Abstract
Understanding the direct role that macronutrient supply (N, P, and K) has on berry chemistry was evaluated in Pinot noir grapevines grown in sand culture. Self-rooted Pinot noir vines were grown for three years with either full nutrition (Control) or three reduced levels of either N, P, or K supply while holding all other nutrients constant. Vines were managed to minimize differences in vine water status (altering irrigation to achieve similar daily soil moisture content) and fruit cluster solar exposure (altering leaf pulling to achieve similar cluster irradiance) due to varying nutrient supply so that indirect effects on berry chemistry could be largely eliminated. Berry chemistry was evaluated in the second and third years after different nutrient supply treatments were imposed. Results showed that low N, but not low P or K, altered berry free amino acid (FAA) and phenolic profiles. Low N supply reduced FAA and yeast assimilable nitrogen (YAN) in both years by up to 70% and altered certain FAAs more than others, thus changing berry FAA profile. The concentration of sugars, anthocyanins, and flavonol-glycosides increased in low N vines during the third season, but the increase in sugars and anthocyanins was attributed to the decline in berry size that year. Condensed tannins and total phenolic acids were increased in low N vines across both years, independent of changes in berry size. Results indicated that low N supply altered YAN to the greatest degree, while anthocyanin enhancement did not occur until yield and berry size were also reduced. Increased concentrations of tannins and phenolic acids in berries occurred in response to low N supply independent of reductions in yield and berry size.
Numerous environmental conditions and viticultural practices are known to alter the composition of berries and affect wine quality. Key factors among these are climatic conditions (temperature, solar radiation, and humidity), grapevine cultivars and rootstocks used, irrigation, fertilization, crop load, and canopy management practices (Jackson and Lombard 1993, Ebeler and Thorngate 2009). Many factors that alter berry composition interact, thus making it difficult to predict how a given practice applied in a given vineyard will improve berry quality. Berry composition and wine quality for red varieties are related to enological phenolics (Cheynier 2005, Versari et al. 2013), nitrogen (N) (Bell and Henschke 2005), carbon, and aroma (Swiegers et al. 2005, Conde et al. 2007) compounds, which have been well reviewed. Such compounds contribute to the overall sensorial wine experience by contributing to appearance, aroma, taste, and mouthfeel (Cheynier 2005).
The impact of vine nutrient supply, particularly on secondary metabolites in berries, is less understood. Although it is well known that too much N supplied to vines is generally detrimental to wine quality (Bell and Henschke 2005), it is not clear whether differences in fruit composition from vines with higher N status is due to direct impact of N supply or to indirect effects of excessive cluster shading (altering solar interception of berries and cluster microclimate) or excessive vegetative growth (altering source-sink relations and reducing ripening). High N supply can also result in excessive yeast assimilable nitrogen (YAN) concentrations in berries, resulting in wines that are more susceptible to ethyl carbamate formation (Bell and Henschke 2005). Low N supply to grapevines can result in reduced yields and YAN concentrations in fruit that can limit the rate of fermentation and increase the chance for excessive formation of hydrogen sulfide and thiol containing compounds (Malherbe et al. 2007). In a review of N nutrition in grapes, Bell and Henschke (2005) concluded that the only consistent impact of N fertilization of grapevines upon berry or must quality parameters is an increase in berry YAN levels. Producers are generally encouraged to aim for moderate vine N status and berry YAN.
A number of studies have shown that high N supply can reduce either berry or must concentrations of various polyphenolics, including anthocyanins, condensed tannins, and flavonol-glycosides (Keller et al. 1999, Hilbert et al. 2003, Okamoto et al. 2003, Bell and Henschke 2005). However, the levels of N applied were exceptionally high, in some cases leading to juice YAN values >1500 mg N/L. In other cases, vine N status and juice YAN were not even measured. Therefore, while it is known that very high N status is detrimental to fruit composition, studies using more moderate levels of vine N status (or N supply) that are likely to be encountered in production systems are needed. Indeed, in some vineyard trials where N status has been manipulated within a moderate range, the impact on berry phenolics and other secondary metabolites can be rather minor or transient (Delas et al. 1991, Delgado et al. 2004).
Much less is known about how phosphorus (P) or potassium (K) may influence berry secondary metabolites in grapevines. Dundon et al. (1984) showed that anthocyanin and phenolics in wine were largely unaffected by K fertilizer use. Delgado et al. (2004) reported an interaction between rates of N and K fertilizer use, such that increasing N supply decreased skin polyphenolics at moderate rates of K supply, but increasing N supply increased skin polyphenolics at a high rate of K supply. Based on our survey of the literature, no research has addressed how P supply may alter berry secondary metabolites. Indeed, little is known as to how much P may be required (or even optimal) by yeasts during fermentation (Archer and Caster 1956, Jones and Gadd 1990).
