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Water status, leaf area and fruit load influence on berry weight and sugar accumulation of cv. ‘Tempranillo’ under semiarid conditions
Scientia Horticulturae 109 (2006) 60–65 www.elsevier.com/locate/scihorti
Water status, leaf area and fruit load influence on berry weight and sugar accumulation of cv. ‘Tempranillo’ under semiarid conditions Luis G. Santesteban *, J. Bernardo Royo Departamento de Produccio´n Agraria, Universidad Pu´blica de Navarra, Campus de Arrosadia, 31006 Pamplona, Spain Received 8 March 2005; received in revised form 13 September 2005; accepted 7 March 2006
Abstract Berry weight (BW) and sugar concentration (SC) are relevant indices in viticulture since they can be easily measured and, when considered together, give a relatively fair estimation of grape quality. This work aims to evaluate the influence of water availability, leaf area and fruit load on BW and SC, estimating the relative importance of these factors. Leaf area (LA), berry number (BN), yield (YLD), water potential in summer (cpds), BW and SC were measured in 16 and 17 ‘Tempranillo’ vineyards in 1999 and 2000, respectively. In all the vineyards, according to local practices, the irrigation amount decreased as summer progressed. The study vineyards comprised a broad range of situations concerning leaf area, fruit load and water status in summer. Average leaf water potential in summer and LA/BN ratio, when considered together, estimated properly BW (R2 = 0.91; P < 0.001) and, in a similar way, cpd-s and LA/YLD ratio estimated SC (R2 = 0.74; P < 0.001). The relative weight of cpd-s in both relationships was much higher than that of any of the LA:fruit ratios, showing that, under semiarid conditions, water availability plays the main role in regulation of berry growth and sugar accumulation and, therefore, the highest attention should be paid in these areas to irrigation management, seeking the degree of stress that allows optimizing the combination of yield and berry quality in each situation. # 2006 Elsevier B.V. All rights reserved. Keywords: Vitis vinifera L.; Plant water relations; Leaf water potential; Leaf area; Fruit load; Berry quality
1. Introduction Wine grape quality cannot be easily defined, as it comprises many concepts, some of difficult objective determination and others whose estimation requires analyzing many chemical compounds that cannot be routinely measured throughout the ripening cycle. Nevertheless, grape growers need some simple and measurable parameters that enable them to adjust vineyard management practices in order to achieve maximum harvest quality. Berry size and sugar concentration are easy to measure and, although cannot themselves evaluate grape quality accurately, they are good predictors, as most satisfying harvests are usually those with small berries and high sugar concentration (Champagnol, 1993). These berries usually produce quality wine as they have a high skin-pulp ratio (Singleton, 1972; Roby et al., 2004) and also due to the existing linkage
* Corresponding author. Tel.: +34 948 169718. E-mail address: [email protected] (L.G. Santesteban). 0304-4238/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2006.03.003
between the sugar and phenolics accumulation processes (Pirie and Mullins, 1977; Boss and Davies, 2001). Berry size at harvest depends on many factors which modify berry growth at any stage of development, mainly environmental conditions (Dokoozlian and Kliewer, 1996), mineral nutrition (Ussahatanonta et al., 1996), fruit load (Dokoozlian and Hirschfelt, 1995), leaf area (Candolfi-Vasconcellos and Koblet, 1990) and water status (Matthews et al., 1987b; Medrano et al., 2003). The effect of these factors is not the same at every stage of berry development, being much more relevant in Stage I, when cell division takes place. In a similar way, sugar accumulation depends on many factors such as light (Dokoozlian and Kliewer, 1995), temperature (Kliewer and Lider, 1970), mineral nutrition (Ussahatanonta et al., 1996), carbohydrate level in the permanent structures of the plant (Sommer and Clingeleffer, 1995), leaf area (Candolfi-Vasconcellos and Koblet, 1990), fruit load (Dokoozlian and Hirschfelt, 1995) and water availability. Water availability affects berry sugar concentration in a relatively complex way as, sometimes, higher availability implies higher sugar concentration as a conse-
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
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concentration at harvest in Vitis vinifera cv. ‘Tempranillo’, under the semiarid climatic conditions typical of southern Europe vineyards. 2. Materials and methods 2.1. Plant material and experimental design
Fig. 1. Monthly rainfall (R) and mean temperature (T) in the average year compared with 1999 and 2000.
quence of higher photosynthetic activity (Matthews and Anderson, 1988); whereas in other situations it implies lower sugar concentration due to the dilution of sugars that occurs as a consequence of increased berry growth (Van Leeuwen and Seguin, 1994). The effect of the above outlined factors is particularly relevant during Stage III of berry development. However, the conditions in earlier stages may also affect sugar concentration according to their effect on both the amount of storage carbohydrates in permanent structures and, particularly, on berry size. The aim of this work is to evaluate the effect of water status, leaf area, and crop load on berry size and sugar
