Methods and Applications for the Advancement of Plant Phenotyping

TOPICAL COLLECTIONS

Guest Editor

Nicky Creux

University of Pretoria, FABI, Department of Plant and Soil Sciences

<p>Dr. Creux completed her PhD at the University of Pretoria in 2014 and focused on the molecular genetics of cellulose synthase regulation during wood formation. After this Nicky’s focus shifted to sunflower circadian rhythms and flower physiology when she joined the Harmer lab at UC Davis. This research focused on the interaction between the environment and the circadian clock to co-ordinate pollinator visits and anthesis. Dr. Creux took up a faculty position at the University of Pretoria in the Forestry and Agricultural Biotechnology Institute (FABI) in 2019, where her team focuses on understanding the environmental factors influencing the floral biology of crop species. For this research, the team employs several different plant phenotyping and image analysis tools. For detailed changes in individual flowers, they use low-cost Raspberry Pi imaging under controlled conditions and weather resistant field cameras for time-lapse photography. To assess general plant and crop development for maize and sunflower, the team is using both field scan systems with LiDAR, RGB and NIR capabilities or UAVs with thermal and multispectral imaging. Recently, Dr. Creux has embarked on a new project with Innovation Africa @UP to grow a plant phenotyping platform at the University of Pretoria to help link platforms across the University and the country. Nicky believes agriculture and food security are important in developing South Africa and access to quality phenotyping is a key element to its success.</p>

Collection Overview

Plant phenotyping is the cornerstone of crop selection or domestication and up until recently has been a laborious, manual task. Technological advancements have accelerated the development of high throughput, non-destructive automated or semi-automated plant phenotyping tools. Currently, modern plant phenotyping is a transdisciplinary field incorporating plant biology, chemistry, physics, engineering, mathematics, and computer science. Coupling the new phenotyping tools to genomic resources provides a powerful strategy for targeted breeding of different crop species. The rapid development of phenotyping tools using multiple sensors, UAVs, robotics, artificial intelligence, and computer vision has focused attention on ensuring protocols and systems are standardized for better data quality and repeatability. Many of these technologies have a high cost and are inaccessible to researchers or industries from lower-income regions, which has also driven the development of open access, and low-cost phenotyping protocols. This collection aims to provide a set of plant phenotyping protocols to contribute to the standardization of plant phenotyping methods for future research. We invite researchers to submit methods and applications related to plant and crop phenotyping in controlled or field environments and for data processing, modeling, or management. We hope to create a balanced collection representing methods and applications both for state-of-the-art and affordable open access phenotyping techniques.

Abstracts

<p>Proximodistal age variation in Nicotiana benthamiana influences the plant hypersensitive response upon transient expression of effector transgenes</p>

Trystan Nadasen^*1

¹Molecular Plant Pathogen Interaction group (MPPI), Forestry and Agricultural Biotechnology Institute (FABI), Faculty of Natural and Agricultural Sciences, University of Pretoria, Pretoria, South Africa