Aromatic Fingerprint of Emerging White Grape Genotypes: Free and Bound Volatiles Under Warm Climate Conditions

Abstract

This study aimed to evaluate the aromatic potential of four new Monastrell-derived white grapevine genotypes (MC180, MC69, MT103, MV67) compared with Verdejo over four consecutive seasons (2020–2023), with particular emphasis on both free and glycosidically bound volatile compounds. This approach provided novel insight into the aromatic composition of emerging cultivars under warm climate conditions and their potential suitability for future viticultural use. Free and glycosidically bound volatile compounds were extracted and analyzed using Gas Chromatography–Mass Spectrometry (GC-MS). Differences in aroma profiles were observed among genotypes and seasons. MV67 and MC69 showed higher levels of monoterpenes and volatile phenols, suggesting enhanced floral and complex aromatic potential. Seasonal effects strongly influenced C6 compounds and norisoprenoids, highlighting the importance of climatic conditions in shaping grape aroma. Multifactorial analysis revealed that season had the greatest impact on most compound families, although genotype and its interaction with season were also significant. These results demonstrate that genotype–environment interactions play a key role in determining aromatic composition. The elevated levels of aroma precursors, particularly glycosidically bound compounds, indicate promising enological potential for producing fresh, aromatic white wines. Therefore, these new cultivars represent suitable alternatives for white wine production in warm climates.

1. Introduction

As a result of climate change, vineyards need to adapt to new environmental conditions. High temperatures associated with warm climates can reduce the accumulation of key aroma compounds and accelerate their degradation, particularly in white grape varieties, leading to wines with lower aromatic intensity and freshness [1].

Wine aroma is one of the key organoleptic attributes used to distinguish between grape varieties, above all in white varieties. It originates not only from fermentation-derived compounds but also from varietal aromas intrinsic to the grape itself. These varietal aromas were associated with both free volatile compounds and non-volatile, glycosidically bound precursors that can be enzymatically or chemically released during winemaking [2]. In fact, a substantial proportion of grape aroma compounds exist in this bound form, which is odorless until hydrolyzed, at which point they contribute significantly to the wine’s sensory profile [3].

One strategy being pursued at the “Instituto Murciano de Investigación y Desarrollo Agrario y Medioambiental” (IMIDA) to address this issue involves the development of new grapevine cultivars derived from Monastrell through targeted crossbreeding with other varieties such as Cabernet Sauvignon, Tempranillo, and Verdejo. While the primary objective was to investigate the phenolic content of new red genotypes, as can be seen in different articles [4,5,6,7,8], these new white genotypes emerged from red varieties, prompting a comprehensive study to elucidate their organoleptic characteristics. Furthermore, the interest in registering these new grapevine cultivars arose due to the current scarcity of white grapevine cultivars in warm regions, which could also provide fresh attributes in line with contemporary consumer preferences. These genotypes (MC180, MC69, MT103, MV67) were selected for their ability to produce high-quality white wines with elevated acidity and a favorable aromatic profile. Furthermore, Verdejo was selected as a reference variety due to its recognized oenological quality and aromatic profile, making it a suitable standard for comparing the aromatic potential of the new genotypes evaluated in this study.

Given the recent development of these new genotypes, understanding their aromatic composition is essential to assess their enological potential. Previous studies have described the aromatic profile of wines produced from these materials [9,10]; however, the aromatic potential of the grapes themselves, particularly distinguishing between free and glycosidically bound fractions, has not yet been evaluated. This represents a key knowledge gap, especially under warm climate conditions where aroma preservation is critical. Therefore, evaluating both free and glycosidically bound fractions at the grape level is essential to better understand the aromatic potential of these new genotypes and their suitability for warm climate viticulture.

Based on the limited availability of white grapevine cultivars in warm regions and the need to provide fresh attributes aligned with contemporary consumer preferences, these genotypes were selected. The pursuit of white grape genotypes adapted to the new conditions has not only begun in the Murcia Region but also in other countries within the viticultural domain.

The development of new grapevine cultivars adapted to warm climates is also being pursued in other viticultural regions worldwide. In France, new white genotypes such as Petit Manseng and Liliorila (Vitis vinifera L.), Voltis and Floréal (multispecific resistant hybrid) are being introduced or evaluated to improve adaptation and maintain wine quality under changing climatic conditions [11,12]. Similarly, the University of California, Davis, has developed new white cultivars such as Caminante blanc and Ambulo blanc (Vitis vinifera L.), currently under evaluation in several regions [13]. In Germany, long-term breeding programs have produced numerous white PIWI varieties (multispecific hybrids) with improved resistance and quality traits [14]. Furthermore, it might be worth mentioning that grapevine breeding is being carried out in nearly every traditional winegrowing country in Europe, including Portugal, Hungary, and Austria. In the US, there are breeding programs in states other than California, most notably NY [15]. These international efforts highlight the growing importance of developing new cultivars capable of maintaining aromatic quality and freshness under warm climate conditions.