The study was carried out in 1999 and 2000 in southern Navarre vineyards in Spain (428 N, 08460 W; altitude: 300–400 m), a region characterized by a semiarid climate (Bs type in Koppen’s classification; P < 350 mm; ETPPenman > 1150 mm). Climatic conditions during 1999 and 2000 were similar to the average (Fig. 1). The vineyards were all planted with a ‘Tempranillo’/110 Richter variety/rootstock combination, and were 5–8 years old. The training system was double-cordon, with inter-row spacing ranging from 2.7 to 3.1 m and in-row from 1.25 to 1.40 m. Bud load was fixed to 8 spurs of 2 buds/plant. Vineyards grew on mid-textured soils that rested directly on a petrocalcic horizon that the roots could not penetrate. Soil depth was therefore clearly limited, and ranged from scarcely 0.5 m to more than 1.2 m, depending on the vineyard. From fruit set (15 June) drip irrigation was applied in all vineyards using six different irrigation strategies that, according to local practices, had in common a progressive reduction in the amount of water applied as summer progressed. Rainfall did not interfere with irrigation, as it was negligible both summers. Experimental measurements in each vineyard were made on 10 homogeneous vines chosen at the beginning of the experiment. Table 1 summarizes the amount of irrigation
Table 1 Irrigation applied, soil depth, plant spacing and bunch number at each vineyard 1999 Vineyard
1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 a
2000 Irrigation amount
20
FS-V
V-V
0.08 0.08 0.08 0.08 0.15 0.20 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.51 0.51
0.00 0.00 0.00 0.00 0.12 0.00 0.17 0.17 0.17 0.22 0.22 0.22 0.22 0.22 0.29 0.29
(1) (1) (1) (1) (6) (9) (9) (9) (9) (13) (13) (13) (13) (13) (17) (17)
a
(0) (0) (0) (0) (3) (0) (3) (3) (3) (5) (5) (5) (5) (5) (5) (5)
20
V -H 0.00 0.00 0.00 0.00 0.05 0.00 0.06 0.06 0.06 0.10 0.10 0.10 0.10 0.10 0.23 0.23
(0) (0) (0) (0) (1) (0) (1) (1) (1) (3) (3) (3) (3) (3) (4) (4)
Soil depthb
Plant spacingc
Bunch numberd
Vineyard
m s m m m d d m m s m m m d d m
3.0 1.40 2.8 1.25 3.0 1.30 3.1 1.30 2.7 1.30 2.7 1.40 3.0 1.25 2.7 1.30 3.0 1.40 2.7 1.40 3.0 1.30 2.7 1.30 3.0 1.30 2.7 1.30 3.0 1.40 2.7 1.30
24.7 20.9 21.2 23.1 25.2 22.3 23.7 23.1 22.3 22.4 23.2 24 27.4 23.7 24.4 22.4
2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17
Irrigation amounts 20
FS-V
V-V
0.08 0.08 0.15 0.15 0.15 0.15 0.15 0.20 0.20 0.20 0.28 0.28 0.28 0.28 0.28 0.28 0.28
0.00 0.00 0.12 0.12 0.12 0.12 0.12 0.00 0.00 0.00 0.17 0.17 0.17 0.17 0.17 0.17 0.22
(1) (1) (6) (6) (6) (6) (6) (9) (9) (9) (9) (9) (9) (9) (9) (9) (13)
(0) (0) (3) (3) (3) (3) (3) (0) (0) (0) (3) (3) (3) (3) (3) (3) (5)
20
V -H 0.00 0.00 0.05 0.05 0.05 0.05 0.05 0.00 0.00 0.00 0.06 0.06 0.06 0.06 0.06 0.06 0.10
(0) (0) (1) (1) (1) (1) (1) (0) (0) (0) (1) (1) (1) (1) (1) (1) (3)
Soil depth
Plant spacing
Bunch number
m d s s m m s d m m m s s m m d m
2.8 1.25 3.0 1.30 2.7 1.30 2.7 1.40 3.0 1.25 3.0 1.40 3.0 1.30 2.7 1.30 3.0 1.40 2.7 1.40 3.0 1.30 2.8 1.30 2.8 1.25 3.0 1.30 3.0 1.25 2.7 1.30 3.1 1.30
23.7 24.1 22.7 21.9 22.8 23.1 19.8 22.1 24.5 21 23.4 16 20.6 22.3 23.1 22.7 24.8
Irrigation amount expressed as fraction of ETo (Penman modified), the number between brackets indicates the number of irrigation events. FS: fruit set; V: veraison; V20: 20 days after veraison; H: harvest. b Soil depth classes: s, shallow (40–60 cm); m, medium (60–90 cm); d, deep (90–150 cm). c Plant spacing in m. d Bunch number per plant.
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L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
summer (cpd-s). This value was calculated from 12 measurements that were performed at each vineyard every 5–8 days beginning 10 days after fruit set until harvest in order to monitor water stress. Leaf water potential was measured on 3–5 healthy young leaves of about 2/3 of their definitive size using a Scholander pressure bomb (P3000, Soil Moisture Corp., Santa Barbara, USA), taking into account recommendations given by Turner (1988). Harvest characteristics: in order to determine the harvest date, from early September samples of 300 berries each were taken from adjacent vines every 3–5 days to estimate berry size and sugar concentration. Harvesting took place when no significant sugar gain was found, always during the second half of September. On harvest day, yield per plant was measured and a 300-berry sample was randomly taken to estimate average berry weight (BW) and sugar concentration (SC) in every vineyard.
applied, soil depth, plant spacing and bud fertility at each vineyard. 2.2. Experimental measurements Leaf area: vine leaf area was calculated as the sum of the area of all the leaves of each vine. Individual leaf area was estimated by non-destructively measuring the length of its secondary nerves following Carbonneau (1976), since we had previously found that there is a close relationship between the sum of the length of secondary P nerves and leaf area (leaf area 2 (cm ) = 133.74 + 15.403 N; R2 = 0.948; P < 0.001; where P N is the sum of the length of secondary nerves in centimeter). This relationship was established using 200 leaves from extra adjacent vines whose area was measured using an image analysis system (WinDias, Delta-T Devices Ltd, Cambridge, UK). Crop load: crop load was estimated as berry number per unit area (BN/m2) and yield per unit area (YLD/m2). Both parameters were measured in each plant at harvest. Water status: water status of each vineyard was characterized as the mean value of predawn leaf water potential in
2.3. Data analysis Multiple regression analysis was employed to estimate the relation of BW and SC with leaf area, fruit load and water
Table 2 Fruit load, leaf area, water status and berry characteristics of the study vineyards Vineyard
LA/m2
BN/m2
cpd a 20
cpd-s
BW
SC
20
FS-V
V-V
V -H
1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16
1.73 1.30 1.44 1.50 1.92 1.18 1.44 1.42 1.74 1.87 2.28 1.88 1.84 2.10 1.69 1.98
1458 1000 744 688 1146 648 840 672 857 682 859 801 935 869 831 663
0.68 0.02 0.86 0.01 0.67 0.05 0.67 0.01 0.42 0.03 0.63 0.05 0.91 0.01 0.33 0.01 0.42 0.01 0.90 0.03 0.67 0.03 0.38 0.01 0.54 0.01 0.45 0.01 0.67 0.01 0.82 0.04
0.77 0.06 0.95 0.08 0.74 0.05 0.71 0.05 0.51 0.03 0.73 0.04 1.03 0.06 0.37 0.01 0.45 0.03 0.91 0.05 0.74 0.04 0.43 0.01 0.58 0.01 0.47 0.01 0.75 0.01 0.83 0.02
0.91 0.06 1.07 0.05 0.87 0.02 0.83 0.01 0.56 0.01 0.78 0.02 1.05 0.04 0.40 0.01 0.54 0.01 1.03 0.01 0.75 0.03 0.45 0.04 0.67 0.03 0.52 0.01 0.78 0.03 0.94 0.04
0.79 0.97 0.77 0.73 0.49 0.71 0.97 0.38 0.49 0.95 0.71 0.41 0.58 0.49 0.73 0.87
