Conference PaperPDF Available


In warm and dry climates, the use of porous systems should be required in order to allow a better leaf distribution inside the plant, causing more space in the clusters area and enhancing determined physiological processes so in the leaf (photosynthesis, ventilation, transpiration) as in berry (growth and maturation). Plant geometry indexes, yield and must composition have been studied in three different systems: sprawl with 12 shoots/m (S1); sprawl system with 18 shoots/m (S2) and vertical positioned system or VSP with 12 shoots/m (VSP1). Total leaf area increases as the crop load does, whoever surface area depends on to two factors: crop load and the training system (VSP vs. sprawl), which can provide differences in leaf exposure efficiencies. The main objective of this study was to validate digital photography measurements used to compare porosity differences among treatments and, as they affect plant microclimate and, therefore, yield and berry quality. Also, all previous studied indexes (LAI, SA, SFEr) tended to overestimate the relationship between exposed leaf surface and porosity of each treatment, but the use of digital method proved to be an effective tool in order to assess canopy porosity. Results showed that not positioned and free systems (sprawl) scored between 25-50% more porosity in the clusters area than the fixed vertical system (VSP), which resulted in a better plant microclimate for test conditions, mainly by improving the exposure of internal clusters and internal canopy ventilation. On the other hand, higher crop load treatment (S2) showed a real increase in yield (16%) without any relevant change into must composition, even improving total anthocyanin content into berry during ripening.
Mario de la FUENTE1*, Rubén LINARES, Pilar BAEZA and José Ramón LISSARRAGUE
1 Departamento de Producción Vegetal: Fitotecnia. Escuela Técnica Superior de Ingenieros Agrónomos. Universidad Politécnica de Madrid.
C/ Senda del Rey s/n, 28040, Madrid, Spain.
*Corresponding author: de la Fuente, M. phone: +34 915491137, Fax: +34 915491137, Email:
In warm and dry climates, the use of porous systems should be required in order to allow a better leaf distribution inside the plant, causing
more space in the clusters area and enhancing determined physiological processes so in the leaf (photosynthesis, ventilation, transpiration) as
in berry (growth and maturation). Plant geometry indexes, yield and must composition have been studied in three different systems: sprawl
with 12 shoots/m (S1); sprawl system with 18 shoots/m (S2) and vertical positioned system or VSP with 12 shoots/m (VSP1). Total leaf area
increases as the crop load does, whoever surface area depends on to two factors: crop load and the training system (VSP vs. sprawl), which
can provide differences in leaf exposure efficiencies. The main objective of this study was to validate digital photography measurements
used to compare porosity differences among treatments and, as they affect plant microclimate and, therefore, yield and berry quality. Also,
all previous studied indexes (LAI, SA, SFEr) tended to overestimate the relationship between exposed leaf surface and porosity of each
treatment, but the use of digital method proved to be an effective tool in order to assess canopy porosity. Results showed that not positioned
and free systems (sprawl) scored between 25-50% more porosity in the clusters area than the fixed vertical system (VSP), which resulted in a
better plant microclimate for test conditions, mainly by improving the exposure of internal clusters and internal canopy ventilation. On the
other hand, higher crop load treatment (S2) showed a real increase in yield (16%) without any relevant change into must composition, even
improving total anthocyanin content into berry during ripening.
Dans les climats chauds et secs, l'utilisation de systèmes poreuses devrait être nécessaire afin de permettre une meilleure distribution de la
feuille à l'intérieur de la vigne, causant plus d'espace dans la zone des grappes et l'amélioration des processus physiologiques déterminés ainsi
dans la feuille (photosynthèse, ventilation, transpiration) comme en raisin (croissance et maturation). Index de la géométrie des plantes,
rendement et doit la composition ont été étudiés dans les trois systèmes différents : système non positionnée avec 12 pampre (S1) ; système
non positionnée avec 18 pampre (S2) et le système de positionnement vertical ou VSP avec 12 pampre (VSP1). La surface foliaire totale
augmente avec la charge, la surface foliarire qui repose sur deux facteurs : charge et système de formation (VSP contre système non
positionnée), qui peut fournir des différences dans la feuille d'efficacités de l'exposition. L'objectif principal de cette étude était de valider les
mesures de photographie numérique utilisés pour comparer les différences de porosité entre les traitements et, car ils modifient le
microclimat des plantes et, par conséquent, rendement et qualité des baies. Aussi, tous les index étudiés précédentes (LAI, SA, SFEr) avaient
tendance à surestimer la relation entre la surface foliaire exposée et la porosité de chaque traitement, mais l'utilisation de la méthode
numérique s'est avérée pour être un outil efficace pour évaluer la porosité de la couvert végétal. Les résultats ont montré que les systèmes
non positionnés et libres (système non positionnée) a marqué entre 25-50 porosité plus dans le domaine des grappes que le système vertical
fixe (VSP), qui a donné lieu à un microclimat de meilleur plante pour les conditions de l'essai, principalement par l'amélioration de
l'exposition des grappes internes et ventilation interne canopée. En revanche, plus charge de traitement (S2) ont montré qu'une réelle
augmentation du rendement (16%) sans changement pertinent dans doit composition des moûts, même teneur en anthocyanes total
amélioration en berry au cours du maturite.
