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Real-time plant phenomics under robotic farming setup: A vision-based platform for complex plant phenotyping tasks
Örebro University, School of Science and Technology. (MRO AASS)ORCID iD: 0000-0003-1827-9698
Örebro University, School of Science and Technology. (MRO AASS)ORCID iD: 0000-0002-2953-1564
2021 (English)In: Computers & electrical engineering, ISSN 0045-7906, E-ISSN 1879-0755, Vol. 92, article id 107098Article in journal, Editorial material (Refereed) Published
Abstract [en]

Plant phenotyping in general refers to quantitative estimation of the plant's anatomical, ontogenetical, physiological and biochemical properties. Analyzing big data is challenging, and non-trivial given the different complexities involved. Efficient processing and analysis pipelines are the need of the hour with the increasing popularity of phenotyping technologies and sensors. Through this work, we largely address the overlapping object segmentation & localization problem. Further, we dwell upon multi-plant pipelines that pose challenges as detection and multi-object tracking becomes critical for single frame/set of frames aimed towards uniform tagging & visual features extraction. A plant phenotyping tool named RTPP (Real-Time Plant Phenotyping) is presented that can aid in the detection of single/multi plant traits, modeling, and visualization for agricultural settings. We compare our system with the plantCV platform. The relationship of the digital estimations, and the measured plant traits are discussed that plays a vital roadmap towards precision farming and/or plant breeding.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 92, article id 107098
Keywords [en]
Automation, Computer vision, Image processing, Object localization, Pattern recognition, Perception, Phenotype, Plant science, Precision agriculture, Robotics, Spectral
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-91569DOI: 10.1016/j.compeleceng.2021.107098ISI: 000663708100004Scopus ID: 2-s2.0-85103247266OAI: oai:DiVA.org:oru-91569DiVA, id: diva2:1548959
Available from: 2021-05-04 Created: 2021-05-04 Last updated: 2021-07-30Bibliographically approved

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Real-time plant phenomics under robotic farming setup: A vision-based platform for complex plant phenotyping tasks(18180 kB)15 downloads
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Arunachalam, AjayAndreasson, Henrik

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Citation style
  • apa
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