Foliar Treatments with Urea and Nano-Urea Modify the Nitrogen Profile of Monastrell Grapes and Wines

Abstract

Foliar application of nitrogen can increase readily assimilable nitrogen in grapes without increasing vegetative growth and yield. Recently, nano-formulations have been used to achieve a controlled and precise release of agrochemicals, avoiding losses due to degradation and volatilisation that could cause environmental problems. In this study, foliar urea treatments were applied to Monastrell grapevines in two different formats during three consecutive seasons. The treatments were administered at veraison and one week later, consisting of control, urea, and calcium phosphate nanoparticles doped with urea. The amino acids and ammonium contents were subsequently quantified in both grapes and resulting wines by HPLC-DAD. The results in the grapes depended on the season: in 2019, both treatments produced an increase in total nitrogen content; in 2020, only the nano-treatment caused it; in 2021, both treatments incremented nitrogen content. With regard to the effect on the wines, the results also depended on the season. Thus, in 2019 and 2020, there were increases in nitrogen content in the wines from the nano-treatments, in contrast to 2021 where the increase was in the urea treatment. In conclusion, both treatments can be used to prevent nitrogen deficiency in grapes and guarantee adequate fermentation development, with the additional economic and environmental advantages of nano-treatment due to the lower dosage.

1. Introduction

Nitrogen (N) is an essential macroelement for grapevines, favouring bud break, the rate of fruit set and the flower induction process, which translates into improved growth and productive capacity. Grapevines are characterised by relatively moderate N needs, with a regular rate of mineral absorption and no critical periods [1]. An excess of N causes an increase in vigour, delays grape ripening, and increases sensitivity to fungal attack [2]. A lack of N not only leads to poor grapevine development with smaller leaves and yellowing, lower berry set and thus lower yields [3], but is also responsible for a poorer N content in grapes [4].

The distribution of N in the plant follows a seasonal cycle. In spring, with rising temperatures, growth restarts at bud break. The N needed for the initial growth comes from the N stored in the wood and roots until the N uptake is enough, which occurs around flowering. Soluble N reaches a maximum just before bud break and then decreases until the beginning of fruit growth. During summer and autumn, the plant accumulates reserves in roots and wood. In late autumn, the vineyards reduce their metabolic activity to a minimum and stop growth. During winter, the N reserves are usually located in the roots as amino acids and proteins [5].

On the one hand, the N composition of grapes is important because a minimum is necessary to ensure a correct depletion of sugars during alcoholic fermentation to obtain dry wines [6]; on the other hand, some amino acids are precursors of aromatic compounds [7]. The N composition of grapes at harvest depends on the N status of the grapevine, which is determined by genetic factors (variety, rootstock, clone), cultural practices (soil and canopy management, irrigation), and environmental conditions (climate, soil). In addition, the application of foliar or soil N and elicitors also influences the N content of grapes [8,9]. The amino acid composition of wines is also important because of the possibility of synthesis of biogenic amines by lactic acid bacteria. Excessive amounts of these compounds can cause health problems [10].

The use of foliar N also carries a lower risk of nitrate leaching to groundwater compared to soil applications, as lower amounts are applied directly to the foliage [11,12]. In addition, foliar N is efficient in meeting specific nutritional needs and can increase the yeast-assimilable N of grapes without affecting vegetative growth and yield [13]. Foliar application of urea is recommended when rapid supply of N is needed or when there are difficulties in root absorption, during spring and autumn, due to excessive soil moisture, cold, extreme pruning, or drought [13]. Urea is a good choice for foliar fertilisation because of its small molecular size, non-ionic character, high solubility, and rapid absorption through the leaf cuticle [12]. Despite the advantages of foliar fertilization with urea, different problems have been reported such as leaf necrosis, leaf burn, low penetration rate, and N volatilisation [14]. Another important factor to take into account is the current context of climate change, in which the energy requirements and the production of greenhouse gases of processes are of great importance. Furthermore, there is an increasing demand for nitrogen fertilisers to grow food crops to meet the growing needs of the world’s population. Therefore, it is very important to optimise urea application doses, and it is necessary to look for new application methods that achieve the same results with lower application rates.

In recent years, the use of nanotechnology in agriculture has increased to make better use of agrochemicals (nanoformulations), create devices that detect biotic or abiotic stress (nanosensors), or introduce new genetic manipulation techniques that allow greater efficiency in plant breeding programmes [15]. Regarding nanoformulations, the aim is to produce a controlled release, as well as less losses due to environmental conditions. After foliar application, the nanoparticles must be absorbed by the plant through the leaf. The nanoparticle size is the key factor for a successful uptake, as the size of the channels present in the cuticle is smaller than 4.8 nm and the size of the stomata is 10–100 nm [16].

In vineyard reports, Sabir et al. [17] applied a nitrogen fertiliser in the form of nano-calcite, finding an improvement in vineyard growth, higher production, and better grape quality and nutrient content in leaf. Moreover, Pérez-Álvarez et al. [18] studied the effect of amorphous calcium phosphate nanoparticles loaded with urea on the amino acid content of Tempranillo grape must, observing that the result was similar to that obtained with conventional urea treatment but using a lower dose. In the particular case of Monastrell variety, no research has been found regarding the effect of foliar treatments with urea, whether applied conventionally or in nanoparticle format, on the N composition of grapes and wines. Therefore, the objective of this research was to evaluate the effect of urea treatments applied conventionally and in nanoparticle format on the nitrogen components of Monastrell grapes and wines.

