Aims: Agroscope investigated the impact of the leaf-to-fruit ratio on nitrogen (N) partitioning in grapevine following a foliar urea application with the aim of increasing the yeast assimilable nitrogen (YAN) concentration in the must.
Methods and results: Foliar urea was applied to field-grown Vitis vinifera L. cv. Chasselas grapevines as part of a split-plot trial with two variable parameters: canopy height (90 or 150 cm) and fruit load (5 or 10 clusters per vine). Foliar application of 20 kg/ha of 15N-labelled urea (10 atom% 15N) was performed at veraison. The isotope labelling method allowed to observe foliar-N partitioning in the plant at harvest. The leaf-to-fruit ratio varied between 0.4 and 1.6 m2/kg, and strongly impacted the N partitioning in the grapevines. Total N and foliar-N partitioning was mainly affected by the variation of canopy height. The YAN concentration varied from 143 to 230 mg/L (+60 %) depending on the leaf area. An oversized canopy (+31 %DW) induced a decrease in the total N concentration of all organs (-17 %), and a decrease in YAN quantity in the must in particular (-53 %). A negative correlation between the N concentration and the carbon isotope discrimination (CID) could be pointed out in a condition of no water restriction (e.g., R2 = 0.65 in the must).
Conclusion: An excessive leaf area can induce YAN deficiency in the must. Thus, a balanced leaf-to-fruit ratio – between 1 and 1.2 m2/kg – should be maintained to guarantee grape maturity, YAN accumulation in the must and N recovery in the reserve organs.
Significance and impact of the study: The results of this study encourage further research to understand the role of other physiological parameters that affect N partitioning in the grapevine – YAN accumulation in the must in particular – and add new perspectives for N management practices in the vineyard.
Nitrogen (N) represents 1 to 4 % of the dry weight of the vine and plays a key role in the plant development, as a component of proteins, DNA and chlorophyll. The optimization of N fertilisation practices in viticulture is required for quality and sustainability of the production while preserving the environment (Champagnol, 1984). In particular, the concentration of yeast assimilable nitrogen (YAN) in the must at harvest is a relevant parameter used to determine wine quality because both its concentration and composition affect the alcoholic fermentation and the formation of aroma compounds (Rapp and Versini, 1991; Bell and Henschke, 2005). Extreme YAN deficiency can even induce atypical ageing off-flavours in wine (Linsenmeier et al., 2007; Reynard et al., 2011). The YAN concentration is usually enhanced by the addition of diammonium phosphate to the must to improve the fermentation kinetics, but it does not appear to have any beneficial effect on wine aroma (Lorenzini and Vuichard, 2012). Indeed, the main source of aroma precursors in the must are free amino-acids (AA), which represent approximately 80 wt.% of the YAN (Ribéreau-Gayon et al., 2004). Hence, it is necessary to correct the YAN concentration, including the AA concentrations, early in the season through the foliar application of urea to grapevine canopies (Lacroux et al., 2008; Dufourcq et al., 2009; Hannam et al., 2013; Nisbet et al., 2014). However, Spring et al. (2011) observed cases of N-deficient musts produced from vigorous grapevines, despite a high level of N in the soil and an absence of water restriction. Knowing that N supply impacts the development of biomass and N allocation in the vine (Metay et al., 2014), the uptake and subsequent translocation of N are key processes in the development of good wine after the application of foliar fertiliser (Porro et al., 2010). As a consequence, the technical and physiological parameters that can improve the efficiency of foliar urea fertilisation, such as application timing (Conradie, 2005; Lasa et al., 2012), canopy height and yield (Murisier and Zufferey, 1997; Spring et al., 2011), must be optimized to increase the YAN concentration in the must at harvest. The YAN concentration in must was found to be higher when urea was applied to the vine at veraison (Verdenal et al., 2015). Though, very few studies have determined the impact of the leaf-to-fruit ratio on N partitioning with a focus on the YAN accumulation in the must (Kliewer and Ough, 1970; Schreiber et al., 2002; Peyrot des Gachons et al., 2005). The leaf-to-fruit ratio, i.e., the light-exposed leaf area per fruit quantity (m2/kg), is known as an essential parameter in grape growing: on one hand, the leaf area, as a source of nutrients, affects the leaf gas exchanges and the quantity of carbohydrates available through photosynthesis for vegetative growth and grape maturation; on the other hand, the grapes, as a sink of nutrients, affect the quantity of C and N required for their maturation (Murisier and Zufferey, 1997; Morinaga et al., 2003; Kliewer and Dokoozlian, 2005; Etchebarne et al., 2010). A balanced grapevine is one that can produce mature grapes while building its reserves for the next year (Champagnol, 1984; Zufferey et al., 2012).
