Resolving Form–Structure–Function Relationships in Plants with MRI for Biomimetic Transfer. (23rd May 2019)

• Record Type: Journal Article
• Authors: Hesse, Linnea; Leupold, Jochen; Poppinga, Simon; Wick, Markus; Strobel, Klaus; Masselter, Tom; Speck, Thomas
• Is Part Of: Integrative and comparative biology. Volume 59:Number 6(2019:Dec.)
• Page Start: 1713
• Page End: 1726
• Publication Date: 2019-05-23
• Subjects: Zoology -- Periodicals; Biology -- Periodicals; Physiology, Comparative -- Periodicals; 590.5
• DOI: 10.1093/icb/icz051
• Languages: English
• ISSNs: 1540-7063

Abstract

Abstract: In many biomimetic approaches, a deep understanding of the form–structure–function relationships in living and functionally intact organisms, which act as biological role models, is essential. This knowledge is a prerequisite for the identification of parameters that are relevant for the desired technical transfer of working principles. Hence, non-invasive and non-destructive techniques for static (3D) and dynamic (4D) high-resolution plant imaging and analysis on multiple hierarchical levels become increasingly important. In this study we demonstrate that magnetic resonance imaging (MRI) can be used to resolve the plants inner tissue structuring and functioning on the example of four plant concept generators with sizes larger than 5 mm used in current biomimetic research projects: Dragon tree ( Dracaena reflexa var. angustifolia ), Venus flytrap ( Dionaea muscipula ), Sugar pine ( Pinus lambertiana ) and Chinese witch hazel ( Hamamelis mollis ). Two different MRI sequences were applied for high-resolution 3D imaging of the differing material composition (amount, distribution, and density of various tissues) and condition (hydrated, desiccated, and mechanically stressed) of the four model organisms. Main aim is to better understand their biomechanics, development, and kinematics. The results are used as inspiration for developing novel design and fabrication concepts for bio-inspired technical fiber-reinforced branchings and smart biomimetic actuators.