Key Words: sprawl, training system, porosity, canopy, grape composition.
Mots –Clés: système non positionnée, systèmes de conduit, couvert végétal, porosité, composition des raisins.
The plant geometry and training system should be joined with a proper sunlight and temperature microclimate in
the clusters area and, also in the rest of the plant (Spayd, et al. 2002). In warm and dry climates is required the
use of porous systems that allow a better leaf distribution inside the plant, cause more space in the clusters area
and enhance several physiological processes so in the leaf (photosynthesis, aeration, transpiration) as in berry
(growth and maturation). Several authors have showed the relevance of 3D spatial measures to describe the
architecture of leaf plant (Schultz 1995; Mabrouk, et al. 1997; Gladstone and Dokoozlian, 2003), for adequate
canopy management and also, can estimate degree shading in clusters area (key factor in the berry ripening
development). Digital image analysis are common used in vineyards to estimate crop coefficients or radiative
balance models (Pieri, 2010). Porosity canopy measurement provides information on leaf surface distribution
along the shoot and its spatial situation into plant air system or canopy volume (Gladstone and Dokoozlian,
At harvest, the value of incident photosynthetic active radiation (PAR) inside the canopy is usually low (about
10% of total ambient radiation). The degree of canopy density changes that percentage and there is a positive
correlation among PAR, leaf area and density into clusters area (Dokoozlian and Kliewer, 1995). Sunlight, air
ventilation within canopy, temperature cluster and microclime is affected by exposure and radiation percentage
received during growth and maturation period. If the lighting inside clusters area decreases during berry state
development, berries will produce less solutes accumulation and also, polyphenols and anthocyanins too
(Dokoozlian and Kliewer, 1995). On the other hand, too much cluster lighting can cause excessive higher
temperatures into cluster areas and produce degradation for these compounds (Spayd, et al. 2002).
Likewise, there are many factors which having important effects into plant microclimate and are related with
training system, so that is the reason for comparing different training systems in this study. Sprawl is a porous
training system with alternating spur-pruned uniform distribution along horizontal cordon that caused spacing
clusters zone. VSP on the other hand, is a vertical, rigid positioning system that shoots and leaf area caused a
linear clusters zone, usually closely spaced. Results show porosity differences among three treatments and will
be compared and related with other typical canopies measures, such as leaf area index (L.A.I.), surface area
(S.A.) or point quadrat method which are more complicated to take than a picture.
This field experiment was conduced over two consecutive seasons (2006 and 2007) into an experimental trial in
Toledo (Spain), under a fine clay-sandy soil (Palexeralf, Soil Survey Staff, 2003) with a 50 cm depth clay
superficial horizon (50-55% of clay). The weather conditions were Mediterranean semiarid (Papadakis, 1966).
The cultivar was Syrah grafted on 110R and spaced 1.2 m inside the NO-SW orientated rows and 2.7 m between
rows. Irrigation system drippers (3·l h-1) were spaced 1.2 m along the planting line and the amount applied was
equal for all treatments. Climatic conditions of 2006 and 2007 were significantly different being the 2006 a
campaign extremely warm while 2007 did not. Differences can be observed mainly in growing degree day
accumulated (2000 vs. 2525 GDD), rainfall (168 vs. 246 mm) and in evapotranspiration reference (1211.1 vs.
1064.6 mm; Eto) index too. Trial was designed with three treatments placed into four blocks at random and each
experimental plot consists of 20 control plants separated by rows and vines edge. Three treatments studied, in
order to assess the impact of training system and crop load, were: i) VSP1, Espaldera or vertical positioned
system (VSP) with 12 shoots/m crop load, ii) S1, Sprawl with 12 shoots/m crop load and iii) S2, Sprawl with 18
shoots/m crop load. (50% crop load more than VSP1 and S1).Vines were spur pruned and trained to a bilateral
cordon at a height of 1.40 m to the floor. The sprawl system had a single couple vegetation wires from 0.4 m to
the basal wire and they opened 0.6 m between wires. VSP system had a couple wires from 0.3 m to the basal
wire and a higher wire at 1.5 m to basal wire.
The measures of the total leaf area index (LAI; m2 leaf·area m-2 soil) were taken in accordance with a
modification of the method described by Carbonneau (1976) according to Sánchez de Miguel et al., (2010). Five
shoots were measured in two vines by treatment and block. Surface area (SA; m2 external foliar·m-2 surface soil)
was calculated based on inner geometric parameters of each system. Five measures were taken at two different
heights, in two vines by treatment and block. In VSP treatment, the area was likened to a parallelepiped and
measures were taken from vegetation lateral wall (total vegetation height, basal vegetation zone and fruiting
zone) and the width of vegetation row. For both sprawl system treatments were calculated by estimated
perimeter with flexible tape and vectorial graphic design program (Cad 2008®) to calculate the circular section of
plant wall along the row.
On the other hand, surface exposed real (SFEr) was calculated such as Carbonneau (1995) described as result of
multiply radiation intercepted percentage by vegetation cover and total leaf area developed (LAI) by the plant. It
took data from radiation throughout ripening in different day hours (8, 12 and 16 s.t.) for this variable calculated.