2. Materials and Methods

2.1. Reagents and Standards

Amorphous calcium phosphate nanoparticles doped with urea from Inorganic Chemistry Department (University of Granada, Spain) were used. The synthesis procedure was described in a previous paper [19] and was optimised towards environmental sustainability and manufacturing costs and reported in Carmona et al. [20]. Urea, Tween 80, DL-2-aminoadipic acid (≥99%), diethyl ethoxymethylenmalonate (99%) (DEEMM), ammonium chloride (NH₄⁺), aspartic acid (Asp), glutamic acid (Glu), serine (Ser), asparagine (Asn), glutamine (Gln), histidine (His), glycine (Gly), threonine (Thr), β-alanine (β-Ala), arginine (Arg), α-alanine (α-Ala), γ-aminobutyric acid (GABA), proline (Pro), tyrosine (Tyr), valine (Val), methionine (Met), cysteine (Cys), isoleucine (Iso), leucine (Leu), tryptophan (Trp), phenylalanine (Phe), ornithine (Orn), and lysine (Lys), were supplied from Sigma-Aldrich (St. Louis, MO, USA). Boric acid (pure, pharma grade), glacial acetic acid (HPLC, PAI), NaOH 40% w.w., Sodium azide PA, HCl 0.1 N, and methanol (HPLC, PAI-ACS) from Applichhem-Panreac GmbH, Darmdast, Germany. Acetonitrile HPLC from (Carlo Erba, Val de Reuil, France). Ultrapure water came from a Milli-Q system (Millipore Corp., Bedford, MA, USA).

2.2. Plant Material, Experimental Design in Field and Treatments

The study on Vitis vinifera L. Monastrell variety (14 years old in 2019) on Richter 110 rootstock (R110) was carried out over three years (2019, 2020, and 2021) in the experimental field Hacienda Nueva, located in Cehegín (Murcia, Spain) (latitude 38.11179 and longitude −1.6808). Plants with vigour or growth problems were excluded from the trial. The foliar treatments were applied at veraison and one week later, and were as follows: (i) Control (water), (ii) urea 4.8 g/L, (iii) nanoparticles loaded with urea (0.6 g/L in urea equivalents). All treatments, including the control, were prepared with Tween 80 (0.1% v/v) as a non-ionic surfactant and emulsifier. Each treatment was applied in triplicate, using 10 plants for each of the replicates, and each plant was sprayed with 200 mL of solution. The application was carried out with a Matabi Evolution 15 L battery-powered electric sprayer (Goizper Group, Antzuola, Spain).

2.3. Vinifications

Harvesting was perfomed by hand, the grapes from each replicate of 10 plants were harvested separately and transported to the experimental winery located in Jumilla. Then, each replicate (3 for each treatment) was destemmed, crushed, sulphited (0.08 g/kg), and placed in 50 L stainless steel tanks. The must acidity was adjusted to 5.5 g L⁻¹ with tartaric acid and inoculated with yeast at 0.25 g L⁻¹ (Zymaflore FX10 S. cerevisiae, Laffort^® (Bordeaux, France)). Maceration was prolonged for 14 days, then the fermented grapes were pressed (pneumatic press at 1.8 bar), and the free-run and pressed wines were collected together and stored at room temperature.

2.4. Physicochemical Parameters of Grapes and Wines

The grapes were physicochemically characterised at harvest by potential alcohol, total soluble solids (°Brix), and total acidity (TA) according to OIV (2020). The °Brix/TA ratio was used as a measure of technological ripeness. The determinations in the wines after alcoholic fermentation were as follows: alcohol percentage (v/v) with an Anton Paar SP-1 M Wine Alcolyzer (Anton Paar GmbH, Graz, Austria) and residual sugars as glucose + fructose with a kit for enzymatic analysis from TDI (Gavá, Barcelona, Spain) using a Miura 200 multianalyzer (I.S.E. S.r.l., Rome, Italy). All analyses were performed in triplicate.

2.5. Analysis of Nitrogen Compounds in Grapes by HPLC

The berries (70 g. per replicate) were crushed with a pestle and mortar and centrifuged for 15 min at 4500 rpm (Meditronic Centrifuge, J.P. Selecta, Abrera, Spain) to separate the must from the skins and seeds. The must obtained and was also centrifuged (Eppendorf Centrifuge 5810R, Wesseling-Berzdorf, Germany) at 10,000 rpm for 5 min. Each sample was derivatized following the methodology proposed by Gómez-Alonso et al. [21] with some modifications. Briefly, in a Pyrex tube with screw cap, 1.750 mL of 1 M borate buffer (pH 9), 750 µL of methanol, 1 mL of sample, 20 μL of internal standard DL-2-aminoadipic acid (1 g/L, in 0.1 N HCl)), and 30 μL of DEEMM as derivatizing agent were added. Subsequently, each sample was gently shaken, sonicated (sonicator LT-100PRO, Tierratech S.L., Guarnizo, Spain) for 30 min, and then placed in a Memmert U40 oven (Schwabach, Germany) at 75 °C for 2 h. After cooling at room temperature, they were filtered using a 0.22 µm nylon filter (Filter-Lab^®, Barcelona, Spain) into 1.5 mL HPLC vials. For the chromatographic separation, the equipment used was an Alliance 2695 liquid chromatograph (Waters, PA, USA) coupled to a Waters 2998 diode array detector with a Cortecs^® Shield RP18 2.7 µm 4.6 × 150 mm (Waters, PA, USA) column at 25 °C. The eluent gradient (0.6 mL/min flow rate) used is detailed in

Table 1. Eluent gradient for HPLC determination of nitrogen compounds in grapes and wines.

Time (min) *	0	10	19	20	23	24	26.5	28.5	32.5	60.5
Phase A (%)	94	86	80	74	70	50	37	0	37	94
Phase B (%)	6	14	20	26	30	50	63	100	63	6

* Elution time.

. The mobile phases were as follows: Phase A: 25 mM acetate buffer pH = 5.8 with 0.02% sodium azide; Phase B: acetonitrile, volume injection 3 µL.

For the quantification of the N compounds, the chromatogram obtained at 280 nm was used. The identification of each compound was carried out using the corresponding standards. Calibration curves (1–100 ppm and 2–2000 ppm for Pro) were obtained from 0.1 M HCl solutions of the different compounds.

