A high‐resolution model of the grapevine leaf morphospace predicts synthetic leaves

A high‐resolution model of the grapevine leaf morphospace predicts synthetic leaves

Societal Impact Statement Grapevine 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 represent...

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Bibliographic Details
Main Authors: Daniel H. Chitwood, Efrain Torres‐Lomas, Ebi S. Hadi, Wolfgang L. G. Peterson, Mirjam F. Fischer, Sydney E. Rogers, Chuan He, Michael G. F. Acierno, Shintaro Azumaya, Seth Wayne Benjamin, Devendra Prasad Chalise, Ellice E. Chess, Alex J. Engelsma, Qiuyi Fu, Jirapa Jaikham, Bridget M. Knight, Nikita S. Kodjak, Adazsofia Lengyel, Brenda L. Muñoz, Justin T. Patterson, Sundara I. Rincon, Francis L. Schumann, Yujie Shi, Charlie C. Smith, Mallory K. St. Clair, Carly S. Sweeney, Patrick Whitaker, James Wu, Luis Diaz‐Garcia
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Plants, People, Planet
Subjects:
ampelography
grapevine
leaf development
leaf shape
morphospace
Vitis
Online Access:https://doi.org/10.1002/ppp3.10561
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