Spatial aerial parts distribution of the plant were measured by Point Quadrat (PQ) method described by Smart
(1985) in the same vines that previous vegetation measures did. Real porosity percentages were calculated
through processing tool photography program (Adobe Photoshop CS3®). Photographs were taken by night and
with the only flash lighting from the digital camera (to well discriminate gaps from leaves). Pictures from
vegetal wall were taken between two consecutive vines for each block (the same vines used for the geometric
measures) and with a distance same as the width of between plant lines (2.7 m).
A reproductive yield study was done during harvest (30/08/2006 and 05/09/2007) in ten previously selected
plants for each treatment and block. Cluster number, average cluster weight, average berry weight, berry number
per cluster and yield (kg m-1) were calculated individually for each harvested plant. A digital field scale was used
for experimental data measures. Also, at harvest a 100-berry sample per single plot was collected to follow 100-
berries weight (g), SST (ºBrix), pH and phenol maturity according to Glories (2001) method, so final values
corresponded to harvest date of each year.
Canopy measures
In both years (Table I), total leaf area of greater crop load treatment (S2) was higher than the other two
treatments with lesser load (VSP1 and S1) between 27-33% over all vegetative cycle, as was likely, emphasizing
differences before stopping vegetative prior to ripening. There were not significant differences between
treatments in relation to growth of secondary shoots. These differences show that total leaf area is directly
related to the level of crop load left in the plant, and did not cause any increase in secondary leaf area between
low load treatments (VSP1 and S1) compared to the higher load treatment (S2). Surface area exposed (Table 1)
at maturity showed that sprawl treatments obtained higher values than VSP (10-30% compares to S treatments in
2006 and 2007 respectively in 2007) when the crop load effect made them open up the top vegetation centre.
However, the best indicator of the relationship between vegetation amount and surface porosity into the canopy
is the ratio called surface real exposed (SFEr; Carbonneau, 1995). Results measured at 8, 12 and 16 s.t. reflect
(Table 1) a greater exposure (during all day) of treatment S2 in relation to the other treatments, reaching much
higher values compared to VSP (increase between 36.4% and 68.4%, P<0.001). S1 obtained intermediate values,
so that it was clear, a combined effect between crop load and training system caused an increase of canopy plant
volume, decreasing crowed vegetation cover and increasing leaf exposure (14-29%) of open systems versus rigid
vertical positioning system. The division of the canopy in more vegetation planes can increase yield and crop
quality (Bordelon et al. 2008), and also, the quality of wines.
These differences are very interesting in warm climates, where one of the main goals is not cause leaf and
clusters overexposure in order to prevent premature senescence and berry overripening process respectively (de
la Fuente, 2009). Increasing load and with a not positioned free exposure, the plant shows a higher overhead
opening and exposed a higher number of leaves to solar radiation but during less time, because flow radiation
unit per leaf is smaller, so senescence process is not caused easily. Also, total leaf area is more efficient because
is working with a larger number of inner leaves than rigid vertical systems, where the number of leaves layers is
usually minor, increasing the leaf exposure to solar radiation, but lowering the undesirable effect of premature
senescence in basal leaves due to excessive heat.
Aerial parts plant positional study by PQ showed lower vegetation density (Table II) in S treatments, with
around 2 and 3 extra-layers more than VSP1. Several authors (Gladstone and Dokoozlian, 2003; Kliewer et al.,
2000 and Vanden Heuvel et al., 2004) obtained values of the leaf layer number in previous trials and considered
at appropriate values of LLN in cluster area between 1.5 to 2 for trellis and 3-4 for other open systems with high
density. Data from trial treatments are within the optimal definition intervals (2-4 LLN) for each training systems
calculated by previous researchers.
Likewise, while there were a higher number of clusters in S treatments comparing with VSP system (differences
among 1.0-1.7 and 0.8-1.6 in 2006 and 2007 respectively, P<0.05), there were a higher percentage of clusters not
subjected to direct radiation (24.9-19.0% more for S2 and S1 in 2007, P<0.01). Several autors obtained
differences in porosity values between 30-10% compairing divided and not divided training systems (Kliewer et
al., 2000; Gladstone and Dokoozlian, 2003; Bordelon et al., 2008).
The results of porosity by digital photography analysis (Table II) show how VSP treatment obtained lower
values of porosity along all the vegetation cover. In the first 40 cm (clusters zone), S1 presented higher porosity
thanVSP (48 and 19% for 2006 and 2007 respectively) with the same crop load. Also, load increase does not
affect to system porosity, because S2 shows higher values in this area during 2006 (+38.6%, P<0.001) or similar
(in 2007) compared to VSP1 treatment. But, that is a key question: Is there a reliable and fast method to calculate
the porosity of a system? However, today it is still difficult to obtain an estimated method to calculate the real
porosity value of a training system. The PQ method defines the number of layers of leaves and the percentage of
non-contacts (gaps) so directs porosity measurements, and like other often used parameters (LAI and SA), are
indirect methods (less precise) and, moreover, certain measures may be overestimated and some system
discontinuities are not consider.
