Rootstock genotype shapes whole-plant 3-D architecture and biomass allocation in field-grown grapevines

砧木基因型影响田间种植葡萄植株的三维结构和生物量分配

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Abstract

BACKGROUND AND AIMS: In perennial crops, efficient resource acquisition critically depends on whole-plant architecture, encompassing both canopy and root systems. In grafted grapevine, research has largely focused on scion 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 vineyard establishment, 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 a vineyard following a randomized complete block design. Whole-plant excavations and high-resolution 3-D digitization were performed to capture spatial data of root and shoot systems from 96 vines at four time points over 2 years (3, 6, 15 and 18 months after planting). Key architectural parameters and biomass partitioning were 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 higher root-to-shoot biomass ratios compared to SO4 and 101-14. Multivariate analysis identified deep root length and overall spatial root system dimensions as primary discriminators among genotypes. Root growth across all genotypes 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 rootstock-mediated traits relevant to resource acquisition and stress adaptation. Our comprehensive 3-D data set provides a valuable foundation for functional-structural plant modelling and offers practical insights for targeted breeding and management strategies to enhance climate resilience in perennial crops.

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