2.6. Analysis of Nitrogen Compounds in Wines by HPLC

The procedure for the extraction and identification of the different N components in the wines was performed following the same protocol described for grapes. The wine samples were previously centrifuged (Eppendorf Centrifuge 5810R, Wesseling-Berzdorf, Germany) at 10,000 rpm for 5 min and 1 mL of wine was used. The chromatographic conditions used were the same as for grapes, but the injection volume was 6 µL. The analyses were performed at the end of alcoholic fermentation in triplicate.

2.7. Statistical Analysis

Significant differences between treatments for each variable were assessed by analysis of variance (ANOVA) using RStudio 3.6.2 (Boston, MA, USA). Multifactorial analysis of variance (MANOVA), linear discriminant analysis, and Pearson correlation coefficients were performed with Statgraphics Centurion XVIII (Statpoint Inc., Warrenton, VA, USA). A least significant difference (LSD) test was used to compare means and differences were considered statistically significant at p < 0.05.

3. Results and Discussion

3.1. Physicochemical Parameters of Grapes and Wines

The results of the different physicochemical parameters measured in grapes and wines are shown in

Table 2. Physicochemical parameters in grapes and wines from control and treated grapes (urea and nano-urea) during three seasons.

		Season	Control	Urea	Nano-Urea	p
Grapes		2019	8.16 ± 0.84	8.17 ± 0.54	7.83 ± 0.30	ns
	°Brix/TA	2020	10.83 ± 0.62	11.07 ± 0.34	10.49 ± 0.84	ns
		2021	12.29 ± 0.93	12.13 ± 0.18	10.91 ± 1.03	ns
	Potential alcohol (% vol 20 °C)	2019	13.55 ± 0.52	13.20 ± 0.51	13.43 ± 0.34	ns
		2020	15.07 ± 0.39	14.45 ± 0.66	14.55 ± 0.26	ns
		2021	13.85 ± 0.26 b	14.33 ± 0.39 a	13.71 ± 0.41 b	*
Wines		2019	12.94 ± 0.16	12.86 ± 0.07	13.15 ± 0.42	ns
	Alcohol	2020	14.72 ± 0.34 a	13.84 ± 0.29 b	14.18 ± 0.20 ab	*
	(% vol 20 °C)	2021	13.44 ± 0.15 b	13.90 ± 0.13 a	13.32 ± 0.05 b	**
		2019	8.50 ± 5.80 a	2.10 ± 0.36 b	1.77 ± 0.06 b	*
	Residual sugar	2020	1.83 ± 0.21 a	1.40 ± 0.10 b	1.40 ± 0.00 b	*
	(g L−1)	2021	2.43 ± 0.49	2.17 ± 0.06	1.73 ± 0.06	ns

TA: must total acidity (g/L tartaric acid). Different letters in the same row indicate significant differences according to LSD test (statistically significant at ** p < 0.01; * p < 0.05; ns: not significant).

.

Regarding the grapes, the ratio °Brix/TA indicated that in 2019, a lower technological maturity was reached due to a lower °Brix and also a higher TA. This was due to the fact that harvest had to be brought forward to avoid rotting problems derived from the torrential rains in mid-September. In contrast, the highest technological maturity was reached in 2021, although the alcoholic potential was lower than in 2020 due to the lower TA values in 2021 compared to the previous year.

As for treatments, they mainly had no effect on potential alcohol, only a higher value was found for the urea treatment in 2021. Moreover, technological maturity was also not affected. In different studies of foliar treatments with urea on Tempranillo, Monastrell, Cabernet Sauvignon, Viognier, Merlot, and Pinot Noir, a diversity of behaviours on grape ripening was found depending on the years studied and also on the varieties [13,22,23].

Concerning the alcohol content of the wine, in 2019, the control wine reached the lowest value, and in 2020, it was the highest. These results are in accordance with the lowest and highest alcohol potential in the control grapes. The treatments produced different effects depending on the year. In 2019, there were no differences between the control and the treatments. In 2020, the wine from control grapes had the highest value of this parameter with respect to both treatments, in contrast to 2021 in which the wine from urea-treated grapes had the highest value. Other authors found no influence on the alcohol content of wines from varieties such as Tempranillo, Cabernet Sauvignon, and Regent after foliar treatments with urea [24,25,26].

Regarding residual sugar, the same tendency was found throughout the three seasons with a higher depletion of residual sugars in the wines from both urea and nano-urea treatments. The results obtained in 2019 were remarkable, in which the must from the control grapes did not reach a complete fermentation (wine residual sugar > 8 g L⁻¹); however, this problem did not appear in the wines from urea and nano-urea treatments.

In addition, Pearson’s product moment statistic was performed (Figure 1), obtaining a correlation of −0.45 between the total content of nitrogen compounds in the must and the level of residual sugars in the wine, which indicates that the lower the content of nitrogen compounds in the must, the higher the probability of having a higher amount of residual sugars in the corresponding wine. As for the individual nitrogen compounds, most of them showed a similar negative correlation, only Asp and Glu showed a discrete positive correlation, suggesting that in this case, Asp and Glu were less important in the depletion of sugars. Compared to the findings of other authors regarding the suitability of different nitrogen sources for S. cerevisiae during alcoholic fermentation, Kemsawasd et al. [27] found that Asp was a good nitrogen source. In addition, other authors have shown that in the case of Glu, growth rates in synthetic musts of S. cerevisiae depend on the strain [28]. Authors such as Gobert et al. [29] showed in a study how a higher amount of residual sugar is consistent with the fact that in nitrogen-deficient musts there is a loss of sugar uptake capacity by the yeast cells, as a nitrogen deficiency is related to a high turnover rate of the sugar transporter.

3.2. Nitrogen Composition of Grapes

Table 3. Must nitrogen composition (mg/L) of control and treated (urea and nano-urea) grapes over 2019, 2020, and 2021.

