| Home > Online First > Rootstock genotype shapes whole-plant 3-D architecture and biomass allocation in field-grown grapevines |
| Journal Article | FZJ-2025-05250 |
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2025
Oxford University Press
Oxford
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Please use a persistent id in citations: doi:10.1093/aob/mcaf193
Abstract: • Background and Aims In perennial crops, efficient resource acquisition critically depends on whole-plantarchitecture, encompassing both canopy and root systems. In grafted grapevine, research has largely focused onscion canopy structure, whereas root system architecture – despite its key role in water and nutrient uptake –remains underexplored. This study comprehensively analysed whole-plant 3-D architecture during vineyardestablishment, investigating how different rootstock genotypes influence both root and shoot development.• Methods Riesling scions were grafted onto three rootstock genotypes (101-14, SO4 and 110R) and planted in avineyard following a randomized complete block design. Whole-plant excavations and high-resolution 3-Ddigitization were performed to capture spatial data of root and shoot systems from 96 vines at four time pointsover 2 years (3, 6, 15 and 18 months after planting). Key architectural parameters and biomass partitioningwere quantified.• Key Results Rootstock genotype strongly influenced whole-plant 3-D architecture and biomass allocation.110R developed significantly deeper, vertically oriented root systems (max depth 180 cm) and exhibited higherroot-to-shoot biomass ratios compared to SO4 and 101-14. Multivariate analysis identified deep root length andoverall spatial root system dimensions as primary discriminators among genotypes. Root growth across allgenotypes was spatially biased along the planting row, with limited extension into the inter-row soil.• Conclusions Rootstock genotype is a key determinant of whole-plant 3-D architecture and biomass partitioning.The integration of above- and below-ground structural data enables mechanistic interpretation of rootstockmediatedtraits relevant to resource acquisition and stress adaptation. Our comprehensive 3-D data set providesa valuable foundation for functional–structural plant modelling and offers practical insights for targetedbreeding and management strategies to enhance climate resilience in perennial crops.
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