The aim of this study was to gain a better understanding of N partitioning in the vine at harvest as a function of canopy height and fruit load after foliar urea application at veraison.
Materials and methods
1. Vineyard site
The experiment was conducted in 2013 at Agroscope (Pully, CH) on field-grown Vitis vinifera L. cv. Chasselas (clone 800) grafted onto rootstock 3309C. During the vine growing season (April-October), the local average temperature was 15.7°C and the total precipitation was 930 mm (2013 data, Pully meteorological station, www.agrometeo.ch). July was the warmest month, with an average temperature of 21.8°C, and August was the driest month, with only 50 mm of precipitation. The vineyard soil was a noncalcareous colluvial soil containing 17 wt.% clay, 46 wt.% sand and 4 wt.% total carbonate as CaCO3. The soil organic matter content was 1.7 wt.%. In May, 30 kg N/ha were applied to the soil and were the only fertilisation before foliar urea was applied in this study. There were no visual symptoms of deficiencies of essential elements such as P, K, Mg or B during the whole season of the experiment. The water-holding capacity was high and non-limiting (> 250 mm). The vines were planted in 2007 at a density of 5880 vines/ha (2 x 0.85 m). Similar to regional practices, the vines were pruned using a single Guyot training system (vertical shoot-positioning) with 7 shoots/plant, and lateral shoots were removed from the bunch area.
2. Experimental design
Five treatments (A, B, C, D, E) consisting of five vines each – each vine being a replicate – were established as presented in Table 1, with the aim of obtaining a large range of leaf-to-fruit ratios. Two factors of variation were chosen, namely, 1) canopy height: during vegetation development, the canopy was trimmed at two different heights (150 cm in treatments A, B and C; 90 cm in treatments D and E), and 2) yield: two yield restrictions were applied (5 bunches per vine in treatments A, B and D; 10 bunches per vine in treatments C and E). Bunch thinning was performed in July before bunch closure. N (5 kg/ha) was applied once a week for four weeks (total 20 kg/ha) in the form of 15N-labelled urea (10 atom% 15N, CO(15NH2)2, Sigma-Aldrich, St-Louis, MO, USA). The period of N application covered the period of veraison. N was applied to the canopy (treatments B, C, D and E) at a dilution rate of 3.3 % (w/v). The method of isotopic labelling allowed the tracking of urea N in the plant and the description of its partitioning in the grapevine organs depending on the leaf-to-fruit ratio. The urea application dates were 08/14, 08/21, 08/26 and 09/02. The control treatment (A) did not receive nitrogen fertilisation.
Table 1. Description of the five treatments. 5 kg of urea per hectare were supplied to the canopy once weekly for four weeks at veraison. The concentration of urea used was 3.3 %w/v. The control treatment A received no nitrogen fertilisation (cv. Chasselas, Pully, 2013).
|Nitrogen supply (kg N/ha)|
3. Field measurements and plant sampling
For each replicate, bud fruitfulness was estimated and expressed as number of bunches per shoot. Shoot trimming was conducted three times during the season (four times for treatments D and E, which had a lower canopy height). The shoots were weighed fresh (g/plant), and the data were pooled per vine at the end of the season. The light-exposed leaf area (m2/m2 of ground area) was estimated using Carbonneau’s method (1995) only once per treatment, since the percentage of holes could not be estimated for each vine separately. The yield was determined for each vine (kg/plant).
At harvest time, each of the 25 vines were dug up, with maximum recovery of roots, and then partitioned into five parts: roots, trunk (including cane), vegetative parts (shoots, leaves, total trimmings), pomace and must. Only the trimmings were collected throughout the season as explained above. For each replicate, the bunches were pressed in a Speidel-20 press to separate the must from the pomace. An aliquot (100 mL per vine) of the must was separated immediately after pressing for chemical analysis (see below).
All plant parts were weighed fresh before drying at 60°C until a constant weight. The musts were frozen while agitated in liquid nitrogen to ensure homogeneity and then dried in a lyophilizer. The dry weight (DW, g) and the percentage of dry mass (%DW) were determined for each plant part. The dried organs were then ground into a fine powder (< 1300 µm) for organic carbon and nitrogen stable isotope analysis, except for the dried musts, which remained hard and sticky.