		2019				2020				2021			Multifactorial Analysis
	Control	Urea	Nano-Urea	p	Control	Urea	Nano-Urea	p	Control	Urea	Nano-Urea	p	T (%)	S (%)	TxS (%)
Asp	27.6 ± 0.3 b	19.4 ± 0.5 c	34.6 ± 1.1 a	***	10.2 ± 0.5 b	9.9 ± 0.2 b	11.6 ± 0.7 a	*	7.7 ± 0.1 b	11.0 ± 0.6 a	7.9 ± 1.0 b	**	4 ***	83 ***	12 ***
Glu	33.3 ± 0.7 b	27.6 ± 0.7 c	44.2 ± 1.1 a	***	13.1 ± 0.6 b	14.4 ± 0.2 b	17.2 ± 1.0 a	***	10.7 ± 0.3 c	20.5 ± 0.9 a	12.5 ± 1.1 b	***	5 ***	80 ***	15 ***
Asn+Ser	42.3 ± 3.5 c	63.8 ± 2.8 b	93.7 ± 3.8 a	***	91.0 ± 6.0	92.5 ± 2.4	104.4 ± 7.8	ns	55.1 ± 2.2 b	94.0 ± 1.9 a	56.8 ± 9.0 b	***	22 ***	39 ***	36 ***
Gln	53.6 ± 4.9 c	88.3 ± 4.3 b	176.7 ± 7.3 a	***	198.5 ± 112.9 b	168.3 ± 6.8 c	239.2 ± 20.0 a	**	68.8 ± 3.2 b	160.2 ± 2.8 a	81.3 ± 112.2 b	***	15 ***	54 ***	29 ***
His	13.1 ± 0.6 c	19.8 ± 0.5 b	43.4 ± 1.5 a	***	69.7 ± 6.2 b	57.6 ± 3.2 b	81.4 ± 8.7 a	*	17.4 ± 1.0 b	38.1 ± 0.9 a	20.3 ± 3.6 b	***	7 ***	77 ***	14 ***
Gly	6.0 ± 0.3 c	6.9 ± 0.1 b	9.5 ± 0.3 a	***	12.3 ± 0.6 a	10.9 ± 0.6 b	13.0 ± 0.8 a	*	6.9 ± 0.1 b	11.0 ± 0.2 a	7.1 ± 0.6 b	***	7 ***	63 ***	28 ***
Thr	14.9 ± 1.2 c	21.7 ± 0.9 b	34.1 ± 1.1 a	***	43.1 ± 3.3	43.0 ± 3.6	49.7 ± 3.7	ns	19.6 ± 1.2 b	33.2 ± 0.5 a	16.1 ± 1.7 c	***	7 ***	70 ***	20 ***
β-Ala	10.5 ± 0.8 c	15.4 ± 0.6 b	24.3 ± 0.8 a	***	28.9 ± 4.3	26.5 ± 0.8	34.5 ± 4.5	ns	13.9 ± 0.8 b	23.6 ± 0.3 a	11.4 ± 1.2 c	***	8 ***	60 ***	27 ***
Arg+GABA	42.5 ± 3.9 c	93.8 ± 4.9 b	202.6 ± 10.7 a	***	213.8 ± 20.2 b	238.9 ± 11.2 b	280.4 ± 25.2 a	*	95.6 ± 4.5 c	268.0 ± 4.9 a	181.1 ± 34.7 b	***	31 ***	45 ***	21 ***
α-Ala	21.5 ± 1.1	22.1 ± 1.8	22.2 ± 0.3	ns	23.8 ± 1.0 b	24.6 ± 1.1 b	27.0 ± 0.8 a	*	31.2 ± 0.8 c	47.9 ± 0.6 b	53.8 ± 1.6 a	***	10 ***	75 ***	14 ***
Pro	199.3 ± 8.4 c	322.8 ± 9.6 b	386.4 ± 6.0 a	***	345.9 ± 14.5 b	357.2 ± 17.3 b	393.6 ± 11.4 a	*	216.2 ± 7.2 b	360.8 ± 7.8 a	291.3 ± 62.4 a	**	45 ***	23 ***	24 ***
NH4+	14.9 ± 0.8 c	25.3 ± 0.8 b	33.0 ± 0.4 a	***	21.6 ± 1.1 b	24.2 ± 1.5 b	33.2 ± 1.8 a	***	9.6 ± 0.3 b	14.1 ± 0.4 a	16.8 ± 3.2 a	**	40 ***	51 ***	7 ***
Tyr	7.0 ± 0.5 c	8.6 ± 0.2 b	10.5 ± 0.3 a	***	26.1 ± 0.8 b	25.4 ± 1.0 b	37.3 ± 1.9 a	***	7.23 ± 0.4 c	16.2 ± 0.6 a	10.8 ± 0.8 b	***	6 ***	85 ***	9 ***
Val	8.9 ± 0.4 c	12.5 ± 0.2 b	20.7 ± 1.3 a	***	33.6 ± 2.1 b	28.4 ± 0.7 c	39.4 ± 2.6 a	**	15.0 ± 0.3 b	26.5 ± 0.7 a	12.7 ± 0.6 c	***	4 ***	72 ***	22 ***
Met	2.8 ± 0.3 b	2.9 ± 0.2 b	4.0 ± 0.6 a	*	4.8 ± 0.7 b	4.8 ± 0.4 b	6.1 ± 0.4 a	*	1.9 ± 0.1	1.9 ± 0.1	1.9 ± 0.12	ns	7 ***	85 ***	3 *
Cys	10.4 ± 1.8 a	6.5 ± 0.5 b	7.1 ± 0.9 b	*	13.2 ± 2.1 a	8.9 ± 0.9 b	9.2 ± 1.5 b	*	12.3 ± 1.0 a	7.4 ± 0.4 b	5.8 ± 0.7 c	***	65 ***	16 **	5
Iso	6.5 ± 0.1 c	8.0 ± 0.0 b	10.8 ± 0.8 a	***	15.1 ± 1.1 ab	13.2 ± 0.6 b	17.0 ± 1.1 a	**	12.3 ± 0.7 b	14.0 ± 0.5 a	8.5 ± 0.7 c	***	1	65 ***	31 ***
Leu	8.1 ± 0.4 c	10.9 ± 0.2 b	16.1 ± 0.7 a	***	24.8 ± 1.7 a	20.6 ± 0.6 b	27.8 ± 2.3 a	**	14.3 ± 0.9 b	20.6 ± 0.6 a	11.3 ± 0.8 c	***	3 ***	70 ***	25 ***
Trp	20.3 ± 1.4 c	23.6 ± 1.2 b	32.2 ± 1.8 a	***	59.3 ± 5.8 a	45.3 ± 2.5 b	52.8 ± 4.3 ab	*	29.7 ± 1.0 b	32.6 ± 0.9 a	18.5 ± 1.9 c	***	1 ns	81 ***	16 ***
Phe	5.3 ± 0.2 c	9.1 ± 0.3 b	13.4 ± 1.0 a	***	17.3 ± 2.7	14.7 ± 0.6	17.7 ± 1.8	ns	9.2 ± 0.6 b	13.8 ± 0.6 a	6.4 ± 0.2 c	***	4 **	57 ***	34 ***
Orn	2.1 ± 0.1 c	2.3 ± 0.1 b	2.8 ± 0.1 a	***	2.6 ± 0.1	2.7 ± 0.1	2.6 ± 0.3	ns	2.2 ± 0.6	2.1 ± 0.1	1.8 ± 0.0	ns	1	42 ***	29 **
Lys	2.7 ± 0.1 c	3.2 ± 0.3 b	3.8 ± 0.2 a	***	3.4 ± 0.1	3.9 ± 0.1	4.1 ± 0.8	ns	2.6 ± 0.2 b	3.0 ± 0.2 ab	3.5 ± 0.3 a	*	45 ***	32 ***	3
Total	553.6 ± 19.7 c	814.6 ± 23.9 b	1226.0 ± 38.8 a	***	1271.9 ± 64.1 b	1235.7 ± 28.8 b	1499.1 ± 91.6 a	**	659.3 ± 23.1 c	1220.3 ± 23.7 a	837.7 ± 126.2 b	***	24 ***	47 ***	26 ***
Total-Pro	354.3 ± 16.6 c	491.8 ± 14.3 b	839.6 ± 32.8 a	***	926.0 ± 60.0 b	878.4 ± 32.3 b	1105.6 ± 82.6 a	**	443.1 ± 16.1 c	859.6 ± 15.9 a	546.4 ± 66.5 b	***	18 ***	53 ***	26 ***
N 1	88.5 ± 3.3 c	136.2 ± 3.4 b	210.9 ± 6.2 a	***	216.0 ± 11.1 b	211.4 ± 5.0 b	261.6 ± 16.2 a	**	105.8 ± 3.7 c	202.7 ± 3.9 a	141.1 ± 18.4 b	***
N-Pro	64.2 ± 2.8 c	96.9 ± 2.3 b	163.9 ± 5.5 a	***	174.0 ± 10.6 b	168.0 ± 5.3 b	213.7 ± 15.1 a	**	79.5 ± 2.9 c	158.8 ± 2.9 a	105.7 ± 11.0 b	***