Therefore, porosity variations are priority to assess a correct leaf area distribution in the plant. Results of digital
photography shown that open systems get better porosity into cluster area between 25 and 50%.that improves the
exposure of inner clusters and would enhance thermal effects such as lowering internal temperature due to
increase ventilation into the canopy. Also, in training systems studies is not only important how many leaves
layers have the canopy, but also the total volume occupied by them. With the PQ method is possible to estimate
correctly the LLN, but not the percentage of gaps into the canopy, so this method should be only applied to
compare values of porosity with the same training system, while the use of digital photography allow to study
different training systems or vine areas or volumes and really estimate the canopy porosity inside the plant.
Yield components, berry sampling and juice analysis
During 2006 and 2007 reflected a main crop load effect was showed (Table III), where higher load treatment
(S2) had an increment of 16% in yield than the others treatments. On the other hand, S2 showed an average
bunch weight lower (from 17.0 to 22.5%) and reduced the number of berries (from 12 to 21%) per cluster, but it
was equilibrated by a higher cluster number per vine (from 32 to 35%) and during 2007 with the same average
berry weight (only in 2006 was lower, between 4.4 to 9.2%), caused by a higher crop load. Therefore, with an
increment of load will get berry size decrease but berries number increase, which has direct effect in total yield
and as same time, an increase in skin/flesh ratio during harvest.
Leaves and cluster microclimate are the key factor (Vanden Heuvel et al. 2004) for determinating the acidity
contents, pH and K must and last, wine composition. Differences obtained during 2007 for acidity and pH values
are not quantitatively significant (8-7%) and are probably due to a greater exposure to radiation clusters, which
increases final pH (Bergqvist et al. 2001 and Spayd et al. 2002). Data from total and extractable anthocyanin
(Table III) content reflect that there is an effect of increasing shading clusters area in the final berry synthesis of
anthocyanins, which is very useful in winemaking process (Haselgrove et al. 2000). It should also be
remembered that cv. Syrah is very sensitive to changes in thermal effects during total anthocyanins synthesis
(Spayd et al. 2002). This effect causes differences in berry anthocyanins content, which are heavier in extremely
hot conditions (2007), getting around 20% in open and not positioned free systems.
Finally, crop load does not change must composition seriously, but it increase total plant yield (Junquera et al.,
2009) becouse gives more clusters but less exposed to sunlight and with the training system, prevent the
degradation of anthocyanins at the end of ripening. The effect of the load is less important than using open
training systems, which increase phenolic and anthocyanic berry content modifying light and thermal
microclimate through spatial distribution of vegetation and shading effects in the plant.
Double effect due to not positioned open system (sprawl) and crop load increment gave to the plant a higher leaf
exposure and a lower vegetation density, which in hot or arid climates means a great microclimate of plant
improvement. Digital photography is a simple, fast and effective tool to evaluate possible differences refers to
porosity and leaf area exposure between training systems. It appears that porosity increase in sprawl treatments
between 25-50% in cluster area compares to VSP and caused a better plant microclimate.
Finally, free and non-positioned systems can help to improve plant microclimate, influence positively on
anthocyanic berry composition but do not change must composition and then allowing a yield increase if there is
enough water availability in plant-soil system.
Bergqvist J., Dokoozlian N., Ebusida N. 2001. Sunlight exposure temperature effects on berry growth and compositon of Cabernet-
Sauvignon and Grenache in the Central San Joaquin Valley of California. Am.J.Enol. Vitic. 52(1).
Bordelon B. P., Skinkis P. A., Howard P.H. 2008. Impact of training system on vine perfomance and fruit composition of Traminette. Am. J.
enol. vitic 59(1), 39-46.
Carbonneau A. 1995. La surface foliare exposée potentielle. Le progrès agricole et viticole 112(9), 204-212.
de la Fuente M. 2009. Caracterización geométrica, ecofisiológica y evaluación agronómica de sistemas continuos de vegetación libre
(SPRAWL) vs. espaldera para atenuar la sobreexposición de hojas de racimos en cv. syrah (Vitis vinifera L.) en viñedos de zonas cálidas.
301 p. Tesis doctoral. E.T.S.I.A. Producción Vegetal: Fitotecnia. Madrid. Universidad Politécnica de Madrid.
Dokoozlian N., Kliewer W. M. 1995. The light environment within grapevine canopies. Am.J.Enol. Vitic. 46(2), 209-226.
Gladstone E. A., Dokoozlian N. 2003. Influence of leaf area density and trellis/training system on the light microclimate within grapevine
canopies. Vitis 42(3), 123-131.
Glories Y. 2001. Caracterisation du potentiel phènolique : adaptation de la vinification. Le Progrès Agricole et Viticole. 118 (15 -16) : 347 –
Haselgrove L., Bottinf D., Heeswijck R., Rod P.B., Dry P., Ford C., Illand P.G. 2000. Canopy microclimate and berry composition: the effect
of bunch exposure on the phenolic composition od Vitis vinifera L. cv Shiraz grape berries. Aus. J. Grape and Wine Research 6: 141-149.
Kliewer W. M., Wolpert J. A., Benz M. 2000. Trellis and vine spacing effects on growth, canopy microclimate, yield and fruit composition
of Cabernet-Sauvignon. V International symposium on grapevine physiology, Jerusalem - Israel, ISHS.21-31.
