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        <dc:title>LeasyScan: 3D scanning of crop canopy plus seamless monitoring of water use to harness&#13;
the genetics of key traits for drought adaptation</dc:title>
        <dc:creator>Vadez, V</dc:creator>
        <dc:creator>Kholova, J</dc:creator>
        <dc:creator>Srikanth, M</dc:creator>
        <dc:creator>Rekha, B</dc:creator>
        <dc:creator>Tharanya, M</dc:creator>
        <dc:creator>Sivasakthi, K</dc:creator>
        <dc:creator>Alimagham, M</dc:creator>
        <dc:creator>Karthika, G</dc:creator>
        <dc:creator>Keerthi, C</dc:creator>
        <dc:subject>Drought</dc:subject>
        <dc:subject>Genetics and Genomics</dc:subject>
        <dc:subject>Plant Physiology</dc:subject>
        <dc:description>With the genomics revolution in full swing, relevant phenotyping&#13;
is now a main bottleneck. New imaging technologies&#13;
provide opportunities for easier, faster and more informative&#13;
phenotyping of many plant parameters. However, it is critical&#13;
that the development of automated phenotyping be driven by a&#13;
clear framing of target phenotypes rather than by a technological&#13;
push, especially for complex constraints. Previous studies&#13;
on drought adaptation shows the importance of water availability&#13;
during the grain filling period, which depends on traits&#13;
controlling the plant water budget at earlier stages. We will&#13;
then discuss “cause” and “consequence” in phenotypes. Drawing&#13;
on this, a phenotyping platform (LeasyScan) was developed&#13;
to target canopy development and conductance traits. Based&#13;
on a novel 3D scanning technique to capture leaf area development&#13;
continuously and a scanner-to-plant concept to increase&#13;
imaging throughput, LeasyScan is also equipped with 1488 analytical&#13;
scales to measure transpiration seamlessly. Examples&#13;
of the first applications are presented: (i) to compare the leaf&#13;
area development pattern of pearl millet breeding material targeted&#13;
to different agro-ecological zones, (ii) for the mapping&#13;
of QTLs for vigour traits in chickpea, shown to co-map with an&#13;
earlier reported “drought tolerance” QTL; (iii) for the mapping&#13;
of leaf area development in pearl millet; (iv) for assessing the&#13;
transpiration response to high vapour pressure deficit in different&#13;
crops. This new platform has the potential to phenotype&#13;
traits controlling plant water use at a high rate and precision,&#13;
opening the opportunity to harness their genetics towards&#13;
breeding improved varieties.</dc:description>
        <dc:date>2017-02</dc:date>
        <dc:type>Conference or Workshop Item</dc:type>
        <dc:type>PeerReviewed</dc:type>
        <dc:format>application/pdf</dc:format>
        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/10293/1/Abstract_Book_125.pdf</dc:identifier>
        <dc:identifier>  Vadez, V and Kholova, J and Srikanth, M and Rekha, B and Tharanya, M and Sivasakthi, K and Alimagham, M and Karthika, G and Keerthi, C  (2017) LeasyScan: 3D scanning of crop canopy plus seamless monitoring of water use to harness the genetics of key traits for drought adaptation.  In: InterDrought-V, February 21-25, 2017, Hyderabad, India.     </dc:identifier></oai_dc:dc>
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