Suitability of Spanish Local White Grape Cultivars for Warm Climates

Abstract

Plant genetic resources are increasingly viewed as a key tool to address the multiple challenges faced by modern viticulture. In this context, local grape cultivars are proposed as a strategy to enhance resilience to climate change and to diversify wine styles. However, while genetic identification has been widely reported, field-based phenotyping information for local cultivars under current climate conditions remains limited. In this context, phenotyping results are presented for six local Andalusian cultivars (Castellano, Beba, Cañocazo, Mantúo de Pilas, Perruno and Vigiriega). All cultivars were grown in a vineyard plot in the Marco de Jerez and evaluated over three consecutive seasons (2023–2025). Morphology was assessed using 46 descriptors, allowing cultivars to be grouped into two main clusters. Phenological monitoring showed a measurable year effect while preserving a consistent relative ranking among cultivars, most clearly during veraison and ripening, with Castellano reaching these stages earlier and Mantúo de Pilas later. Grape must composition highlighted contrasting ripening dynamics, with Palomino Fino and Castellano generally reaching higher sugar levels, whereas Vigiriega and Mantúo de Pilas showed the most acidic profiles. These results provide growers with performance-based comparative information to support cultivar selection for new plantings and to explore the potential of local cultivars for developing new wine styles under warm climate conditions.

1. Introduction

Interest in the conservation and enhancement of autochthonous or local grapevine cultivars (Vitis vinifera L.) has intensified in recent decades due to several factors affecting the wine industry [1,2]. First, the progressive concentration of commercial vineyards on a limited number of cultivars has reduced the varietal diversity currently represented in viticulture [3,4,5]. Second, the global warming scenario and increased climatic variability have renewed interest in recovering local cultivars [6] that may be better suited to thermal and water stress while also supporting the diversification of wine styles [7], particularly in warm climate regions [8].

In Europe, viticulture plays a major role both economically and socially [9] and is characterized by a wide diversity of grapevine cultivars adapted to different environments [10]. Nevertheless, the introduction of phylloxera (Daktulosphaira vitifoliae) from America at the end of the 19th century triggered extensive vineyard replanting and resulted in substantial loss of autochthonous plant material [5,11,12]. This situation prompted the exploration, collection, and conservation of varietal resources in grapevine germplasm collections, which were established to safeguard plant genetic resources and prevent the loss of local cultivars. In this context, each region has preserved cultivars adapted to its specific microclimatic conditions and viticulture traditions [4,6,13].

The management of these collections, together with practical needs such as plant material certification, traceability, and the control of cultivar identity, has consolidated the use of molecular characterization tools for cultivar identification and characterization [14]. Among these, microsatellite markers (SSRs, Simple Sequence Repeats) remain widely used in grapevine because they allow genotype discrimination and the detection of synonymies and homonymies [15,16,17]. Numerous studies have used SSR markers to identify grapevine cultivars in different European regions [1,2,6,14,18,19,20,21]. SSR markers have also been widely applied to authenticate local cultivars recovered after periods of abandonment or near disappearance from cultivation [2,18,22,23]. Accordingly, genotype matching is typically supported by international databases such as the Vitis International Variety Catalogue (VIVC), which hosts microsatellite profiles and synonymy information for grapevine cultivars [24].

Spain currently maintains 18 grapevine germplasm banks [25]. Among them, the IFAPA “Rancho de la Merced” collection in Jerez de la Frontera (Andalusia, Spain) is considered one of the oldest and most diverse grapevine collections in Europe [26]. Although the literature has addressed genetic identification and, to a lesser extent, morphological characterization of local cultivars, fewer studies have integrated these data with phenotypic performance under the same cultivation conditions in a climate change context. Therefore, it is essential to combine genotypic identity with phenotypic data under current growing conditions in order to provide an updated and more complete profile of cultivars.

This need is particularly relevant in historic regions such as the Marco de Jerez (Andalusia, Spain), one of the most significant wine-producing regions in southern Spain and among the southernmost viticultural areas in continental Europe [27]. Historical sources prior to the phylloxera outbreak describe the Marco de Jerez as a region with high varietal diversity, with numerous cultivars forming part of the traditional vineyard [28,29]. However, following vineyard replanting and the subsequent development of regulatory frameworks, varietal selection became progressively more restricted [30]. Traditionally, wine production under the Denominations of Origin (DOs) “Jerez-Xérès-Sherry” and “Manzanilla–Sanlúcar de Barrameda” has relied primarily on Palomino Fino, Pedro Ximénez and Muscat of Alexandria. More recently, a revision of the DO specification expanded the list of authorized cultivars for wine production to include Beba, Vigiriega, and Perruno [31].

In this context, the aim of this study is a characterization of six local cultivars from Andalusia: Castellano, Beba, Cañocazo, Mantúo de Pilas, Perruno, and Vigiriega. SSR-based genetic identification, ampelographic characterization, phenological monitoring, and ripening assessment were carried out over three consecutive seasons (2023–2025) to provide comparative information relevant to growers and to support the future assessment of local cultivars for warm climate viticulture.

2. Materials and Methods

2.1. Plant Material and Experimental Design

Six local grapevine cultivars were evaluated: Beba (BB), Castellano (CS), Vigiriega (VG), Mantúo de Pilas (MP), Cañocazo (CÑ), and Perruno (PR). Palomino Fino (PF) was used as the reference cultivar, as it currently accounts for approximately 95% of the cultivated area in the Marco de Jerez region [32,33].

All cultivars were grown in a commercial vineyard located in Trebujena (Cádiz, Spain) (36°53′12″ N, 6°10′14″ W) at 45 m above sea level. The vineyard was planted in 2016, and the vines were 7 years old at the beginning of the experiment. The experimental planting included 20 vines per cultivar in total. Vines were arranged in two randomized blocks, each containing 10 vines per cultivar. Vines were grafted onto 161-49 Couderc rootstock and planted on calcareous (limestone) soil. This rootstock is well suited to calcareous soils because of its tolerance to active lime and its adaptation to non-compacted soils, which are typical of the Marco de Jerez region [34,35]. The vineyard was vertically trellised with a planting density of 1.8 × 1.2 m (row × vine spacing) and trained according to the traditional “Vara y Pulgar” (stick and thumb) system. No irrigation or fertilization was applied during the studied period. The vineyard was managed under organic practices, and pest and disease control were restricted to products authorized under Regulation (EU) 2018/848 on organic production and labeling of organic products [36].

For each cultivar, five vines were selected from each of the two blocks, giving a total of ten representative vines for phenotyping and grape must physicochemical characterization, following the criteria proposed by Santesteban et al. [37] in order to minimize sampling-related intrinsic variability. Trunk cross-sectional area (TCSA) was determined at 30 cm above ground using a digital caliper (Vernier Caliper Maurer 93110, Padova, Italy).