Taking everything into account, the aim of this article was to aromatically characterize these new Monastrell-derived white grapevine cultivars, with particular attention paid to their free and bound aromatic compound profiles. Notably, their aromatic composition, both in terms of free and bound compounds, has never been analyzed before in these new genotypes, making this a novel and valuable contribution to the field. This characterization sought to evaluate their enological potential and provide a foundation for their future use in the production of distinctive, high-quality white wines adapted to warm climates, aligned with evolving consumer preferences for freshness and aromatic complexity.

2. Materials and Methods

2.1. Experimental Conditions

The grapevines used for this study come from crosses between the Monastrell variety and others such as Cabernet Sauvignon, Verdejo and Tempranillo. The plant material under investigation comprises four new genotypes, named MC69 (Monastrell × Cabernet Sauvignon), MT103 (Monastrell × Tempranillo), MV67 (Monastrell × Verdejo) and MC180 (Monastrell × Cabernet Sauvignon). These new genotypes were compared to Verdejo, a Spanish white reference variety.

The experiment was carried out over four consecutive years (2020–2023). These grapevines were cultivated in a randomized and replicated fashion in vineyards of Vitis vinifera L. grafted onto R110 rootstocks. The vineyard is located within an experimental site in “El Chaparral,” in the municipality of Cehegín in Murcia, southeastern Spain. The geographical coordinates of this location are 38.11° latitude and −1.68° longitude.

In terms of vineyard management, each genotype was systematically arranged in a trellis system with a planting density of 3 × 1.25 m (2670 vines/ha). The cultivation regimen consisted of deficit drip irrigation, with a maximum allowance of 0.665 m³ per plant per year, with the actual amount administered being dependent on annual precipitation levels.

Agrometeorological data were obtained from a nearby station situated in the vineyard “SIAM” Murcia Agrarian Information System. This information is available in Supplementary Material (Tables S1 and S2).

2.2. Physicochemical Grape Parameters

The maturation process of the grapes was monitored weekly. Approximately 150 g of berries were collected at each sampling point using random sampling from different bunches and from different positions within each bunch (upper, middle, and lower parts) to ensure representative samples. Harvest date was determined based on technological and sensory criteria for white grapes, including soluble solids (20–23 °Brix), titratable acidity and pH to preserve freshness, probable alcohol estimated by refractometry, and organoleptic evaluation of berries (flavor, primary aromas, and seed maturity).

Each genotype consisted of 20 plants (e.g., 20 plants per genotype), and grapes were selectively harvested by hand from these plants. Grapes were harvested and taken to the winery situated in Jumilla, where grapes were analyzed according to °Brix (sugar content), pH levels, and total acidity. °Brix was carried out using a Refractometer Atago RX-5000X (Atago Co., Ltd., Tokyo, Japan) [16]. Furthermore, the total acidity of the grapes, expressed as tartaric acid (gL⁻¹), and their pH levels were determined [16]. These measurements were performed using a Metrohm (MetrohmAG, Herisau, Switzerland) with a glass electrode (Metrohm, Herisau, Switzerland). All physicochemical measurements were performed in triplicate (analytical replicates); grapes from these plants were pooled to obtain a representative composite sample for each genotype and season.

2.3. Grape Sample Preparation

In order to carry out the extraction of volatile compounds, the methodology described by Oliveira et al. [17] with some modifications of Vilanova et al. [18] was adopted.

Grape samples (600 g) for each new genotype and Verdejo were destemmed and crushed to obtain the must using Thermomix (Worwerk, Wuppertal, Germany) at speed 4 for 20 s to ensure even pressing on all samples. All samples were analyzed in triplicate (analytical replicates). Then, must samples were frozen and stored at −20 °C in order to determine the volatile composition. Before the analysis was carried out, samples were thawed the previous day. The must was centrifuged in an Eppendorf Centrifuge 5810 (Enfield, CT, USA) for 10 min (5 °C-10,000 rpm), and 75 mL of must was filtered with glass wool; then, 25 µL of 2 octanol (Sigma-Aldrich, Madrid, Spain) (100 ppb) as internal standard was added and passed through a LiChrolut EN cartridge (Merck, 500 mg, 40–120 µm). The cartridges were previously pre-conditioned with dichloromethane (Panreac, Barcelona, Spain) (10 mL), methanol (Panreac, Barcelona, Spain) (5 mL) and aqueous alcoholic solution 10% v/v (10 mL). Free and bound fractions were eluted successively with 5 mL of pentane–dichloromethane azeotrope (Panreac, Barcelona, Spain) and 7 mL of ethyl acetate (Panreac, Barcelona, Spain), respectively. The pentane–dichloromethane elute was concentrated to 200 µL by solvent evaporation with nitrogen prior to analysis. The ethyl acetate eluate was concentrated to dryness in a nitrogen concentrator, Techne DB3 (Madrid, España) (40 °C), and redissolved in 200 µL of 0.1 M citrate–phosphate buffer (pH = 5.0). A quantity of 70 mg/mL enzyme Rapidase Revel aroma (Oenobrands SAS, Montpellier, France) was added to the glycoside extract and the mixture was incubated at 40 °C for 17 h. Released aglycons were extracted with pentane–dichloromethane azeotrope, after the addition of 2 µg of octanol as an internal standard. The organic phase was then concentrated to 200 µL with nitrogen.