1.40 0.75 1.53 1.97 2.27 1.87 1.34 2.62 2.17 1.47 1.81 2.77 2.18 2.19 1.44 1.65
19.0 18.6 18.9 18.8 21.3 21.6 19.2 21.5 21.0 19.0 19.3 22.7 20.3 21.2 18.6 18.9
2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17
1.53 2.03 1.60 1.57 1.72 1.97 1.48 1.48 1.95 1.20 1.51 0.94 1.25 1.23 1.67 1.21 2.35
776 571 1195 828 872 1080 523 786 735 566 822 403 622 737 737 912 1106
0.43 0.01 0.43 0.03 0.75 0.02 0.72 0.03 0.72 0.04 0.42 0.01 0.51 0.02 0.50 0.01 0.49 0.03 0.51 0.02 0.79 0.02 0.91 0.03 0.73 0.01 0.75 0.02 0.43 0.01 0.48 0.03 0.67 0.02
0.52 0.03 0.47 0.04 0.8 0.03 0.8 0.05 0.8 0.03 0.52 0.01 0.51 0.02 0.54 0.01 0.49 0.02 0.54 0.04 0.89 0.03 1.01 0.02 0.82 0.01 0.88 0.01 0.48 0.01 0.52 0.01 0.77 0.02
0.53 0.02 0.52 0.01 0.92 0.07 0.89 0.08 0.83 0.04 0.53 0.02 0.57 0.02 0.65 0.01 0.57 0.02 0.66 0.03 0.93 0.01 1.04 0.01 0.87 0.02 0.88 0.02 0.53 0.01 0.55 0.01 0.84 0.01
0.51 0.47 0.80 0.80 0.78 0.49 0.54 0.58 0.53 0.59 0.83 0.98 0.78 0.84 0.49 0.51 0.74
2.17 2.50 1.45 1.82 1.54 2.52 2.17 2.09 2.24 2.19 1.31 1.17 1.62 1.63 2.27 1.81 1.94
21.6 22.0 18.9 19.1 19.5 22.3 22.3 21.8 22.8 20.0 17.1 19.0 19.3 18.5 20.8 20.1 21.6
a cpd: predawn water potential followed by standard error values; FS: fruit set; V: veraison; V20: 20 days after veraison; H: harvest; cpd-s: predawn water potential in summer.
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
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Table 3 Relationship between berry weight (g) and predawn leaf water potential in summer (cpd-s) and leaf fruit ratio expressed as LA/BN Year
N
R2
P
VIFa
Intercept
LA/BN
cpd-s b
b
b
c
P
b
b
P
1999 2000
16 17
0.920 0.859
<0.001 <0.001
1.021 1.005
2.768 3.117
2.307 2.344
0.874 0.928
<0.001 <0.001
0.032 0.016
0.301 0.206
0.001 0.054
Total
33
0.895
<0.001
1.002
2.979
2.343
0.905
<0.001
0.023
0.249
<0.001
a b c
Variance inflation factor. Non-standardized regression coefficient. Standardized regression coefficient.
status. BW regression analysis included as independent variables water potential (cpd-s), leaf area (LA/m2), berry number (BN/m2) and the ratio of the two latter parameters (LA/ BN). SC was estimated in a similar way, using as independent variables cpd-s, LA/m2, yield (YLD/m2), and the ratio LA/ YLD. The pertinence of each independent variable was evaluated using backward stepwise analysis, and the potential collinearity among independent variables was tested calculating variance inflation factor (VIF), considering 10 as the threshold for variable inclusion in the model (Neter, 1996). Relative weight of each independent variable in the model was evaluated through standardized coefficient (b) calculation. Separate analysis was performed with data from each year and the obtained equations were compared through covariance analysis. When there was no year effect, all data were pooled and the relationship recalculated. Statistical analyses were performed using SPSS v11.5 (SPSS Inc, Chicago, IL). 3. Results Table 2 includes data of LA/m2, BN/m2 and cpd evolution in summer at each vineyard. Our research has included a wide range of situations of both LA/m2 (from 0.97 to 2.35) and BN/ m2 (from 523 to 1458 berries/m2). Variability in soil depth, leaf area, fruit load, and different irrigation rates has created a broad range of situations concerning water status, ranging from low-mid stress cpd-s = 0.38 MPa) to high stress (cpd-s = 0.97 MPa). Interaction of vegetative development, fruit load and water status has led to a wide range of berry characteristics (BW ranged from hardly 0.8 to almost 2.8 g and SC from 19 to 22.58Brix). These berry characteristics embrace most harvests that are likely to be found in this type of vineyard and, therefore, the obtained results can be extended to them.
Berry weight at harvest is related to cpd-s and LA/BN in both study years, whereas LA and BN are dropped from the model (Table 3). As covariance analysis showed no year effect (Pyear = 0.681), data were pooled and a new model calculated. The model produced explained BW at harvest with a high coefficient of determination (R2corr ¼ 0:91), with no collinearity between independent variables, as VIF values were all below 1.5, far from those considered problematic (Neter, 1996). As shown in Table 3, BW was found to be positively related to cpd-s and LA/BN according to the equation: BW = 2.979 + 2.343cpd-s + 0.023 LA/BN (P < 0.001). In a similar way, SC was related to cpd-s and LA/YLD both years, whereas LA/m2 and YLD/m2 were dropped from the model (Table 4). Data from both study years were pooled and analysed together as there was no year effect (Pyear = 0.303). The constructed model estimates SC with a relatively high coefficient of determination (R2corr ¼ 0:74) and without collinearity problems (VIF < 3), showing a positive effect of cpd-s and LA/YLD on sugar concentration at harvest (SC = 24.197 + 9.011cpd-s + 0.197 LA/YLD; P < 0.001). 4. Discussion The close relationship found between cpd-s and both BW and SC allows us to state that cpd has estimated properly vineyard water status and, therefore its use may be recommended under low-mid to severe stress conditions. cpd has been widely used in earlier work since it is considered one of the best methods to measure directly plant water status under field conditions (Jones, 2004), although when stress level is low (cpd > 0.3 MPa) vine water status might be better estimated through midday stem water potential (Chone´ et al., 2001). The integration of long-term cpd values into a single value was
Table 4 Relationship between berry sugar concentration (8Brix) and predawn leaf water potential in summer (cpd-s) and leaf fruit ratio expressed as LA/YLD Year
N
R2
P
VIFa
Intercept
LA/YLD
cpd-s b
b
b
c
P
b
b
P
1999 2000
16 17
0.725 0.766
<0.001 <0.001
3.570 1.904
23.134 24.728
7.485 8.233
1.274 1.084
<0.001 <0.001
0.181 0.106
0.527 0.325
0.060 0.072
Total
33
0.736
<0.001
2.386
24.197
9.011
1.118
<0.001
0.197
0.374
0.012
a b c
Variance inflation factor. Non-standardized regression coefficient. Standardized regression coefficient.
