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Depositordc.contributorMcCormick, Alistair
Funderdc.contributor.otherBBSRC - Biotechnology and Biological Sciences Research Councilen_UK
Funderdc.contributor.otherEPSRC - Engineering and Physical Sciences Research Councilen_UK
Funderdc.contributor.otherUniversity of Edinburghen_UK
Data Creatordc.creatorMcCormick, Alistair
Data Creatordc.creatorDobrescu, Andrei
Data Creatordc.creatorScorza, Livia CT
Date Accessioneddc.date.accessioned2017-11-24T14:52:08Z
Date Availabledc.date.available2017-11-24T14:52:08Z
Citationdc.identifier.citationMcCormick, Alistair; Dobrescu, Andrei; Scorza, Livia CT. (2017). Manual, [text]. University of Edinburgh. School of Biological Sciences. Institute of Molecular Plant Sciences. http://dx.doi.org/10.7488/ds/2256.en
Persistent Identifierdc.identifier.urihttp://hdl.handle.net/10283/2956
Persistent Identifierdc.identifier.urihttp://dx.doi.org/10.7488/ds/2256
Dataset Description (abstract)dc.description.abstractImprovements in high-throughput phenotyping technologies are rapidly expanding the scope and capacity of plant biology studies to measure growth traits. Nevertheless, the costs of commercial phenotyping equipment and infrastructure remain prohibitively expensive for wide-scale uptake, while academic solutions can require significant local expertise. Here a low-cost methodology for plant biologists to build their own phenotyping system for quantifying growth rates and phenotypic characteristics of Arabidopsis thaliana rosettes throughout the diel cycle is presented. The group constructed an image capture system consisting of a near infra-red (NIR, 940 nm) LED panel with a mounted Raspberry PI NoIR camera and developed a MatLab-based software module (iDIEL Plant) to characterise rosette expansion. The software was able to accurately segment and characterise multiple rosettes within an image, regardless of plant arrangement or genotype, and batch process image sets. To further validate the system, wild-type Arabidopsis plants (Col-0) and two mutant lines with reduced Rubisco contents, pale leaves and slow growth phenotypes (1a3b and 1a2b) were grown on a single plant tray. Plants were imaged from 9 to 24 days after germination every 20 minutes throughout the 24 hour light-dark growth cycle (i.e. the diel cycle). The resulting dataset provided a dynamic and uninterrupted characterisation of differences in rosette growth and expansion rates over time for the three lines tested. The methodology offers a straightforward solution for setting up automated, scalable and low-cost phenotyping facilities in a wide range of lab environments that could greatly increase the processing power and scalability of Arabidopsis soil growth experiments. iDIEL Plant software and CAD files for image capture system (ICS).en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburgh. School of Biological Sciences. Institute of Molecular Plant Sciencesen_UK
Relation (Is Referenced By)dc.relation.isreferencedbyhttps://doi.org/10.1186/s13007-017-0247-6en_UK
Relation (Is Referenced By)dc.relation.isreferencedbyDobrescu, Andrei; Scorza, Livia CT; Tsaftaris, Sotirios A; McCormick, Alistair J. (2017) 'A "Do-It-Yourself" phenotyping system: measuring growth and morphology throughout the diel cycle in rosette shaped plants'. Plant Methods 2017 13:95 https://doi.org/10.1186/s13007-017-0247-6en_UK
Subjectdc.subject2Den_UK
Subjectdc.subjectArabidopsis thalianaen_UK
Subjectdc.subjectnear-infrared LED arrayen_UK
Subjectdc.subjectimage analysisen_UK
Subjectdc.subjectlow costen_UK
Subjectdc.subjectRubiscoen_UK
Subject Classificationdc.subject.classificationBiological Sciencesen_UK
Titledc.titleManualen_UK
Typedc.typetexten_UK

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