Junquera, P., Jiménez L., Sánchez de Miguel P., Lissarrague J.R. 2009. Effect of shoot number on vine balance and berry composition of
Tempranillo grapevines. 16th International GiESCO Symposium, 2009. University of California, Davis (CA, USA). 419-424.
Mabrouk H., Sinoquet H., Carbonneau A. 1997. Canopy structure and radiation regime in grapevine II: Modelling radiation interception and
distribution inside the canopy. Vitis 36(3), 125-132.
Pieri P. 2010. Modelling radiative balance in a row-crop canopy: Cross-row distribution of net radiation at the soil surface and energy
available to clusters in a vineyard. Ecological Modelling, 221, 802–811.
Sánchez de Miguel P., Junquera P., de la Fuente M., Jiménez L., Linares R., Baeza P., Lissarrague J.R. 2011. Estimation of vineyard leaf
area by linear regression. Spanish Journal of Agricultural Research 9(1): 202 - 212
Schultz H. R. 1995. Grape canopy structure, light microclimate and photosynthesis I. A two dimensional model of the spatial distribution of
surface area densities and leaf ages in two canopy systems. Vitis 34(4), 211-215.
Smart, R. E. 1985. Principles of grapevine canopy microclimate manipulation with implications for yield and quality. A review. Am.J.Enol.
Vitic. 36(3), 230-239.
Spayd S., Tarara J., Mee D.L., Fergurson J.C. 2002. Separation of sunlight and temperature effects on the composition of Vitis vinifera cv.
Merlot berries. American Journal of Enology and Viticulture 53(3), 171-182.
Vanden Heuvel J. E., Proctor J. T. A., Sullivan J.A., Fisher K.H. 2004. Influence of training/trellising system and rootstock selection on
productivity and fruit composition of Chardonnay and Cabernet franc grapevines in Ontario, Canada. Am. J. Enol. Vitic 55(3): 253-264.
The authors gratefully acknowledge the effort of Osborne Distribuidora S.A. company for technical and financial support for the
implementation of this project (MEC, IDI: P030260221). Also, D. Juan Dominguez Torre (REDISEÑA S.L.) for their invaluable and
uninterested support by assistance in digital image analysis
Table I
Vegetative development (LAI, m2·m-2), surface area (SA, m2·m-2) and surface real exposed (SFEr) for three
treatmets at harvest.
Développement végétatif (LAI, m2·m-2), surface habitable (SA, m2·m-2) et real surface exposée (SFEr) pour trois
treatmets à la récolte.
Table II
Point Quadrat and digital porosity estimation method for three treatmets during maturation period.
Point Quadrat et méthode d'estimation de porosité numérique pour trois treatmets au cours de la période de
Table III
Yield partitioning and must composition in 2006 and 2007 growing seasons for three treatments at harvest.
Composantes du rendement et moût en 2006 et 2007 pour les trois traitements à la récolte.
1 EEM: standard average error for n= 40 and 8 samples per yield and must composition respectively.
2 Sig: significant differences; ns, *, ** and *** means to there is no significant differences, P<0,05, P<0,01 and P<0,001
respectively. The values with the same letter are equal (T. Duncan). P-values were determined by analysis of variance.
Main Lateral Main Lateral 8 s.t. 12 s.t. 16 s.t. 8 s.t. 12 s.t. 16 s.t.
VSP1 1.16b 0.63 1.28b 1.32 1.06b 1.11b 0.47c 0.31c 0.41b 1.08b 1.03b 1.38
S1 1.34b 0.68 1.40b 1.33 1.15b 1.26ab 0.83b 0.56b 1.12b 1.01b 0.74b 1.59
S2 2.00a 0.73 2.12a 1.24 1.50ª 1.31ª 1.15ª 0.98ª 1.23ª 1.78a 1.62a 1.65
(n=8) 0.16 0.104 0.076 0.075 0.06 0.07 0.08 0.08 0.08 0.08 0.08 0.08
* ns *** ns ** * *** *** *** *** *** ns
2006 2007 2007Treatment SA
2006 2007 2006
Le af
Int ern al
(%) Late ral In te rnal
Le ave s
Le af
Int ern al
(%) Late ral In te rna l
Le ave s
cm. 40-70
cm. 70-100
cm. 0-40
cm. 40-70
cm. 70-100
VSP1 2,20 15,00 77,90 2,7
2,20 7,50 65,6
S1 2,60 10,00 82,40 5,0
58,3ª 2,40 7,50 81,0
5,8ª 66,1ª 14,63ª 26,25ª 85,00
14,83ª 66,87ª
S2 2,50 20,00 82,10 5,9ª 60,0
2,60 5,00 87,3ª 6,5
68,1ª 12,33
(n=8) 0,23 4,5 0,5 0,41 2,01 0,22 1,8 0,56 0,31 1,53 0,88 1,15 6,73 0,17 1,81 6,3
ns ns ns *** *** ns ns ** ** ** *** ** * ** * **
Vegetation Zone PQ 2006
Cluster Zone
Treatment Clus ter Zone Vegetation Zone % Po ro si ty
2006 2007
PQ 2006
Yie ld ( Kg·m
wei ght (g)
100 Berries
wei gh t (g)
berries ·cluste r
Yie ld ( Kg·m
wei ght (g)
100 Berries
wei ght (g)
berries·cl uste r
VSP1 24.68 b 1.73 b 190.42 a 111.34 a 171.19 a 20.96 b 1.61 b 204.36 a 150.54 b 135.63 a
S1 23.82 b 1.71 b 195.10 a 104.57 b 187.34 a 21.04 b 1.61 b 206.55 a 160.09 a 128.29 a
S2 36.20 a 2.05 a 153.24 b 101.05 c 152.06 b 30.66 a 1.93 a 169.32 b 158.7 a 106.92 b
(n=40) 0.604 0.041 6.09 0.081 1.02 0.46 0.10 7.71 1.39 5.05
** ** ** ** ** *** *** ** *** ***
Yie ld pa rtit ioni ng 2006 Yie ld pa rtit ioni ng 2 007
Treatment ºBrix pH IPT An toci an
Total Antocian
content (mg·L
)ºBrix pH IPT Ant oci an
Total Antocian
content (mg·L
VSP1 25.1 3.5 46.7 794.33
1470.35 b
25.2 3.06 b 45.8 931.0
S1 25.9 3.5 54.7 936.95
1804.34 a
25.4 3.13 a 51.8 976.5
S2 25.8 3.5 52.7 983.94
1903.30 a
24.7 3.20 a 47.7 861.0
(n=8) 0.76 0.02 2.54 76.94
0.27 0.02 4.1 102.7
ns ns ns ns
ns ** ns ns
Must Composition 2006 Must Composition 2007