2.2. Climatic Conditions

Climatic data were compiled for the study period each month, including average temperature (Tavg, °C), average relative humidity (RHavg, %), and precipitation (mm). Data were obtained from the Agroclimatic Information Network of Andalusia (RIA, https://www.juntadeandalucia.es/agriculturaypesca/ifapa/riaweb/web/, accessed on 8 March 2026), Lebrija I station (Seville, Spain), located approximately 5 km from the experimental vineyard.

2.3. Microsatellite Analysis

A total of 22 nuclear microsatellite loci were employed to perform the cultivar identification, consisting of the six recommended by the Organisation Internationale de la Vigne et du Vin (OIV) and agreed upon as a result of the GENRES 081 project (VVMD5, VVMD7, VVMD27, VVS2, VrZAG62, and VrZAG79). This has been extended to 22 with those proposed by the European GrapeGen06 project. SSR amplification and genotyping were performed following the protocol described by Jiménez-Cantizano et al. [38].

2.4. Morphological Characterization

Morphological characterization was performed following the criteria described by Benito et al. [39]. During the three growing seasons, a total of 10 organs per cultivar (young shoots, young and mature leaves, inflorescences/flowers, bunches and berries) were evaluated using 46 descriptors from the OIV Descriptor List for grapevine cultivars [40]. Fourteen priority descriptors, as indicated by the OIV “EU GENRES CT96 No81” project (OIV 001, OIV 004, OIV 016, OIV 051, OIV 067, OIV 068, OIV 070, OIV 076, OIV 079, OIV 081-2, OIV 084, OIV 087, OIV 223, OIV 225), were used for the primary description, together with 32 additional descriptors. Each cultivar was described by five different ampelographers. For each descriptor, the reported value corresponded to the modal value obtained from the observations recorded across the three growing seasons.

2.5. Phenological Stages

Phenological development was monitored weekly from April to August in both 2024 and 2025, as field observations in 2023 could not be initiated early enough to ensure reliable recording of the full phenological sequence. Phenological stages were visually assessed using the Baggiolini scale [41]. Assessments were conducted on the ten selected vines per cultivar, considering the fruiting cane (“vara”). The monitored stages ranged from F (inflorescences clearly visible) to N (ripening). For each vine, observations were made on the organs corresponding to each developmental stage, including buds during the early stages and later leaves, inflorescences, and clusters as development progressed. The phenological stage assigned to each vine corresponded to the stage observed in more than 50% of the evaluated organs. At the cultivar level, a given phenological stage was considered reached when at least 50% of the monitored vines had reached that stage.

2.6. Grape Must Physicochemical Characterization

For grape must characterization, 5 kg of berries per cultivar were collected manually and randomly from the 10 vines (500 g per vine) previously selected for field monitoring. The harvest date was determined following the grower’s criteria and in accordance with the specifications of the “Jerez-Xérès-Sherry” and “Manzanilla-Sanlúcar de Barrameda” DOs, which establish that grape musts intended for wines under these appellations must reach at least 10.5 °Be [31]. Since all cultivars were grown in the same vineyard, samples were harvested simultaneously, using the harvest date of Palomino Fino as the common reference point. The samples were preserved in plastic bags and transported for analysis. Subsequently, grape samples were destemmed and manually crushed to obtain the grape must. After crushing, samples were centrifuged for 5 min at 6000 rpm to remove suspended solids (Z 216 M, Hermle Labortechnik, Wehingen, Germany).

Grape must composition was determined using the following oenological parameters: total soluble solids content (°Be), total sugars (TS, g/L), total acidity (TA, g/L TH₂), pH, organic acids (L-tartaric, D-gluconic, L-citric, and L-malic) (g/L), total iron (TI, mg/L), total polyphenols (TP, mg/L) and Yeast Assimilable Nitrogen (YAN). °Be was determined using a calibrated Dujardin–Salleron hydrometer (Laboratories Dujardin–Salleron, Arcueil Cedex, France). TA was determined by titration with 0.1 M NaOH (NaOH; Merck, Darmstadt, Germany) using bromothymol blue (PanReac AppliChem, Barcelona, Spain) as an indicator. TS, TI, TP and organic acids were quantified using a Micro Miura™ chemical analyzer (TDI, Barcelona, Spain). pH was measured using a portable pH meter (pH7+DHS, XS instruments, Barcelona, Spain). YAN was calculated as the sum of ammonium nitrogen (NH₄⁺) and primary amino nitrogen (α-NH₂), determined by enzymatic and colorimetric analysis using the Micro Miura™ chemical analyzer (TDI, Barcelona, Spain). All analyses were performed according to the official OIV methods for grape must analysis [42]. All measurements were performed in triplicate (n = 3), and replicate values were used for statistical comparisons.

2.7. Statistical Analysis

Physicochemical results are presented as mean values ± standard deviation, and significant differences were evaluated by a one-way ANOVA. For each cultivar and season, the three replicate measurements corresponded to analytical replicates obtained from a single composite grape must sample and did not represent independent biological replicates. When the ANOVA was significant (p < 0.05), mean separation was performed using Tukey’s HSD test, and homogeneous groups were indicated using letter-based grouping (Sigma Plot statistical software version 14.0, Systat Software, Inc., San Jose, CA, USA).

A hierarchical cluster analysis was performed to assess morphological relationships among the analyzed grapevine cultivars based on ampelographic data. A total of 46 OIV descriptors were used for the analysis. Euclidean distance was calculated to generate the distance matrix, and hierarchical clustering was carried out using Ward’s minimum variance method (Ward.D2). Principal component analysis (PCA) was performed using the “prcomp” function (centered and scaled variables). The analysis was carried out on mean values for each cultivar × year combination. Hierarchical cluster analysis and PCA were performed using R software (version 2026.01.0+392).

3. Results

3.1. Climatic Conditions Across Seasons

Climatic conditions differed among seasons mainly in rainfall amount and distribution, whereas average temperature followed a broadly similar seasonal pattern across years. In all three seasons, average temperature decreased during winter and increased progressively towards summer, with average values ranging from 9–13 °C in winter to 24–27 °C in summer. The detailed climatic data for each season are presented in Supplementary Material Figure S1.

The main interannual differences were observed in rainfall. In 2022–2023, precipitation was concentrated mainly in late autumn and early winter, with a marked peak in December (118.40 mm), while spring and summer remained relatively dry. In 2023–2024, rainfall was distributed from autumn to early spring, with a noticeable maximum in March (150.20 mm), followed again by dry conditions during late spring and summer. In 2024–2025, rainfall variability was even more pronounced, with two intense rainfall events during the season, in October (224.80 mm) and March 2025 (236.60 mm).