4. Must analyses
The fresh must samples were analysed at the Institute for Food Sciences (IDA, Agroscope) to determine general parameters, e.g., total soluble solids (TSS, °Brix), titratable acidity (TA, g/L as tartaric acid), tartaric and malic acids (g/L), pH, and YAN (mg/L) using an infrared spectrophotometer (FOSS WineScan™).
Primary free AA were quantified using an Agilent 1200 HPLC System equipped with a Zorbax Eclipse AAA column. The OPA-AA derivatives were detected using UV absorbance and expressed in mg N/L considering all the N atoms of each AA (as detailed in Verdenal et al., 2015). The ammonium concentration (NH4+, mg/L) was quantified using an enzymatic method (Boehringer Mannheim, 1997).
5. C and N analyses
The total organic C and N (TOC and TON values, respectively, expressed as %DW) and the stable C and N isotope composition (δ13C and δ15N values, respectively) of the plant parts were determined at the Stable Isotopes Laboratory of the University of Lausanne (UNIL) using elemental analysis-isotope ratio mass spectrometry (EA-IRMS). On one hand, the measurement of 13C/12C ratio at natural isotopic abundance in the must at harvest is an integrated index of the water restriction experienced by the vine during grape maturation (Van Leeuwen et al., 2001). On the other hand, the measurement of 15N/14N ratio after the labelled urea application allowed to describe N distribution in the grapevine. The stable C and N isotopic compositions are reported as δ13C and δ15N values, respectively, as the per mil (‰) deviations of the isotope ratio relative to known standards:
where R is the ratio of the heavy to light isotopes (13C/12C, 15N/14N). All the isotopic analyses were performed in duplicate (as detailed in Verdenal et al., 2015).
A maturity index was calculated as follows:
In the different plant parts of each vine, the following parameters were calculated as detailed in Verdenal et al. (2015):
The total N quantity (QN, g):
QNorgan = DWorgan X %Norgan
The abundance (A%) or proportion of heavy isotope 15N per 100 N atoms:
The relative specific abundance (RSA) or proportion of newly incorporated N atoms (from urea) relative to total N atoms in each organ. In other words, the RSA represents the importance of the organ sink strength, which is independent of its size (Deléens et al., 1997):
The new N pool (g). The new N pool of the whole vine is the sum of the new N pools of each plant part:
The partitioning (%P) or distribution of the new N in the different plant parts. The sum of all the %P of a vine equals 100%.
7. Statistical analyses
The differences between the control A and the other treatments were statistically evaluated using analysis of variance (ANOVA, p values < 0.05), and then a multiple comparison using the Newman-Keuls test was conducted using ©XLSTAT 2014.2.02. The control A was used as a reference without N supply, then ignored to focus on a second experimental design (split-plot) considering only the four other treatments (B, C, D and E). The split-plot design, which considered the canopy height and fruit load as main and sub-factors, respectively, allowed the separate determination of the impact of each factor and then their possible interaction.
1. Phenology and bud fruitfulness
The 2013 vintage induced a late phenological development: cv. Chasselas flowering occurred on the 4th of July, whereas the 1993-2012 average flowering date was the 15th of June, and veraison occurred on the 23rd of August. There was no difference in phenology between the treatments. The grapes were harvested on the 9th of October, just before full maturity to preserve grape integrity and prevent rot. The effects of canopy height and fruit load on the vine parameters, yield components and must composition at harvest are presented in Table 2. The average bud fruitfulness was 1.8 ± 0.2 bunches per shoot (average ± 1 SD), with no difference between treatments.
Table 2. The effect of canopy height and fruit load on vine parameters, yield components and must composition at harvest. The split-plot analysis allowed the separate determination of the impact of both factors of variation (fruit load and canopy height) and their interaction. For each factor, the average of two treatments is presented. B (5 bunches; 150 cm canopy), C (10; 150), D (5; 90) and E (10; 90) (cv. Chasselas, Pully, 2013). Significant correlations (p < 0.05) are in bold.
