Search Results (2,045)

Indigenous pig breeds in Vietnam represent an important genetic reservoir, offering traits adapted to local environments, cultural preferences, and disease resistance. However, rapid industrialization and the expansion of commercial breeds have endangered many indigenous populations. This review explores the trajectory of conservation efforts for Vietnamese local pig breeds, from the early use of microsatellites and mitochondrial DNA to recent advances in SNP genotyping. Firstly, we summarize the key characteristics and values of 26 local breeds. Secondly, we highlight key findings on genetic diversity, population structure, and inbreeding levels across major breeds. In addition, we discuss challenges in the development of conservation breeding programs and national strategies, as well as challenges in data generation, infrastructure, and policy implementation and provide potential solutions for these challenges. This review provides the first integrated synthesis linking breed-level genetic evidence to practical conservation recommendations for indigenous pigs in Vietnam. By identifying the key breeds for conservation priority, such as Huong, Van Pa, Soc, ChuProng, Co Aluoi, and Lung Pu, as well as highlighting the exotic introgression in H’mong pig populations, this review might provide a resource for sustainable conservation and use of Vietnam’s rich pig genetic resources. Full article

Indigenous sheep breeds represent valuable reservoirs of genetic diversity shaped by long-term adaptation to local environments and management systems. Greek autochthonous sheep breeds remain underrepresented in genomic and functional studies. The objective of this study was to characterize and compare coding sequence variation in three indigenous Greek sheep breeds—Lesvos (LES), Serres (SER), and Thrace (THR)—and to identify shared and breed-associated functional patterns. The study was designed using a two-stage approach, comprising a discovery (exploratory) phase and a validation phase. In the discovery phase, whole genome sequencing data (one animal per breed; total n = 3; mean sequencing depth ~36.9×) were analyzed to identify protein-altering exonic variants, focusing on missense single-nucleotide polymorphisms (SNPs) and exonic insertions/deletions (indels). Variants were examined at breed-specific and comparative levels, followed by functional enrichment analyses using Gene Ontology (GO) and KEGG pathways. Normalized variant density metrics identified genes with elevated polymorphism levels. In the validation phase, a subset of prioritized missense SNPs was genotyped in an independent cohort of 54 animals (18 per breed) using MassARRAY genotyping. Genes harboring prioritized missense SNPs showed a conserved enrichment profile across breeds, dominated by genome maintenance, DNA repair, cytoskeletal organization, and core regulatory functions. Distinct breed-associated patterns were also observed. LES showed enrichment in metabolic, biosynthetic, and sensory-related processes, SER in regulatory and signaling functions, and THR in cytoskeletal, extracellular matrix, and organelle-associated pathways. Polymorphism density analyses highlighted highly variable genes across breeds, including olfactory receptor (OR) gene families, keratin-associated protein genes (KRTAPs), and loci involved in immune and regulatory functions (e.g., PRKDC, CDH15). The validation phase confirmed the expected allele frequency patterns for most prioritized SNPs, supporting the robustness of the approach. This study identifies functionally relevant coding variation across Greek indigenous sheep breeds, revealing conserved genomic patterns and breed-associated signatures linked to metabolic, structural, and regulatory processes. Full article

The main approach for improving multiple traits simultaneously is the selection index. The most widely used selection indices are those based on factor analysis, which overcome statistical limitations such as multicollinearity and the reliance on arbitrary weights of the classical Smith–Hazel approach and support multi-environment trials. Nevertheless, the efficiency indices are affected by factors such as genotype number, environment and trait correlation, and heritability. In this study, we simulated different scenarios varying the mentioned factors to evaluate the performance of the Factor-Analysis and Ideotype-Design-Based Index (FAI-BLUP), Multi-trait Genotype–Ideotype Distance Index (MGIDI), and Multi-Trait Stability Index (MTSI). All correlations were positive and constant within each scenario, while the ideotype sought genetic gains for traits in opposite directions. Simulations were conducted using AlphaSimR and FieldSimR, and indices were implemented via the metan package. Results showed that index efficiency was higher in scenarios with larger numbers of genotypes, low-to-moderate trait correlations, and moderate-to-high inter-environment correlations. However, strong correlations among traits, particularly when combined with high heritability, compromise selection index efficiency in scenarios with antagonistic trait objectives. Despite that, the MGIDI consistently outperformed the other indices across most scenarios. Therefore, we emphasize accounting for trait genetic architectures, genotype–trait correlations, and target environment correlations. Full article