¹: calculated nitrogen (determined from the concentration of each amino acid and its relative N content). Multifactorial analysis of nitrogen compounds in wines with the factors of treatment (T), season (S), and treatment–season interaction (TxS). Different letters in the same row indicate significant differences according to the LSD test (statistically significant at *** p < 0.001; ** p < 0.01; * p < 0.05; ns: no significant).

shows the values obtained in the must of the control grapes and those treated with urea and nano-urea during the three years studied. The concentrations of each amino acid and NH₄⁺ ion varied according to the year of study. In 2020, the synthesis of N compounds was the highest, followed by 2021 and 2019. The lower concentration obtained in 2019 could be partly due to the lack of maturity of the grapes. Authors such as Garde-Cerdán et al. [30] point out that in the Monastrell variety, the maximum composition of nitrogen coincides with the maximum phenological and technological maturity.

Regarding total N calculated, in 2019, the control must showed the lowest concentration, reaching only 88.5 mg/L, and discounting Pro contribution, an amino acid that is more difficult for yeasts to assimilate. The concentration dropped to 64.2 mg/L, much lower than the minimum established for yeast-assimilable nitrogen (YAN) of 140 mg/L to guarantee an adequate consumption of sugars at the end of alcoholic fermentation [6]. These very low values could be related to the fact that this year control musts did not finish depleting the sugars at the end of the alcoholic fermentation (Table 2). The calculated N obtained in 2020 was much higher than that obtained in 2019, above that minimum value (140 mg/L). In 2021, it was, again, higher, considerably higher than in 2019. Even so, during these two years, the development of alcoholic fermentation was optimal.

The effect of the treatments varied depending on the season: in 2019, both treatments (urea and nano-urea) caused an increase in total N compounds, being 47% and 121%, respectively. In contrast, in 2020, only the nano-urea treatment was able to increase them by 18%. In 2021, the treatment with urea was the most effective, so the increase in N compounds was 85%, and 27% with nano-urea. The calculated N increased in 2019 and 2021 for both treatments; however, in 2020, there was only an increase in the musts with the nano-urea treatment. This difference in 2020 could be due to the fact that in this year, the N requirements of the vineyard were lower, which is reflected in the optimal N content in the control must. This same fact was reported by Garde-Cerdán et al. [22], who showed that when the vineyard had a low N requirement, the application of urea hardly affected the amino acid content in the must.