|Fruit load per vine||Canopy height||Interaction|
|p value||p value|
|Exposed leaf area (m2/m2)||1.5||1.2||1.1||-||0.9||1.4||-||-|
|Total trimmings (g/plant)||452||447||429||0.599||524||351||0.002||0.216|
|Leaf-to-fruit ratio (m2/kg)||1.4||1.2||0.5||-||0.6||1.1||-||-|
|Fruit load (kg/plant)||1.9||2.0||3.8||<0.0001||3.1||2.8||0.097||0.055|
|Total Acidity (g/L)||9||9.1||9.4||0.130||9.6||8.9||0.005||0.766|
|Tartaric acid (g/L)||6.4||6.8||6.7||0.336||6.9||6.7||0.202||0.669|
|Malic acid (g/L)||4.7||5.1||5.4||0.067||5.5||5.0||0.0001||0.618|
2. Leaf-to-fruit ratio
The fruit loads were 2.0 ± 0.5 and 3.8 ± 0.4 kg/plant in the treatments with 5 and 10 bunches per plant, respectively (Table 2). The light-exposed leaf areas were 0.9 ± 0.0 and 1.4 ± 0.1 m2/m2 in the treatments with canopy heights of 90 and 150 cm, respectively. As a consequence of the variability of these two factors of variation, the leaf-to-fruit ratio varied between 0.4 and 1.6 m2/kg and had a considerable influence on grape maturity.
3. Must composition
The maturity index varied significantly from 173 to 197 (Table 2). The average TSS content in the must was 17.1 ± 0.9 °Brix with a minimum value of 16.0 °Brix in treatment E and a maximum value of 18.2 °Brix in treatment B. The Brix degree was initially positively correlated with the leaf-to-fruit ratio (R2 = 0.86) but then reached a plateau when the leaf-to-fruit ratio exceeded approximately 1.2 (Figure 1). Meanwhile, TA (average 9.3 ± 0.5 g/L) and YAN (average 186 ± 42) were negatively correlated with canopy height (R2 = 0.33 and 0.37, respectively). No interaction was observed between the fruit load and canopy height. The control A could only be distinguished from the treatment B by its YAN content in the must, which was significantly lower (93 versus 143 mg/L).
Figure 1. Impact of leaf-to-fruit ratio variation (m2/kg) on total soluble solid (TSS, °Brix) and titratable acidity (TA, g/L as tartaric acid) (cv. Chasselas, Pully, 2013).
4. Dry organic matter
The effects of the fruit load and canopy height on the DW, TOC, δ13C, TON and δ15N values are presented in Table 3. The average whole plant DW for all treatments was 1.83 ± 0.28 kg. As expected, the grape and canopy DW values were correlated with the fruit load and canopy height, respectively, while the roots and trunk DW values were not influenced by these factors.
Table 3. The effect of canopy height and fruit load on DW, TOC, δ13C, TON, δ15N and QN in the different plant parts at harvest. The split-plot analysis allowed the separate determination of the impact of both factors of variation (fruit load and canopy height) and their interaction. For each factor, the average of two treatments is presented. B (5 bunches; 150 cm canopy), C (10; 150), D (5; 90) and E (10; 90) (cv. Chasselas, Pully, 2013). Significant correlations (p < 0.05) are in bold.
|Variable||Organ||Control A||Fruit load per vine||Canopy height||Interaction|
|p value||p value|
5. TOC and δ13C
The average whole plant TOC was 46.5 ± 0.6 %DW and was only influenced by the fruit load. The TOC values at harvest varied between the different plant parts: the lowest average TOC was found in the must, which was only 39.1 ± 0.9 %DW. When considered individually, the plant parts did not exhibit TOC variations with respect to the leaf-to-fruit ratio (Table 3). No interaction was observed between the two factors of variation. The δ13C values varied between -29.5 ‰ in the pomace and -27.7 ‰ in the must. The δ13C values were significantly lower in each vine part (increasing carbon isotopic discrimination, CID) when the canopy height was more important, while fruit load had no effect. For example, δ13C in the must varied between -28.7 and -28.3 ‰ (-28.5 ± 0.1 ‰) when canopy height was 150 cm and between -28.0 and -27.2 ‰ (-27.7 ± 0.2 ‰) when canopy height was 90 cm. An interaction in terms of δ13C could be observed in the roots between the two factors of variation.