3.2. SSR Genotyping Results

SSR genotyping based on 22 loci allowed the assignment of the six local cultivars and the reference control to known cultivar profiles (

Table 1. Genetic profiles of the locals and reference cultivars at 22 microsatellite loci. Allele sizes are given in base pairs.

Cultivar Code	BB		CS		VG		MP		CÑ		PR		PF
Microsatellite Locus
VVIB01	290	294	290	306	290	290	306	306	290	306	290	306	290	306
VMC1b11	185	188	185	185	173	188	185	188	188	188	188	188	185	188
VMC4F31	184	186	166	174	166	186	182	188	186	205	172	186	174	204
VVMD5	233	237	219	222	236	240	222	228	231	233	233	237	224	237
VVMD7	241	247	237	247	239	249	245	247	241	247	237	237	237	247
VVMD21	248	255	242	265	248	248	242	248	248	255	248	255	242	248
VVMD24	208	210	208	210	208	210	208	208	208	208	208	210	208	208
VVMD25	253	253	253	253	241	255	237	253	239	253	239	239	239	239
VVMD27	178	186	178	178	182	186	180	182	182	191	178	178	182	191
VVMD28	243	257	243	243	258	258	243	245	233	247	233	247	235	247
VVMD32	254	270	270	270	256	272	270	270	254	270	254	270	254	256
VVIH54	165	167	167	169	167	169	167	169	167	167	167	167	167	167
VVIN16	150	152	150	150	148	152	150	152	152	152	152	152	150	150
VVIN73	256	264	264	264	264	264	264	264	264	264	264	264	264	264
VVIP31	190	192	176	176	184	190	176	190	188	190	176	188	188	190
VVIP60	317	321	321	321	321	321	317	325	317	325	317	325	317	321
VVIQ52	82	84	84	88	84	88	84	88	84	84	84	84	84	84
VVS2	133	141	141	141	137	145	131	141	141	143	131	143	131	143
VVIV37	161	163	163	167	153	163	161	161	163	177	163	177	163	167
VVIV67	363	371	364	375	357	371	371	375	357	371	363	371	363	365
VrZAG62	187	203	187	193	188	204	188	196	187	203	187	196	187	193
VrZAG79	240	244	234	256	247	251	240	246	234	244	244	254	248	254

BB: Beba; CS: Castellano; VG: Vigiriega; MP: Mantúo de Pilas; CÑ: Cañocazo; PR: Perruno; PF: Palomino Fino.

). SSR profiles were first compared with those reported in the Vitis International Variety Catalogue (VIVC) [24] and the European Vitis Database [43], allowing the assignment of each profile to a corresponding known cultivar. In addition, the genotypes were compared with published profiles from the Rancho de la Merced Germplasm Bank [13,18,44], El Encín Germplasm Bank [45,46], and other published SSR studies [21] to confirm cultivar identity. Overall, the concordance with published references and database records was sufficient to confirm the identity of the cultivars analyzed in this work.

3.3. Ampelographic Characterization

Morphological characterization (

Table 2. Modal values of the OIV ampelographic descriptors for the seven analyzed grapevine cultivars, assessed across three consecutive years.

