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Tracking dynamic changes of leaves in response to nutrient availability using an open-source cloud-based phenotyping system (OPEN Leaf)
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  • Landon G. Swartz,
  • Suxing Liu,
  • Drew Dahlquist,
  • Emily S Walter,
  • Sam Mcinturf,
  • Alexander Bucksch,
  • David G Mendoza-Cozatl
Landon G. Swartz
University of Missouri-Columbia

Corresponding Author:[email protected]

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Suxing Liu
University of Georgia
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Drew Dahlquist
University of Missouri-Columbia
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Emily S Walter
C.S. Bond Life Sciences Center
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Sam Mcinturf
C.S. Bond Life Sciences Center
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Alexander Bucksch
University of Georgia
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David G Mendoza-Cozatl
University of Missouri-Columbia
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Abstract

(250 words) Micronutrients, such as iron, zinc, and sulfur, play a vital role in both plant and human development. Understanding how plants sense and allocate nutrients within their tissues may offer different venues to develop plants with high nutritional value. Despite decades of intensive research, more than 40% of genes in Arabidopsis remain uncharacterized or have no assigned function. While several resources such as mutant populations or diversity panels offer the possibility to identify genes critical for plant nutrition, the ability to consistently track and assess plant growth in an automated, unbiased way is still a major limitation. High-throughput phenotyping (HTP) is the new standard in plant biology but few HTP systems are open source and user friendly. Therefore, we developed OPEN Leaf, an open source HTP for hydroponic experiments. OPEN Leaf is capable of tracking changes in both size and color of the whole plant and specific regions of the rosette. We have also integrated communication platforms (Slack) and cloud services (CyVerse) to facilitate user communication, collaboration, data storage, and analysis in real time. As a proof-of-concept, we report the ability of OPEN Leaf to track changes in size and color when plants are growing hydroponically with different levels of nutrients. We expect that the availability of open source HTP platforms, together with standardized experimental conditions agreed by the scientific community, will advance the identification of genes and networks mediating nutrient uptake and allocation in plants.