6. TON, δ15N and QN
The average whole plant TON was 0.84 ± 0.07 %DW and varied from 0.28 ± 0.08 %DW in the must to 1.69 ± 0.21 %DW in the pomace (Table 3). All the plant part TON values were highly negatively correlated with canopy height and there was no interaction between the two factors of variation. Conversely, the fruit load only influenced the must and root TON values: the must TON increased by 0.04 %DW with an increase in the fruit load, while the root TON decreased by 0.06 %DW. As expected, the 15N abundances in the control A samples were similar in all plant parts and were equivalent to a natural abundance of 0.37 atom% (results not shown). In the 15N-labelled treatments, the δ15N values showed important variations between plant parts and ranged from 1514 ‰ (A%must = 0.92 ± 0.25 %) in the roots to 6170 ‰ in the must (A%must = 2.57 ± 0.25 %) (Table 3). Both the fruit load and canopy height influenced new N abundance in the reproductive organs (grapes) and the reserve organs (trunk and roots) without influencing A% in the canopy, which remained constant at 1.25 ± 0.11 A%. The δ15N value in the trunk was only influenced by fruit load. An interaction between the two factors in terms of 15N abundance was observed in the grapes and the trunk. The average QN in the whole plant was 15.2 ± 1.8 g and increased with fruit load but was independent of canopy height. The average QN in the canopy (7.6 ± 1.0 g) represented 50 % of the TON in the plant and was correlated with canopy height. Conversely, the average QN in the must (1.0 ± 0.5 g) represented only 6 % of the TON, which was the smallest N pool in the vine. Only the QN in the grapes was correlated with both factors of variation: it was positively correlated with the fruit load and negatively correlated with the canopy height. The interaction between both factors only influenced the QN in the pomace.
7. RSA, new N pool and partitioning
The effects of canopy height and fruit load on the RSA, new N and its partitioning in the plant are presented in Table 4. The average RSA in the whole plant was 12 ± 1 % and was independent of both factors of variation. The average RSA in the different plant parts varied between 6 ± 3 % in the roots and 23 ± 3 % in the must. Grapes (must and pomace) had the strongest sink-effect in all the treatments. The RSA was affected by both factors of variation in the roots and grapes and only by the fruit load in the trunk. The RSA was indeed higher in the grapes when the fruit load and/or canopy height were lower. The RSA in the canopy remained constant at 9 ± 1 % and was independent of both factors of variation. A strong interaction between both factors was observed in the grapes and the trunk, as well as in the whole plant. As a consequence of the RSA and organ size, the new N pool in the grapes and roots also varied with both factors of variation. The new N quantity in the whole plant was reduced by approximately 10 % by the increase in canopy size and tended to be reduced (only significant at p < 0.10) by the decrease in fruit load. An interaction between the factors of variation was observed only in the pomace.
Table 4. The effect of canopy height and fruit load on RSA (% TON), new N quantity (g) and its partitioning (%) in the different vine organs at harvest. The split-plot analysis allowed the separate determination of the impact of both factors of variation (fruit load and canopy height) and their interaction. For each factor, the average of two treatments is presented. B (5 bunches; 150 cm canopy), C (10; 150), D (5; 90) and E (10; 90) (cv. Chasselas, Pully, 2013). Significant correlations (p < 0.05) are in bold.
|Variable||Organ||Fruit load per vine||Canopy height||Interaction|
|p value||p value|
The variation in the new N pool in the different organs as a function of the leaf-to-fruit ratio is shown in Figure 2. The new N pools in the canopy and trunk were independent of the leaf-to-fruit ratio (R2 = 0.06 and 0.03 for the canopy and trunk, respectively). When the ratio increased to 1.6, the new N pool in the grapes decreased considerably (from 1.07 to 0.28 g, R2 = 0.93), while it increased slightly in the roots (from 0.03 to 0.18 g, R2 = 0.63). With respect to the TON, a similar correlation was observed between new N in the grapes (must + pomace) and reserves (trunk + roots) (R2 = 0.42), indicating that reserve organs take advantage of new N partitioning under a lower fruit load. In the case of a higher canopy, the new N content in the roots increased by 40 %, while the new N content in grapes was reduced by 33 % (Table 4). New N partitioning was clearly affected by organ size (canopy and/or fruits) and new N partitioning was balanced accordingly. The trunk was only affected by the fruit load. The new N content in the must varied from 6.1 ± 0.5 % in treatment B (leaf-to-fruit ratio = 1.6) to 20.9 ± 2.3 % in treatment E (leaf-to-fruit ratio = 0.4).
Figure 2. Impact of leaf-to-fruit ratio variation (m2/kg) on the new N partitioning (g) per vine organ (cv. Chasselas, Pully, 2013).
