Composite modeling of leaf shape along shoots discriminates <i>Vitis</i> species better than individual leaves
Abigail E. Bryson, Maya Wilson Brown, Joey Mullins, Wei Dong, Keivan Bahmani, Nolan Bornowski, Christina Chiu, Philip Engelgau, Bethany Gettings, Fabio Gómez-Cano, Luke M. Gregory, Anna Haber, Donghee Hoh, Emily E. Jennings, Zhongjie Ji, Prabhjot Kaur, Sunil K. Kenchanmane Raju, Y. F. Long, Serena Lotreck, Davis Mathieu, Thilanka Ranaweera, Eleanore J. Ritter, Rie Sadohara, Robert Z. Shrote, Kaila Smith, Scott J. Teresi, Julian Venegas, Hao Wang, McKena Lipham Wilson, Alyssa R. Tarrant, Margaret H. Frank, Zoë Migicovsky, Jyothi Kumar, Robert VanBuren, Jason P. Londo, Daniel H. Chitwood
Abstract
PREMISE: spp.) 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. METHODS: 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. RESULTS: 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. DISCUSSION: 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.