Managing nutrient supply (particularly N) to control vine vigor is critical for western Oregon producers of Pinot noir because high soil moisture in the spring and early summer can lead to large canopies. The focus in the region on low crop loads for premium quality may also require adjustment of vine nutrient status indicators (leaf blade and petiole standards) that have been developed in other areas that typically carry more crop. Viticulturists in the region do not have accurate guidelines as to how nutrient supply and vine nutrient status influence the balance of attaining desirable levels of vegetative growth and yield versus desired fruit composition for premium wine production. The concept of regulated N deficit (similar to regulated deficit irrigation) may prove to be a useful approach to limit vine vigor in areas of high rainfall that cannot be otherwise controlled by water availability (Schreiner et al. 2013). The goal of this research is to provide a better understanding of how N, P, and K supply alters production and fruit quality using a system where nutrient inputs are carefully controlled. The impacts of N, P, and K supply on vine growth, nutrient status, and yield from this trial were reported previously (Schreiner et al. 2013). The focus of this study was to examine the effect of nutrient supply on free amino acids and phenolic profiles in Pinot noir berries.
Materials and Methods
Experimental design and vine management.
The experimental pot-in-pot vineyard and vine management and treatment protocols were described in detail previously (Schreiner et al. 2013). Briefly, self-rooted Pinot noir grapevines were grown from 2003 to 2005 in a sand medium supplied with ½ strength Hoagland’s solution (Hoagland and Arnon 1950) using vertical shoot-positioning on a single Guyot system. From 2006 to 2008, three lower rates of either N, P, or K (at 50%, 20%, and 10% of the rate supplied to the Control) along with the full nutrition Control rate (½ strength Hoagland’s solution providing 7.5 mM N, 0.5 mM P, and 3.5 mM K) were supplied to 20 vines, each in a randomized complete block design with four replicates consisting of five continuous vines per plot (experimental unit). For example, vines in the 50%N treatment received 3.75 mM N, but all other nutrients (including P and K) were supplied at the same rate as the Control. In this way, only N supply was altered in the low N treatments, only P supply was altered in the low P treatments, and only K was altered in the low K treatments. There were nine low nutrient treatments and a Control (total 10) for a total of 40 experimental units. However, only the lowest P supply and K supply treatments (10% of Control) were evaluated here with respect to berry composition because low P and K supply treatments had no impact on vine and berry growth parameters (Schreiner et al. 2013). Differences in fruit cluster solar exposure and vine water status resulting from differences in canopy size among the different treatments (i.e., indirect effects of nutrient supply) were minimized by applying variable levels of leaf removal and irrigation in different treatments (see Schreiner et al. 2013). All vines were thinned to the same number of fruit clusters per shoot in 2007 (1.5) and 2008 (2.0). Fruit was harvested from all plots on the same day in 2007 and 2008 when a composite berry sample from all treatments reached ~22 Brix.
Berry composition.
Berry chemistry was examined in 2007 and 2008 after sufficient vine training and fruit cropping level was attained. Berry composition was examined in each of the lowest rates of P and K supply (10%P and 10%K) together with the Control (100% all nutrients) and all low N treatments (50%N, 20%N, and 10%N). After determining yield parameters (reported in Schreiner et al. 2013), seven whole clusters were randomly selected from each replicate and immediately frozen (and stored) at −80°C. Berries were stripped from these clusters, sorted into three size classes (>1.2, 0.9–1.2, and <0.9 mm diam), counted, and weighed. A 100 berry subsample was reconstituted from each experimental plot to reflect the berry size distribution as determined above (to avoid any discrepancy in berry size distribution of subsamples used for different analyses) and shipped overnight in dry ice to the collaborating facility.
Fruit metabolite analysis.
