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Curr Biol. 2017 Jul 24;27(14):2078-2088.e3. doi: 10.1016/j.cub.2017.06.009. Epub 2017 Jul 6.

A Statistical Description of Plant Shoot Architecture.

Author information

1
Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
2
Howard Hughes Medical Institute and Plant Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
3
Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
4
Integrative Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA. Electronic address: navlakha@salk.edu.

Abstract

Plant architectures can be characterized statistically by their spatial density function, which specifies the probability of finding a branch at each location in the territory occupied by a plant. Using high-precision 3D scanning, we analyzed 557 plant shoot architectures, representing three species, grown across three to five environmental conditions, and through 20-30 developmental time points. We found two elegant properties in the spatial density functions of these architectures: all functions could be nearly modified in one direction without affecting the density in orthogonal directions (called "separability"), and all functions shared the same underlying shape, aside from stretching and compression (called "self-similarity"). Surprisingly, despite their striking visual diversity, we discovered that all architectures could be described as variations on a single underlying function: a Gaussian density function truncated at roughly two SDs. We also observed systematic variation in the spatial density functions across species, growth conditions, and time, which suggests functional specialization despite following the same general design form.

KEYWORDS:

3D scanning; branch density; growth principles; plant architectures; self-similarity; separability

PMID:
28690115
PMCID:
PMC6130893
DOI:
10.1016/j.cub.2017.06.009
[Indexed for MEDLINE]
Free PMC Article

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