Objectives: Attention-deficit hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder diagnosed during childhood, primarily characterized by continuous symptoms of inattention, hyperactivity, and impulsivity. The present study aimed to investigate the genetic association between polymorphisms in the serotonergic system-related genes, HTR1B and HTR2A, and the susceptibility to ADHD in a Korean sample. Methods: The study cohort consisted of 234 children diagnosed with ADHD and 1686 healthy controls. Clinical diagnosis was established based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria. Genetic analysis focused on single nucleotide polymorphisms (SNPs) within the serotonergic pathway: rs6296 in HTR1B, and three SNPs (rs6311, rs6313, and rs9534495) in HTR2A. Genotype and allele frequencies were analyzed using Chi-square tests. Risk estimates were calculated as odds ratios (OR) with 95% confidence intervals (CI) across dominant, recessive, and additive inheritance models. Results: A statistically significant association was observed between the HTR2A rs9534495 polymorphism and ADHD. Specifically, significant associations were identified under the dominant (OR 0.67, 95% CI 0.48–0.93, p = 0.017), recessive (OR 0.67, 95% CI 0.48–0.93, p = 0.016), and additive (OR 0.80, 95% CI 0.65–1.00, p = 0.046) models. However, these significant findings did not persist after applying the Bonferroni correction for multiple comparisons. Conversely, no significant associations were detected for the HTR1B (rs6296) and the other HTR2A (rs6311, rs6313) polymorphisms. Conclusions: These findings suggest that genetic variations in the serotonergic system, particularly within the HTR2A gene, may contribute to the genetic susceptibility to ADHD. This study confirmed gene SNIPs associated with the serotonergic system in the pathophysiology of ADHD. Future research involving large-scale multi-ethnic cohorts, functional assays, and gene–environment interaction analyses is warranted to further elucidate the underlying mechanisms of serotonergic genes. Full article

Genomic selection (GS) may improve the adaptation of white lupin to drought or moderately calcareous soil, enabling to realize its potential as a high-protein crop. This study aimed to (a) verify breeders’ ability to identify the top-, mid-, and bottom-performing genotypes of published GS models of breeding lines and landrace genotypes for adaptation to drought and moderately calcareous soil; and (b) compare the top-performing materials produced by GS and phenotypic selection. Twelve selected genotypes were evaluated in four managed environments obtained through combining two soils (non-calcareous; moderately calcareous) with two water treatments (moderate terminal drought; moisture-favorable). GS based on the genotyping-by-sequencing of independent material was challenged by validation conditions that were partly different from the training ones and an imposed similarity of genomically predicted genotype phenology (to exploit drought resistance rather than drought escape). Grain yield reduction relative to favorable conditions averaged 19% for drought and 23% for calcareous soil. GS correctly identified the top-performing material for drought-prone or moderately calcareous soil, except for one model based on a small training set. The best GS lines performed comparably to the best phenotypically selected material. A higher harvest index was associated with better adaptation to drought and calcareous soil. Crossover genotype × water treatment interaction underpinned the selection for adaptation to drought. Full article