... In warm climates, where problems like over-ripening and sunburnt clusters often appear, the use of porous systems can help plants to establish a better leaf and cluster distribution, providing more space and enhancing certain physiological processes (de la Fuente et al. 2013), and causing a better utilisation of natural resources. Vegetative (aerial parts or root development) and reproductive yield are frequently determined by two inputs: water consumption and sun exposure (mainly, among others like soil composition, weather conditions, etc). ...
... size will decrease but the number of berries will increase (better skin/flesh ratio), giving more yield due to the increase in cluster number.Finally, what about quality? Because leaves and cluster microclimate are usually key factors determining the must parameters and consequently, wine composition(De la Fuente et al. 2013). No differences were obtained during 2006 for Brix, acidity and pH values ...
Full-text available
A big challenge to climate change adaptation is water use efficiency due to its scarcity, mainly in semiarid conditions like the Mediterranean. A study was undertaken to assess the relevance of canopy management, irrigation and the efficient use of natural resources in yield and berry quality within a Mediterranean viticultural context.
... Several authors have showed (Schultz 1995; Mabrouk, et al. 1997; Gladstone and Dokoozlian, 2003) a real improvement of yield and berry quality with an adequate canopy management. An adequate leaf exposure porosity and canopy density, as well as a certain degree shading in clusters area (a key factor during the ripening), can help obtaining the objectives chosen by the vineyard and cellar managers (de la Fuente et al., 2013). The plant geometry and training system should be accompanied by a proper sunlight and temperature microclimate in the clusters area and in the rest of the plant (). ...
... These differences are very interesting in warm climates, where one of the main goals is not to cause leaf and clusters overexposure in order to prevent premature senescence and berry over ripening process (de la Fuente et al., 2013). It seems to be clear that a combined effect between crop load and training system may mitigate light over exposure, and avoid undesirable over ripening berry effects. ...
... Leaves and cluster microclimate are the key factors for determining the acidity content, pH and K of must and consequently, wine composition [16]. No differences were obtained during 2006 for Brix degree, acidity and pH values (Table 6). ...
... Surface area is less time exposed with open and nonpositioned systems (S1 and S2) comparing with vertical systems (VSP1), so VSP1 should suffers the water deficit before sprawl systems, within the same environmental conditions [16]. However, its stomatal closure occurs soon after due to the lower total leaf surface exposed, causing a less consumption of soil water availability. ...
Conference Paper
Full-text available
One of the main objectives in Mediterranean vineyards is the water use efficiency due to its scarcity. During the growing season, total available water is significantly lower than the evaporative demand, being this a limiting factor for quality production. Beside other factors, the choice of an adequate training system can help mitigate this negative effect in regard with soil-plant hydric consumption. The use of porous systems can help plants establish a better leaf distribution inside the clusters area, providing more space and enhancing certain physiological processes, both in leaves and berries (de la Fuente et al., 2013), and causing a better utilization of natural resources. Water consumption, dynamics and hydric relations in plants (water potential) and soil (soil water tension and capacity) have been studied on three different systems: sprawl system with 12 shoots m–1 (S1); sprawl system with 18 shoots m–1 (S2) and verti- cal positioned system or VSP with 12 shoots m–1 (VSP1). Yield, dry matter partitioning and berry and must composition have also been obtained at the maturity stage. The main objective of this study was to show the differences in consumption and water use efficiency due to different canopy managements, and to quantify these effects on yield, berry and must composition. The results showed that the vertical system (VSP1) benefited less from total available water at medium level (20; 30 and 50 cm) in the profile soil (0.5–1.5% available water vol.), in comparison with non-positioned and free systems (S1 and S2). On the other hand, S1 and S2 treatments caused more stress to the plant at midday from flowering to veraison (8–10%), but not during ripening. Sprawl system (S1) helps produce more balanced plants compared to VSP1, because it obtains higher number (and weight) of main leaves by shoot, increasing the number of secondary shoots and maximizing the canopy volume. No dif- ferences were observed in the number of clusters, berry size or yield between VSP1 and S1, but higher crop load treatment (S2) showed an evident yield increase (16%) at harvest. Berry and must composition did not change (Brix, pH and total acidity) much, while the composition of anthocyanins improved with low exposure and non-positioned systems (S1 and S2). In addition, both positive effects of sprawl treatments (crop load and training system) resulted in better yield and quality in Mediterranean semiarid conditions under the same inputs (sun, water and soil), causing higher efficiency of natural resources.