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L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
introduced by Myers (1988) through his definition of water stress index (WSI). He reported that there was a strong relationship (R2 = 0.91) between pine trunk growth and water stress integral, over a 4-year period. Since then, the integration of long-term cpd values has been widely used in other species (Gonza´lez-Altozano and Castel, 1999; Eamus, 2003), and also in Vitis vinifera: Ginestar (1998) found that WSI and yield were strongly related, as has also been reported recently by Salo´n et al. (2004), who also found that average cpd was related to enological parameters such as berry weight and concentration of anthocyanins and phenolics in wine. In those works, vineyards grew under steadily increasing water stress conditions in a similar way to ours but when describing water regimes that consist of several stages with marked differences in water availability is attempted, cpd has to be considered separately for each crop stage as done by Marsal et al. (2000) for pear tree. The increase in BW as a consequence of higher water availability has been widely reported (e.g., Matthews and Anderson, 1988; Esteban et al., 1999), and it occurs due to an increase in turgor pressure (Matthews et al., 1987a) and in photosynthetic rate (Schultz, 2003). The effect of higher water availability on SC is slightly more complex since, despite the fact that it always implies an increase in sugar accumulation, SC may be sometimes reduced due to dilution after higher berry growth (Winkler, 1975). This explains discrepancies in earlier works. Thus, papers that compare low vs. mid stress situations often report that vines with higher water availability yield less sugared berries (Van Leeuwen and Seguin, 1994); whereas when mid and high stress situations are confronted, the reported results agree with ours: the less sugared berries are obtained when water availability is low (e.g., Matthews and Anderson, 1988). Our results indicate that ‘Tempranillo’ vines, in the studied range of cpd-s, and with the same fruit load, produced berries with higher SC as water stress was lessened. Berry weight was also was related to LA/BN, though the weight of LA/BN in the equation was much lower (bcpd-s = 0.905 versus bLA/BN = 0.249). The LA/BN ratio synthesizes into a single parameter the balance between sources and sinks and, despite many previous works which have shown that berry size increases when LA increases (CandolfiVasconcellos and Koblet, 1990) and BN decreases (Dokoozlian and Hirschfelt, 1995), we are not aware of any previous report integrating these effects into a single parameter. Under our conditions, this ratio has estimated variations in BW better than LA/m2 and BN/m2 together. Therefore, we suggest that LA/BN could be an interesting parameter to be considered in research works that aim to study factors affecting berry growth. Sugar concentration has depended on LA/YLD, though its relative importance in the equation was clearly less than that of bcpd-s (bcpd-s = 1.118 versus bLA/YLD = 0.374). The effect of LA and BN on SC has been extensively reported (CandolfiVasconcellos and Koblet, 1990), and LA/YLD ratio is widely employed as an estimator of vineyard potential to ripen berries properly (Howell, 2001). The relatively small weight that LA/ YLD has shown in our work for SC estimation suggests that, in climates where light interception is not the limiting factor,
photosynthesis depends largely on water status, and it probably explains discrepancies found among the LA/YLD minimum values that had been previously reported as necessary to reach proper harvest maturity, values which range from scarcely 5–10 cm2/g (Kliewer and Antcliff, 1970) up to 15–17 cm2/g (Winkler, 1930; Buttrose, 1966). 5. Conclusion The results here presented allow us to state that BW and SC can be well managed through modifications in the water regime and in the source/sink ratio in vineyards in semiarid areas. However, as modifications in water regime have shown to affect BW and SC much more intensively, the highest attention in these areas should be paid to irrigation management, seeking the degree of stress that allows optimizing the combination of yield and berry quality in each situation. References Boss, P.K., Davies, C., 2001. Molecular biology of sugar and anthocyanin accumulation in grape berries. In: Roubelakis-Angelakis, K.A. (Ed.), Molecular Biology and Biotechnology of the Grapevine. Kluwer Academic Publishers, Dordrecht, The Nederlands, pp. 1–57. Buttrose, M.S., 1966. The effect of reducing leaf area on the growth of roots, stems and berries of Gordo grape vines. Vitis 5, 455–464. Candolfi-Vasconcellos, M.C., Koblet, W., 1990. Yield, fruit quality, bud fertility and starch reserves as a function of leaf removal in Vitis vinifera—evidence of compensation and stress recovering. Vitis 29, 199–221. Carbonneau, A., 1976. Principes et me´thodes de mesure de la surface foliaire. Essai de caracte´risation des types de feuilles dans le genre Vitis. Annals Ame´liorament des Plantes 26, 327–343. Champagnol, F., 1993. La dimension des baies, facteur de qualite´ de la vendage? Prog. Agric. Viticult. 110, 11–16. Chone´, X., Van Leeuwen, C., Dubourdieu, D., Gaudillere, J.P., 2001. Stem water potential is a sensitive indicator of grapevine water status. Ann. Bot. 87, 477–483. Dokoozlian, N.K., Hirschfelt, D.J., 1995. The influence of cluster thinning at various stages of fruit development on flame seedless table grapes. Am. J. Enol. Viticult. 46, 429–436. Dokoozlian, N.K., Kliewer, W.M., 1995. The light environment within grapevine canopies. II. Influence of leaf area density on fruit zone light environment and some canopy assessment parameters. Am. J. Enol. Viticult. 46, 219–226. Dokoozlian, N.K., Kliewer, W.M., 1996. Influence of light on grape berry growth and composition varies during fruit development. J. Am. Soc. Hort. Sci. 121, 869–874. Eamus, D., 2003. How does ecosystem water balance affect net primary productivity of woody ecosystems? Funct. Plant Biol. 30, 187–205. Esteban, M.A., Villanueva, M.J., Lissarrague, J.R., 1999. Effect of irrigation on changes in berry composition of Tempranillo during maturation: sugars, organic acids and mineral elements. Am. J. Enol. Viticult. 50, 418–433. Ginestar, C., 1998. Use of sap-flow sensors to schedule vineyard irrigation. II. Effects of post-veraison water deficits on composition of shiraz grapes. Am. J. Enol. Viticult. 49, 421–428. Gonza´lez-Altozano, P., Castel, J.R., 1999. Regulated deficit irrigation in ‘Clementina de Nules’ citrus trees. I. Yield and fruit quality effects. J. Hort. Sci. Biotechnol. 74, 706–713. Howell, G.S., 2001. Sustainable grape productivity and the growth-yield relationship: a review. Am. J. Enol. Viticult. 52, 165–174. Jones, H.G., 2004. Irrigation scheduling: advantages and pitfalls of plant-based methods. J. Exp. Bot. 55, 2427–2436.