Soybean rust caused by the fungus Phakopsora pachyrhizi threatens global soybean production, causing yield losses of up to 80%. Race-specific Rpp genes provide short-term resistance due to pathogen variability, whereas partial resistance (PR) offers durable, broad-spectrum protection, though its genetic basis remains unclear. This study aimed to identify genomic regions and candidate genes underlying PR using the Fixed and Random Model Circulating Probability Unification (FarmCPU) genome-wide association study (GWAS) and machine learning (ML) methods, Random Forest (RF) and Support Vector Regression (SVR). A panel of 312 soybean accessions was evaluated under natural infection across six Ugandan environments. Rust index (RI), derived from rust severity and sporulation level, was used to estimate heritability (H²) and rank genotypes through Best Linear Unbiased Predictions (BLUPs), while Best Linear Unbiased Estimators (BLUEs) supported GWAS input. After quality control, 8272 SNPs were analyzed within a ±60 kb linkage disequilibrium (LD) window. Multi-environmental Analysis (MEA) of RI showed significant genetic effects (p < 0.01); H² = 0.57–0.68. Sixty-one loci were detected: six by FarmCPU, 15 by RF, and 41 by SVR. Key genes included Glyma.01G128100 (a WRKY transcription factor) and Glyma. 13G228000, receptor-like kinase) and Glyma.20G173100 (WD40-domain regulator). Integrating ML with GWAS improved locus detection, confirming the polygenic nature of PR and supporting the use of genomic selection and locus pyramiding for durable rust resistance. Full article

Bolting height is a key genetic trait that affects the stress tolerance, environmental adaptation, and winter survival of Brassica napus winter rapeseed. It is particularly important for enhancing winter survival in the arid–frigid regions. This study aimed to elucidate the genetic relationship between bolting height and cold stress tolerance, thereby supporting breeding for enhanced cold tolerance. Ninety-five winter rapeseed accessions were used in this study. Through both spring and autumn sowing trials, the dynamic changes in bolting height under different environments were systematically analyzed, and the genetic stability of bolting height as well as its correlation with cold tolerance were clarified. Bolting height showed consistent variation trends between spring and autumn sowing trials, exhibiting high genetic stability. It displayed an extremely significant negative correlation with cold tolerance: genotypes with lower bolting height possessed stronger cold tolerance. The regulatory mechanism underlying low bolting and cold tolerance was revealed at cellular and molecular levels. Low bolting accessions exhibited flat and broad shoot apical meristems, with small and compact cells, a high nucleoplasmic ratio, and indistinct vacuoles. The gibberellin synthesis gene BnaA06g24070D was downregulated, while the key cold-tolerant gene BnCBF5 was upregulated. Exogenous hormone treatment preliminarily verified the causal regulatory effect of bolting height on cold tolerance. In both spring and autumn sowing trials, bolting height at the initial flowering stage showed an extremely significant positive correlation with vernalization index, with correlation coefficients of 0.80 and 0.78, respectively. Lower bolting height corresponded to a smaller vernalization index and stronger temperature sensitivity. Moreover, bolting height at the initial flowering stage showed an extremely significant negative correlation with comprehensive cold tolerance scores, with correlation coefficients of −0.77 and −0.80, respectively. Low-bolt materials had significantly higher overwintering rates and comprehensive cold tolerance scores, as well as a markedly lower semi-lethal temperature (LT₅₀), compared with high-bolt accessions. Low-bolt accessions presented significantly prolonged bolting stage, bud stage, initial flowering stage, and whole growth durations, and their agronomic trait stability across years was significantly superior to that of high-bolt accessions. This study confirmed that low bolting height is a crucial breeding trait for the cold tolerance of winter rapeseed, and thus an important selection indicator for the cold tolerance improvement of winter rapeseed in arid–frigid regions in northern China. Full article

Background/Objectives: Fall armyworm (FAW) (Spodoptera frugiperda) is a major constraint to maize production in Sub-Saharan Africa, including Mozambique. This study aimed to evaluate maize genotypes for resistance to FAW under greenhouse and field conditions and to assess the association between phenotypic resistance and genomic variation based on single nucleotide polymorphisms (SNPs). Methods: A total of 20 maize genotypes from the Agricultural Research Institute of Mozambique (IIAM) and the International Maize and Wheat Improvement Center (CIMMYT) were evaluated. FAW damage was quantified using the area under the damage progress curve (AUDPC). Phenotypic data were analyzed using ANOVA and mixed models, while molecular analysis was conducted using 10,603 SNP markers located on chromosomes previously associated with FAW resistance. Results: Significant genotypic differences were observed under greenhouse conditions (F = 1.94, p = 0.012) and in the field (p = 0.021), although environmental factors reduced variation in the field. Genotypes such as CML67, CML338, and Kenya amarelo (Acc3550) exhibited consistently lower AUDPC values across environments, indicating stable resistance. However, SNP allele proportion was not significantly associated with phenotypic resistance (r = 0.34, p = 0.147), and regression and ANOVA analyses confirmed the absence of a significant relationship (p > 0.05). Conclusions: FAW resistance in maize is quantitatively inherited and not explained by general genomic variation across candidate regions. Phenotypic screening remains essential, and further studies are required to identify specific loci for effective marker-assisted selection. The identified stable genotypes represent valuable resources for breeding FAW-resistant maize adapted to Mozambique. Full article

