Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/105687
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Type: Journal article
Title: Phenotyping of plants in competitive but controlled environments: a study of drought response in transgenic wheat
Author: Kovalchuk, N.
Laga, H.
Cai, J.
Kumar, P.
Parent, B.
Lu, Z.
Miklavcic, S.
Haefele, S.
Citation: Functional Plant Biology: an international journal of plant function, 2017; 44(3):290-301
Publisher: CSIRO Publishing
Issue Date: 2017
ISSN: 1445-4408
1445-4416
Statement of
Responsibility: 
Nataliya Kovalchuk, Hamid Laga, Jinhai Cai, Pankaj Kumar, Boris Parent, Zhi Lu, Stanley J. Miklavcic and Stephan M. Haefele
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.
Keywords: Canopy coverage imaging; competitive growth conditions; plant phenotyping; transcription factors
Rights: Journal compilation © CSIRO 2017
DOI: 10.1071/FP16202
Grant ID: ARC
Published version: http://dx.doi.org/10.1071/fp16202
Appears in Collections:Agriculture, Food and Wine publications
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