Code	Descriptor	BB	CS	VG	MP	CÑ	PR	PF
OIV 001	Young shoot: opening of the shoot tip; 1 closed, 3 half open, 5 fully open.	5	5	5	5	5	5	5
OIV 003	Young shoot: intensity of anthocyanin coloration on prostrate hairs of the shoot tip; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	5	5	1	1	1	5	5
OIV 004	Young shoot: density of prostrate hairs on the shoot tip; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	5	5	5	7	5	3	5
OIV 016	Shoot: number of consecutive tendrils; 1 two or less, 2 three or more.	1	1	1	1	1	1	1
OIV 051	Young leaf: color of upper side of blade (4th leaf); 1 green, 2 yellow, 3 bronze, 4 copper-reddish.	3	1	3	3	1	3	3
OIV 053	Young leaf: density of prostrate hairs between main veins on lower side of blade (4th leaf); 1 none or very low, 3 low, 5, medium, 7 high, 9 very high.	7	7	1	9	3	1	7
OIV 067	Mature leaf: shape of blade; 1 cordate, 2 wedge-shaped, 3 pentagonal, 4 circular, 5 kidney-shaped.	4	4	3	3	4	4	4
OIV 068	Mature leaf: number of lobes; 1 one, 2 three, 3 five, 4 seven, 5 more than seven.	4	3	3	3	3	3	3
OIV 070	Mature leaf: area of anthocyanin coloration of main veins on upper side of blade; 1 absent, 2 only at the petiolar point, 3 up to the 1st bifurcation, 4 up to the 2nd bifurcation, 5 beyond the 2nd bifurcation.	1	1	1	2	1	2	4
OIV 072	Mature leaf: goffering of blade. 1 absent or very weak, 3 weak, 5 medium, 7 strong, 9 very strong.	3	3	1	1	5	3	5
OIV 074	Mature leaf: profile of blade in cross section; 1 flat, 2 V-shaped, 3 involute, 4 revolute, 5 twisted.	5	5	5	5	5	5	5
OIV 075	Mature leaf: blistering of upper side of blade; 1 absent or very weak, 3 weak, 5 medium, 7 strong, 9 very strong.	9	3	1	7	5	5	9
OIV 076	Mature leaf: shape of teeth; 1 both sides concave, 2 both sides straight, 3 both sides convex, 4 one side concave on side convex, 5 mixture between both sides straight and both sides convex.	3	3	2	2	5	3	5
OIV 079	Mature leaf: degree of opening/overlapping of petiole sinus; 1 very wide open, 3 open, 5 closed, 7 overlapped, 9 strongly overlapped.	7	3	1	5	7	3	3
OIV 080	Mature leaf: shape of base petiole sinus; 1 U-shaped, 2 brace-shaped, 3 V-shaped.	3	3	3	3	3	3	3
OIV 081-1	Mature leaf: teeth in the petiole sinus; 1 none, 9 present.	9	9	1	1	1	9	1
OIV 081-2	Mature leaf: petiole sinus base limited by vein; 1 not limited, 3 on one side, 3 on both sides.	1	1	1	1	1	1	1
OIV 083-2	Mature leaf: teeth in the upper lateral sinuses; 1 none, 9 present.	9	1	1	1	1	1	1
OIV 084	Mature leaf: density of prostrate hairs between main veins on lower side of blade; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	3	5	1	5	5	1	7
OIV 085	Mature leaf: density of erect hairs between main veins on lower side of blade; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	3	3	1	3	5	5	3
OIV 087	Mature leaf: density of erect hairs on main veins on lower side of blade; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	1	3	1	3	5	7	1
OIV 202	Bunch: length (peduncle excluded); 1 very short, 3 short, 5 medium, 7 long, 9 very long.	9	5	3	7	5	7	9
OIV 203	Bunch: width; 1 very narrow, 3 narrow, 5 medium, 7 wide, 9 very wide.	7	5	3	5	5	7	7
OIV 204	Bunch: density; 1 very loose, 3 loose, 5 medium, 7 dense, 9 very dense.	5	5	3	5	3	7	5
OIV 207	Bunch: lignification of peduncle; 1 at the base only, 5 up to about the middle, 7 more than the middle.	5	1	1	1	1	5	7
OIV 208	Bunch: shape; 1 cylindrical, 2 conical, 3 funnel-shaped.	2	2	2	2	2	4	4
OIV 209	Bunch: number of wings of the primary bunch; 1 absent, 2 1–2 wings, 3 3–4 wings, 4 5–6 wings, 5 more than 6 wings.	2	2	2	3	2	2	2
OIV 220	Berry: length; 1 very short, 3 short, 5 medium, 7 long, 9 very long.	5	5	5	5	5	5	3
OIV 221	Berry: width; 1 very narrow, 3 narrow, 5 medium, 7 wide, 9 very wide.	5	5	3	5	5	5	3
OIV 222	Berry: uniformity of size; 1 not uniform, 2 uniform.	2	2	2	2	2	2	2
OIV 223	Berry: shape; 1 obloid, 2 globose, 3 broad ellipsoid, 4 narrow ellipsoid, 5 cylindric, 6 obtuse ovoid, 7 ovoid, 8 obovoid, 9 horn-shaped, 10 finger-shaped.	3	6	3	5	1	2	2
OIV 225	Berry: color of skin; 1 green yellow, 2 rose, 3 red, 4 gray, 5 dark red violet, 6 blue-black.	1	1	1	1	1	1	1
OIV 226	Berry: uniformity of skin color; 1 not uniform, 2 uniform.	2	1	2	2	2	2	1
OIV 227	Berry: bloom; 1 none or very low, 3 low, 5 medium, 7 high, 9 very high.	5	7	5	7	5	5	5
OIV 228	Berry: thickness of skin; 1 very thin, 3 thin, 5 medium, 7 thick, 9 very thick.	9	7	9	9	9	9	9
OIV 229	Berry: hilum; 1 little visible, 2 visible.	2	2	2	2	2	2	2
OIV 231	Berry: intensity of flesh anthocyanin coloration; 1 none or very weak, 2 weak, 5 medium, 7 strong, 9 very strong.	1	1	1	1	1	1	1
OIV 232	Berry: juiciness of flesh; 1 slightly juicy, 2 medium juicy, 3 very juicy.	2	1	2	1	2	2	2
OIV 233	Berry: must yield; 3 little (up to about 65%), 5 medium (about 65–75%), 7 high (about 75% and more).	3	3	3	3	3	3	3
OIV 235	Berry: firmness of flesh; 1 soft, 2 slightly firm, 3 very firm.	2	2	1	2	2	2	1
OIV 236	Berry: particular flavor; 1 none, 2 muscat, 3 foxy, 4 herbaceous, 5 other flavor than muscat, foxy or herbaceous.	1	1	1	1	1	1	1
OIV 238	Berry: length of pedicel; 1 very short (up to about 4 mm), 3 short (about 7 mm), 5 medium (about 10 mm), 7 long (about 13 mm), 9 very long (about 16 mm and more).	1	1	3	1	3	7	5
OIV 240	Berry: ease of detachment from pedicel; 1 very easy, 2 easy, 3 difficult.	3	3	3	3	3	3	3
OIV 241	Berry: formation of seeds, 1 none, 2 rudimentary, 3 complete.	3	3	3	3	3	3	3
OIV 242	Berry: length of seeds, 1 very short, 3 short, 5 medium, 7 long, 9 very long.	3	3	3	3	3	3	3
OIV 244	Berry: transversal ridges on dorsal side of seeds; 1 absent, 9 present.	1	1	1	1	1	1	1

BB: Beba; CS: Castellano; VG: Vigiriega; MP: Mantúo de Pilas; CÑ: Cañocazo; PR: Perruno; PF: Palomino Fino.

) showed that each cultivar exhibited a distinct phenotypic profile. Hierarchical clustering of the 46 OIV ampelographic descriptors further resolved consistent patterns of morphological similarity among cultivars (Figure 1).

The dendrogram revealed a major bifurcation separating two well-defined groups at high Euclidean distances, indicating pronounced morphological differentiation between both sets. The first group comprised Vigiriega, Castellano, Mantúo de Pilas, and Cañocazo. Within this group, Mantúo de Pilas and Cañocazo showed the closest association, evidencing a high degree of phenotypic affinity; Castellano subsequently joined this subgroup, whereas Vigiriega clustered at a higher distance level, representing the relatively most divergent member within the cluster. The second group included Perruno, Beba, and Palomino Fino. Beba and Palomino Fino clustered together at a low Euclidean distance, whereas Perruno joined this pair at a higher distance, indicating overall similarity with additional distinguishing traits.

The separation between both groups was supported by a subset of descriptors showing marked contrasts, particularly traits related to the young shoot (OIV 003 and 004), mature leaf (OIV 081-1, 083-2, and 075), bunch (OIV 202, 203, 204, 208, and 207), and berry (OIV 238 and 223), which contributed substantially to the observed morphological differentiation. Overall, comparison with the available literature showed a high level of agreement with previously reported descriptions, although minor discrepancies were detected for specific OIV descriptors.

3.4. Phenological Dynamics During Two Consecutive Growing Seasons

The seven cultivars followed the expected sequential progression of Baggiolini phenological stages (Figure 2) from F (inflorescences clearly visible) to N (ripening) across the two consecutive growing seasons (2024 and 2025), expressed as day of year (DOY). In both years, stage transitions followed the expected sequential pattern from early reproductive development (F/G-H-I1-I2) through berry growth (J-K-L) and ripening (M1-M2-N).

In 2024, differences among cultivars were modest at the earliest stages, with some overlap across cultivars, but became clearer from fruit set (J) onwards and were most evident during the late season progression (L-M1-M2-N). Castellano showed the earliest phenological development, reaching subsequent stages ahead of the other cultivars. It was followed by Perruno and Palomino Fino, which advanced earlier than the remaining cultivars but after Castellano. A second intermediate group, composed of Vigiriega, Beba, and Cañocazo, displayed similar timing across most of the cycle. Mantúo de Pilas was the latest cultivar, with the transition into ripening (M1-M2-N) occurring later in the year (higher DOY) than the other cultivars.