This study was conducted in Northwest Ethiopia in 2025 to estimate genetic parameters for dairy cattle hybrids under a group-based mass selection scheme. The objective was to investigate lactation milk yield (MY), lactation length (LL), and key fitness traits across varying breed compositions, aligned with suitable agro-ecological zones and milkshed systems. The findings may then serve as a framework to develop economically efficient and sustainable dairy genotypes tailored to the region. Data were collected from 355 dairy households using semi-structured questionnaires and monthly monitoring of MY. A mass selection scheme was applied to evaluate the productive and reproductive performance of Holstein-Friesian (HF) and Jersey hybrids across varying levels of exotic breed compositions. To identify superior genotypes, a total merit index (TMI) was developed, utilizing economic weights of +0.20 for production traits and −0.12 for reproductive traits. General liner model (GLM) analyses were performed to evaluate the performance of different breeds and exotic breed composition. Realized genetic parameters including genetic correlations (rg) as an indicator of pleiotropy, genetic gain (GG) per trait, and aggregate genetic response (AGG) were estimated for each group using specialized procedures in R software. Breed type (stratified by exotic breed composition), agro-ecology zone, and milkshed system were defined as the main and sub-fixed effects. The genetic contribution to the performance of hybrids indicated that the Holstein-Friesian (HF) hybrid baseline scheme achieved significantly higher efficiency, with an aggregate genetic gain) (AGG) of 155.50, compared with 136.03 for the Jersey hybrid schemes. Specifically, the >75% HF hybrid group exhibited the highest predicted AGG (183.00), a result primarily underpinned by significant gains in MY (182.53 L) and extended LL (0.28 months). This indicated that higher exotic breed composition in HF crosses maximizes the genetic gain when selection is weighted toward productivity. Conversely, the 62.5% Jersey hybrid exhibited the lowest AGG (110.38) and GG for MY (109.86 L), indicating that intermediate Jersey breed compositions may be suboptimal under the studied conditions. Analysis of interaction effects revealed environment-specific superiorities: in the Bahir Dar midland milkshed, the >75% HF hybrids achieved the highest genetic gains in MY (182.53 L) and a superior AGG (181.34). In contrast, within the Gondar midland milkshed, >75% Jersey hybrids reached the highest overall AGG (177.11), with a corresponding GG for MY of 178.75 L per lactation. The observed variance in MY (δ² = 362.44) indicated significant potential for genetic improvement through group-based selection. Pleiotropy was identified between MY and LL (r_g = 0.14), whereas an antagonistic trade-off was observed between maturity and conception efficiency (r_g = −0.34). The consistent upward trend in the performance of hybrids as breed composition increased from 50% to >75% across both main and sub-effects suggests that these genotypes are suited to the environment. In conclusion, single- and multiple-trait predictions based solely on breed and breed comparisons were suboptimal; instead, selection strategies incorporating genotype-by-environment (G × E) interactions offered the most effective alternative for regional dairy selection alternatives. Full article