2.4. Gas Chromatographic Analysis

Gas chromatographic analysis of volatile compounds was performed using a Gerstel auto-sampling device (Gerstel GmbH&Co. KG, Mellinghofen, Germany) and an HP 7890B gas chromatograph (GC) system coupled to an HP 5977A quadrupole mass spectrometer (Agilent Technologies, Palo Alto, CA, USA). A 1 μL injection was made into a DB-WAXetr capillary column (30 m × 250 µm, 0.25 µm film thickness; Agilent Technologies). The temperature of the injector was programmed at 250 °C. The injection was in pulsed splitless mode. The oven temperature was held at 50 °C for 2 min, then programmed to rise from 50 °C to 170 °C, at 3 °C/min (ramp 1); it was then programmed to increase at 4.5 °C/min and held for 7 min at 260 °C (ramp 2). The carrier gas was helium 8.0 (Abelló Linde SA, Barcelona-Spain). The detector was set to electronic impact mode (70 eV), with an acquisition range from 20 to 400 m/z. Identification was performed using the GC/MSD ChemStation Software 2013 (Agilent), by comparing mass spectra (Wiley and Nist libraries). All of the compounds were analyzed semi-quantitatively as 2-octanol equivalents.

2.5. Statistical Analysis

Significant differences among grape and wine samples were evaluated by one-way analysis of variance (ANOVA) separately for each response variable (e.g., oenological and phenolic parameters), after verifying normality (Shapiro–Wilk test) and homogeneity of variances (Levene test). A two-way multivariate analysis of variance (MANOVA) was then applied to the set of response variables to assess the main effects of variety and vintage, as well as their interaction. When omnibus F-tests were significant (p < 0.05), mean separation was performed using Fisher’s least significant difference (LSD) test, acknowledging its greater sensitivity to type I error inflation compared with more conservative procedures. All ANOVA and MANOVA models were fitted in RStudio 3.6.2 (Boston, MA, USA). Linear discriminant analysis (LDA) was conducted with Statgraphics Centurion 18 (StatPoint Technologies, Warrenton, VA, USA) to classify samples according to variety and vintage; model performance was evaluated by leave-one-out cross-validation and reported as overall classification accuracy and confusion matrices.

3. Results and Discussion

3.1. Physicochemical Characteristics

Table 1. Physicochemical characteristics of Verdejo and four Monastrell-derived white grapevine genotypes (MC69, MT103, MV67, MC180) evaluated over four consecutive seasons (2020–2023) under warm climate conditions in southeastern Spain.

