Accurate models of plant morphology, accounting for development and changes in plant architecture across evolutionary distances, are vital in the plant sciences. Breeding the next generation of agricultural crops to feed a rising global population, predicting the effects of climate change, and sustaining ecosystems and biodiversity all require not only a mechanistic understanding of how plant development unfolds, but a comprehensive mathematical framework to describe the resultant morphology of plants. Ultimately, such a description of morphology requires geometric and topological descriptors of plant organ shapes and architecture to fully characterize the plant phenotype. Yet, the current plant phenotyping framework mostly relies on simple statistics of geometric measurements, such as length, diameter, and curvature, as well as counts of biological features to describe plant morphology topologically. These approaches fail to capture the exquisite architecture of plants in that they neglect the multivariate relationships between measureable plant features, elegant mathematical descriptions to comprehensively measure the plant form, and quantifications beyond the abilities of human vision. Hence, a holistic description of plant shape is fundamental given the global importance of plants for our societies but remains out of reach.
In this Frontiers Research Topic, we seek to bring together plant biologists concerned with morphology and architecture—whether they be developmental biologists, agronomists, ecologists, or physiologists—with mathematicians, computer scientists, and engineers, specializing in fields relevant to the description of the plant form who use and develop techniques in the contexts of computational geometry and topology, remote sensing, and graph theory. We encourage submission of all article types (Original Research, Hypothesis & Theory, Methods, Reviews, Mini Reviews, Perspective and Opinion). Plant biology topics can be as diverse as modeling the canopy of forests, describing the topology of complex root architectures, modeling the aerodynamics of leaves fluttering in the wind, comprehensive measures of leaf shape variation, the intricate shapes of cells, or complex multivariate responses to environmental stresses. Mathematical topics may include landmark-free shape comparisons, graph reduction schemes to extract shape information from data, the determination of self-nestedness of branching structures as an underlying graph signature, and the use of persistent homology to reveal the scaling of phenotypes in plants. In short, this Research Topic seeks to uniquely integrate descriptions of plant morphology with mathematics to arrive at an accurate description of plant architecture.
This Research Topic was inspired by the NIMBioS Investigative Workshop “Morphological Plant Models” (held September 2-4, 2015 at the University of Tennessee, Knoxville) which we hope will generate novel collaborations and insights leading to contributed manuscripts, but contributions from all interested individuals are welcome.
Accurate models of plant morphology, accounting for development and changes in plant architecture across evolutionary distances, are vital in the plant sciences. Breeding the next generation of agricultural crops to feed a rising global population, predicting the effects of climate change, and sustaining ecosystems and biodiversity all require not only a mechanistic understanding of how plant development unfolds, but a comprehensive mathematical framework to describe the resultant morphology of plants. Ultimately, such a description of morphology requires geometric and topological descriptors of plant organ shapes and architecture to fully characterize the plant phenotype. Yet, the current plant phenotyping framework mostly relies on simple statistics of geometric measurements, such as length, diameter, and curvature, as well as counts of biological features to describe plant morphology topologically. These approaches fail to capture the exquisite architecture of plants in that they neglect the multivariate relationships between measureable plant features, elegant mathematical descriptions to comprehensively measure the plant form, and quantifications beyond the abilities of human vision. Hence, a holistic description of plant shape is fundamental given the global importance of plants for our societies but remains out of reach.
In this Frontiers Research Topic, we seek to bring together plant biologists concerned with morphology and architecture—whether they be developmental biologists, agronomists, ecologists, or physiologists—with mathematicians, computer scientists, and engineers, specializing in fields relevant to the description of the plant form who use and develop techniques in the contexts of computational geometry and topology, remote sensing, and graph theory. We encourage submission of all article types (Original Research, Hypothesis & Theory, Methods, Reviews, Mini Reviews, Perspective and Opinion). Plant biology topics can be as diverse as modeling the canopy of forests, describing the topology of complex root architectures, modeling the aerodynamics of leaves fluttering in the wind, comprehensive measures of leaf shape variation, the intricate shapes of cells, or complex multivariate responses to environmental stresses. Mathematical topics may include landmark-free shape comparisons, graph reduction schemes to extract shape information from data, the determination of self-nestedness of branching structures as an underlying graph signature, and the use of persistent homology to reveal the scaling of phenotypes in plants. In short, this Research Topic seeks to uniquely integrate descriptions of plant morphology with mathematics to arrive at an accurate description of plant architecture.
This Research Topic was inspired by the NIMBioS Investigative Workshop “Morphological Plant Models” (held September 2-4, 2015 at the University of Tennessee, Knoxville) which we hope will generate novel collaborations and insights leading to contributed manuscripts, but contributions from all interested individuals are welcome.