Regarding the individual amino acids analysed, the majority were Pro, followed by Arg+GABA which coeluted and Glu. In contrast, the least abundant amino acids were Orn and Lys.

In terms of treatments, in 2019, treatment with urea led to a general increase in all of them except Asp, Glu, and Cys, which had lower concentrations than the control must, and α-Ala and Met, which were not affected by this treatment. The treatment with nano-urea generally increased all amino acids except Cys, which had lower concentrations than the control, and α-Ala, which was not affected by the treatment. In 2020, the urea treatment had lower concentrations of some N compounds (Gln, Val, Cys, Iso, Leu, and Trp) than the control must. In contrast, there was a general increase with the nano-urea treatment, except for Cys and Trp, which showed lower values than the control. Phe, Orn, and Lys were not affected by the treatment. In 2021, there was a general increase in amino acids and NH₄⁺ ion with the urea treatment, except for Cys, which had a lower value than the control. Met and Orn were not affected. With the nano-urea treatment, the levels of Thr, β-Ala, Val, Cys, Trp, Iso, Leu, and Phe were lower than in the control must. In contrast, Met and Orn were not affected and Glu, Arg+GABA, α-Ala, NH₄⁺, Pro, Tyr, and Lys increased.

The results found by other authors varied depending on the vintage and variety of the study. Thus, Garde-Cerdán et al. [31] showed an increase in the synthesis of most amino acids in Tempranillo grapes treated with urea. In contrast, in another study by the same author [22] in Tempranillo and Monastrell during two vintages, one of the years studied had lower concentrations than the controls in both varieties, but in the following vintage no changes were found in either Tempranillo or Monastrell. Another report from Pérez-Álvarez et al. [18], in which the effect of urea at two different doses and of nano-urea on Tempranillo was evaluated, it was observed that YAN increased with all treatments, as did the different amino acids with the highest dose of urea and with the nano-treatment. Murillo-Peña et al. [32], in a study with different doses of urea in foliar application, found an increase in the total amount of amino acids but not of YAN in treatments during pre-veraison and in veraison.

The multifactorial analysis showed that vintage was the determining factor for the results obtained, highlighting its effect on Asp, Glu, Tyr, Met, and Trp, which reached or exceeded 80% of the variability explained. On the opposite side, we found Pro (23%) and Cys (16%). Treatment was relevant for Arg+GABA, Pro, NH₄⁺, Cys, and Lys. In addition, the interaction treatment–season was also important, especially in the case of amino acids Asn+Ser, Iso, and Phe.

3.3. Nitrogen Composition of Wines

Table 4. Wine nitrogen composition (mg/L) of control and treated (urea and nano-urea) grapes during 2019, 2020, and 2021.