		Verdejo	MC69	MT103	MV67	MC180	p-Value
°Brix	2020	19.85 d ± 0.07	21.05 b ± 0.07	21.50 a ± 0.00	20.25 c ± 0.07	20.20 c ± 0.00	2 ***
Total Acidity (g/L) 1		5.30 c ± 0.01	5.83 a ± 0.01	5.61 b ± 0.02	5.16 d ± 0.03	4.92 e ± 0.03	***
pH		3.52 a ± 0.01	3.37 d ± 0.01	3.30 e ± 0.00	3.45 c ± 0.01	3.47 b ± 0.00	***
Tartaric acid (g/L)		5.65 c ± 0.04	4.11e ± 0.03	5.76 b ± 0.02	5.84 a ± 0.02	4.95 d ± 0.00	***
Malic acid (g/L)		2.59 b ± 0.02	3.40 a ± 0.00	2.17 c ± 0.02	2.09 d ± 0.03	2.56 b ± 0.04	***
°Brix	2021	20.95 a ± 0.07	19.05 c ± 0.07	19.15 c ± 0.07	19.15 c ± 0.08	19.85 b ± 0.07	***
Total Acidity (g/L)		4.78 b ± 0.29	5.54 a ± 0.13	5.26 a ± 0.03	4.46 b ± 0.08	4.74 b ± 0.00	**
pH		3.58 a ± 0.01	3.39 c ± 0.00	3.29 d ± 0.00	3.53 b ± 0.00	3.52 b ± 0.01	***
Tartaric acid (g/L)		5.10 c ± 0.09	4.69 d ± 0.20	6.37 a ± 0.00	5.78 b ± 0.04	5.10 c ± 0.05	***
Malic acid (g/L)		2.57 c ± 0.01	3.08 a ± 0.04	1.38 e ± 0.07	1.97 d ± 0.03	2.96 b ± 0.02	***
°Brix	2022	18.95 b ± 0.07	19.05 b ± 0.07	19.90 a ± 0.00	20.00 a ± 0.00	18.55 c ± 0.08	***
Total Acidity (g/L)		9.22 a ± 0.07	9.11 a ± 0.15	6.39 c ± 0.23	8.73 b ± 0.00	6.14 c ± 0.06	***
pH		3.26 b ± 0.00	3.15 c ± 0.00	3.16 c ± 0.00	3.24 b ± 0.00	3.36 a ± 0.03	***
Tartaric acid (g/L)		5.12 c ± 0.01	4.23 d ± 0.02	5.78 a ± 0.04	5.78 a ± 0.04	5.30 b ± 0.03	***
Malic acid (g/L)		5.40 ab ± 0.37	5.88 a ± 0.06	2.59 d ± 0.35	4.98 b ± 0.31	3.32 c ± 0.01	***
°Brix	2023	21.25 d ± 0.07	21.95 a ± 0.07	21.75 b ± 0.00	21.50 c ± 0.08	21.85 ab ± 0.07	***
Total Acidity (g/L)		4.41 c ± 0.03	5.15 a ± 0.01	4.28 d ± 0.01	5.02 b ± 0.00	4.42 c ± 0.01	***
pH		3.62 c ± 0.01	3.64 b ± 0.00	3.49 d ± 0.01	3.67 a ± 0.01	3.68 a ± 0.01	***
Tartaric acid (g/L)		5.27 b ± 0.18	3.66 d ± 0.01	4.45 c ± 0.04	5.66 a ± 0.22	4.23 c ± 0.05	***
Malic acid (g/L)		2.64 d ± 0.11	4.77 a ± 0.03	2.50 e ± 0.03	3.55 c ± 0.01	3.74 b ± 0.01	***

¹ Total acidity expressed in g/L of tartaric acid. Data represent the means ± standard deviation. Different letters in the same row indicate differences according to the LSD test (p < 0.05). ² Statistically significant at: ** p ≤ 0.01 and *** p ≤ 0.001, respectively.

shows the main physicochemical characteristics of Verdejo and the new white genotypes (°Brix, total acidity, pH, malic acid and tartaric acid) during four seasons of study. First of all, ºBrix indicates the degree of ripeness of the grape, which is an important factor in determining the composition of the grape and, consequently, the final quality of the wines; consequently, grape composition determines the sensory properties of wines, and hence wine quality and acceptability [19]. Regarding °Brix levels across the four seasons, values ranged between 18.00 and 21.50, showing different trends from year to year. Notably, in the last season studied (2023), grape maturation was significantly higher, with all genotypes reaching values above 21 °Brix. In contrast, the 2022 season recorded the lowest °Brix levels (18.55–20.00). These inter-annual differences can largely be attributed to climatic variability, particularly rainfall patterns (Table S1) and temperature (Table S2), which directly influence the ripening process.

However, it is also important to note that the same genotype did not always show the highest or lowest °Brix across seasons, indicating that the optimal harvest time varied depending on the year. This highlights the importance of accurately determining harvest dates, as the stage of ripeness at harvest can have a direct impact on the accumulation of volatile compounds, especially those in the bound fraction [20], ultimately affecting the aromatic potential of the resulting wines. This relationship will be explored in detail in the following sections.

Grape maturity also had a fundamental impact on the acidity of harvest grapes; in the 2022 season, the highest values were obtained. It is widely known that from fresh fruit to mature fruit, titratable acidity decreases [21]. Specifically, on the one hand, the most noticeable acidity was observed in the MC69 genotype across the four seasons of study, followed by MT103. However, MC180 obtained the lowest values across the four studied seasons. With respect to pH, as could be expected, the genotypes MC69 and MT103 showed the lowest values, with the exception of MC69 in the last season; however, no clear evidence trend was observed with the other studied genotypes.

Nevertheless, a clear trend in the presence of tartaric and malic acids in the new genotypes was observed. Tartaric acid was higher in two genotypes, namely MV67 and MT103. Yet the MC69 genotype obtained the lowest value for tartaric acid but the highest value for malic acid across the four seasons of study; this parameter is of greater importance for obtaining fresh wines. In a study carried out by Moreno-Olivares et al. [10], the authors also observed that MC69 was characterized by a high malic acid content, although it does not always have the lowest °Brix. MV67 obtained the lowest value for malic acid in the 2020 and 2021 seasons, while in the 2022 and 2023 seasons, MT103 achieved the lowest value.