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65 Kliewer, W.M., Antcliff, A.J., 1970. Influence of defoliation, leaf darkening, and cluster shading on the growth and composition of Sultana grapes. Am. J. Enol. Viticult. 21, 26–36. Kliewer, W.M., Lider, L.A., 1970. Effects of day temperature and light intensity on growth and composition of Vitis vinifera L. fruits. J. Am. Soc. Hort. Sci. 95, 766–769. Marsal, J., Rapoport, H.F., Manrique, T., Girona, J., 2000. Pear fruit growth under regulated deficit irrigation in container-grown trees. Sci. Hort. 85, 243–259. Matthews, M.A., Anderson, M.M., 1988. Fruit ripening in Vitis vinifera L.: responses to seasonal water deficits. Am. J. Enol. Viticult. 39, 313–320. Matthews, M.A., Cheng, G., Weinbaum, S.A., 1987a. Changes in water potential and dermal extensibility during grape berry development. J. Am. Soc. Hort. Sci. 112, 314–319. Matthews, M.E., Anderson, M.M., Schultz, H.R., 1987b. Phenological and growth responses to early and late season water deficits in Cabernet franc. Vitis 26, 147–160. Medrano, H., Escalona, J.M., Cifre, J., Bota, J., Flexas, J., 2003. A ten-year study on the physiology of two Spanish grapevine cultivars under field conditions: effects of water availability from leaf photosynthesis to grape yield and quality. Funct. Plant Biol. 30, 607–619. Myers, B.J., 1988. Water stress integral—a link between short-term stress and long-term growth. Tree Physiol. 4, 315–323. Neter, J., 1996. Applied Linear Regression Models. Irwin, Chicago, USA. Pirie, A.J.G., Mullins, M.G., 1977. Interrelationships of sugars, anthocyanins, total phenols and dry weight in the skin of the grape berries during ripening. Am. J. Enol. Viticult. 28, 204–209.
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Roby, G., Harbertson, J.F., Adams, D.A., Matthews, M.A., 2004. Berry size and vine water deficits as factors in winegrape composition: anthocyanins and tannins. Aust. J. Grape Wine Res. 10, 100–107. Salo´n, J.L., Me´ndez, J.V., Chirivella, C., Castel, J.R., 2004. Irrigation and wine quality of Vitis vinifera cv. Bobal in Requena, Spain. Acta Hort. 646, 167–174. Schultz, H.R., 2003. Differences in hydraulic architecture account for nearisohydric and anisohydric behaviour of two field-grown Vitis vinifera L. cultivars during drought. Plant Cell Environ. 26, 1393–1405. Singleton, V.L., 1972. Effects on red wine quality of removing juice before fermentation to simulate variation in berry size. Am. J. Enol. Viticult. 23, 106–113. Sommer, K.J., Clingeleffer, P.R., 1995. Vine canopy development and carbohydrate partitioning is influenced by pruning. In: Proceedings of the Ninth Australian Wine Industry Technical Conference, Winetitles, pp. 123–127. Turner, N.C., 1988. Measurement of plant water status by the pressure chamber technique. Irr. Sci. 9, 289–308. Ussahatanonta, S., Jackson, D.I., Rowe, R.N., 1996. Effects of nutrient and water stress on vegetative and reproductive growth in Vitis vinifera L. Aust. J. Grape Wine Res. 2, 64–69. Van Leeuwen, C., Seguin, G., 1994. Incidences de l’alimentation en eau de la vigne, aprecie´e par l’etat hydrique du feuillage, sur le de´veloppement de l’appareil ve´ge´tatif et la maturation du raisin (Vitis vinifera var. ‘Cabernet Franc’). J. Int. Sci. Vigne Vin. 28, 81–110. Winkler, A.J., 1930. The relation of number of leaves to quality and size of table grapes. Proc. Am. Soc. Hort. Sci. 27, 158–160. Winkler, A.J., 1975. General Viticulture. University of California Press.
Water status, leaf area and fruit load influence on berry weight and sugar accumulation of cv. ‘Tempranillo’ under semiarid conditions Luis G. Santesteban *, J. Bernardo Royo Departamento de Produccio´n Agraria, Universidad Pu´blica de Navarra, Campus de Arrosadia, 31006 Pamplona, Spain Received 8 March 2005; received in revised form 13 September 2005; accepted 7 March 2006
Abstract Berry weight (BW) and sugar concentration (SC) are relevant indices in viticulture since they can be easily measured and, when considered together, give a relatively fair estimation of grape quality. This work aims to evaluate the influence of water availability, leaf area and fruit load on BW and SC, estimating the relative importance of these factors. Leaf area (LA), berry number (BN), yield (YLD), water potential in summer (cpds), BW and SC were measured in 16 and 17 ‘Tempranillo’ vineyards in 1999 and 2000, respectively. In all the vineyards, according to local practices, the irrigation amount decreased as summer progressed. The study vineyards comprised a broad range of situations concerning leaf area, fruit load and water status in summer. Average leaf water potential in summer and LA/BN ratio, when considered together, estimated properly BW (R2 = 0.91; P < 0.001) and, in a similar way, cpd-s and LA/YLD ratio estimated SC (R2 = 0.74; P < 0.001). The relative weight of cpd-s in both relationships was much higher than that of any of the LA:fruit ratios, showing that, under semiarid conditions, water availability plays the main role in regulation of berry growth and sugar accumulation and, therefore, the highest attention should be paid in these areas to irrigation management, seeking the degree of stress that allows optimizing the combination of yield and berry quality in each situation. # 2006 Elsevier B.V. All rights reserved. Keywords: Vitis vinifera L.; Plant water relations; Leaf water potential; Leaf area; Fruit load; Berry quality
1. Introduction Wine grape quality cannot be easily defined, as it comprises many concepts, some of difficult objective determination and others whose estimation requires analyzing many chemical compounds that cannot be routinely measured throughout the ripening cycle. Nevertheless, grape growers need some simple and measurable parameters that enable them to adjust vineyard management practices in order to achieve maximum harvest quality. Berry size and sugar concentration are easy to measure and, although cannot themselves evaluate grape quality accurately, they are good predictors, as most satisfying harvests are usually those with small berries and high sugar concentration (Champagnol, 1993). These berries usually produce quality wine as they have a high skin-pulp ratio (Singleton, 1972; Roby et al., 2004) and also due to the existing linkage
* Corresponding author. Tel.: +34 948 169718. E-mail address: [email protected] (L.G. Santesteban). 0304-4238/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2006.03.003
between the sugar and phenolics accumulation processes (Pirie and Mullins, 1977; Boss and Davies, 2001). Berry size at harvest depends on many factors which modify berry growth at any stage of development, mainly environmental conditions (Dokoozlian and Kliewer, 1996), mineral nutrition (Ussahatanonta et al., 1996), fruit load (Dokoozlian and Hirschfelt, 1995), leaf area (Candolfi-Vasconcellos and Koblet, 1990) and water status (Matthews et al., 1987b; Medrano et al., 2003). The effect of these factors is not the same at every stage of berry development, being much more relevant in Stage I, when cell division takes place. In a similar way, sugar accumulation depends on many factors such as light (Dokoozlian and Kliewer, 1995), temperature (Kliewer and Lider, 1970), mineral nutrition (Ussahatanonta et al., 1996), carbohydrate level in the permanent structures of the plant (Sommer and Clingeleffer, 1995), leaf area (Candolfi-Vasconcellos and Koblet, 1990), fruit load (Dokoozlian and Hirschfelt, 1995) and water availability. Water availability affects berry sugar concentration in a relatively complex way as, sometimes, higher availability implies higher sugar concentration as a conse-
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
61
concentration at harvest in Vitis vinifera cv. ‘Tempranillo’, under the semiarid climatic conditions typical of southern Europe vineyards. 2. Materials and methods 2.1. Plant material and experimental design
Fig. 1. Monthly rainfall (R) and mean temperature (T) in the average year compared with 1999 and 2000.