All berry metabolite analyses were performed as described previously (Lee and Rennaker 2011), with the following minor changes. Liquid nitrogen powdered whole berries were extracted with acidified methanol, the methanol was evaporated, and extracts were redissolved in water (Lee and Martin 2009). Briefly, total anthocyanins (TACY; 520 nm and 700 nm, expressed as malvidin-glucoside equivalents) were determined by pH differential method (Lee et al. 2005, Lee and Martin 2009), total phenolics (TP-FC; 765 nm, expressed in gallic acid) were determined by Folin-Ciocalteu method (Waterhouse 2002), total tannins (TT-MCP; 280 nm, expressed in epicatechin) by methylcellulose precipitation method (Sarneckis et al. 2006), and ammonia (340 nm, expressed in mg N) by an enzymatic assay (Lee and Schreiner 2010). Absorbance readings were conducted using a SpectraMax M2 microplate reader (Molecular Devices Corp., Sunnyvale, CA). Detailed individual compound analysis was determined by HPLC-refractive index detector for simple sugars (TS-LC) (Lee et al. 2009), HPLC-diode array detector (DAD) and fluorescence detector for free amino acids (abbreviated FAA, or amino-N) (Lee et al. 2009, Lee and Schreiner 2010, Lee and Rennaker 2011), and HPLC-DAD and HPLC-DAD-ion trap MS for anthocyanins and polyphenolics other than anthocyanin analyses (Lee and Martin 2009). An Agilent HPLC 1100 system (Agilent Technologies Inc., Palo Alto, CA) was used for this investigation. Specific HPLC settings (such as column information and column compartment temperature) were as previously described (Lee and Martin 2009, Lee and Schreiner 2010). YAN was calculated as described in Lee and Schreiner (2010) by summing ammonia and primary FAAs. The total non-anthocyanin polyphenolics determined by HPLC (TP-LC) included all phenolic compounds resolved by chromatography. The total phenolic acids (TPA) included the sum of protocatechuic, caftaric, coutaric, and fertaric acids (expressed as caffeic acid) determined by HPLC. Total flavanols (TFLA; expressed as catechin) included the sum of proanthocyanidins 1 and 2, catechin, epicatechin, epicatechin gallate, and (epicatechin)catechin-epicatechin gallate. Total flavonol-glycosides (TFLO; expressed as rutin) included the sum of quercetin-galactoside, quercetin-glucuronide, kaempferol-glucoside, and isorhamnetin-glucoside. All chemicals and solvents were purchased from Sigma-Aldrich (St. Louis, MO), except for malvidin-glucoside, which was purchased from Polyphenols Laboratories AS (Sandnes, Norway).
Statistical analysis.
All berry compositional data are expressed in mg per kg berry fresh mass or the relative proportion (%) of that concentration. The concentrations of FAAs and their relative proportions were calculated based on mg N per kg berry fresh mass. The impact of N supply was analyzed using analysis of covariance (ANCOVA) with year as a categorical factor and N rate (7.5 mM N for Control, 3.75 mM N for 50%N, 1.5 mM N for 20%N, 0.75 mM N for 10%N supply) as covariate. A homogeneity of slopes model was first tested to determine if the response to N rate differed by year, and separate models were run for each year if significant (p ≤ 0.05). Variance assumptions were tested using Cochran’s test and residuals were examined to ensure normality. For those berry attributes that were differentially altered by N rate in 2008 (consistent with the reduction in berry weight that year), stepwise regression using N rate and berry weight as regressors was performed to examine the extent that either factor contributed to the response. The 10%P and 10%K supply rates were compared to the Control treatment using factorial ANOVA with year and treatment as main effects in a complete factorial model. For this analysis, variance assumptions were tested using Cochran’s test. Statistica software (ver. 8.0; StatSoft Inc., Tulsa, OK) was used for all analyses, and effects were considered significant at 95% confidence (p ≤ 0.05).
Results
The nutrient treatments applied to Pinot noir vines altered the yield of grapes and the average berry weight in 2008, such that both were significantly reduced in the 50%N (3.75 mM), 20%N (1.5 mM), and 10%N (0.75 mM) treatments, as compared to the Control (see Schreiner et al. 2013). No other treatments differed from the Control in 2008, nor did any low nutrient supply treatment affect yield or berry size in 2007. Vegetative growth based on pruning weights was reduced by ~27% in both the 20%N and 10%N treatments in 2007 and by 28% in 50%N vines in 2008 or by ~40% in both the 20%N and 10%N treatments in 2008 (Schreiner et al. 2013). In 2008, berry weights were reduced from 1.38 g in Control vines to 0.83 g in 50%N vines, 0.73 g in 20%N vines, and 0.67 g in 10%N vines (Schreiner et al. 2013). Berry composition (for both groups of metabolites and for specific metabolites within each group) was not altered (p > 0.05) in the vines receiving 10%P or 10%K supply in either year (data not shown).