Malic acid degrades during the ripening process; therefore, the more mature the grapes are, the lower the levels of malic acid [22]. Furthermore, in some cases, the lower concentrations of malic acid are also due to its lower concentrations in berries, especially in grapes grown in warmer regions, so this genotype (MC69) could be more adapted to climatic conditions from this area. Whatever the case, any factor that affects vine growth and/or physiology directly or indirectly impacts fruit composition, which results in wide quality variations from one year to another [23].

3.2. Free and Glycosylate Fractions

Figure 1 shows the aromatic trend over the four years of study with respect to the free and bound composition; furthermore, it shows the total sum between them. In addition, the absolute maximum temperatures are found during the month of August, which represents harvest time for white genotypes in this area.

In general, seasonal variation significantly influenced the accumulation of aroma compounds, both free and bound. The most pronounced effects were observed in 2023, where bound aroma concentrations were the lowest across all genotypes. This coincided with the highest °Brix values (up to 21.95 in MC69, Table 1), suggesting over-ripening. High temperatures during veraison, with 16 days reaching over 35 °C in August, and a sharp shift from wet to dry conditions may have led to heat stress (see Supplementary Table S1), which is known to suppress the biosynthesis of glycosidically bound volatiles, particularly norisoprenoids [24].

In contrast, 2022 showed the highest concentration of free aroma compounds and moderately high levels of bound volatiles. This season was marked by earlier harvest dates (5–10 days early), lower °Brix values, and moderate to severe water stress during veraison (June–July). Moderate water stress applied before veraison, especially during the dormant phase, can significantly increase the concentration of volatile compounds, both in their free and glycosylated forms, in grape berries [25]. Furthermore, other studies demonstrate that severe water stress can significantly alter the concentration of primary metabolites, polyphenols, and volatile compounds in grape leaves, supporting the need to consider climatic conditions when evaluating the aroma profile of grapes and the resulting wines [26]. As shown in Figure 1, the new genotypes outperformed Verdejo in this respect.

In 2021, both free and bound aroma levels were comparatively low. This season was characterized by late harvests and abundant rainfall during veraison and harvest moment, as can be seen in Supplementary Table S1 (171.5 mm). The dilution effect caused by high water availability could likely reduce volatile concentrations [27,28].

The 2020 season presented a more balanced profile. Bound volatiles were more abundant than in 2023, though below 2022 levels. However, free volatiles were similar to those obtained in 2021. This intermediate behavior could be attributed to steady, moderate water deficit and temperatures, with low rainfall from April to August (53 mm total), particularly from June onward (Table S1). Similar findings were reported by [20], which reported enhanced aroma expression under mild stress conditions, especially for genotypes adapted to warm climates.

3.3. Aromatic Compound Profiles in Grape Genotypes: Analysis of Free Volatile Families

The following section (Figure 2) examines the behavior of the studied grape genotypes with respect to each family of free volatile aromatic compounds, which are directly responsible for the expression of varietal aroma (mean of four years).

Firstly, the monoterpene family comprising two groups (monoterpene alcohol and monoterpene oxides) was studied. The concentrations of monoterpene alcohols were generally low across all genotypes. Regarding monoterpene oxides and diols, MV67 showed the highest relative abundance, accounting for 39.33 µg/L of the total, approximately twice the proportion observed in Verdejo (17.51 µg/L). Although free monoterpenes (alcohols + oxides and diols) were present at low concentrations, the differences among genotypes suggest that MC69 and MV67 may contribute more prominently to floral and fresh aromatic nuances [29]. Additionally, the concentration of monoterpenes can be affected by fermentation conditions, which in turn influence the retention and perception of these aromas [30]

In the case of C13-norisoprenoids, compounds which provide aromas (violet, ripe fruit and tobacco), no differences were observed.

Free alcohols were prevalent in all genotypes, particularly in MV67 (265.15 µg/L), where they are likely to enhance fruity, herbaceous, and alcoholic notes. Conversely, MC69 and MC180 exhibited markedly lower proportions (≈180 µg/L) although these differences were not significant, which could be associated with a cleaner or more refined aromatic expression [31]. Additionally, the interplay between higher alcohols and esters is essential in shaping the overall aromatic profile [32].

Volatile phenols, known to contribute complexity through spicy, smoky or clove-like notes when present at balanced levels [33], were notably higher in MV67 (18.30 µg/L) with high variance, potentially enriching its sensory profile. While they can add complexity at low concentrations, higher levels may lead to off-flavors. Recent research has explored the origins and sensory impacts of volatile phenols in wine, emphasizing the importance of controlling their levels during winemaking [34].

