Engineering plants for tomorrow: how high-throughput phenotyping is contributing to the development of better crops View Full Text


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Article Info

DATE

2018-12

AUTHORS

Zachary C. Campbell, Lucia M. Acosta-Gamboa, Nirman Nepal, Argelia Lorence

ABSTRACT

High-throughput plant phenotyping has been advancing at an accelerated rate as a response to the need to fill the gap between genomic information and the plasticity of the plant phenome. During the past decade, North America has seen a stark increase in the number of phenotyping facilities, and these groups are actively contributing to the generation of high-dimensional, richly informative datasets about the phenotype of model and crop plants. As both phenomic datasets and analysis tools are made publicly available, the key to engineering more resilient crops to meet global demand is closer than ever. However, there are a number of bottlenecks that must yet be overcome before this can be achieved. In this paper, we present an overview of the most commonly used sensors that empower digital phenotyping and the information they provide. We also describe modern approaches to identify and characterize plants that are resilient to common abiotic and biotic stresses that limit growth and yield of crops. Of interest to researchers working in plant biochemistry, we also include a section discussing the potential of these high-throughput approaches in linking phenotypic data with chemical composition data. We conclude by discussing the main bottlenecks that still remain in the field and the importance of multidisciplinary teams and collaboration to overcome those challenges. More... »

PAGES

1-15

References to SciGraph publications

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  • Journal

    TITLE

    Phytochemistry Reviews

    ISSUE

    N/A

    VOLUME

    N/A

    Author Affiliations

    From Grant

  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11101-018-9585-x

    DOI

    http://dx.doi.org/10.1007/s11101-018-9585-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1105856516


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