Growth curve registration for evaluating salinity tolerance in barley

Handle URI:
http://hdl.handle.net/10754/623087
Title:
Growth curve registration for evaluating salinity tolerance in barley
Authors:
Meng, Rui ( 0000-0003-4639-5792 ) ; Saade, Stephanie; Kurtek, Sebastian; Berger, Bettina; Brien, Chris; Pillen, Klaus; Tester, Mark A. ( 0000-0002-5085-8801 ) ; Sun, Ying ( 0000-0001-6703-4270 )
Abstract:
Background: 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Biological and Environmental Sciences and Engineering (BESE) Division
Citation:
Meng 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.
Publisher:
Springer Nature
Journal:
Plant Methods
Issue Date:
23-Mar-2017
DOI:
10.1186/s13007-017-0165-7
Type:
Article
ISSN:
1746-4811
Sponsors:
The 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).
Is Supplemented By:
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:10.6084/m9.figshare.c.3723835; HANDLE:http://hdl.handle.net/10754/624148
Additional Links:
http://link.springer.com/article/10.1186/s13007-017-0165-7
Appears in Collections:
Articles; Biological and Environmental Sciences and Engineering (BESE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMeng, Ruien
dc.contributor.authorSaade, Stephanieen
dc.contributor.authorKurtek, Sebastianen
dc.contributor.authorBerger, Bettinaen
dc.contributor.authorBrien, Chrisen
dc.contributor.authorPillen, Klausen
dc.contributor.authorTester, Mark A.en
dc.contributor.authorSun, Yingen
dc.date.accessioned2017-04-10T07:49:50Z-
dc.date.available2017-04-10T07:49:50Z-
dc.date.issued2017-03-23en
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.en
dc.identifier.issn1746-4811en
dc.identifier.doi10.1186/s13007-017-0165-7en
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.en
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).en
dc.publisherSpringer Natureen
dc.relation.urlhttp://link.springer.com/article/10.1186/s13007-017-0165-7en
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.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectFunctional ANOVA modelen
dc.subjectHigh-throughput phenotypingen
dc.subjectNested association mappingen
dc.subjectPlant growthen
dc.subjectSpatial variationen
dc.subjectTemporal variationen
dc.titleGrowth curve registration for evaluating salinity tolerance in barleyen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.identifier.journalPlant Methodsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionThe Ohio State University, Department of Statistics, Columbus, OH, , United Statesen
dc.contributor.institutionUniversity of Adelaide, Australian Plant Phenomics Facility, The Plant Accelerator, Urrbrae, SA, 5064, , Australiaen
dc.contributor.institutionUniversity of South Australia, Phenomics and Bioinformatics Research Centre, Adelaide, SA, 5001, , Australiaen
dc.contributor.institutionMartin Luther University Halle-Wittenberg, Institute of Agricultural and Nutritional Sciences, Betty-Heimann-Str. 3, Halle, 06120, , Germanyen
kaust.authorMeng, Ruien
kaust.authorSaade, Stephanieen
kaust.authorTester, Mark A.en
kaust.authorSun, Yingen
dc.relation.isSupplementedByMeng, 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.3723835en
dc.relation.isSupplementedByDOI:10.6084/m9.figshare.c.3723835en
dc.relation.isSupplementedByHANDLE:http://hdl.handle.net/10754/624148en
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