Volatile fatty acids, which may confer lactic, fruity, or rancid characteristics, were present at moderate levels in MV67 (92.66 µg/L) with high variance, a range considered desirable for white wines. Excessive concentrations, however, can negatively affect sensory quality [35]. Fermentation conditions and microbial activity significantly influence the concentration of volatile fatty acids in wine. Additionally, the balance between fatty acids and their corresponding esters is crucial in determining the overall aroma profile.

C6 compounds, responsible for fresh, green aromas (e.g., cut grass, green apple) [36], were detected at high levels in all genotypes (≈1000 µg/L). In this case, no differences were observed. These compounds are formed through the lipoxygenase pathway during grape crushing and are influenced by factors like grape maturity and processing techniques. Research indicates that the concentration of C6 compounds can be modulated through viticultural practices and winemaking decisions, impacting the freshness and herbaceousness of the wine. Furthermore, the perception of these compounds can be affected by their interaction with other aroma constituents [37].

Carbonyl compounds, which can arise from alcohol oxidation, Strecker degradation, or barrel aging [38], were found in similar ranges among the genotypes. However, MC69 exhibited the highest concentration (86.53 μg/L), followed by MV67 (80.81 μg/L), without differences. Their formation and sensory contribution are influenced by factors such as grape genotype, fermentation parameters, and oxygen exposure during aging [39].

Finally, among the miscellaneous compounds detected in the wines, MV67 (28.88 µg/L) displayed notably higher levels of compounds such as acetoin, butyrolactone, and benzophenone, in comparison to Verdejo (14.41 µg/L). These compounds are associated with complex sensory descriptors, including creamy, sweet-lactic, and mildly spicy notes [40]. MC180 presented the lowest value (10.51 µg/L), indicating a more restrained aromatic profile in this category. These findings suggest that MV67 may exhibit a distinctive aromatic expression potentially linked to its varietal metabolism and fermentative dynamics.

A multifactorial analysis was performed (

Table 2. Multifactor analysis of free volatile compound families indicating the percentage of variance explained by genotype, season, and genotype × season interaction in Verdejo and four Monastrell-derived white grapevine genotypes across four consecutive seasons (2020–2023).

	Multifactor Analysis
	Genotype %	Season %	G × S %
Monoterpene Alcohols	21.13 ***	45.81 ***	30.83 ***
Monoterpene Oxides and Diols	25.08 ***	46.65 ***	24.29 ***
C13-Norisoprenoids	11.56 ***	68.29 ***	16.17 ***
Alcohols	31.20 ***	30.14 ***	31.95 ***
Volatile Phenols	26.75 ***	23.03 ***	44.46 ***
Volatile Fatty Acids	27.97 ***	20.76 ***	47.37 ***
C6 Compounds	7.40 ***	73.39 ***	18.32 ***
Carbonyl Compounds	13.03 ***	46.82 ***	36.57 ***
Miscellaneous	39.92 ***	24.48 ***	31.84 ***

Separation by multiple range test at 99.9% *** (p < 0.001).

) to evaluate the contribution of grape genotype, growing season, and their interaction to the variability observed in key classes of aroma compounds in grape. The percentage of variance explained by each factor varied across compound classes, reflecting the complexity of aroma compound formation.

Seasonal effects were the predominant source of variation for several compound groups, particularly C6 compounds (73.39%), C13-norisoprenoids (68.29%), and carbonyl compounds (46.82%). This indicates that environmental conditions, such as temperature, sunlight exposure, and rainfall, have a substantial influence on the biosynthesis and accumulation of these compounds in grape berries. In contrast, the varietal component (genotype) had a greater influence on the variance in miscellaneous compounds (39.92%) and alcohols (31.20%), suggesting a genetic basis for the production of these volatiles.

The interaction between genotype and season also accounted for a considerable portion of the total variance, most notably in volatile fatty acids (47.37%), volatile phenols (44.46%), and carbonyl compounds (36.57%). These results emphasize the importance of both genetic and environmental factors and their interplay in determining the final aromatic profile of wines.

Overall, this study underscores the multifactorial nature of wine aroma development, highlighting the critical roles of grape genotype, climatic conditions, and their interaction. These findings reinforce the importance of season variation and cultivar selection in viticultural and winemaking practices aimed at optimizing wine aromatic quality [41].

3.4. Aromatic Compound Profiles in Grape Genotypes: Analysis of Bound Volatile Families

Figure 3 presents the average values of different families of bound volatile compounds in five grape genotypes: the parental variety Verdejo and four experimental crossings (MC180, MC69, MT103 and MV67). The analysis of these averages allows for the assessment of how genetic variability influences the concentration of glycosidically bound aroma precursors in grape berries.