Most of the major groups of compounds examined were at higher concentrations in berries in 2008 versus 2007, including TP-LC, TACY, TPA, TFLA, TFLO, and YAN (Table 1). Only TP-FC, TT-MCP, and TS-LC were unaltered by year. In general, polyphenolics were at greater concentrations in berries in 2008 than in 2007, even though sugars and total tannins did not differ by year. Berry YAN concentrations were ~1.6 times higher in 2008 compared to 2007 across all treatments, due in part to more frequent fertigation events used in 2008 to boost overall vine nutrient status (see Schreiner et al. 2013). Greater N supply increased YAN in berries (Table 1) and response of YAN to N supply was greater in 2008 than in 2007. In contrast, greater N supply decreased berry TT-MCP and TPA concentrations similarly in both years. The concentrations of TACY, TFLO, and TS-LC in berries decreased with greater N supply only in 2008, but not in 2007. These changes in TACY, TFLO, and TS-LC were consistent with the decline in berry size in response to low N supply that occurred in 2008. The increase in TS-LC in berries in vines receiving low N supply in 2008 was consistent with juice % soluble solids (Brix) reported previously (Schreiner et al. 2013).
The interrelationship among N supply, berry weight, and concentrations of anthocyanins, flavonol-glycosides, YAN, and sugars was investigated using stepwise regression. Greater concentrations of TACY and TS-LC in 2008 under low N supply were driven by the reduction in berry size, since stepwise regression revealed that berry weight was a better and sole predictor (p < 0.001) of TACY and TS-LC (data not shown). In contrast, N supply was a better and sole predictor (p < 0.001) in determining TFLO concentrations in berries in 2008, while both N rate (p < 0.001) and berry weight (p = 0.027) were significant predictors for YAN in berries in 2008 (data not shown).
All five previously established Pinot noir anthocyanins (Keller et al. 1999, Lee and Martin 2009) were found in berries via HPLC despite vine nutrient alteration. Similar to the impact on TACY (spectrophotometric method), each individual anthocyanin decreased in berries as N supply increased only in 2008 (data not shown). Expressing the individual anthocyanins on a relative basis showed that the two most abundant anthocyanins were altered by year, such that malvidin-glucoside increased in 2008 while peonidin-glucoside decreased in 2008 compared to 2007 (data not shown). Malvidin-glucoside was the main contributor to total berry anthocyanin, comprising ~60% of the total anthocyanin pool across all treatments (data not shown).
The concentrations of individual flavanols detected by HPLC and the relative abundance of each of the three flavanol monomers (catechin, epicatechin, and epicatechin gallate) in berries were only altered by year. The supply of N did not alter the concentration of specific flavanols in berries (data not shown). Catechin was the most abundant flavanol monomer in Pinot noir berries, contributing >50% to the total flavanol pool.
Overall, 22 free amino acids (FAAs) were identified and quantified in Pinot noir berries from 2007 and 2008 (Table 2; listed in order of elution). Year and N supply altered the concentration of most amino acids in berries. The impact of N supply on berry FAA concentrations in 2007 was reported previously (Lee and Schreiner 2010). A brief summary of the impact of year and N supply on FAA concentrations follows here. The concentration of 13 FAAs were greater in 2008 than in 2007, similar to the effect of year on YAN. However, four FAAs (ASP, GLY, TRP, and LYS; abbreviations of amino acids defined in Table 2) were at higher concentrations in berries in 2007 despite lower YAN in 2007. The concentrations of 15 FAAs were significantly increased with greater N supply across both years (data not shown). Higher N supply increased the concentration of two amino acids (ARG and CIT) to a greater degree in 2008 than in 2007, similar to the impact on berry YAN (data not shown). Among individual amino acids, concentrations of CIT and ARG had changed the most in response to both year and N supply (data not shown).
Arginine was the most important contributor to amino-N in Pinot noir berries (Table 2). When FAAs were expressed as a proportion of total free amino-N, three FAAs (THR, CIT, and ARG) contributed more to berry amino-N in 2008 over 2007 (Table 2). In contrast, almost all of the remaining FAAs (except ASN, HIS, MET, PHE, and HYP) contributed proportionally more amino-N to berries in 2007 than in 2008. Nitrogen supply had similar effects on the relative proportion of specific amino acids in berries in both years (slope of regression did not differ between years). There are two groups of FAAs in Pinot noir berries that respond in an opposing manner to increased N supply: those that increase in proportion as N supply increases and those that decrease in proportion as N supply increases. Greater N supply increased the proportion of CIT, ARG, and ALA in berries and decreased the proportion of 13 other FAAs (Table 2). In general, higher N supply had the greatest influence on increasing the proportion of ARG while decreasing the proportion of GLN in berries.