A comparable pattern was observed in 2025, with the relative ordering largely conserved. Castellano again showed the earliest phenological progression, followed by Perruno, and then Palomino Fino. Beba and Cañocazo exhibited a closely aligned trajectory throughout most stages, whereas Vigiriega tended to occur slightly later, especially approaching ripening. Mantúo de Pilas remained the most delayed cultivar in the late-season stages, reaching N at the latest DOY. In addition, the 2025 timelines show a general shift toward later dates (higher DOY) compared with 2024, indicating a slight phenological delay that is already apparent at early stages, including flowering (I1-I2), and becomes more pronounced during the transitions into and through ripening (L-M1-M2-N). The observed delay was approximately two weeks relative to the 2024 season.

Across both seasons, Castellano consistently reached ripening (N) approximately two weeks earlier than Mantúo de Pilas, with an even larger gap during veraison (M1-M2), where Castellano advanced roughly 2–3 weeks ahead of Mantúo de Pilas. In addition, Perruno was also slightly earlier than Palomino Fino in late-season stages (M1-N; ~3–7 days), while Vigiriega generally lagged behind Beba and Cañocazo by about one week. Beba and Cañocazo showed closely aligned timing throughout ripening.

3.5. Grape Must Physicochemical Composition

Across the three consecutive years evaluated (2023, 2024, and 2025), grape must physicochemical composition showed clear differences among cultivars, together with a measurable year effect for several parameters (

Table 3. Physicochemical profile of grape musts from the seven cultivars over three consecutive growing seasons.

Grape Must Physicochemical Characterization
Cultivars	°Be	Total Sugars	pH	Total Acidity	Tartaric Acid	Malic Acid	Gluconic Acid	Citric Acid	α-NH2	NH4	YAN	Total Iron	Total Polyphenols
2023
BB	10.00 ± 0.00 d	176.71 ± 3.84 c	3.89 ± 0.01 b	3.22 ± 0.04 b	6.14 ± 0.09 c	1.28 ± 0.00 b	0.05 ± 0.00 c	0.20 ± 0.02 a	144 ± 1 d	60 ± 3 b	205 ± 4 c	0.15 ± 0.02 b	442 ± 4 d
CS	10.90 ± 0.00 c	193.79 ± 0.56 b	4.06 ± 0.03 a	3.18 ± 0.00 b	6.40 ± 0.06 b	1.06 ± 0.00 c	0.67 ± 0.00 a	0.17 ± 0.01 a	189 ± 1 b	40 ± 1 c	230 ± 4 b	0.10 ± 0.02 b	557 ± 1 b
VG	11.10 ± 0.00 b	199.82 ± 3.89 b	3.83 ± 0.02 c	4.58 ± 0.10 a	7.11 ± 0.09 a	1.69 ± 0.02 a	0.06 ± 0.00 c	0.19 ± 0.00 a	210 ± 4 a	79 ± 4 a	288 ± 7 a	0.00 ± 0.00 c	514 ± 3 c
MP	7.60 ± 0.10 g	127.53 ± 3.38 e	3.81 ± 0.00 d	3.00 ± 0.05 c	5.52 ± 0.05 d	0.63 ± 0.00 e	0.05 ± 0.01 c	0.11 ± 0.01 b	117 ± 1 f	25 ± 0 d	142 ± 0 e	0.00 ± 0.00 c	374 ± 10 e
CÑ	8.60 ± 0.00 e	159.92 ± 5.5 d	4.05 ± 0.00 a	2.40 ± 0.00 d	5.40 ± 0.00 d	0.82 ± 0.10 d	0.18 ± 0.01 b	0.18 ± 0.01 a	123 ± 3 f	19 ± 1 d	142 ± 4 e	0.45 ± 0.00 a	331 ± 9 f
PR	8.40 ± 0.00 f	153.52 ± 4.38 d	4.05 ± 0.02 a	2.44 ± 0.05 d	3.71 ± 0.05 e	0.82 ± 0.04 d	0.16 ± 0.00 b	0.16 ± 0.01 a	132 ± 0 e	24 ± 1 d	156 ± 1 d	0.40 ± 0.00 a	319 ± 4 f
PF	11.90 ± 0.10 a	218.82 ± 2.08 a	3.92 ± 0.00 b	3.14 ± 0.06 b,c	6.96 ± 0.06 a	0.38 ± 0.00 f	0.05 ± 0.01 c	0.07 ± 0.00 b	175 ± 2 c	45 ± 1 c	219 ± 3 c	0.00 ± 0.00 c	573 ± 6 a
2024
BB	10.10 ± 0.00 b	183.17 ± 0.06 b	3.82 ± 0.02 d	3.07 ± 0.00 d	6.19 ± 0.04 d	1.15 ± 0.00 b	0.01 ± 0.00 a	0.16 ± 0.00 a	145 ± 5 c,d	77 ± 1 a	222 ± 4 b	0.10 ± 0.00 b	429 ± 8 b
CS	8.90 ± 0.00 d	161.83 ± 1.39 c	4.10 ± 0.00 a	2.16 ± 0.05 f	6.31 ± 0.01 c	0.82 ± 0.01 d	0.01 ± 0.00 a	0.08 ± 0.01 c	156 ± 3 b	34 ± 1 e	189 ± 11 d	0.20 ± 0.05 a	400 ± 1 a,b
VG	10.60 ± 0.10 a	192.13 ± 1.76 a	3.74 ± 0.01 f	3.67 ± 0.09 a,b	6.57 ± 0.06 b	1.68 ± 0.04 a	0.01 ± 0.00 a	0.15 ± 0.01 a	178 ± 6 a	67 ± 1 b	244 ± 6 a	0.10 ± 0.01 b	458 ± 6 a
MP	8.25 ± 0.00 e	152.08 ± 0.30 e	3.95 ± 0.00 b	3.47 ± 0.11 b	5.58 ± 0.04 f	0.89 ± 0.01 c,d	0.02 ± 0.01 a	0.13 ± 0.00 a,b	117 ± 1 f	32 ± 2 e	148 ± 3 f	0.00 ± 0.00 c	283 ± 4 a,b
CÑ	8.20 ± 0.00 e	152.98 ± 2.23 d,e	3.78 ± 0.01 e	3.07 ± 0.00 d	6.09 ± 0.00 e	0.93 ± 0.01 c	0.02 ± 0.01 a	0.13 ± 0.02 b	133 ± 10 c	47 ± 1 c	179 ± 9 e	0.25 ± 0.03 a	313 ± 2 a,b
PR	9.20 ± 0.00 c	157.88 ± 0.21 c,d	3.88 ± 0.00 c	2.49 ± 0.00 c	4.96 ± 0.02 g	1.08 ± 0.01 b	0.02 ± 0.00 a	0.08 ± 0.01 c	147 ± 0 d	44 ± 2 d	191 ± 1 d	0.10 ± 0.00 b	408 ± 1 a
PF	10.00 ± 0.07 b	183.14 ± 2.20 a,b	3.60 ± 0.00 g	3.88 ± 0.00 a	8.79 ± 0.18 a	0.34 ± 0.01 e	0.01 ± 0.00 a	0.08 ± 0.01 c	142 ± 1 b	69 ± 2 b	216 ± 8 c	0.00 ± 0.00 c	442 ± 1 a
2025
BB	10.90 ± 0.00 c	194.99 ± 1.11 c	3.99 ± 0.01 d	3.01 ± 0.04 d	5.08 ± 0.08 a,b	1.10 ± 0.02 b	0.01 ± 0.00 b	0.20 ± 0.01 a,b	142 ± 1 e	81 ± 1 a	223 ± 1 c	0.10 ± 0.04 b	471 ± 1 c
CS	11.50 ± 0.00 b	207.78 ± 0.51 b	4.06 ± 0.01 c	2.89 ± 0.04 d	5.33 ± 0.08 a,b	0.94 ± 0.03 c	0.01 ± 0.00 b	0.11 ± 0.01 c	216 ± 3 a	68 ± 1 b	284 ± 4 a	0.05 ± 0.00 c	548 ± 1 b
VG	10.25 ± 0.07 d	181.14 ± 1.15 d	3.71 ± 0.01 g	3.93 ± 0.04 b	5.99 ± 0.03 a	1.24 ± 0.05 a	0.02 ± 0.01 a,b	0.16 ± 0.00 b,c	157 ± 1 d	82 ± 3 a	239 ± 2 b	0.00 ± 0.00 c	442 ± 1 d
MP	8.80 ± 0.00 f	152.96 ± 1.05 e	3.89 ± 0.01 f	4.08 ± 0.10 a	6.37 ± 0.06 a,b	1.49 ± 0.02 a	0.01 ± 0.00 b	0.25 ± 0.01 a	151 ± 1 d,e	40 ± 1 d	191 ± 1 d	0.10 ± 0.05 b	369 ± 1 g
CÑ	10.45 ± 0.00 c,d	186.31 ± 0.40 c	3.95 ± 0.02 e	3.00 ± 0.02 d	4.61 ± 0.13 a,b	1.04 ± 0.03 b,c	0.01 ± 0.00 b	0.20 ± 0.02 a,b	184 ± 4 b	41 ± 0 d	225 ± 4 c	0.15 ± 0.03 a,b	424 ± 0 d
PR	10.05 ± 0.07 e	178.04 ± 0.72 d	4.10 ± 0.01 a	2.28 ± 0.05 e	3.89 ± 0.02 b	0.99 ± 0.02 b,c	0.07 ± 0.02 a	0.13 ± 0.01 c	170 ± 0 c	49 ± 1 c	219 ± 1 c	0.20 ± 0.05 a	389 ± 1 g
PF	12.50 ± 0.10 a	225.49 ± 1.96 a	4.09 ± 0.01 b	3.51 ± 0.04 c	5.84 ± 0.05 a	0.50 ± 0.07 d	0.01 ± 0.00 b	0.09 ± 0.02 c	189 ± 1 b	33 ± 1 e	222 ± 1 c	0.05 ± 0.00 c	569 ± 2 a