Regarding monoterpene alcohols (Figure 3), MC69, MV67 and MC180 displayed the highest levels (31.39, 17.06 and 15.63 µg/L, respectively), significantly exceeding those observed in Verdejo (4.34 µg/L). Similarly, the concentrations of monoterpene oxides and diols were notably higher in MC69 (158.99 µg/L) and MC180 (111.35 µg/L) compared to Verdejo (50.79 µg/L) and MT103 (28.70 µg/L), which exhibited markedly lower levels. Monoterpenes are key contributors to floral and citrus aromas (e.g., linalool, geraniol), and their enhanced accumulation in the genotypes suggests a potential improvement in the floral aromatic profile. This observation aligns with findings by González-Barreiro et al. (2015) [42], who highlighted the role of monoterpenes in varietal aromatic differentiation in white grapes.

In relation to C13-norisoprenoids, all genotypes showed concentrations comparable to Verdejo (110.70 µg/L), except for MT103, which exhibited a notably higher level (235.59 µg/L). This suggests a greater biosynthetic capacity for these carotenoid-derived compounds, which are known to contribute mature fruit and balsamic notes. Their accumulation is likely influenced by both genetic factors and environmental conditions such as water stress, as reported by Fariña et al. [43].

With respect to alcohols, no differences were shown. As previously shown in Figure 2, this family of compounds is associated with herbaceous and fruity aromas, reinforcing the sensory impact of their differential accumulation.

On the one hand, for the group of volatile phenols and C6 compounds, no differences were shown. As previously discussed, fatty acids derived from lipid metabolism can yield both pleasant fruity notes and off-flavors, and their expression is modulated by grape maturity and lipoxygenase activity [44]; however, no differences were shown in this study.

On the other hand, differences were observed in the concentrations of carbonyl compounds. Verdejo exhibited a markedly higher level (83.84 µg/L), while the experimental genotypes showed significantly lower concentrations (3–4 µg/L). These differences may be attributed to genetic background or harvest and post-harvest conditions [45].

Finally, no meaningful differences were observed among the genotypes in the family of miscellaneous bound compounds, with all values remaining close to 1%.

As observed in the multivariate analysis (

Table 3. Multifactor analysis showing the percentage of variance explained by genotype, season, and their interaction (G × S) for the main families of glycosidically bound volatile compounds in Verdejo and four Monastrell-derived white grapevine genotypes evaluated over four consecutive seasons (2020–2023).

	Multifactor Analysis
	Genotype %	Season %	G × S %
Monoterpene Alcohols	70.92 ***	4.54 ***	20.30 ***
Monoterpene Oxides and Diols	61.74 ***	18.44 ***	15.86 ***
C13-Norisoprenoids	27.28 ***	49.80 ***	18.27 ***
Alcohols	9.26 ***	66.49 ***	19.32 ***
Volatile Phenols	6.23 ***	16.56 ***	69.30 ***
Volatile Fatty Acids	5.08 ***	67.61 ***	19.24 ***
C6 Compounds	7.62 ***	73.21 ***	11.55 ***
Carbonyl Compounds	73.75 ***	6.35 ***	18.41 ***
Miscellaneous	2.01 **	81.53 ***	10.94 ***

Separation by multiple range test at 99.9% *** (p < 0.001) and 99% ** (p < 0.01).

), the results demonstrate that both genotype and season factors, as well as their interaction, play critical roles in shaping the volatile composition of grapes. Overall, the season effect was more pronounced, particularly in compounds closely linked to climatic conditions, such as miscellaneous volatiles and C6 compounds. However, high season variability was also observed in other compound families, including fatty acids, alcohols and C13-norisoprenoids.

In contrast, the genotype factor exerted greater influence on compounds whose biosynthesis is primarily under genetic control, such as monoterpenes. Additionally, the genotype factor showed a high proportion of significant differences within the carbonyl compound family.

Notably, volatile phenols emerged as the most responsive family under the interaction between them, highlighting their sensitivity to both genetic and environmental modulation.

Furthermore, some authors such as Suter et al. [46] and Baltazar et al. [1] assert that genetic and environmental factors and the interaction between genotype and season indicate that the adaptability of specific grape genotypes to particular climatic scenarios is a critical determinant of final aromatic expression.

3.5. Discriminant Analysis of Grape Free Volatile Aromas

Linear discriminant analysis (LDA) (Figure 4) was applied to characterize varietal differences in free (non-glycosidically bound) volatile compounds in white grapes across five genotypes (Verdejo, MC180, MC69, MT103, MV67). The model was constructed using nine chemical classes: monoterpene alcohols, oxides and diols, C13-norisoprenoids, volatile phenols, volatile fatty acids, C6 compounds, carbonyl compounds, alcohols and miscellaneous volatiles.

