4.6 Article

MultispeQ Beta: a tool for large-scale plant phenotyping connected to the open PhotosynQ network

期刊

ROYAL SOCIETY OPEN SCIENCE
卷 3, 期 10, 页码 -

出版社

ROYAL SOC
DOI: 10.1098/rsos.160592

关键词

agriculture; chlorophyll fluorescence; open-source hardware; phenomics; photosynthesis

资金

  1. U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES) [DE-FG02-91ER20021]
  2. MSU AgBioResearch program
  3. USAID
  4. McKnight Foundation

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Large-scale high-throughput plant phenotyping (sometimes called phenomics) is becoming increasingly important in plant biology and agriculture and is essential to cutting-edge plant breeding and management approaches needed to meet the food and fuel needs for the next century. Currently, the application of these approaches is severely limited by the availability of appropriate instrumentation and by the ability to communicate experimental protocols, results and analyses. To address these issues, we have developed a low-cost, yet sophisticated open-source scientific instrument designed to enable communities of researchers, plant breeders, educators, farmers and citizen scientists to collect high-quality field data on a large scale. The MultispeQ provides measurements in the field or laboratory of both, environmental conditions (light intensity and quality, temperature, humidity, CO2 levels, time and location) and useful plant phenotypes, including photosynthetic parameters-photosystem II quantum yield (FII), non-photochemical exciton quenching (NPQ), photosystem II photoinhibition, light-driven proton translocation and thylakoid proton motive force, regulation of the chloroplast ATP synthase and potentially many others-and leaf chlorophyll and other pigments. Plant phenotype data are transmitted from the MultispeQ to mobile devices, laptops or desktop computers together with key metadata that gets saved to the PhotosynQ platform (https://photosynq.org) and provides a suite of web-based tools for sharing, visualization, filtering, dissemination and analyses. We present validation experiments, comparing MultispeQ results with established platforms, and show that it can be usefully deployed in both laboratory and field settings. We present evidence that MultispeQ can be used by communities of researchers to rapidly measure, store and analyse multiple environmental and plant properties, allowing for deeper understanding of the complex interactions between plants and their environment.

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