Cucurbit crops—including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), and melon (Cucumis melo)—are of major economic and nutritional importance worldwide. Yet their productivity and quality are severely compromised by foliar fungal diseases, particularly powdery mildew (PM), downy mildew (DM), and target leaf spot (TLS). While PM and DM have been extensively studied, TLS has emerged as an increasingly prevalent and damaging disease in key production regions, yet it remains comparatively understudied—especially with respect to its molecular basis and comparative pathobiology relative to PM and DM. Current reliance on chemical fungicides is hampered by escalating pathogen resistance and concerns over residual toxicity, whereas conventional breeding approaches face inherent limitations in pyramiding durable, broad-spectrum resistance against multiple pathogens. In this context, cucumber has emerged as a pivotal model species for dissecting foliar disease resistance mechanisms in cucurbits, supported by a high-quality reference genome, extensive resequencing datasets, diverse germplasm collections, and an efficient Agrobacterium-mediated transformation system. Despite these advantages, existing reviews predominantly address PM or DM resistance in isolation; comprehensive syntheses integrating TLS resistance advances—and critically, cross-disease comparisons of genetic architecture, transcriptional reprogramming, and defense signaling—are notably scarce. Furthermore, the translational pipeline—from gene discovery and functional validation to deployment in marker-assisted or genome-edited breeding—lacks systematic evaluation. Here, we provide a focused, cucumber-centered review that (i) synthesizes recent progress in mapping QTLs and GWAS loci, and characterizing key resistance-associated gene families (such as NLRs, RLKs, PR genes) conferring resistance to PM, DM, and TLS; (ii) integrates transcriptomic, epigenomic, and proteomic evidence to delineate conserved versus pathogen-specific host responses; (iii) highlights breakthroughs and unresolved questions in TLS resistance research, including the roles of novel susceptibility factors and non-canonical immune regulators; and (iv) critically assesses bottlenecks in translating resistance genes into practical breeding outcomes—such as linkage drag, functional redundancy, and genotype-by-environment interactions—and proposes empirically grounded strategies for accelerating molecular design of multi-disease-resistant cultivars. Collectively, this review aims to bridge fundamental insights with applied breeding goals, offering a conceptual and strategic framework for integrated management of foliar fungal diseases and the development of durable, broad-spectrum resistance in cucurbits. Full article

Wheat amylase trypsin inhibitors (ATIs) are prominent allergens in Baker’s asthma and contribute to innate inflammation in non-celiac wheat sensitivity (NCWS), linking them to metabolic and autoimmune diseases. Their tetra-, di-, and monomeric forms, stabilized by disulfide bonds, confer resistance to digestion, baking, and heating. Although proteomic studies reveal minor variation in ATI subtypes among cultivars and major variation among species, the influence of environment and wheat genotype on ATI levels and TLR4-stimulating activity remains unclear. We assessed the effect of the environment on the in vitro inflammatory bioactivity of ATIs extracted from 60 German wheat genotypes focusing on breeding over time between 1891 and 2010, and cultivation across three climatically distinct years. We found considerable genotype-dependent variation in ATI bioactivity that did not correlate with ATI subtype abundance, and observed no consistent difference between old and modern cultivars. ATIs from samples grown in 2019, a warm and dry year, showed reduced TLR4 activity, highlighting the significant impact of environmental conditions on inflammatory ATI bioactivity. Full article

Copper (Cu) contamination poses severe threats to agricultural productivity and food safety, particularly affecting economically important crops such as rapeseed (Brassica napus L.). This study investigated the protective effects of selenium nanoparticles (SeNPs) against Cu toxicity in four B. napus cultivars. Exposure to Cu (200 μM) caused severe reductions in growth and photosynthetic efficiency while significantly elevating oxidative stress markers across all cultivars. Application of SeNPs (25 μM) effectively mitigated these adverse effects, improving biomass, restoring chlorophyll content, and enhancing photosynthetic performance compared to Cu-stressed plants. SeNP treatment significantly enhanced antioxidant enzyme activities, with corresponding upregulation of antioxidant gene expression. Secondary metabolite profiling revealed cultivar-specific responses, with sensitive cultivar Zheda 622 exhibiting metabolic adaptation and higher volatile organic compound (VOC) accumulation, while tolerant cultivar Zheda 635 maintained metabolic stability. PCA analysis demonstrated distinct metabolic clustering patterns, reflecting differential stress-responsive strategies. The study demonstrates that SeNPs attenuate Cu-induced toxicity through integrated mechanisms encompassing diminished Cu acquisition, augmented antioxidant defense systems, and comprehensive metabolic reprogramming. Cultivar-specific responses highlighted substantial genetic variation in tolerance mechanisms across B. napus genotypes. These findings substantiate SeNPs as a viable and efficacious nanomaterial for sustainable agronomic management in Cu-contaminated edaphic environments. The approach offers dual benefits of improved crop productivity and reduced Cu accumulation, ensuring enhanced food safety. Full article

