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Societal Impact StatementGrapevine leaves are emblematic of the strong visual associations people make with plants. Leaf shape is immediately recognizable at a glance, and therefore, this is used to distinguish grape varieties. In an era of computationally enabled machine learning‐derived representations of reality, we can revisit how we view and use the shapes and forms that plants display to understand our relationship with them. Using computational approaches combined with time‐honored methods, we can predict theoretical leaves that are possible, enabling us to understand the genetics, development, and environmental responses of plants in new ways. SummaryGrapevine leaves are a model morphometric system. Sampling over 10,000 leaves using dozens of landmarks, the genetic, developmental, and environmental basis of leaf shape has been studied and a morphospace for the genusVitispredicted. Yet, these representations of leaf shape fail to capture the exquisite features of leaves at high resolution.We measure the shapes of 139 grapevine leaves using 1672 pseudo‐landmarks derived from 90 homologous landmarks with Procrustean approaches. From hand traces of the vasculature and blade, we have derived a method to automatically detect landmarks and place pseudo‐landmarks that results in a high‐resolution representation of grapevine leaf shape. Using polynomial models, we create continuous representations of leaf development in 10Vitisspp.We visualize a high‐resolution morphospace in which genetic and developmental sources of leaf shape variance are orthogonal to each other. Using classifiers,Vitis vinifera,Vitisspp., rootstock and dissected leaf varieties as well as developmental stages are accurately predicted. Theoretical eigenleaf representations sampled from across the morphospace that we call synthetic leaves can be classified using models.By predicting a high‐resolution morphospace and delimiting the boundaries of leaf shapes that can plausibly be produced within the genusVitis, we can sample synthetic leaves with realistic qualities. From an ampelographic perspective, larger numbers of leaves sampled at lower resolution can be projected onto this high‐resolution space, or, synthetic leaves can be used to increase the robustness and accuracy of machine learning classifiers.
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Terroir and rootstock effects on leaf shape in California Central Valley vineyards
Societal Impact StatementThe innumerable effects of terroir—including climate, soil, microbial environment, biotic interactions, and cultivation practice—collectively alter plant performance and production. A more direct agricultural intervention is grafting, in which genetically distinct shoot and root genotypes are surgically combined to create a chimera that alters shoot performance at a distance. Selection of location and rootstock are intentional decisions in viticulture to positively alter production outcomes. Here, we show that terroir and rootstock alter the shapes of grapevine leaves in commercial vineyards throughout the California Central Valley, documenting the profound effects of these agricultural interventions that alter plant morphology. SummaryEmbedded in a single leaf shape are the latent signatures of genetic, developmental, and environmental effects. In viticulture, choice of location and rootstock are important decisions that affect the performance and production of the shoot. We hypothesize that these effects influence plant morphology, as reflected in leaf shape.We sample 1879 leaves arising from scion and rootstock combinations from commercial vineyards in the Central Valley of California. Our design tests 20 pairwise contrasts between Cabernet Sauvignon and Chardonnay scions from San Joaquin, Merced, and Madera counties from vines grafted to Teleki 5C, 1103 Paulsen, and Freedom rootstocks.We quantify clear differences between Cabernet Sauvignon and Chardonnay leaves. However, we also detect a separate, statistically independent source of shape variance that affects both Cabernet Sauvignon and Chardonnay leaves similarly. We find that this other shape difference is associated with differences in rootstock and location.The shape difference that arises from rootstock and location affects the basal part of the leaf near the petiole, known as the petiolar sinus, and affects its closure. This shape effect is independent from previously described shape differences that arise from genetic, developmental, or size effects.
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- Award ID(s):
- 2310355
- PAR ID:
- 10595890
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- PLANTS, PEOPLE, PLANET
- ISSN:
- 2572-2611
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/ppp3.10620