		2019				2020				2021			Multifactorial Analysis
	Control	Urea	Nano-Urea	p	Control	Urea	Nano-Urea	p	Control	Urea	Nano-Urea	p	T (%)	S (%)	TxS (%)
Asp	2.06 ± 0.15 c	2.43 ± 0.11 b	3.06 ± 0.11 a	***	3.26 ± 0.13	3.23 ± 0.51	3.99 ± 0.26	ns	4.89 ± 0.27 a	3.78 ± 0.15 b	2.48 ± 0.08 c	***	2	37 ***	56 ***
Glu	4.12 ± 0.64 b	4.34 ± 0.29 b	7.68 ± 1.56 a	**	9.41 ± 2.83	8.48 ± 1.23	12.74 ± 1.56	ns	2.94 ± 0.21 a	3.07 ± 0.33 a	1.91 ± 0.18 b	**	7 **	75 ***	9 ***
Asn+Ser	1.26 ± 0.19 b	1.32 ± 0.18 b	2.80 ± 0.47 a	**	6.44 ± 1.43 b	6.66 ± 0.64 b	9.23 ± 1.23 a	*	7.28 ± 0.45 b	10.74 ± 0.60 a	6.91 ± 0.33 b	***	4 **	80 ***	13 ***
Gln	2.23 ± 0.17 b	2.53 ± 0.39 b	5.57 ± 2.14 a	*	5.68 ± 0.74 b	5.74 ± 0.28 b	7.69 ± 0.59 a	**	2.58 ± 0.50 b	5.98 ± 0.70 a	2.56 ± 0.17 b	***	13 ***	42 ***	33 ***
His	3.37 ± 0.11	3.52 ± 0.21	4.02 ± 0.50	ns	5.64 ± 0.82	5.19 ± 0.38	6.51 ± 0.80	ns	4.25 ± 0.19 b	7.17 ± 0.42 a	3.41 ± 0.35 c	***	7 **	40 ***	44 ***
Gly	4.55 ± 0.08 b	4.69 ± 0.06 b	5.52 ± 0.22 a	***	7.66 ± 1.03 b	7.61 ± 0.51 b	9.68 ± 0.85 a	*	4.58 ± 0.16 b	6.08 ± 0.33 a	4.74 ± 0.18 b	***	6 **	78 ***	11 ***
Thr	3.40 ± 0.14	3.48 ± 0.03	3.66 ± 0.13	ns	4.19 ± 0.22	4.00 ± 0.15	4.57 ± 0.31	ns	2.91 ± 0.13 b	3.54 ± 0.12 a	2.95 ± 0.09 b	***	3 *	76 ***	14 ***
β-Ala	2.37 ± 0.03 b	2.42 ± 0.12 b	2.61 ± 0.08 a	*	3.64 ± 0.78	3.29 ± 0.21	3.73 ± 0.02	ns	2.04 ± 0.11 b	2.22 ± 0.08 a	1.89 ± 0.03 b	**	0	85 ***	4
Arg	4.29 ± 0.29	4.67 ± 0.14	5.28 ± 0.64	ns	10.82 ± 2.68 b	10.87 ± 0.98 b	15.65 ± 1.73 a	*	2.90 ± 0.12 b	6.44 ± 0.85 a	3.43 ± 0.61 b	***	4 **	80 ***	10 ***
GABA	4.75 ± 0.21 b	4.75 ± 0.12 b	7.12 ± 1.45 a	*	15.42 ± 3.95 b	14.20 ± 1.31 b	20.86 ± 2.02 a	*	3.33 ± 0.43 c	9.54 ± 1.39 a	5.65 ± 0.66 b	***	6 **	79 ***	10 ***
α-Ala	2.18 ± 0.04 b	2.30 ± 0.07 b	3.03 ± 0.53 a	*	5.49 ± 0.93 b	5.33 ± 0.57 b	8.18 ± 1.70 a	*	1.30 ± 0.17 c	3.71 ± 0.54 a	2.20 ± 0.26 b	***	8 **	72 ***	13 ***
Pro	102.73 ± 35.67 b	109.34 ± 22.22 b	263.41 ± 57.22 a	**	564.93 ± 88.04 ab	449.66 ± 59.60 b	679.66 ± 48.61 a	*	94.82 ± 26.79 b	272.28 ± 19.55 a	75.11 ± 23.36 b	***	3 **	81 ***	13 ***
NH4+	2.52 ± 0.13	2.45 ± 0.07	5.73 ± 2.77	ns	4.08 ± 1.15	4.13 ± 0.65	6.33 ± 1.11	ns	3.17 ± 0.28 a	3.34 ± 0.61 a	2.31 ± 0.26 b	*	19 *	24 **	27 *
Tyr	3.18 ± 0.35 b	3.76 ± 0.08 b	4.57 ± 0.54 a	*	5.36 ± 0.30 b	4.46 ± 0.06 c	6.44 ± 0.68 a	**	2.64 ± 0.14	3.08 ± 0.43	2.82 ± 0.43	ns	11 ***	72 ***	11 ***
Val	2.56 ± 0.07	2.46 ± 0.05	2.58 ± 0.09	ns	2.86 ± 0.13 b	2.92 ± 0.02 b	3.32 ± 0.19 a	*	2.40 ± 0.21 a	2.68 ± 0.14 a	2.08 ± 0.04 b	**	1	63 ***	28 ***
Met	2.67 ± 0.37	2.84 ± 0.14	2.84 ± 0.13	ns	3.12 ± 0.25	3.18 ± 0.09	3.47 ± 0.27	ns	2.19 ± 0.13 a	2.11 ± 0.10 a	1.56 ± 0.04 b	***	0	83 ***	10 **
Cys	3.18 ± 0.06	3.05 ± 0.11	3.15 ± 0.34	ns	4.61 ± 0.62	4.14 ± 0.27	3.51 ± 0.42	ns	5.58 ± 0.20 a	5.14 ± 0.61 a	3.88 ± 0.16 b	**	18 ***	60 ***	11 *
Iso	3.62 ± 0.17	3.44 ± 0.34	3.96 ± 0.26	ns	4.72 ± 0.37	3.98 ± 0.37	4.47 ± 0.25	ns	2.61 ± 0.09 b	2.89 ± 0.12 a	2.40 ± 0.03 c	**	1	83 ***	8 **
Leu	3.90 ± 0.10 b	4.06 ± 0.02 b	4.32 ± 0.17 a	*	5.25 ± 0.56	4.97 ± 0.26	5.80 ± 0.31	ns	3.73 ± 0.12 b	4.92 ± 0.25 a	4.03 ± 0.17 b	***	7 **	63 ***	20 ***
Trp	4.03 ± 0.09 b	4.13 ± 0.16 b	4.59 ± 0.17 a	**	4.97 ± 0.21	4.81 ± 0.32	5.40 ± 0.28	ns	3.54 ± 0.28 b	4.17 ± 0.16 a	3.36 ± 0.08 b	**	3 *	74 ***	16 ***
Phe	2.7 ± 0.28	3.10 ± 0.23	3.19 ± 0.17	ns	3.74 ± 0.24	3.80 ± 0.27	4.49 ± 0.57	ns	2.18 ± 0.22 b	3.24 ± 0.36 a	2.15 ± 0.10 b	**	8 **	66 ***	16 **
Orn	1.97 ± 0.05	2.21 ± 0.10	2.34 ± 0.28	ns	3.11 ± 0.32	3.05 ± 0.15	3.62 ± 0.50	ns	1.48 ± 0.02 b	1.64 ± 0.04 a	1.52 ± 0.04 b	**	3 *	88 ***	3
Lys	4.25 ± 1.29	3.77 ± 0.04	4.99 ± 0.55	ns	8.64 ± 2.71	8.13 ± 1.27	10.24 ± 0.90	ns	2.68 ± 0.35 c	6.77 ± 0.61 a	4.69 ± 0.66 b	***	6 *	67 ***	14 *
Total	171.90 ± 38.69 b	181.07 ± 22.75 b	356.03 ± 57.68 a	**	693.04 ± 108.50 ab	571.83 ± 67.16 b	839.58 ± 58.68 a	*	166.03 ± 27.28 b	374.54 ± 26.75 a	144.00 ± 27.34 b	***	3 **	80 ***	13 ***

Multifactorial analysis of nitrogen compounds in wines with the factors of treatment (T), season (S), and treatment–season interaction (TxS). Different letters in the same row indicate significant differences according to the LSD test (statistically significant at *** p < 0.001; ** p < 0.01; * p < 0.05; ns: not significant).

shows the values for nitrogen composition in wines made from control grapes and those treated with urea and nano-urea at the end of alcoholic fermentation during the three years studied.

In relation to the N compounds in the control wines, 2019 and 2021 showed similar values; in contrast, in 2020, the total amount of N compounds was much higher than in the other two years.