Four discriminant functions were extracted, of which the first two were significant at p < 0.05. Function 1 accounted for 48.90% of the total variance, while Function 2 explained 32.66%, totaling 81.56% of the discriminatory power. Canonical correlations (0.76 for F1, 0.69 for F2) indicate moderate-to-strong separation among groups.

Statistical tests confirm the overall robustness of the model: Wilks’ λ was 0.1406 for the first function (χ² = 101.99, p < 0.0001), reflecting strong discrimination across genotypes. However, functions 3 and 4 were not statistically significant (p = 0.0526 and 0.2675, respectively), suggesting diminishing discriminatory value beyond the first two dimensions.

The discriminant plot (Figure 4) shows some overlap among genotypes, particularly between MT103 and MC69, reflecting more similar free volatile profiles. Verdejo appears moderately separated along Function 1. This may reflect the greater influence of seasonal and environmental variation on free volatiles, which are more susceptible to metabolic shifts post veraison and during harvest, as can be seen.

In addition, the first discriminant function (F1), which accounted for the greatest proportion of variance, was most strongly influenced by monoterpene oxides and diols (+1.232), C13-norisoprenoids (+1.001), and volatile fatty acids (+0.953), all of which loaded positively. In contrast, volatile phenols (–1.483), C6 compounds (–1.162), and monoterpene alcohols (–0.630) showed strong negative contributions. This suggests that F1 primarily differentiates samples with higher levels of terpenoids and lipid-derived volatiles.

3.6. Discriminant Analysis of Grape Bound Volatile Aromas

To assess the varietal differentiation based on glycosidically bound aroma compounds, linear discriminant analysis (LDA) was performed using five white genotypes (Verdejo, MC180, MC69, MT103, MV67). The analysis included nine quantitative variables corresponding to key aroma precursor families: monoterpene alcohols, monoterpene oxides and diols, C13-norisoprenoids, volatile phenols, volatile fatty acids, alcohols, C6-compounds, carbonyls, and miscellaneous compounds.

Four discriminant functions were obtained, all significant (p < 0.05) based on Wilks’ lambda and chi-squared tests. The first two functions accounted for 92.27% of the total variance (Function 1: 67.66%, Function 2: 24.61%) and were selected for interpretation and visualization. Canonical correlations were high (0.937 for F1, 0.858 for F2), indicating strong discriminating power. All four discriminant functions were statistically significant (Wilks’ λ < 0.05), with Function 1 achieving the lowest Wilks’ λ (0.012) and highest chi-squared value (χ² = 230.8, p < 0.0001), confirming it as the primary source of group separation.

The discriminant plot (Figure 5) showed distinct varietal clustering, with Verdejo forming a well-separated group along F1, associated with higher levels of carbonyls and norisoprenoids, reflecting its established aromatic profile. Breeding genotypes such as MT103 and MV67 were more dispersed, indicating variability in their bound volatile composition, possibly due to differences in genetic background or sensitivity to environmental variation across vintages.

The first discriminant function (F1), which explained the majority of the variance, was primarily influenced by monoterpene oxides and diols (+1.546) and miscellaneous compounds (+0.631), which loaded positively, while alcohols (–0.561), C13-norisoprenoids (–0.746), and carbonyl compounds (–0.719) contributed negatively. This suggests that F1 separates genotypes with higher terpene aromas.

These findings support the use of glycosidically bound volatiles as effective markers for varietal differentiation and suggest that this analysis can complement classical ampelographic and enological evaluations. The results also point to the potential of new genotypes such as MV67 and MC69 for producing white wines with differentiated and potentially marketable aromatic profiles, especially under warm climate viticulture.

4. Conclusions

This study provides a comprehensive aromatic characterization of four new white grapevine genotypes derived from Monastrell (MC180, MC69, MV67 and MT103) compared to Verdejo over four consecutive seasons. The analysis of both free and bound volatile fractions revealed that the varietal differences were not only genetically driven but also significantly modulated by climatic conditions and harvest timing. Multifactorial and discriminant analyses confirmed that seasonality played a major role in shaping the volatile profiles. These results underscore the importance of genotype × environment interactions when assessing the enological potential of emerging genotypes under warm climate viticulture.

Among the evaluated genotypes, MV67 and MC69 appeared particularly promising for white wine production, showing higher concentrations of key aromatic compounds and favorable compositional characteristics, suggesting strong potential for producing fresh and aromatic wines under warm climate conditions.

The characterization of these emerging white grape genotypes is of strategic importance for the wine sector. Their high-quality aromatic potential not only offers new tools to viticulturists and winemakers facing the challenges of climate change, but also supports the development of fresh, aromatic wines tailored to consumer preferences in increasingly warm growing regions. These genotypes represent a valuable asset for sustainable viticulture and innovation in wine production.