BB: Beba; CS: Castellano; VG: Vigiriega; MP: Mantúo de Pilas; CÑ: Cañocazo; PR: Perruno; PF: Palomino Fino. Different superscript letters mean a significant difference between the cultivars (ANOVA, p < 0.05) determined by a one-way ANOVA and applying Tukey’s HSD test.

). The largest compositional contrasts among cultivars were observed in technological ripeness indicators, particularly sugars (°Be and total sugars) and organic acid traits (total acidity, tartaric acid, and malic acid) (ANOVA, p < 0.05). The analytical comparison also indicated differences for variables related to nitrogen content (YAN) and total polyphenols (ANOVA, p < 0.05). In contrast, gluconic acid, citric acid, and total iron showed limited variation and no consistent cultivar pattern, indicating a lower discriminatory value under the conditions evaluated.

With respect to °Be, a stable pattern was observed across seasons: Palomino Fino exhibited the highest values, reaching the overall maximum in 2025 (12.50 °Be; Table 3), whereas Mantúo de Pilas consistently showed the lowest °Be (minimum in 2023: 7.60 °Be), in line with its lower sugar content. At the oenological level, these two cultivars also showed the clearest separation from the remaining samples (ANOVA, p < 0.05). Year on year, 2024 generally showed lower °Be values than 2023 and 2025 for several cultivars, whereas 2025 displayed a broadly increased °Be.

Clear differences among cultivars were also evident in acidity parameters. Grape must pH remained comparatively high overall, with Castellano repeatedly showing among the highest values (maximum in 2024: 4.10). In contrast, Vigiriega had lower pH values (3.83 in 2023 and 3.71 in 2025), and Palomino Fino reached a marked minimum in 2024 (3.60). Regarding total acidity, Vigiriega and Mantúo de Pilas showed the most acidic profiles (maximum of 4.58 g/L in 2023 and 4.08 g/L in 2025, respectively). By contrast, Perruno and Castellano had the lowest values (minimum of 2.28 g/L in 2025 and 2.16 g/L in 2024, respectively) with significant differences relative to the other cultivars (ANOVA, p < 0.05). Malic acid also showed pronounced variation among cultivars, with Palomino Fino consistently displaying the lowest concentrations in all three years (ANOVA, p < 0.05).

Among the additional parameters showing noticeable differences, YAN was high in Vigiriega in 2023 and 2024 and reached a maximum in Castellano in 2025, whereas total polyphenols were consistently high in Palomino Fino and Castellano, compared with lower values in Mantúo de Pilas, particularly in 2024. By contrast, gluconic acid and citric acid remained at very low levels across all cultivars and years. Finally, total iron concentrations were low for all cultivars, typically within the 0.00–0.20 mg/L range.

3.6. Principal Component Analysis of the Grape Must Composition

The principal component analysis (PCA) and the corresponding loadings are shown (Figure 3 and

Table 4. Principal component loadings.