quence of higher photosynthetic activity (Matthews and Anderson, 1988); whereas in other situations it implies lower sugar concentration due to the dilution of sugars that occurs as a consequence of increased berry growth (Van Leeuwen and Seguin, 1994). The effect of the above outlined factors is particularly relevant during Stage III of berry development. However, the conditions in earlier stages may also affect sugar concentration according to their effect on both the amount of storage carbohydrates in permanent structures and, particularly, on berry size. The aim of this work is to evaluate the effect of water status, leaf area, and crop load on berry size and sugar
The study was carried out in 1999 and 2000 in southern Navarre vineyards in Spain (428 N, 08460 W; altitude: 300–400 m), a region characterized by a semiarid climate (Bs type in Koppen’s classification; P < 350 mm; ETPPenman > 1150 mm). Climatic conditions during 1999 and 2000 were similar to the average (Fig. 1). The vineyards were all planted with a ‘Tempranillo’/110 Richter variety/rootstock combination, and were 5–8 years old. The training system was double-cordon, with inter-row spacing ranging from 2.7 to 3.1 m and in-row from 1.25 to 1.40 m. Bud load was fixed to 8 spurs of 2 buds/plant. Vineyards grew on mid-textured soils that rested directly on a petrocalcic horizon that the roots could not penetrate. Soil depth was therefore clearly limited, and ranged from scarcely 0.5 m to more than 1.2 m, depending on the vineyard. From fruit set (15 June) drip irrigation was applied in all vineyards using six different irrigation strategies that, according to local practices, had in common a progressive reduction in the amount of water applied as summer progressed. Rainfall did not interfere with irrigation, as it was negligible both summers. Experimental measurements in each vineyard were made on 10 homogeneous vines chosen at the beginning of the experiment. Table 1 summarizes the amount of irrigation
Table 1 Irrigation applied, soil depth, plant spacing and bunch number at each vineyard 1999 Vineyard
1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 a
2000 Irrigation amount
20
FS-V
V-V
0.08 0.08 0.08 0.08 0.15 0.20 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.51 0.51
0.00 0.00 0.00 0.00 0.12 0.00 0.17 0.17 0.17 0.22 0.22 0.22 0.22 0.22 0.29 0.29
(1) (1) (1) (1) (6) (9) (9) (9) (9) (13) (13) (13) (13) (13) (17) (17)
a
(0) (0) (0) (0) (3) (0) (3) (3) (3) (5) (5) (5) (5) (5) (5) (5)
20
V -H 0.00 0.00 0.00 0.00 0.05 0.00 0.06 0.06 0.06 0.10 0.10 0.10 0.10 0.10 0.23 0.23
(0) (0) (0) (0) (1) (0) (1) (1) (1) (3) (3) (3) (3) (3) (4) (4)
Soil depthb
Plant spacingc
Bunch numberd
Vineyard
m s m m m d d m m s m m m d d m
3.0 1.40 2.8 1.25 3.0 1.30 3.1 1.30 2.7 1.30 2.7 1.40 3.0 1.25 2.7 1.30 3.0 1.40 2.7 1.40 3.0 1.30 2.7 1.30 3.0 1.30 2.7 1.30 3.0 1.40 2.7 1.30
24.7 20.9 21.2 23.1 25.2 22.3 23.7 23.1 22.3 22.4 23.2 24 27.4 23.7 24.4 22.4
2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17
Irrigation amounts 20
FS-V
V-V
0.08 0.08 0.15 0.15 0.15 0.15 0.15 0.20 0.20 0.20 0.28 0.28 0.28 0.28 0.28 0.28 0.28
0.00 0.00 0.12 0.12 0.12 0.12 0.12 0.00 0.00 0.00 0.17 0.17 0.17 0.17 0.17 0.17 0.22
(1) (1) (6) (6) (6) (6) (6) (9) (9) (9) (9) (9) (9) (9) (9) (9) (13)
(0) (0) (3) (3) (3) (3) (3) (0) (0) (0) (3) (3) (3) (3) (3) (3) (5)
20
V -H 0.00 0.00 0.05 0.05 0.05 0.05 0.05 0.00 0.00 0.00 0.06 0.06 0.06 0.06 0.06 0.06 0.10
(0) (0) (1) (1) (1) (1) (1) (0) (0) (0) (1) (1) (1) (1) (1) (1) (3)
Soil depth
Plant spacing
Bunch number
m d s s m m s d m m m s s m m d m
2.8 1.25 3.0 1.30 2.7 1.30 2.7 1.40 3.0 1.25 3.0 1.40 3.0 1.30 2.7 1.30 3.0 1.40 2.7 1.40 3.0 1.30 2.8 1.30 2.8 1.25 3.0 1.30 3.0 1.25 2.7 1.30 3.1 1.30
23.7 24.1 22.7 21.9 22.8 23.1 19.8 22.1 24.5 21 23.4 16 20.6 22.3 23.1 22.7 24.8
Irrigation amount expressed as fraction of ETo (Penman modified), the number between brackets indicates the number of irrigation events. FS: fruit set; V: veraison; V20: 20 days after veraison; H: harvest. b Soil depth classes: s, shallow (40–60 cm); m, medium (60–90 cm); d, deep (90–150 cm). c Plant spacing in m. d Bunch number per plant.