8. Soluble N in the must
The effects of canopy height and fruit load on AA and NH4+ concentrations are presented in Table 5. The control treatment A had a significantly lower concentration of total AA and NH4+ in the must, i.e., 154 mg N/L versus an average of 313 mg N/L in the four other treatments that received foliar-applied urea. The increase in the fruit load had no significant impact on the total AA concentration but positively affected the NH4+ concentration. However, canopy height strongly affected both the total AA and NH4+ concentrations: the higher the canopy, the lower the YAN concentration in the must. Most of the AAs were highly negatively correlated with canopy height (p < 0.001). No interaction was noted between canopy height and fruit load.
Table 5. The effect of canopy height and fruit load on the concentrations of amino-acids and ammonium in the must. The split-plot analysis allowed the separate determination of the impact of both factors of variation (fruit load and canopy height) and their interaction. For each factor, the average of two treatments is presented. B (5 bunches; 150 cm canopy), C (10; 150), D (5; 90) and E (10; 90) (cv. Chasselas, Pully, 2013). Significant correlations (p < 0.05) are in bold. n.d., not determined.
|Fruit load per vine||Canopy height||Interaction|
|p value||p value|
|NH4+ (mg N/L)||19.8||44.0||70.2||0.005||80.5||33.7||<0.0001||0.177|
1. The foliar urea increased the YAN concentration
The results of this study indicated that there were no side-effects of urea application at veraison on vine physiology. Besides the increased YAN concentration in the must (+50 mg/L), there was no difference between the control treatment A and treatment B in terms of vigour (leaf area, pruning weight), yield per vine or must composition. This confirms the results obtained by Neilsen et al. (2013), who showed that foliar urea fertilisation enhanced the soluble N content in the must without increasing plant vigour.
2. The leaf-to-fruit ratio impacted the must composition
The leaf-to-fruit ratio had a strong impact on the maturity index, which is in line with the results reported in other studies (Murisier and Zufferey, 1997; Kliewer and Dokoozlian, 2005). Insufficient canopy height affected grape maturation in terms of TSS accumulation, malic acid degradation and YAN accumulation, while high fruit load only affected TSS accumulation in the must. This would explain the lower correlation of TA with the leaf-to-fruit ratio (R2 = 0.33; Figure 1). These results contrast with those reported by Kliewer and Ough (1970), who found a negative correlation between YAN and fruit load. This divergence can most likely be explained by the wide range of numbers of bunches per vine they studied (i.e., up to 48) or by the different climatic conditions (Köppen-Geiger climate classification subtypes Csa-Csb for the warm to hot summer Mediterranean-like climate in California and Cfb for the marine West coast climate in Pully; Peel et al., 2007).
3. The leaf-to-fruit ratio did not impact the leaf N-uptake
It is likely that N absorption is determined by favourable atmospheric relative humidity and vintage climatic conditions (Porro et al., 2010; Eichert, 2013). Knowing the quantity of urea applied and the average new N quantity in the vine at harvest, 15N-labelling indicated that 48 ± 6 mass% of urea was absorbed through the leaves into the vines. This is a fairly good absorption rate in comparison to the results of other studies, which showed that only 30 to 40 mass% of the applied urea was assimilated by the plant (Jakovljevic et al., 1995; Verdenal et al., 2015). N absorption rate was not significantly related to fruit load nor leaf area. However, it tended to be higher when the leaf area was smaller (51 %) and when the fruit load was higher (51 %).
4. The canopy height increased the C isotope discrimination
The TOC concentration per organ was not influenced by the variation of the leaf-to-fruit ratio. However, the CID in all the organs was substantially affected by the canopy height; the δ13C values were lower for a larger canopy. Indeed, Farquhar et al. (1989) showed that CID is negatively correlated with instantaneous water use efficiency (WUE, estimated as CO2 assimilation divided by canopy transpiration) and positively correlated with the ratio of intercellular CO2 concentration to ambient CO2 concentration (Ci/Ca), which is a balance between stomatal conductance and photosynthetic activity. Therefore, for a given leaf area, CID would depend on either stomatal conductance or photosynthetic activity per leaf (Dubey and Chandra, 2008). In this study, the CID value measured in the must (δ13C = -28.1 ± 0.4 ‰) did not indicate a water restriction over the period of grape maturation (e.g., Van Leeuwen et al., 2009). As a consequence, CID would have depended mainly on the photosynthetic activity per unit of leaf area and not on stomatal behaviour.