Caftaric acid was the most abundant phenolic acid, comprising >50% of TPA in Pinot noir berries (Table 3). The concentrations of individual phenolic acids were all higher in berries in 2008 than in 2007, although relative proportions were similar between years. Each of four phenolic acids identified by HPLC had increased in concentration in berries by 30 to 40% over the 2007 levels. Greater N supply decreased caftaric and coutaric acid concentrations similarly across both years and decreased fertaric acid only in 2008 (Table 3). When individual phenolic acids were expressed as a proportion of TPA, greater N supply decreased the proportion of caftaric acid and increased the proportion of protocatechuic acid.
Quercetin-glucuronide was the most abundant flavonol-glycoside in Pinot noir berries (Table 4). The concentrations of all four flavonol-glycosides identified from Pinot noir berries were greater in 2008 compared to 2007. When expressed as a proportion of berry TFLO, only kaempferol-glucoside was altered by year with a greater proportion in 2008 than 2007. Greater N supply decreased the concentration of each flavonol-glycoside only in 2008 (Table 4). In 2007, greater N supply increased kaempferol-glucoside in berries. The interrelationship between N supply, berry weight, and concentrations of flavonol-glycosides was investigated using stepwise regression. The higher concentrations of kaempferol-glucoside (p < 0.001) and isorhamnetin-glucoside (p = 0.001) in berries in 2008 under low N were driven by the reduction in berry size. In contrast, N supply was a better and sole predictor (p < 0.001) in determining the concentrations of both quercetin-glycosides (data not shown).
Discussion
Reducing N supply to Pinot noir vines grown in sand altered FAA and phenolic metabolite profiles in berries, consistent with the impact of low N supply on vine growth, berry size, and yield reported previously (Schreiner et al. 2013). Low P or low K supply, however, had no detectable impact on berry metabolites examined here. This finding is consistent with the lack of effects of both low P and low K treatments on vine growth or yield (Schreiner et al. 2013). Even though low P supply reduced P concentrations in berries and low K supply altered juice pH, the levels of P and K nutrient stress achieved here did not alter berry FAA or phenolic composition. We predicted that anthocyanins would be altered in berries in response to low P supply, as these compounds have increased in P-deficient grape cell cultures (Dedaldechamp et al. 1995) and are typically expressed in leaves of P-deficient plants (Marschner 1995), but this was not apparent in berries here. Topalovic et al. (2011) reported a small increase in berry anthocyanins shortly after applying foliar P + K fertilizer, opposite of expectations, but final concentrations in berries at fruit maturity were not different.
The impact of low N supply on both primary (reduced amino acids) and secondary (increased polyphenolics) berry metabolites found here was often associated with a significant reduction in berry size in the low N treatments in 2008. Berry weight was a better predictor than N supply for total (TACY) and individual anthocyanins, total sugars (TS-LC), kaempferol-glucoside, and isorhamnetin-glucoside. In contrast, FAAs, total tannins (TT-MCP), and total phenolic acids (TPA) were altered by low N supply independent of changes in berry mass. There are two reasons why berry weight did not account for the changes in some berry metabolites in response to low N supply. First, berry mass was not altered by nutrient supply in 2007. Second, berry mass was reduced nearly as much (40% reduction) in the 50%N supply vines as it was in the 20%N and 10%N vines (47 to 51% reduction in berry size) in 2008. However, the increase in certain phenolic constituents as N supply declined was driven largely by the 20%N and 10%N supply treatments, even though the greater share in berry size reduction had already occurred at 50%N supply.
The greatest and most consistent effect of low N supply on berry composition was the loss of amino-N, which was expected (Hilbert et al. 2003, Bell and Henschke 2005). Amino acids contributing to YAN were reduced to a greater degree than the associated increases in some phenolic compounds. YAN declined in the 20%N and 10%N berries ~48% in 2007 and 64% in 2008, while total tannin increased by 31% over both years and total phenolic acids increased by 27% over both years. Anthocyanins (TACY) had increased by 33% and sugars increased by 13% in the two lowest N rates only in 2008. A similar response was found previously in relation to N supply (Hilbert et al. 2003, Delgado et al. 2004). YAN levels in berries are apparently more sensitive to vine N status than are changes in berry phenolics, which lends support to developing vine N tissue standards for winegrapes based on obtaining desired YAN levels.