62
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
summer (cpd-s). This value was calculated from 12 measurements that were performed at each vineyard every 5–8 days beginning 10 days after fruit set until harvest in order to monitor water stress. Leaf water potential was measured on 3–5 healthy young leaves of about 2/3 of their definitive size using a Scholander pressure bomb (P3000, Soil Moisture Corp., Santa Barbara, USA), taking into account recommendations given by Turner (1988). Harvest characteristics: in order to determine the harvest date, from early September samples of 300 berries each were taken from adjacent vines every 3–5 days to estimate berry size and sugar concentration. Harvesting took place when no significant sugar gain was found, always during the second half of September. On harvest day, yield per plant was measured and a 300-berry sample was randomly taken to estimate average berry weight (BW) and sugar concentration (SC) in every vineyard.
applied, soil depth, plant spacing and bud fertility at each vineyard. 2.2. Experimental measurements Leaf area: vine leaf area was calculated as the sum of the area of all the leaves of each vine. Individual leaf area was estimated by non-destructively measuring the length of its secondary nerves following Carbonneau (1976), since we had previously found that there is a close relationship between the sum of the length of secondary P nerves and leaf area (leaf area 2 (cm ) = 133.74 + 15.403 N; R2 = 0.948; P < 0.001; where P N is the sum of the length of secondary nerves in centimeter). This relationship was established using 200 leaves from extra adjacent vines whose area was measured using an image analysis system (WinDias, Delta-T Devices Ltd, Cambridge, UK). Crop load: crop load was estimated as berry number per unit area (BN/m2) and yield per unit area (YLD/m2). Both parameters were measured in each plant at harvest. Water status: water status of each vineyard was characterized as the mean value of predawn leaf water potential in
2.3. Data analysis Multiple regression analysis was employed to estimate the relation of BW and SC with leaf area, fruit load and water
Table 2 Fruit load, leaf area, water status and berry characteristics of the study vineyards Vineyard
LA/m2
BN/m2
cpd a 20
cpd-s
BW
SC
20
FS-V
V-V
V -H
1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16
1.73 1.30 1.44 1.50 1.92 1.18 1.44 1.42 1.74 1.87 2.28 1.88 1.84 2.10 1.69 1.98
1458 1000 744 688 1146 648 840 672 857 682 859 801 935 869 831 663
0.68 0.02 0.86 0.01 0.67 0.05 0.67 0.01 0.42 0.03 0.63 0.05 0.91 0.01 0.33 0.01 0.42 0.01 0.90 0.03 0.67 0.03 0.38 0.01 0.54 0.01 0.45 0.01 0.67 0.01 0.82 0.04
0.77 0.06 0.95 0.08 0.74 0.05 0.71 0.05 0.51 0.03 0.73 0.04 1.03 0.06 0.37 0.01 0.45 0.03 0.91 0.05 0.74 0.04 0.43 0.01 0.58 0.01 0.47 0.01 0.75 0.01 0.83 0.02
0.91 0.06 1.07 0.05 0.87 0.02 0.83 0.01 0.56 0.01 0.78 0.02 1.05 0.04 0.40 0.01 0.54 0.01 1.03 0.01 0.75 0.03 0.45 0.04 0.67 0.03 0.52 0.01 0.78 0.03 0.94 0.04
0.79 0.97 0.77 0.73 0.49 0.71 0.97 0.38 0.49 0.95 0.71 0.41 0.58 0.49 0.73 0.87
1.40 0.75 1.53 1.97 2.27 1.87 1.34 2.62 2.17 1.47 1.81 2.77 2.18 2.19 1.44 1.65
19.0 18.6 18.9 18.8 21.3 21.6 19.2 21.5 21.0 19.0 19.3 22.7 20.3 21.2 18.6 18.9
2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17
1.53 2.03 1.60 1.57 1.72 1.97 1.48 1.48 1.95 1.20 1.51 0.94 1.25 1.23 1.67 1.21 2.35
776 571 1195 828 872 1080 523 786 735 566 822 403 622 737 737 912 1106
0.43 0.01 0.43 0.03 0.75 0.02 0.72 0.03 0.72 0.04 0.42 0.01 0.51 0.02 0.50 0.01 0.49 0.03 0.51 0.02 0.79 0.02 0.91 0.03 0.73 0.01 0.75 0.02 0.43 0.01 0.48 0.03 0.67 0.02
0.52 0.03 0.47 0.04 0.8 0.03 0.8 0.05 0.8 0.03 0.52 0.01 0.51 0.02 0.54 0.01 0.49 0.02 0.54 0.04 0.89 0.03 1.01 0.02 0.82 0.01 0.88 0.01 0.48 0.01 0.52 0.01 0.77 0.02
0.53 0.02 0.52 0.01 0.92 0.07 0.89 0.08 0.83 0.04 0.53 0.02 0.57 0.02 0.65 0.01 0.57 0.02 0.66 0.03 0.93 0.01 1.04 0.01 0.87 0.02 0.88 0.02 0.53 0.01 0.55 0.01 0.84 0.01
0.51 0.47 0.80 0.80 0.78 0.49 0.54 0.58 0.53 0.59 0.83 0.98 0.78 0.84 0.49 0.51 0.74
2.17 2.50 1.45 1.82 1.54 2.52 2.17 2.09 2.24 2.19 1.31 1.17 1.62 1.63 2.27 1.81 1.94
21.6 22.0 18.9 19.1 19.5 22.3 22.3 21.8 22.8 20.0 17.1 19.0 19.3 18.5 20.8 20.1 21.6
a cpd: predawn water potential followed by standard error values; FS: fruit set; V: veraison; V20: 20 days after veraison; H: harvest; cpd-s: predawn water potential in summer.
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
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Table 3 Relationship between berry weight (g) and predawn leaf water potential in summer (cpd-s) and leaf fruit ratio expressed as LA/BN Year
N
R2
P
VIFa
Intercept
LA/BN
cpd-s b
b
b
c
P
b
b
P
1999 2000
16 17
0.920 0.859
<0.001 <0.001
1.021 1.005
2.768 3.117
2.307 2.344
0.874 0.928
<0.001 <0.001
0.032 0.016
0.301 0.206
0.001 0.054
Total
33
0.895
<0.001
1.002
2.979
2.343
0.905
<0.001
0.023
0.249
<0.001
a b c
Variance inflation factor. Non-standardized regression coefficient. Standardized regression coefficient.
