Grapevine has been clonally propagated for thousands of years. Though clonal propagation aims at maintaining varietal identity, somatic mutations and epigenetic modifications accumulated over hundreds to thousands of years lead to intra-varietal diversity. This intra-varietal variation is a very valuable resource in grapevine breeding, as it creates the opportunity to improve important traits related to yield, phenology, stress tolerance, and quality without altering the varietal identity which is extremely important for the industry. Recent advances in genomics, epigenetics, and phenotyping technologies are providing completely new opportunities to gain functional insights into the drivers underlying trait variation and to explore this for accelerated grapevine breeding. This review discusses the interaction between somatic mutations, epigenetic regulation, and emerging breeding technologies. We begin by exploring the phenotypic variation observed within clonal populations across various commercially important varieties, focusing on both agronomic and winemaking-related traits. Next, we examine the extent of genomic and epigenomic variation among clones, highlighting known mutations responsible for somatic variants. We also address how grapevine clonal populations serve as an advantageous model for understanding how genetic and epigenetic variants shape complex trait variation. Given recent advances, we discuss the potential of predictive breeding strategies to accelerate clonal evaluation and how genome editing technologies open new opportunities for targeted genetic improvements without passing through the tedium and unpredictability of clonal selection, driven by natural mutation. Ultimately, these new breeding technologies enable the integration of advanced methods into breeding programmes, optimizing grapevine performance while preserving the unique heritage of historic cultivars.

Row orientation, among others, is a crucial factor in determining grapevine performance and health status, thus affecting berry components that form the basis of the later wine profile. However, the literature about the impact of changes in row orientation at steep slope sites on grapevine fruit composition as well as the differentiation between canopy sides hardly exists. Thus, the aim of this work was to gain knowledge about the impact of row orientation in steep slope vineyards on selected primary and secondary metabolites in berries of Vitis vinifera L. cv. Riesling. Samples were taken from both canopy sides of different row orientations of terraced and downslope vineyards in steep slopes. Free amino acids in the juice and flavonols in the berry skin had a positive correlation to sunlight exposure. Furthermore, grapevines showed adaptations to constantly higher light conditions, e.g., physiologically in reduction in chlorophyll content or protective mechanisms resulting in a lower susceptibility to sunburn damage. Thus, grapevine fruit parameters are affected by row orientation change in steep slopes.

Societal Impact Statement: Grape production relies signifcantly on agrochemicals, such as fertilizers and pesticides, to sustain vine health and yield. However, excessive or improper use of these inputs leads to detrimental environmental effects, including soil degradation, water contamination, and biodiversity decline. To address this, research must explore sustainable alternatives. Enhancing the symbiotic interactions between grapevine rootstocks and beneficial soil microorganisms offers a viable pathway. By fostering these natural relationships, producers and scientists can develop environmentally sustainable viticulture practices that strengthen vine resilience without compromising productivity. This approach also supports the broader transition to regenerative, ecologically balanced agricultural systems.Summary: The productivity and resilience of vineyards are influenced by complex interactions between grapevine rootstocks and the surrounding soil microbiome. Emerging research has highlighted the pivotal role of these microbe‐rootstock alliances in modulating nutrient acquisition, water‐use efficiency, and pathogen resistance. By leveraging the symbiotic potential of beneficial soil microorganisms, viticulturists can optimize vineyard management practices to enhance overall productivity, stability, and sustainability. Through the strategic selection of rootstocks with enhanced mycorrhizal associations and the targeted introduction of plant growth‐promoting rhizobacteria, growers can support the grapevine in adapting to challenging soil conditions. Aditionally, manipulating the rhizosphere microbiome, through techniques such as biofertilization and reverse microdialysis, can foster the development of robust, disease‐suppressive communities that safeguard the vines against biotic and abiotic stressors. Integrating these microbiome‐centric approaches into comprehensive vineyard management strategies, and potentially in future rootstock genetic improvement programs, holds promise for improving grape yield, quality, and the long‐term resilience of viticultural systems.

Key message: Centuries of clonal propagation have shaped remarkable intra-varietal genetic diversity in grapevine, offering valuable opportunities to dissect complex traits and accelerate genetic improvement while safeguarding varietal integrity. Climate change poses significant challenges to global grapevine ( Vitis vinifera L.) production, highlighting the urgent need for adaptive breeding strategies to accelerate genetic improvement. While clonal propagation preserves varietal identity and heterozygosity, it also limits the rate of genetic gain due to prolonged breeding cycles. This study assessed phenotypic and genetic variation within eight clonal populations of key grapevine varieties (Pinot Blanc, Pinot Gris, Pinot Noir, Pinot Noir Précoce, Riesling, Müller-Thurgau, Auxerrois, and Savagnin Rose) using 14 years of data collected in Germany across six agronomic, quality, and disease-related traits. Estimates of broad-sense heritability, genetic correlations, and key variance components were derived using linear mixed models. Substantial intra-varietal phenotypic variation was observed across all traits, with moderate to high heritability estimates, confirming that a meaningful proportion of the phenotypic variation can be attributed to the genetic differences among clones. Substantial year and year-by-field variance and interaction components were found to contribute to the total phenotypic variance for most traits, aligning with previous reports of substantial genotype-by-environment interaction in clonal grapevine populations. Genetic correlations revealed both strong positive and strong negative trait relationships, emphasising the importance of informed multi-trait selection strategies. The results highlight considerable potential to enhance clonal selection by integrating predictive breeding tools such as genomic and phenomic selection. Optimisation-based multi-trait selection approaches also offer promising alternatives to traditional index methods, particularly in the context of negative trait correlations. Ultimately, the high intra-varietal genetic variation uncovered in this study represents a valuable resource for improving adaptation to future environments while maintaining varietal integrity in grapevine.

Grapevine cluster architecture is a key selection target in breeding programs because it influences disease susceptibility, yield stability and juice quality. High-throughput phenotyping offers a rapid and non-destructive approach to capture biochemical and structural variation in these traits, yet the influence of plant organ reflectance and data partitioning strategies on trait prediction remains poorly understood. In this study, we evaluated how hyperspectral reflectance from different grapevine organs contributes to the prediction of cluster architecture and juice quality traits in two clonal populations of Riesling and Pinot. Using partial least squares regression (PLSR), we assessed the prediction accuracy of eight cluster architecture and six juice quality traits under two data partitioning strategies. Models based on cluster reflectance outperformed those using dry leaf reflectance for most traits, except for pH. Partitioning the dataset by cluster type increased trait variance and improved predictions for number of berries (R² = 0.53), berry diameter (R² = 0.79), and total acidity (R² = 0.48). Visible, red-edge and NIR spectra were most informative regions to predict the traits studied. Together, our results highlight the importance of organ-specific data and appropriate calibration strategies to improve phenomic models for the development of scalable proxies for grapevine improvement. Highlight: Spectral phenomics reveals that prediction accuracy in grapevine depends on organ spectral signatures and traits, with cluster reflectance outperforming leaves, informing new phenotyping strategies for breeding improvement.