Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/90002
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C₄ cereal crop plant to nitrogen and water deficiency over time
Other Titles: Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C(4) cereal crop plant to nitrogen and water deficiency over time
Author: Neilson, E.
Edwards, A.
Blomstedt, C.
Berger, B.
Møller, B.
Gleadow, R.
Citation: Journal of Experimental Botany, 2015; 66(7):1817-1832
Publisher: Oxford University Press
Issue Date: 2015
ISSN: 0022-0957
1460-2431
Statement of
Responsibility: 
E.H. Neilson, A.M. Edwards, C.K. Blomstedt, B. Berger, B. Lindberg Møller and R.M. Gleadow
Abstract: The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator(®) at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf 'greenness' correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants.
Keywords: Cyanogenesis
drought
growth
LemnaTec Scanalyzer
nitrogen deficiency
phenomics
Sorghum.
Rights: © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1093/jxb/eru526
Grant ID: http://purl.org/au-research/grants/arc/LP100100434
http://purl.org/au-research/grants/arc/DP130101049
Appears in Collections:Agriculture, Food and Wine publications
Aurora harvest 2

Files in This Item:
File Description SizeFormat 
hdl_90002.pdfPublished version3.38 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.