Karine  Chenu

Dr. Karine Chenu

Centre for Plant Science, Queensland Alliance for Agriculture and Food Innovation, 306 Carmody Road, The University of Queensland, St Lucia QLD 4072, Australia
orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2014 in Environmental Modelling & Software
Verified
Journal Article
Closed access
DHDean P. Holzworth
Dean P. Holzworth
NHNeil I. Huth
Neil I. Huth
PDPeter G. Devoil
Peter G. Devoil
EZEric J. Zurcher
Eric J. Zurcher
NHNeville I. Herrmann
Neville I. Herrmann
BKBrian A. Keating
Brian A. Keating

25 November 2005 in New Phytologist
Verified
Journal Article
Open access
PDF file
CGChristine Granier
Christine Granier
LALuis Aguirrezabal
Luis Aguirrezabal
KCKarine Chenu
Karine Chenu
SCSarah Jane Cookson
Sarah Jane Cookson
MDMyriam Dauzat
Myriam Dauzat
FTFrançois Tardieu
François Tardieu
• The high‐throughput phenotypic analysis of Arabidopsis thaliana collections requires methodological progress and automation. Methods to impose stable and reproducible soil water deficits are presented and were used to analyse plant responses to water stress. • Several potential complications and methodological difficulties were identified, including the spatial and temporal variability of micrometeorological conditions within a growth chamber, the difference in soil water depletion rates between accessions and the differences in developmental stage of accessions the same time after sowing. Solutions were found. • Nine accessions were grown in four experiments in a rigorously controlled growth‐chamber equipped with an automated system to control soil water content and take pictures of individual plants. One accession, An1, was unaffected by water deficit in terms of leaf number, leaf area, root growth and transpiration rate per unit leaf area. • Methods developed here will help identify quantitative trait loci and genes involved in plant tolerance to water deficit.

1 June 2017 in Trends in Plant Science
Verified
Journal Article
Closed access
KCKarine Chenu
Karine Chenu
JPJohn Roy Porter
John Roy Porter
PMPierre Martre
Pierre Martre
BBBruno Basso
Bruno Basso
SCScott Chapman
Scott Chapman
SASenthold Asseng
Senthold Asseng

23 September 2015 in Global Change Biology
Verified
Journal Article
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PDF file
DLDavid Lobell
David Lobell
GHGraeme Hammer
Graeme Hammer
KCKarine Chenu
Karine Chenu
BZBangyou Zheng
Bangyou Zheng
GMGreg McLean
Greg McLean
SCScott Chapman
Scott Chapman

1 March 2011 in Journal of Experimental Botany
Verified
Journal Article
Open access
PDF file
KCKarine Chenu
Karine Chenu
MCM. Cooper
M. Cooper
GHGraeme Hammer
Graeme Hammer
KMK. L. Mathews
K. L. Mathews
MDM. F. Dreccer
M. F. Dreccer
SCScott Chapman
Scott Chapman
Genotype–environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.