Light availability is a key environmental factor regulating nitrogen assimilation, carbon metabolism, and nutritional quality in leafy vegetables grown in controlled environments. However, how practical lighting regimes used in plant factories with artificial lighting (PFALs) influence the coordination between nitrogen assimilation and central carbon metabolism across different lettuce cultivar types remains insufficiently understood. This study investigated how moderate differences in photosynthetic photon flux density (PPFD) influence nitrogen metabolism and metabolic coordination in hydroponically cultivated lettuce. Two cultivars representing contrasting morphological types, iceberg lettuce (‘Celebration’) and leaf lettuce (‘Sunny’), were grown under LED light intensities of 150 and 200 µmol·m⁻²·s⁻¹. Nitrate, nitrite, and ammonium concentrations were measured together with the activities of nitrate reductase (NRA) and nitrite reductase (NiRA), as well as ascorbic acid content. Metabolomic profiling was additionally performed to characterize broader metabolic responses. Higher light intensity enhanced nitrate reduction capacity in both cultivars, but the resulting patterns of nitrogen accumulation were strongly genotype-dependent. The leaf lettuce cultivar ‘Sunny’ exhibited increased NRA and reduced nitrate accumulation under higher light intensity, whereas the iceberg lettuce cultivar ‘Celebration’ accumulated more nitrate under the same conditions. Ammonium responses further suggested differences in downstream nitrogen assimilation processes. Elevated light intensity also increased ascorbic acid levels in both cultivars. Metabolomic analysis revealed contrasting cultivar-specific shifts in central carbon metabolism, particularly involving soluble sugars and tricarboxylic acid cycle intermediates, indicating differential coordination between carbon metabolism and nitrogen utilization. Overall, these findings demonstrate that moderate changes in light intensity within the practical PFAL cultivation range can significantly influence the integration of carbon and nitrogen metabolism in lettuce. Importantly, cultivar-specific physiological traits determine how these metabolic responses translate into nitrate accumulation and nutritional quality in controlled-environment production systems. Full article

White clover (Trifolium repens L.) is a major legume in Mediterranean agroecosystems. This study systematically evaluates 15 autochthonous white clover populations from the Trikala region of Greece, focusing on chemical composition and derived nutritional indices relevant for germplasm characterization and breeding. Fifteen local populations were evaluated under controlled pot cultivation over two consecutive years. Clonal plants were harvested at the early flowering stage. Key traits—crude protein (CP), Ash, Fat, crude fibre (FIBRE), acid detergent fibre (ADF), neutral detergent fibre (NDF), digestible dry matter (DDM), dry matter intake (DMI), and relative feed value (RFV)—were measured. Combined ANOVA revealed significant differences among populations for all traits (p ≤ 0.001), while genotype × year interactions were present but generally minor compared to genotypic effects. Broad-sense heritability was high across most traits (H² = 90.8–99.4%), demonstrating strong genetic control. CP showed positive correlations with DDM, DMI, and RFV, whereas ADF and NDF were negatively correlated with intake and digestibility. Canonical and discriminant analyses showed that a reduced set of traits (CP, Ash, FIBRE, RFV) contributed strongly to differentiation among populations. Hierarchical clustering (heatmap) confirmed these groupings based on fibre and digestibility-related traits. Populations such as Dendrochori and Gorgogyri consistently showed favorable chemical and nutritional profiles, while Fiki and Dendrochori showed the highest stability across years. The present study highlights substantial genetic variability among local white clover populations and identifies trait structures of relevance for germplasm characterization. These findings enhance the characterization of genetic diversity in Trifolium repens and support its potential use in future breeding research under Mediterranean environments. Full article

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. Full article