... Among other factors, the sustainable production depends on the appropriate ratio of exposed leaves and its relation with the clusters produced (Howell, 2001). An adequate canopy management a correct relation between leaf and cluster exposures and therefore, the shading degree in the clusters zone, are the key factors during ripening and berry development (De la Fuente et al., 2013), managing its advance, delay or the harvest timing. Several authors recommended ratios between 15-20 cm2·g-1 (Bonnisseau and Dufourcq 2004;Dufourcq et al., 2005;Kliewer and Dokoozlian 2005) for high quality ripe fruit. ...
Full-text available
This work shows the relevance of the yield prediction, the physiological bases and some different methodologies applied nowadays. Likewise, three alternative models were proposed for predicting harvest in two different moments of vine cycle: fruitset and veraison. For that, an experimental trial was carried out during four years (2004-2007) in a commercial vineyard formed on more than 700 ha (14 experimental plots were established depending on cultivars and rootstocks), in Mediterranean conditions In the experimental trial, the results showed that veraison (V1 and V2) models obtained the highest correlations and the lowest errors, while the fruitset (FS) model obtained the lowest correlation and the highest error. Fruit Set (FS) model may be of interest because it can help wineries by providing the information early in the grapevine cycle, but with a higher error. The V1 and V2 models could be used to predict grapevine yields accurately, but later in the vine cycle in comparison with the previous model (Bulletin de l'OIV, 2014, vol. 87, n.° 1001-1002-1003, p. 387-394).
Full-text available
In order to study the effects of shoot density on vine balance and its influence on yield and berry composition, an experimental trial was carried out during 2007 and 2008 using Tempranillo grapevines (Vitis vinifera L.) grafted onto 110R and vertical shoot positioned. The distance between plants in the row was 1.1 m and rows were 2.5 m apart. Five treatments were applied: 6, 8, 10, 12 and 14 shoots per meter of row. The increase in the density of the shoots implies a decrease in the vegetative growth per unit and in the relative importance of the laterals shoots. Differences in the number of shoots was compensated by the unitary growth per shoot, differences in vine size were not noted The first year the treatments were applied, yield increased only because of shoot number and thus number of clusters, but neither fertility nor cluster weight was affected. In 2008, as shoot density increased both clusters per shoot and berries per cluster decreased. Microclimatic conditions and reserves accumulated in 2007 could have affected these parameters. Thus, while in 2007 differences in leaf-to-fruit ratio speeded up berry maturing as shoot load was lower, no differences between vegetative development to yield ratio were found in 2008 which lead to less differences in the berry ripening process for the different treatments. ºBrix and pH were the parameters of must composition that were most affected by shoot density.
The influence of leaf area density and canopy configuration on the light microclimate within 6 wine grape trellis/training systems commonly used in California (single curtain, double curtain, vertically shoot positioned, lyre, Smart-Henry and Smart-Dyson) was examined in two experimental vineyards (Oakville and Parlier). Mean canopy leaf area density varied considerably among the systems, ranging from approximately 2.8 m2 m-3 for the Wye to 10.1 m2 m-3 for the VSP. Non-positioned systems were characterized by a layer of relatively high leaf area density in their outer envelope and lower leaf area densities in their interior. In contrast, leaf area density in positioned systems increased from the top of the canopy moving downward to the fruit zone. Mean leaf area density within the fruit zone ranged from near 6 m2 m-3 in the DC to over 12 m2 m-3 in the VSP and LYR. The pattern of light attenuation within the canopy was generally similar among the systems, with PPF reaching its lowest level in or near the fruit zone. Fruit zone PPF was >10% of ambient sunlight in low density canopies and <5% in high density canopies. A gradual decline in fruit zone PPF was found as leaf area density increased in positioned systems. PPF decreased sharply in the fruit zone of non-positioned systems as leaf area density increased from 2 to 4 m2 m-3, then leveled as leaf area density exceeded 6 m2m -3. Fruit zone PPF decreased as the leaf area density of divided systems increased from 2 to 4 m2 m-3, then declined gradually as leaf area density approached 6m2 m-3. Fruit zone PPF in non-divided systems was initially lower, and declined more gradually as leaf area density increased, compared to divided systems. Compared to positioned systems, leaf layer number in the fruit zone rose more sharply in non-positioned systems as leaf area density increased. Leaf layer number was greater in non-divided systems compared to divided systems, but declined at similar rates in both systems as leaf area density increased. Shoot-positioned systems achieved well-exposed fruit zones at higher leaf area densities, but lower leaf layer numbers, compared to non-positioned canopies.
