Phenotyping of plants in competitive but controlled environments: a study of drought response in transgenic wheat
Nataliya Kovalchuk A , Hamid Laga B C , Jinhai Cai B , Pankaj Kumar B , Boris Parent D , Zhi Lu B , Stanley J. Miklavcic B and Stephan M. Haefele A E
+ Author Affiliations
- Author Affiliations
A Australian Centre for Plant Functional Genomics, University of Adelaide, SA 5064, Australia.
B Phenomics and Bioinformatics Research Centre, University of South Australia, SA 5095, Australia.
C School of Engineering and Information Technology, Murdoch University, WA 6150, Australia.
D INRA, Laboratoire d’Ecophysiologie des Plantes sous Stress Environnementaux, 34060 Montpellier Cedex 1, France.
E Corresponding author. Email: stephan.haefele@acpfg.com.au
Functional Plant Biology 44(3) 290-301 https://doi.org/10.1071/FP16202
Submitted: 31 May 2016 Accepted: 5 November 2016 Published: 21 December 2016
Abstract
In recent years, the interest in new technologies for wheat improvement has increased greatly. To screen genetically modified germplasm in conditions more realistic for a field situation we developed a phenotyping platform where transgenic wheat and barley are grown in competition. In this study, we used the platform to (1) test selected promoter and gene combinations for their capacity to increase drought tolerance, (2) test the function and power of our platform to screen the performance of transgenic plants growing in competition, and (3) develop and test an imaging and analysis process as a means of obtaining additional, non-destructive data on plant growth throughout the whole growth cycle instead of relying solely on destructive sampling at the end of the season. The results showed that several transgenic lines under well watered conditions had higher biomass and/or grain weight than the wild-type control but the advantage was significant in one case only. None of the transgenics seemed to show any grain weight advantage under drought stress and only two lines had a substantially but not significantly higher biomass weight than the wild type. However, their evaluation under drought stress was disadvantaged by their delayed flowering date, which increased the drought stress they experienced in comparison to the wild type. Continuous imaging during the season provided additional and non-destructive phenotyping information on the canopy development of mini-plots in our phenotyping platform. A correlation analysis of daily canopy coverage data with harvest metrics showed that the best predictive value from canopy coverage data for harvest metrics was achieved with observations from around heading/flowering to early ripening whereas early season observations had only a limited diagnostic value. The result that the biomass/leaf development in the early growth phase has little correlation with biomass or grain yield data questions imaging approaches concentrating only on the early development stage.
Additional keywords: canopy coverage imaging, competitive growth conditions, plant phenotyping, transcription factors.
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