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The recent trend in sedentary lifestyles and nutritionally‐imbalanced diets has elevated the prevalence of Type 2 diabetes in many parts of the world. Some pharmacological glycemic management can cause undesirable gastrointestinal side effects or hypoglycemia. Thus, there is a growing interest in safe glycemic management using dietary (poly)phenols.

As a leaf expands, its shape dynamically changes. Previously, we documented an allometric relationship between vein and blade area in grapevine leaves. Larger leaves have a smaller ratio of primary and secondary vein area relative to blade area compared to smaller leaves. We sought to use allometry as an indicator of leaf size and plasticity.

We measured the ratio of vein‐to‐blade area from the same 208 vines across four growing seasons (2013, 2015, 2016, and 2017). Matching leaves by vine and node, we analyzed the correlation between the size and shape of grapevine leaves as repeated measures with climate variables across years.

The proportion of leaf area occupied by vein and blade exponentially decreased and increased, respectively, during leaf expansion making their ratio a stronger indicator of leaf size than area itself. Total precipitation and leaf wetness hours of the previous year but not the current showed strong negative correlations with vein‐to‐blade ratio, whereas maximum air temperature from the previous year was positively correlated.

Our results demonstrate that vein‐to‐blade ratio is a strong allometric indicator of leaf size and plasticity in grapevines measured across years. Grapevine leaf primordia are initiated in buds the year before they emerge, and we found that total precipitation and maximum air temperature of the previous growing season exerted the largest statistically significant effects on leaf morphology. Vein‐to‐blade ratio is a promising allometric indicator of relationships between leaf morphology and climate, the robustness of which should be explored further.

Modern biological approaches generate volumes of multi-dimensional data, offering unprecedented opportunities to address biological questions previously beyond reach owing to small or subtle effects. A fundamental question in plant biology is the extent to which below-ground activity in the root system influences above-ground phenotypes expressed in the shoot system. Grafting, an ancient horticultural practice that fuses the root system of one individual (the rootstock) with the shoot system of a second, genetically distinct individual (the scion), is a powerful experimental system to understand below-ground effects on above-ground phenotypes. Previous studies on grafted grapevines have detected rootstock influence on scion phenotypes including physiology and berry chemistry. However, the extent of the rootstock's influence on leaves, the photosynthetic engines of the vine, and how those effects change over the course of a growing season, are still largely unknown.

Here, we investigate associations between rootstock genotype and shoot system phenotypes using 5 multi-dimensional leaf phenotyping modalities measured in a common grafted scion: ionomics, metabolomics, transcriptomics, morphometrics, and physiology. Rootstock influence is ubiquitous but subtle across modalities, with the strongest signature of rootstock observed in the leaf ionome. Moreover, we find that the extent of rootstock influence on scion phenotypes and patterns of phenomic covariation are highly dynamic across the season.

These findings substantially expand previously identified patterns to demonstrate that rootstock influence on scion phenotypes is complex and dynamic and underscore that broad understanding necessitates volumes of multi-dimensional data previously unmet.

Leaf morphology is dynamic, continuously deforming during leaf expansion and among leaves within a shoot. Here, we measured the leaf morphology of more than 200 grapevines (Vitisspp.) over four years and modeled changes in leaf shape along the shoot to determine whether a composite leaf shape comprising all the leaves from a single shoot can better capture the variation and predict species identity compared with individual leaves.

Using homologous universal landmarks found in grapevine leaves, we modeled various morphological features as polynomial functions of leaf nodes. The resulting functions were used to reconstruct modeled leaf shapes across the shoots, generating composite leaves that comprehensively capture the spectrum of leaf morphologies present.

We found that composite leaves are better predictors of species identity than individual leaves from the same plant. We were able to use composite leaves to predict the species identity of previously unassigned grapevines, which were verified with genotyping.

Observations of individual leaf shape fail to capture the true diversity between species. Composite leaf shape—an assemblage of modeled leaf snapshots across the shoot—is a better representation of the dynamic and essential shapes of leaves, in addition to serving as a better predictor of species identity than individual leaves.