Enabling next level research on roots: Automatizing Minirhizotron Image Acquisition and Analysis (NextMR-IAA) for Research and Agricultural Management

Boris Rewald, Liaqat Seehra, Ofer Hadar, Adam Soffer, Pavel Baykalov, Mor Elmakies, Gernot Bodner, Kaining Zhou, Naftali Lazarovitch

Research output: Contribution to conferencePaperpeer-review

Abstract

Non-invasive imaging technologies continue to rise in use; innovation of root and rhizosphere imaging devices has however not kept pace. The lack of automated, high-resolution root imaging and analysis hampers our scientific understanding and prevents application of minirhizotrons in agricultural and environmental settings. Two complementary automatic minirhizotron systems for applied and research purposes were developed, the latter featuring an unprecedented position-accuracy and image-quality. Two pipelines based on CNN models allow for feature extraction for research and practical applications (e.g. fertigation scheduling), respectively. NIR-wavebands for soil water content estimation were tested. Our technological innovations will make rooting information widely accessible.
Original languageEnglish
StatePublished - 31 Aug 2020

Keywords

  • Automation
  • Sustainable Agriculture
  • Breeding
  • C sequestration
  • CNN
  • Minirhizotron Imaging
  • Root ecology
  • Root traits

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