Parameters	Components
	1	2
Be	−0.511	−0.283
Total acidity	−0.360	0.382
pH	0.094	−0.404
Malic acid	−0.220	0.499
Citric acid	−0.089	0.475
Gluconic acid	−0.031	−0.170
YAN	−0.544	−0.030
Total polyphenols	−0.497	−0.324

, respectively). The analysis was performed using the oenological parameters results obtained from the grape must characterization of the different cultivars across three seasons. The first two components accounted for 62.7% of the total variance.

The first principal component (PC1) explained 36.9% of the variance and was mainly defined by YAN (−0.54), °Be (−0.51) and total polyphenols (−0.50). Accordingly, samples with negative PC1 scores are associated with higher °Be, higher YAN and higher polyphenols, whereas samples with positive PC1 scores reflect the opposite pattern. The second component (PC2) explained 25.8% of the variance and was mainly associated with total acidity (+0.38) and the organic acids malic (+0.50) and citric (+0.48), while pH loaded negatively (−0.40).

The PC1-PC2 score plot enabled an effective discrimination of samples and revealed a structured separation driven by both cultivar and season. Across the three years, Vigiriega clustered at positive PC2 values, in agreement with its more acidic profile. In contrast, Palomino Fino and Castellano are grouped in the lower left quadrant, indicating association with higher sugar, YAN and polyphenol content. A clear year effect was observed for Castellano, with CS_24 shifting to the positive side of PC1 relative to its 2023 and 2025 positions. Perruno occupied the lower right quadrant, separating it from the high °Be, YAN, and polyphenol region and aligning it with higher pH and lower acid content. Mantúo de Pilas showed the largest dispersion, with MP_23 and MP_24 located at positive PC1 values and MP_25 shifting markedly toward positive PC2 in 2025. Beba and Cañocazo showed intermediate placements overall.

4. Discussion

Microsatellite (SSR) markers remain a standard tool for cultivar identification in grapevines [16,30]. In practical terms, SSR profiles provide a genetic fingerprint that is sufficiently discriminant for the detection of synonymies and the verification of plant material conserved in collections. In this study, SSR genotyping was used to confirm the cultivar identity of the studied accessions by comparison with published profiles and databases, as the plant material originated from a commercial vineyard and the cultivars had been grafted in the field rather than sourced as nursery stock.

The SSR profiles obtained in this study support the identity of the accessions and are consistent with previously reported synonymies [13,30,47]. The genotype identified for Castellano matched the profile reported for “Manteudo”, while Mantúo de Pilas showed the same genotype described for “De Rey” and “Uva Rey”. In both cases, the profiles were concordant with those reported by Sancho-Galán et al. [30]. Perruno matched the genotype associated with “Zalema” and “Mantúo Perruno”, whereas Vigiriega was consistent with published profiles for “Vijariego Blanco”. Among the cultivars analyzed, Beba is particularly notable, as it is associated with 198 registered synonymies in the VIVC and is conserved in multiple germplasm collections worldwide [24]. In Spain, these cultivars are currently conserved at Rancho de la Merced and Finca El Encín (Holding Institution Codes ESP074 and ESP080, respectively). Notably, the VIVC currently lists Castellano as held only at El Encín. However, our findings confirm that it is also conserved at IFAPA Rancho de la Merced [26,44], highlighting the need to update the corresponding database entry.

Ampelographic assessment of the seven cultivars revealed both shared and distinct phenotypic features. For Perruno, descriptions were largely consistent with Puertas-García [48] and later García de Luján et al. [49], with differences limited to OIV 051, 053, 070, 072, 079, 203, 208, 233 and 238. Likewise, Cañocazo, Castellano and Mantúo de Pilas broadly matched the descriptions reported by Sancho-Galán et al. [30,47], while differing in Cañocazo for OIV 053, 067, 076 and 202; in Castellano for OIV 003, 051, 067, 079, 084, 085 and 223; and in Mantúo de Pilas for OIV 070, 074, 075, 085 and 223. Vigiriega generally agreed with Rodríguez-Torres [50], except for OIV 004, 008, 202 and 203, whereas Beba showed a high overall concordance with González et al. [51], with discrepancies in OIV 003, 051, 067, 084, 087 and 203. Across cultivars, the most pronounced differences were observed primarily in mature leaf traits and, to a lesser extent, in cluster/berry characteristics. These descriptors are particularly sensitive to methodological factors (sampling and the developmental stage of the organ assessed) and the environmental conditions, which likely contributes to the differences observed among studies [30].

The trichomes’ density may be relevant under warm climate conditions because it can contribute to thermoregulation by modifying the leaf boundary layer and can reduce the leaf transpiration rate, saving water for the plant [52,53]. Palomino Fino was characterized by higher prostrate hair development, whereas Perruno showed more marked erect hair development; in contrast, Vigiriega displayed low vine hair. The observed differences could influence cultivar performance under high radiation and temperature [53]. In this context, the contrasting trichome patterns observed among cultivars may represent traits of interest for adaptation to climate change, particularly in viticultural areas increasingly exposed to high temperatures and water stress.

Grapevine phenology is influenced by the environmental conditions where it is cultivated, among other factors [54,55]. In this context, the phenological monitoring over two consecutive seasons highlighted a clear year effect. Although average temperatures were similar between years (Supplementary Material Figure S1), all cultivars in 2025 showed an overall shift in phenological stages toward later dates (higher DOY), which was particularly evident during flowering (I1 and I2, Figure 2). Periods of soil water saturation can temporarily reduce vine growth and physiological activity [56], which may slow phenological development even in the absence of marked differences in ambient temperature. In this sense, this shift may be partly related to the episode of intense and persistent rainfall recorded in March 2025 (≈236.6 mm; Figure S2B). In addition, these events also caused soil erosion and required soil restoration practices, which could have contributed to the observed delay. Despite this seasonal effect, the relative ranking among cultivars remained consistent across both years. This result may be relevant under the current agroclimatic conditions of warm viticultural regions because cultivars with later phenological progression may deserve further attention, as they could favor a better balance between sugar accumulation and acidity retention. By contrast, earlier cultivars may be more exposed to accelerated ripening under high summer temperatures [57].