5. The canopy height reduced the N concentration in the whole plant
The impact of canopy height on the N concentration in all the organs suggests that the TON was diluted by the volume of the whole plant: for a constant N quantity (QN = 15.2 ± 1.8 g), the TON in the whole plant was reduced by 12 %DW when exposed leaf area was increased by 55 %. This result confirms the observations of Spring et al. (2011).
6. The CID and the N concentration were negatively correlated
These results suggest that an increase in canopy height and therefore leaf area index (LAI, i.e., the total leaf area per m2 of soil) in the absence of water restriction would have induced a lower photosynthetic activity per unit of leaf area with two major consequences for the whole plant (Figure 3): (1) a reduction in photosynthetic-N use efficiency (PNUE), which would result in a lower N concentration; and (2) a reduction in WUE, which would induce a higher CID. This hypothesis can explain the negative correlation between CID and the N content (i.e., R2 = 0.65 in the must). This relationship was previously observed in Coffea by Gutierrez and Meinzer (1994) and in Arachis by Nageswara Rao and Wright (1994), but requires further research to confirm the results in grapevine.
Figure 3. Relationship between leaf area index (LAI), carbon isotope discrimination (CID) and N concentration in the whole plant under no water restriction (cv. Chasselas, Pully, 2013). PNUE, photosynthetic-N use efficiency; WUE, water use efficiency; δ13C, carbon isotope composition.
7. The fruit load reduced the TON concentration in the roots
On the other hand, the variation in the fruit load resulted in a linear relationship between the grape dry weight (must DW + pomace DW) and N quantity (QN) (R2 = 0.84). A similar trend was shown by González-Real et al. (2008) for sweet pepper plants. In other words, the TON concentration in the grapes remained constant at 0.71 ± 0.10 %DW (must DW + pomace DW), and the QN increased accordingly.
However, a negative correlation between the TON values in the must and roots (R2 = 0.42) suggested that a high fruit load would result in lower N reserves in the roots for the next season. Zapata et al. (2004) demonstrated that the N reserves used on the spring flush were precisely those of the roots as the main N storage organ. Crop modellers often consider the roots as an invariant fraction of the whole plant dry mass, without any active role in N partitioning (González-Real et al., 2008). Nevertheless, Morinaga et al. (2003) suggested that a larger quantity of bunches (the strongest sink organ) would prevent the development of new fine roots and, as a consequence, would reduce whole root activity and N accumulation. Moreover, lower N reserves in the roots would largely affect the sustaining growth and the fruiting of grapevine in the following season (Cheng and Xia, 2004).
8. The canopy height highly affected the YAN concentration in the must
With respect to new N, when the leaf-to-fruit ratio was 0.5 m2/kg or lower, more than half (52 %) of the foliar-applied N went to the grapes (must + pomace) compared with only 23 % when the leaf-to-fruit ratio was 1.5 m2/kg or higher (Figure 2). In fact, the impact of foliar-N application on YAN and AA concentrations in the must was mostly affected by the excess of leaf area (p value < 0.0001). These observations support the results of Spring et al. (2011), who showed that YAN-deficient musts could be produced from vigorous vines in spite of high soil N availability, pointing out the key role of canopy management in YAN accumulation in the must.
It is a well-established fact that a minimum leaf-to-fruit ratio (approximately 1.0-1.2 m2/kg in the context of Swiss vineyards) must be maintained to guarantee optimal TSS accumulation in the grapes and N recovery in the reserve organs. However, bearing in mind the major role of YAN in must composition in terms of fermentation kinetics and aroma development, this study demonstrated that excessive leaf area reduces YAN concentration in the must and can potentially induce a YAN deficiency that could impair wine quality. These results add new perspectives regarding foliar-N fertilisation management as a function of the leaf-to-fruit ratio. The development of indicators to manage foliar-N fertilisation efficiency, such as an eventual early YAN concentration monitoring in the grape along with thresholds, would be necessary. Further research is required to better understand the role of the roots in the N partitioning in the vine – e.g., their development, activity and organ size – and to determine other technical and physiological parameters which would optimize N accumulation in the grapes and guarantee the maximum efficiency of foliar urea supply at veraison.
Acknowledgements: The authors would like to thank the vineyard and laboratory teams of Agroscope and Sol-Conseil for their assistance.
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