Approaches to three-dimensional reconstruction of plant shoot topology and geometry

Gibbs, Jonathon; Pound, Michael P.; French, Andrew P.; Wells, Darren M.; Murchie, Erik H.; Pridmore, Tony P.

Abstract

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and reducing the amount of land available for agriculture. Recent studies show that without crop climate adaption, crop productivity will deteriorate. With access to 3D models of real plants it is possible to acquire detailed morphological and gross developmental data that can be used to study their ecophysiology, leading to an increase in crop yield and stability across hostile and changing environments. Here we review approaches to the reconstruction of 3D models of plant shoots from image data, consider current applications in plant and crop science, and identify remaining challenges. We conclude that although phenotyping is receiving an increasing amount of attention – particularly from computer vision researchers – and numerous vision approaches have been proposed, it still remains a highly interactive process. An automated system capable of producing 3D models of plants would significantly aid phenotyping practice, increasing accuracy and repeatability of measurements.

Citation

Gibbs, J., Pound, M. P., French, A. P., Wells, D. M., Murchie, E. H., & Pridmore, T. P. (2016). Approaches to three-dimensional reconstruction of plant shoot topology and geometry. Functional Plant Biology, 44(1), 62-75. https://doi.org/10.1071/FP16167

• Journal Article Type: Article
• Acceptance Date: Jul 23, 2016
• Online Publication Date: Jul 26, 2016
• Publication Date: Aug 26, 2016
• Deposit Date: Aug 15, 2016
• Publicly Available Date: Aug 15, 2016
• Journal: Functional Plant Biology
• Print ISSN: 1445-4408
• Electronic ISSN: 1445-4416
• Publisher: CSIRO Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 44
• Issue: 1
• Pages: 62-75
• DOI: https://doi.org/10.1071/FP16167
• Keywords: image-based, plant modelling, reconstruction, three-dimensional
• Public URL: https://nottingham-repository.worktribe.com/output/799419
• Publisher URL: http://www.publish.csiro.au/FP/FP16167
• Contract Date: Aug 15, 2016