A 3D version of the radiation model of Sinoquet and Bonhomme (1992) was used to simulate the light microclimate of grapevine. It was tested against measurements of radiation interception and distribution within two canopy systems (Open Lyre and Geneva Double Curtain) exhibiting different vigor levels. The agreement between the model and the measurements was generally good. Discrepancies may have arisen from incorrect assumptions concerning leaf azimuth distribution and leaf dispersion as well as a lack of accuracy in the description of the distribution of leaf area density inside the canopy. The model also permitted to assess light partitioning between main and lateral shoot leaves which can influence global canopy photosynthesis and berry ripening. As an example of application, the model was used to evaluate the consequences of lateral leaf removing on the interception efficiency of the canopy and the light environment of the fruit zone. The possible use of a geometrical approach to simulate the radiation interception at the canopy scale was also discussed.
Cabernet Sauvignon trained to six different trellising systems each with in-row vine spacings of 1,2 and 3m and grafted onto two different rootstocks (110R and 039-16) were evaluated for differences in vegetative growth, productivity, fruit composition and canopy microclimate over a period of three years (1993 to 1995) at Oakville, CA. Crop yield of the VSP, SH, TK2T, GDC, Lyre and V trellis systems averaged 9.9. 12.8, 15.3, 16.8 and 18.6 mt/ha, respectively. Yield increases above that obtained with the VSP trellis were due mainly due to greater number of shoots and clusters per ha. The number of shoots and leaf area (m2) per m of canopy length ranged from 9 to 14 and 2.9 to 4.7, respectively. Pruning weight (kg) per m of canopy length ranged from 0.48 (Lyre (to 0.89 (VSP); weight per cane (g) ranged from 38 (Lyre) to 64 (VSP) and yield/pruning weight ratios ranged from 4.9 (VSP, SH) to 7.4 (Lyre). Fruit from divided canopy trellis systems at harvest generally were lower in titratable acidity (TA), malic acid and potassium than fruit from the VSP system. The fruiting region of the divided canopy trellis systems had lower leaf layer number (LLN) and higher percent exterior leaves, exterior clusters and canopy gaps than the VSP trellis system. Only the VSP trained vines at one m vine spacing had excessively dense vine canopy as judged by LLN, pruning weight and total leaf area per m canopy length. Closer vine spacing produced higher yields per ha due mainly to greater number of shoots and clusters per ha. Wider vine spacing produced more shoots per vine but shorter shoots and internode lengths, less leaf area and weight per shoot, and higher yield/pruning weight ratio than narrow vine spacing. Fruit from close vine spacing was higher in °Brix, pH, malic acid and K but did not differ in TA and total anthocyanin. LLN, percent interior leaves and clusters increased with closer vine spacing, whereas canopy gaps decreased.
Light microclimate, yield components, and fruit composition were investigated from 1999 to 2002 on vines growing in the Niagara Peninsula in Ontario, Canada. Six training systems (four cane-pruned: four-cane Kniffin, two-tier flatbow, Scott Henry, pendelbogen; and two spur-pruned: low cordon, vertiko), two cultivars (Chardonnay clone 96 and Cabernet franc clone 331), and two rootstocks (Kober 5BB and Riparia Gloire de Montpellier) were investigated in a 6 x 2 x 2 split-split plot design, with training system as the main factor, followed by cultivar and then rootstock. Over the four-year study, Cabernet franc had higher yields (13%) in the cane- versus the spurpruned systems. Chardonnay showed the same trend, but pendelbogen had the highest yield among the cane-pruned systems (26% greater than spur-pruned). The lowest yielding systems, low cordon and vertiko, produced fruit with the highest mean Brix over the four-year period in both cultivars, although the low-cordon canopy had a high leaf layer number, while vertiko had a low leaf layer number during the first two years of study. Must pH and titratable acidity were generally not affected by training system. Vines growing on 5BB rootstock produced greater yields, pruning weights, and had lower crop-load ratios compared to vines growing on Riparia. Vines with Riparia rootstock produced fruit higher in Brix in two of the four years.
The performance of own-rooted Traminette vines was investigated over a 5-year period on three training systems: high cordon (HC), midwire cordon (MWC), and Scott Henry (SH). Yield, vine size, and canopy density were strongly influenced by training system. Berry composition (soluble solids, pH, titratable acidity and monoterpenes) was only slightly influenced by training system. Vines trained to divided-canopy SH had the highest yield and largest vine size, resulting in 5-year mean crop load (ratio of yield to cane pruning weight) of 7.8, which is at the low end of the generally accepted appropriate range of 8 to 12. Midwire cordon vines were 22% lower yielding, but with similar vine size, resulting in a lower than desired 5-year mean crop load of 6.0. High-cordon vines had moderate yield and vine size, and a 5-yr mean crop load of 8.1. Canopy density as measured by point quadrat analysis differed between training systems. High-cordon vines had dense canopies with four leaf layers, 2% gaps, and less than 20% exposed clusters, while SH and MWC vines had one to two leaf layers, approximately 10% gaps, and 40% exposed clusters. Despite differences in canopy density and crop load ratios, fruit composition at harvest was similar for all training systems.