Higher berry anthocyanin concentrations in response to lower N supply has been reported in several studies (Delas et al. 1991, Keller et al. 1999, Hilbert et al. 2003), although increases in anthocyanins have occasionally occurred as N supply was increased (Bell and Henschke 2005). Based on these findings and our results here, it appears that berry anthocyanins can be enhanced in vines receiving a moderate supply of N as compared to excessive N rates (Hilbert et al. 2003, Okamoto et al. 2003) and that berry anthocyanins can be enhanced further as vines approach N deficiency (Chone et al. 2006). When N is manipulated within a more moderate range of vine N status, anthocyanins may increase or decrease with added N supply (Delgado et al. 2004). Some of these differing effects of N supply on berry pigment levels in past studies could be explained by varying levels of cluster shading (indirect effect of N supply) by canopy leaves (Spayd et al. 2002) in different treatments. The solar exposure of fruit clusters among different treatments in this study was controlled by leaf removal (Schreiner et al. 2013), so the increase in anthocyanins (and other phenolics) found here was not due to differences in cluster shading but rather to smaller berries.
Our data with Pinot noir indicate that total tannins and phenolic acids in berries may be more consistently altered by low N supply as compared to other polyphenolics. Total tannins and phenolic acids increased in berries in low N vines similarly over both years, while increases in anthocyanins and flavonol-glycosides were only apparent in 2008 (Table 1), after berry weight and yield (Schreiner et al. 2013) was also reduced. To our knowledge, increased concentrations of phenolic acids under low N supply have not been reported previously. Higher berry tannin concentrations have been observed previously in vines receiving lower N supply in vineyards (Delas et al. 1991, Delgado et al. 2004), although the changes in tannins found here, for Pinot noir, were of greater magnitude. An increase in tannins by lower N supply is a positive trend, as higher tannin levels in Shiraz and Cabernet Sauvignon wines received higher wine grades (based on price category; Mercurio et al. 2010, Smith et al. 2008). Further work is needed to understand the relationship between skin and seed tannin levels in Pinot noir berries and in wines and how vine N status alters tannin types and size.
Some of the individual metabolites within various groups of compounds examined here showed wide variation in response to N supply. For example, among the FAAs, the concentrations of CIT and ARG (precursors for urea and ethyl carbamate; Bell and Henschke 2005) decreased the most in response to low N supply, leading to a significant decline in their relative contribution to YAN among the amino acids. While numerous FAAs did not change in concentration in low N berries, their relative contribution to amino-N in berries had actually increased under low N supply. Clarifying the relationships between catabolism/anabolism of various amino acids and phenolic biosynthesis in berries is an important aspect in future research.
The individual phenolic acids, caftaric and coutaric, had both increased in berries as N supply was reduced, while protocatechuic acid was not altered by N supply. Higher levels of coutaric and caftaric acids in the low N supply berries may suggest that these grapes would be more susceptible to oxidation during crush/winemaking (Singleton et al. 1985) and possibly result in unwanted browning in wines.
Conclusion
The key finding from this trial was that numerous phenolic metabolites known to contribute to wine quality were enhanced under low N supply in Pinot noir, but berry YAN and certain amino acids were sharply reduced, which would likely have a negative impact on quality. Indeed, musts from the 10%N treatment in 2008 and all three low N rate treatments in 2007 (50%N, 20%N, and 10%N) would likely have become problematic fermentations if a moderate or high YAN-requiring yeast was used in winemaking, as juice YAN in these treatments was <140 mg N/L. In addition, the positive impact on anthocyanins did not occur until yield in 2008 was simultaneously reduced to an uneconomical level of production. The positive increase in total tannins and phenolic acids that occurred across both years as N supply was reduced, however, suggests that these berry components may be improved by reducing N supply before yield is reduced. Further work is needed to confirm whether tannins and phenolic acids are indeed more sensitive to N supply than other phenolic constituents in Pinot noir berries. Additional research to examine how grafted Pinot noir vines respond to nutrient supply (particularly N) in terms of achieving the best balance of productivity and berry composition is also needed.
Acknowledgments
Acknowledgments: This project was funded in part by the Northwest Center for Small Fruits Research and by USDA-ARS CRIS projects 5358-21000-042-00D and 5358-21000-041-00D. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. The authors thank Matthew Scott and Christopher Rennaker for technical assistance.
- Received March 2013.
- Revision received August 2013.
- Accepted September 2013.
- Published online February 2014
- ©2014 by the American Society for Enology and Viticulture