Grape must physicochemical characterization (Table 3) showed differentiated ripening dynamics among cultivars. The harvest date was set using the reference cultivar Palomino Fino, following the grower’s criteria and in accordance with the specifications of the “Jerez-Xérès-Sherry” and “Manzanilla-Sanlúcar de Barrameda” DOs, which establish that grape musts intended for wines under the DO must reach at least 10.5 °Be [31]. Since all cultivars were harvested simultaneously, the differences observed in grape must composition should be interpreted in relation to a common harvest point rather than to the optimal ripening stage of each cultivar. Further studies would therefore be useful to evaluate grape must composition when each cultivar reaches its own optimal ripening stage. In this context, Palomino Fino consistently showed the highest °Be values across the three seasons (maximum in 2025), followed by Castellano, and both cultivars met the required threshold at harvest. These results are also consistent with their status as one of the earliest cultivars in their phenological cycle (Figure 2). In contrast, Mantúo de Pilas displayed the lowest °Be and total sugar values and, therefore, the greatest deviation relative to the reference cultivar. Beba exceeded the threshold only in 2025, whereas Cañocazo and Perruno did not reach it in any season, even though Perruno showed a relatively early phenology (Figure 2). This finding points to differences among cultivars in sugar accumulation capacity under the experimental conditions in this study. Vigiriega, despite exhibiting later phenological development, showed comparatively high sugar levels at harvest. The results suggest that cultivars that tend to remain below the established °Be threshold may be of interest for alternative technological approaches. First, over-ripening and postharvest sun dehydration (asoleo) could be considered to concentrate sugars through berry water loss [58]. Second, these cultivars could alternatively be used as blending components in non-monovarietal wines to modulate must composition and reduce the potential alcoholic strength of riper musts from other cultivars [59].

During 2024, a general decrease in sugars (°Be and total sugars) was observed compared with 2023 and 2025 in several cultivars, particularly Castellano and Palomino Fino. This pattern could have been influenced, at least in part, by biotic factors such as the green leafhopper (Jacobiasca lybica) outbreak recorded during ripening [60]. This pest causes foliar damage that reduces gas exchange and photosynthetic performance, and it has been reported to cause ripening delay, with a consequent reduction in berries’ sugar accumulation [61,62,63].

With regard to technological ripening, the results reflect the typical imbalance observed under warm climate conditions, whereby an increase in sugar content is generally accompanied by lower titratable acidity and higher pH [30,47]. In grape must, tartaric and malic acids together account for approximately 69% to more than 90% of total organic acids [64,65]. The relationship between these two acids is of considerable oenological interest, as it reflects the interaction between grapevine genotype and environmental conditions. In this context, the decay in total acidity may be closely linked to the evolution of malic acid concentration, which can be consumed during ripening through respiratory combustion in the grain cell and other metabolic processes. Its degradation accelerates at higher temperatures [66,67]. The later cultivars Vigiriega and Mantúo de Pilas exhibited relatively more acidic profiles, whereas Perruno and Castellano generally showed the lowest total acidity values, consistent with their shorter phenological cycle. Unlike malic acid, tartaric acid is more stable during ripening [66]. Consequently, although Palomino Fino, the predominant cultivar in the region, exhibited the lowest malic acid concentrations over three years, its higher tartaric acid levels helped maintain total acidity levels similar to those of the more acidic cultivars, partially counteracting the sugar-acid imbalance. This suggests that the relative contribution of malic and tartaric acid may be useful when comparing cultivar behavior under warm conditions. Since malic acid is more sensitive to temperature, tartaric acid is generally more stable and plays a different role in pH regulation, both of which may influence compositional balance during ripening.

Regarding total polyphenols, Palomino Fino and Castellano tended to show higher values, which could be associated with a higher potential for oxidative reactions and implications for sensory stability. However, as the present results only reflect compositional differences at the grape must level, they cannot be taken as direct evidence of sensory or oxidative behavior in the final wine. Finally, YAN showed both cultivars and seasonal variability. According to several authors, at least 140 mg N/L YAN is required for complete and successful alcoholic fermentation [68,69]. All cultivars were above this threshold across the three seasons, indicating an overall nitrogen status compatible with alcoholic fermentation under standard winemaking conditions.

The PCA is consistent with the cultivar patterns described in Table 3 and provides a coherent multivariate summary of grape must composition across seasons. The separation along the first two principal components (PC1 and PC2) discriminated cultivars mainly according to two different dimensions: a ripeness component (PC1), driven by °Be, YAN and total polyphenols, and an acidity component (PC2), driven by titratable acidity and organic acids in opposition to pH. Across seasons, samples formed coherent groupings that reflect their physicochemical composition. Cultivars associated with higher °Be and, in several cases, higher YAN and polyphenols tended to cluster toward the negative side of PC1, as observed for Palomino Fino, Castellano and Vigiriega. PC2 added an additional layer of separation by organizing cultivars according to their acidity status: cultivars characterized by higher malic acid and lower pH tended to group on the positive side of PC2, as seen for Mantúo de Pilas and Vigiriega and, to a lesser extent, Beba. Despite the year-to-year variability, most cultivars retained a recognizable multivariate tendency across seasons, indicating that cultivar differences in must composition were robust under the experimental conditions.

5. Conclusions

This study provides an integrated overview of cultivar identity, ampelography, phenology and grape must traits for six local white grape cultivars grown under warm climate conditions, using Palomino Fino as a regional reference. Based on the results obtained, the following conclusions can be stated: (1) SSR genotyping confirmed the identity of the studied accessions and supported previously reported synonymies, providing a solid basis for working with correctly identified plant material. (2) Ampelographic assessment revealed clear phenotypic differentiation among cultivars. Beba showed the closest morphological similarity to Palomino Fino, followed by Perruno. (3) Phenological monitoring showed a consistent ranking among cultivars across seasons, most clearly during veraison and ripening. Castellano reached these stages earlier, whereas Mantúo de Pilas showed the latest progression. Perruno and Palomino Fino followed early/intermediate trajectories, whereas Beba and Cañocazo showed closely aligned timing. Vigiriega generally progressed later, close to Mantúo de Pilas. (4) Grape must composition differed among cultivars, indicating distinct ripening dynamics. Palomino Fino and Castellano generally reached higher °Be, whereas Vigiriega and Mantúo de Pilas tended to show comparatively more acidic profiles. Palomino Fino combined higher sugar content with lower malic acid. Castellano and Perruno were characterized by comparatively low total acidity. (5) These compositional differences highlight contrasting ripening profiles under the studied conditions and may provide a useful basis for future winemaking research, depending on the desired balance between sugar accumulation and acidity retention.

Overall, these results provide updated, field-based phenotyping evidence for local grape cultivars grown in a warm climate region under current conditions influenced by climate change. This information supports cultivar selection for new plantings and helps explore the potential of local cultivars for developing new wine styles. However, the results should be interpreted taking into account that productivity-related traits were not evaluated in the present study and that grape must composition was assessed at a common harvest point based on the reference cultivar, rather than at the optimal ripening stage of each cultivar. These aspects limit a full agronomic and adaptive assessment of the cultivars under the studied conditions. Future research should integrate yield and other agronomic variables with phenology and grape composition, together with cultivar-specific ripening assessment and broader field evaluation, in order to better define the potential of these local cultivars under warm climate conditions.