status. BW regression analysis included as independent variables water potential (cpd-s), leaf area (LA/m2), berry number (BN/m2) and the ratio of the two latter parameters (LA/ BN). SC was estimated in a similar way, using as independent variables cpd-s, LA/m2, yield (YLD/m2), and the ratio LA/ YLD. The pertinence of each independent variable was evaluated using backward stepwise analysis, and the potential collinearity among independent variables was tested calculating variance inflation factor (VIF), considering 10 as the threshold for variable inclusion in the model (Neter, 1996). Relative weight of each independent variable in the model was evaluated through standardized coefficient (b) calculation. Separate analysis was performed with data from each year and the obtained equations were compared through covariance analysis. When there was no year effect, all data were pooled and the relationship recalculated. Statistical analyses were performed using SPSS v11.5 (SPSS Inc, Chicago, IL). 3. Results Table 2 includes data of LA/m2, BN/m2 and cpd evolution in summer at each vineyard. Our research has included a wide range of situations of both LA/m2 (from 0.97 to 2.35) and BN/ m2 (from 523 to 1458 berries/m2). Variability in soil depth, leaf area, fruit load, and different irrigation rates has created a broad range of situations concerning water status, ranging from low-mid stress cpd-s = 0.38 MPa) to high stress (cpd-s = 0.97 MPa). Interaction of vegetative development, fruit load and water status has led to a wide range of berry characteristics (BW ranged from hardly 0.8 to almost 2.8 g and SC from 19 to 22.58Brix). These berry characteristics embrace most harvests that are likely to be found in this type of vineyard and, therefore, the obtained results can be extended to them.
Berry weight at harvest is related to cpd-s and LA/BN in both study years, whereas LA and BN are dropped from the model (Table 3). As covariance analysis showed no year effect (Pyear = 0.681), data were pooled and a new model calculated. The model produced explained BW at harvest with a high coefficient of determination (R2corr ¼ 0:91), with no collinearity between independent variables, as VIF values were all below 1.5, far from those considered problematic (Neter, 1996). As shown in Table 3, BW was found to be positively related to cpd-s and LA/BN according to the equation: BW = 2.979 + 2.343cpd-s + 0.023 LA/BN (P < 0.001). In a similar way, SC was related to cpd-s and LA/YLD both years, whereas LA/m2 and YLD/m2 were dropped from the model (Table 4). Data from both study years were pooled and analysed together as there was no year effect (Pyear = 0.303). The constructed model estimates SC with a relatively high coefficient of determination (R2corr ¼ 0:74) and without collinearity problems (VIF < 3), showing a positive effect of cpd-s and LA/YLD on sugar concentration at harvest (SC = 24.197 + 9.011cpd-s + 0.197 LA/YLD; P < 0.001). 4. Discussion The close relationship found between cpd-s and both BW and SC allows us to state that cpd has estimated properly vineyard water status and, therefore its use may be recommended under low-mid to severe stress conditions. cpd has been widely used in earlier work since it is considered one of the best methods to measure directly plant water status under field conditions (Jones, 2004), although when stress level is low (cpd > 0.3 MPa) vine water status might be better estimated through midday stem water potential (Chone´ et al., 2001). The integration of long-term cpd values into a single value was
Table 4 Relationship between berry sugar concentration (8Brix) and predawn leaf water potential in summer (cpd-s) and leaf fruit ratio expressed as LA/YLD Year
N
R2
P
VIFa
Intercept
LA/YLD
cpd-s b
b
b
c
P
b
b
P
1999 2000
16 17
0.725 0.766
<0.001 <0.001
3.570 1.904
23.134 24.728
7.485 8.233
1.274 1.084
<0.001 <0.001
0.181 0.106
0.527 0.325
0.060 0.072
Total
33
0.736
<0.001
2.386
24.197
9.011
1.118
<0.001
0.197
0.374
0.012
a b c
Variance inflation factor. Non-standardized regression coefficient. Standardized regression coefficient.
64
L.G. Santesteban, J.B. Royo / Scientia Horticulturae 109 (2006) 60–65
introduced by Myers (1988) through his definition of water stress index (WSI). He reported that there was a strong relationship (R2 = 0.91) between pine trunk growth and water stress integral, over a 4-year period. Since then, the integration of long-term cpd values has been widely used in other species (Gonza´lez-Altozano and Castel, 1999; Eamus, 2003), and also in Vitis vinifera: Ginestar (1998) found that WSI and yield were strongly related, as has also been reported recently by Salo´n et al. (2004), who also found that average cpd was related to enological parameters such as berry weight and concentration of anthocyanins and phenolics in wine. In those works, vineyards grew under steadily increasing water stress conditions in a similar way to ours but when describing water regimes that consist of several stages with marked differences in water availability is attempted, cpd has to be considered separately for each crop stage as done by Marsal et al. (2000) for pear tree. The increase in BW as a consequence of higher water availability has been widely reported (e.g., Matthews and Anderson, 1988; Esteban et al., 1999), and it occurs due to an increase in turgor pressure (Matthews et al., 1987a) and in photosynthetic rate (Schultz, 2003). The effect of higher water availability on SC is slightly more complex since, despite the fact that it always implies an increase in sugar accumulation, SC may be sometimes reduced due to dilution after higher berry growth (Winkler, 1975). This explains discrepancies in earlier works. Thus, papers that compare low vs. mid stress situations often report that vines with higher water availability yield less sugared berries (Van Leeuwen and Seguin, 1994); whereas when mid and high stress situations are confronted, the reported results agree with ours: the less sugared berries are obtained when water availability is low (e.g., Matthews and Anderson, 1988). Our results indicate that ‘Tempranillo’ vines, in the studied range of cpd-s, and with the same fruit load, produced berries with higher SC as water stress was lessened. Berry weight was also was related to LA/BN, though the weight of LA/BN in the equation was much lower (bcpd-s = 0.905 versus bLA/BN = 0.249). The LA/BN ratio synthesizes into a single parameter the balance between sources and sinks and, despite many previous works which have shown that berry size increases when LA increases (CandolfiVasconcellos and Koblet, 1990) and BN decreases (Dokoozlian and Hirschfelt, 1995), we are not aware of any previous report integrating these effects into a single parameter. Under our conditions, this ratio has estimated variations in BW better than LA/m2 and BN/m2 together. Therefore, we suggest that LA/BN could be an interesting parameter to be considered in research works that aim to study factors affecting berry growth. Sugar concentration has depended on LA/YLD, though its relative importance in the equation was clearly less than that of bcpd-s (bcpd-s = 1.118 versus bLA/YLD = 0.374). The effect of LA and BN on SC has been extensively reported (CandolfiVasconcellos and Koblet, 1990), and LA/YLD ratio is widely employed as an estimator of vineyard potential to ripen berries properly (Howell, 2001). The relatively small weight that LA/ YLD has shown in our work for SC estimation suggests that, in climates where light interception is not the limiting factor,
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