Vadez, V and Kholova, J and Hummel, G and Zhokhavets, U and Gupta, S K and Hash, C T (2015) LeasyScan: a novel concept combining 3D imaging and lysimetry for high-throughput phenotyping of traits controlling plant water budget. Journal of Experimental Botany, 66 (18). pp. 5581-5593. ISSN 1460-2431
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Abstract
In this paper, we describe the thought process and initial data behind the development of an imaging platform (LeasyScan) combined with lysimetric capacity, to assess canopy traits affecting water use (leaf area, leaf area index, transpiration). LeasyScan is based on a novel 3D scanning technique to capture leaf area development continuously, a scanner-to-plant concept to increase imaging throughput and analytical scales to combine gravimetric transpiration measurements. The paper presents how the technology functions, how data are visualised via a web-based interface and how data extraction and analysis is interfaced through ‘R’ libraries. Close agreement between scanned and observed leaf area data of individual plants in different crops was found (R2 between 0.86 and 0.94). Similar agreement was found when comparing scanned and observed area of plants cultivated at densities reflecting field conditions (R2 between 0.80 and 0.96). An example in monitoring plant transpiration by the analytical scales is presented. The last section illustrates some of the early ongoing applications of the platform to target key phenotypes: (i) the comparison of the leaf area development pattern of fine mapping recombinants of pearl millet; (ii) the leaf area development pattern of pearl millet breeding material targeted to different agro-ecological zones; (iii) the assessment of the transpiration response to high VPD in sorghum and pearl millet. This new platform has the potential to phenotype for traits controlling plant water use at a high rate and precision, of critical importance for drought adaptation, and creates an opportunity to harness their genetics for the breeding of improved varieties.
Item Type: | Article |
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Divisions: | RP-Dryland Cereals |
CRP: | CGIAR Research Program on Dryland Cereals |
Uncontrolled Keywords: | Drought, Gravimetric transpiration, High-throughput phenotyping, Lysimetric platform, Multi-discipline, Physiology, Vapour pressure deficit, 3D laser scanner, Pearl millet |
Subjects: | Mandate crops > Millets > Pearl Millet |
Depositing User: | Mr Ramesh K |
Date Deposited: | 18 Apr 2016 06:03 |
Last Modified: | 21 Oct 2016 04:44 |
URI: | http://oar.icrisat.org/id/eprint/9435 |
Official URL: | http://dx.doi.org/10.1093/jxb/erv251 |
Projects: | UNSPECIFIED |
Funders: | UNSPECIFIED |
Acknowledgement: | The authors are thankful for the funding from ICRISAT for the capital investment in the LeasyScan facility, to the Kirkhouse Trust fund and USAID (Feed the Future Innovation Lab—Climate Resilient Chickpea) for contributing to the acquisition of additional analytical scales, and the CGIAR Research Program on Dryland Cereals (CRP-DC), Grain Legumes (CRP-GL), and Climate Change, Agriculture and Food Security (CCAFS), for some operational funding. |
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