{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/isolating-phyllotactic-patterns-embedded-in","title":"Isolating phyllotactic patterns embedded in the secondary growth of sweet cherry (Prunus avium L.) using magnetic resonance imaging","arxiv_id":"1812.03321","date":"2018-12-08","proceeding":null,"authors":["Mitchell Eithun","Daniel H. Chitwood","James Larson","Gregory Lang","Elizabeth Munch"],"abstract":"Epicormic branches arise from dormant buds patterned during the growth of\nprevious years. Dormant epicormic buds remain on the surface of trees, pushed\noutward from the pith during secondary growth, but maintaining vascular\nconnections. Epicormic buds can be reactivated, either through natural\nprocesses or intentionally, to rejuvenate orchards and control tree\narchitecture. Because epicormic structures are embedded within secondary\ngrowth, tomographic approaches are a useful method to study them and understand\ntheir development.\n  We apply techniques from image processing to determine the locations of\nepicormic vascular traces embedded within secondary growth of sweet cherry\n(Prunus avium L.), revealing the juvenile phyllotactic pattern in the trunk of\nan adult tree. Techniques include breadth-first search to find the pith of the\ntree, edge detection to approximate the radius, and a conversion to polar\ncoordinates to threshold and segment phyllotactic features. Intensity values\nfrom Magnetic Resonance Imaging (MRI) of the trunk are projected onto the\nsurface of a perfect cylinder to find the locations of traces in the \"boundary\nimage\". Mathematical phyllotaxy provides a means to capture the patterns in the\nboundary image by modeling phyllotactic parameters. Our cherry tree specimen\nhas the conspicuous parastichy pair $(2,3)$, phyllotactic fraction 2/5, and\ndivergence angle of approximately 143 degrees.\n  The methods described not only provide a framework to study phyllotaxy, but\nfor image processing of volumetric image data in plants. Our results have\npractical implications for orchard rejuvenation and directed approaches to\ninfluence tree architecture. The study of epicormic structures, which are\nhidden within secondary growth, using tomographic methods also opens the\npossibility of studying the genetic and environmental basis of such structures.","url_abs":"http://arxiv.org/abs/1812.03321v1","url_pdf":"http://arxiv.org/pdf/1812.03321v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"isolating-phyllotactic-patterns-embedded-in","repo_url":"https://github.com/eithun/cherry-phyllotaxy","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"edge-detection","task_name":"Edge Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}