The effect of the treatments depended on the vintage, so in 2019, the control wines and the wine from urea treated grapes showed almost the same total content of N compounds, while the wine from nano-urea treatment doubled it. In 2020, the wine from the urea treatment showed lower concentrations than the control wine, but the wine from the nano-urea treatment increased them, although these changes were not significant. In 2021, there was only an increase in total N compounds in the wine from the urea treatment. These values are in line with the initials in grapes, with a decrease corresponding to consumption during fermentation, although the extent of the reduction depended on the vintage. Thus, in 2019, an average decrease of around 73% was detected for the different treatments in the amount of N compounds in the grapes. This decrease was similar in 2021 with an average of 75%. In contrast, the decrease in 2020 was 48% on average for all treatments. This lower percentage reduction was due to the higher content of N compounds in the 2020 musts.

In relation to the different nitrogen compounds analysed, the main amino acid was Pro, representing between 52% and 82% of total N compounds. Regarding treatments, in the 2019 wines from the nano-urea treatment, half of them showed higher values than those obtained in the control wine, while the other half did not vary. Only Asp increased with the urea treatment. In 2020, some amino acids increased with the nano-urea treatment: Asn+Ser, Gln, Gly, Arg, GABA, α-Ala, Pro, Tyr, and Val, but the rest were not altered. In 2021, increases were mainly observed with the urea treatment, except for Asp, which showed lower contents than the control wines. Glu, Thr, β-Ala, NH₄⁺, Tyr, Val, and Cys contents were not affected. However, in the nano-urea treatment, most of the amino acids analysed were not affected, except for Asp, Glu, His, Val, Met, Cys, Iso, and NH₄⁺ ion, which showed lower concentrations than the control wines. GABA and Lys increased their values.

As can be seen, the concentration of the main N compounds decreased in all vintages compared to that shown in the musts due to their consumption by the yeasts during alcoholic fermentation. In contrast, the variation of Pro depended on the amount of readily available N in the musts. Thus, in 2019 and 2021, when the calculated N-Pro parameter showed values below 164 mg/L, there were decreases in the Pro content in the wines (compared to the musts). This behaviour could indicate that when there is less N availability in the musts, yeasts are also able to consume Pro during fermentation. This fact was already reported by Arias-Gil et al. [33] as they detected a higher consumption of Pro by yeasts when musts had a low composition in the rest of amino acids. Moreover, in 2020, when N-Pro was higher, the Pro content in the wines increased. This increase may be due to several factors, the first of which is that this year there should not have been any Pro consumption, as the must was rich in other amino acids. In addition, during fermentation, there is a loss of mass of about 10% due to CO₂ emissions, which also influences the increase in concentration. Furthermore, under certain circumstances, it has been reported that yeasts can accumulate proline due to the overexpression of several genes. In the case of S. cerevisiae, the PRO1 gene causes this accumulation, which is related to an improvement in stress tolerance due to the presence of ethanol [34]. This could be related to the fact that the highest ethanol concentrations in wine were reached in 2020. Gutiérrez-Gamboa et al. [35] in Tempranillo wines from urea treated grapes found lower values than those obtained in control wines for 10 of the amino acids studied, and an increase only in Met; the rest of the amino acids analysed, including Pro, were not affected.

The multifactorial analysis indicated that the most important factor affecting the results was the season, as was the case for grapes, followed by the treatment–season interaction and finally the treatment. However, in the case of Asp, His, and NH₄⁺, the most important factor was the treatment–year interaction, with 56%, 44%, and 27% respectively. Moreover, the treatment factor had a limited influence, with its effect only on the amino acids Cys, Gln, and Tyr.

3.4. Multivariate Discriminant Analysis

A discriminant analysis was performed with the different measures of the variables in grapes and wines at the end of alcoholic fermentation in the three years studied. This analysis is a widget that, using a linear relation, allows a classification in different groups and provides the possibility of classifying new measures of the variables in the previously established groups. Figure 2 shows that two statistically significant (p < 0.05) canonic discriminating functions were obtained, explaining 100% of the variance. The relative percentage was 63.48% for Function 1 and 36.52% for Function 2.

The nano-urea treatment was the best separated, being located in the bottom left of the graph; however, the control was in the bottom right and urea was near the centre of the graph. This means that the results obtained from the control and nano-urea treatments were the most differentiated.

The standardised coefficient (

Table 5. Standardised coefficient of the discriminant function for the treatment factor.

	Function 1	Function 2
Asp	−4.470	−4.528
Glu	3.265	2.850
Asn+Ser	11.249	10.866
Gln	−8.503	−4.487
His	17.221	2.873
Gly	−4.831	−2.567
Thr	7.317	4.214
β-Ala	5.397	2.069
Arg+GABA	−13.709	−5.698
α-Ala	5.186	2.527
Pro	2.150	−0.303
NH4+	−7.363	−2.951
Tyr	−7.018	0.122
Val	19.354	0.668
Met	1.728	1.517
Cys	0.793	0.465
Iso	−1.497	−8.096
Leu	−16.820	1.317
Trp	−10.434	−8.579
Phe	2.176	7.474
Orn	0.578	0.339
Lys	−0.274	0.542

) of the different variables indicated that the highest discriminating powers for Function 1 were Val, His, and Leu and Asp+Ser, Trp, and Iso for Function 2.

4. Conclusions

Based on the results obtained, it can be concluded that in grapes, both urea and nano-urea treatments caused an increase in nitrogen compounds in all the vintages studied, more significant when the amount of N in the control grapes was low. Thus, both treatments could be used to prevent a lack of nitrogen compounds in the grapes and thus guarantee a correct development of alcoholic fermentation. However, in the wines, the effect of the treatments was diluted and more variable, with wines in which the N content was not affected by the treatments, as well as decreases and increases. This variability is due both to the different initial amount in the grapes and to the different nitrogen consumption during fermentation. In any case, these results in the wines were mainly dependent on the year and to a lesser extent on the treatment.

Nevertheless, the nano-treatment offers the additional advantage of a urea dose eight times lower than that of conventional treatment, providing comparable results. This could be an economic and environmental advantage for farmers.