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dc.contributor.authorMeng, Rui
dc.contributor.authorSaade, Stephanie
dc.contributor.authorKurtek, Sebastian
dc.contributor.authorBerger, Bettina
dc.contributor.authorBrien, Chris
dc.contributor.authorPillen, Klaus
dc.contributor.authorTester, Mark A.
dc.contributor.authorSun, Ying
dc.date.accessioned2017-04-10T07:49:50Z
dc.date.available2017-04-10T07:49:50Z
dc.date.issued2017-03-23
dc.identifier.citationMeng R, Saade S, Kurtek S, Berger B, Brien C, et al. (2017) Growth curve registration for evaluating salinity tolerance in barley. Plant Methods 13. Available: http://dx.doi.org/10.1186/s13007-017-0165-7.
dc.identifier.issn1746-4811
dc.identifier.doi10.1186/s13007-017-0165-7
dc.identifier.urihttp://hdl.handle.net/10754/623087
dc.description.abstractBackground: Smarthouses capable of non-destructive, high-throughput plant phenotyping collect large amounts of data that can be used to understand plant growth and productivity in extreme environments. The challenge is to apply the statistical tool that best analyzes the data to study plant traits, such as salinity tolerance, or plant-growth-related traits. Results: We derive family-wise salinity sensitivity (FSS) growth curves and use registration techniques to summarize growth patterns of HEB-25 barley families and the commercial variety, Navigator. We account for the spatial variation in smarthouse microclimates and in temporal variation across phenotyping runs using a functional ANOVA model to derive corrected FSS curves. From FSS, we derive corrected values for family-wise salinity tolerance, which are strongly negatively correlated with Na but not significantly with K, indicating that Na content is an important factor affecting salinity tolerance in these families, at least for plants of this age and grown in these conditions. Conclusions: Our family-wise methodology is suitable for analyzing the growth curves of a large number of plants from multiple families. The corrected curves accurately account for the spatial and temporal variations among plants that are inherent to high-throughput experiments.
dc.description.sponsorshipThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). This research was also partially supported by NSF DMS 1613054 (to SK).
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/article/10.1186/s13007-017-0165-7
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectFunctional ANOVA model
dc.subjectHigh-throughput phenotyping
dc.subjectNested association mapping
dc.subjectPlant growth
dc.subjectSpatial variation
dc.subjectTemporal variation
dc.titleGrowth curve registration for evaluating salinity tolerance in barley
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentDesert Agriculture Initiative
dc.contributor.departmentPlant Science
dc.contributor.departmentStatistics Program
dc.identifier.journalPlant Methods
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionThe Ohio State University, Department of Statistics, Columbus, OH, , United States
dc.contributor.institutionUniversity of Adelaide, Australian Plant Phenomics Facility, The Plant Accelerator, Urrbrae, SA, 5064, , Australia
dc.contributor.institutionUniversity of South Australia, Phenomics and Bioinformatics Research Centre, Adelaide, SA, 5001, , Australia
dc.contributor.institutionMartin Luther University Halle-Wittenberg, Institute of Agricultural and Nutritional Sciences, Betty-Heimann-Str. 3, Halle, 06120, , Germany
kaust.personMeng, Rui
kaust.personSaade, Stephanie
kaust.personTester, Mark A.
kaust.personSun, Ying
dc.relation.issupplementedbyDOI:10.6084/m9.figshare.c.3723835
refterms.dateFOA2018-06-14T00:05:01Z
display.relations<b> Is Supplemented By:</b> <br/> <ul><li><i>[Dataset]</i> <br/> Meng, R., Saade, S., Kurtek, S., Berger, B., Brien, C., Pillen, K., … Sun, Y. (2017). Growth curve registration for evaluating salinity tolerance in barley. Figshare. https://doi.org/10.6084/m9.figshare.c.3723835. DOI: <a href="https://doi.org/10.6084/m9.figshare.c.3723835">10.6084/m9.figshare.c.3723835</a> HANDLE: <a href="http://hdl.handle.net/10754/624148">10754/624148</a></li></ul>
dc.date.published-online2017-03-23
dc.date.published-print2017-12


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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.