 0.975).
Table 1. Average values of measured Leaf Water Potential (LWP) and estimated Crop Water Stress Indecx
(CWSI) in the crop phonological phases.
Avg. LWP (Mpa)
Upslope Downslope
(P1)
(P4)
Data
Phenological
stage
06/06/2011
Shootgrowth
-0.69
-0.62
16/06/2011
Flowering
-0.81
27/07/2011
Berry formation
-1.01
02/10/2011
Berry ripening
-1.40
The analyses carried out on grape bunches have shown
a very robust qualitative differentiation between the
two sites. The parameters investigated like sugar,
antocians (avg. 559 mg/kg for P1 and 381 mg/kg for
P4), poliphenols in the skin (avg 2265 mg/kg for P1
and 1596 mg/kg for P4), color intensity (avg. 5.1 and
3.3 for P1 and P4), tannins in the skin (avg. 3.1 g/kg
for P1 and 2.3 g/kg for P4) and pH (avg 3.3 and 3.1 for
P1 and P4) were always higher in the P1 (upslope)
during the berry ripening if compared to the P4
(downslope). But the titratable acidity (avg 7.5 g/l for
P1 and 8.6 g/l for P4), the volume (avg.166 cm3 for P1
and 200 cm3 for P4) and weight of 100 berries(avg.181
g for P1 and 216 g for P4) were lower in P1. The first
results of microvinification have shown higher values
of ethanol (12.2 %v for P4 and 13.3 %v for P1), color
intensity (7.8 for P4 and 12.8 for P1) and tannins (2.9
g/l for P4 and 4.6 g/l for P1) in P1 compared to P4.
Avg. CWSI (%)
Upslope Downslope
(P1)
(P4)
2.67
0.01
-0.63
0.08
0.03
-0.82
18.01
7.18
-1.10
37.89
38.56
downslope site, seem to be correlated to the higher
value of CWSI realized in the berry formation phase.
This finding could also justify the differences between
the sites on the volume and weight of grape berry at
harvest. Finally the geophysical study has shown to be
very successful in planning the pedological campaign
and the identification of reference vineyards.
REFERENCES
1. E. VAUDOUR, 2003. Les terroirs viticoles
Definitions, caractérisation et protection. Dunod, Paris.
2. M. FREGONI (eds), 1988. Informatore Agrario)
Viticoltura di Qualità, 23/E-37133 Verona (IT).
3. E. VAUDOUR, 2001. Thèse de doctorat, Istitut
national agronomique Paris-Grignon, Paris.
4. A. BONFANTE, A. BASILE, G. LANGELLA, P.
MANNA, F. TERRIBILE, 2011. GEODERMA, 167168, 103-117.
5. L. GARDIN, E.A.C. COSTANTINI, R. NAPOLI,
2002. Guida alla descrizione dei suoli in campagna e
definizione delle loro qualità MiPAF-ISSDS,
REGIONE TOSCANA.
http://www.soilmaps.it/download/atrguidasuoliRT02.pdf
6. A. BASILE, A. COPPOLA, R. DE MASCELLIS, L.
RANDAZZO, 2006. Vadose Zone J. 5, 1005-1016.
7. J.D. HANSON, K.W. ROJAS, M.J. SHAFFER,
1999. Agron. J. 91, 171-177.
8. J.C. VAN DAM, J. HUYGEN, J.G. WESSELING,
R.A FEDDES, P. KABAT, P. VAN WALSUM, P.
GROENENDIJK, C.A. VAN DIEPEN, 1997. Theory
of SWAP version 2.0. Report 71, Dpt. of Water
Resources, WAU, Wageningen, The Netherlands.
4 CONCLUSIONS
The first results of ZOVISA project seem to confirm
the potentiality, at farm scale, of using physically based
approach to the analysis of terroir. The agreement
between the CWSI estimated by the model and the
measured crop water stress status (LWP) strengthens
the usefulness of simulation model application in the
terroir evaluation approach.
The differences of crop development and must quality
between the two references vineyards seem to be due
to the different vineyard water stress realized in both
experimental plots. In particular the best grapes
quality, in terms of antocians, poliphenols, sugar and
titratable acidity, of upslope site compared to the
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