NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Bai, Geng; Ge, Yufeng; Scoby, David; Leavitt, Bryan; Stoerger, Vincent; Kirchgeßner, Norbert; Irmak, Suat; Graef, George L.; Schnable, James C.; Awada, Tala

doi:10.1016/j.compag.2019.03.009

Cited by 85 publications

(38 citation statements)

References 24 publications

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“…The feasibility of FIP in monitoring canopy coverage and canopy height of winter wheat, maize, and soybean was verified by Kirchgessner et al ( 2017 ). Furthermore, the Nu-Spidercam at the University of Nebraska has a multi-sensor systems, a subsurface drip irrigation (SDI) system and an automatic weather station (Bai et al, 2019 ), which is capable of accurately and flexibly capturing crop traits, such as plant height, canopy cover, and spectral reflection. Its sensor bar integrates numerous sensors, so software is designed for selecting available sensors to meet particular experimental needs.…”

Section: Ht3p For Field Phenotyping In Notoriously Heterogeneous Condmentioning

confidence: 99%

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Quan

Song

et al. 2021

Front. Bioeng. Biotechnol.

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Food scarcity, population growth, and global climate change have propelled crop yield growth driven by high-throughput phenotyping into the era of big data. However, access to large-scale phenotypic data has now become a critical barrier that phenomics urgently must overcome. Fortunately, the high-throughput plant phenotyping platform (HT3P), employing advanced sensors and data collection systems, can take full advantage of non-destructive and high-throughput methods to monitor, quantify, and evaluate specific phenotypes for large-scale agricultural experiments, and it can effectively perform phenotypic tasks that traditional phenotyping could not do. In this way, HT3Ps are novel and powerful tools, for which various commercial, customized, and even self-developed ones have been recently introduced in rising numbers. Here, we review these HT3Ps in nearly 7 years from greenhouses and growth chambers to the field, and from ground-based proximal phenotyping to aerial large-scale remote sensing. Platform configurations, novelties, operating modes, current developments, as well the strengths and weaknesses of diverse types of HT3Ps are thoroughly and clearly described. Then, miscellaneous combinations of HT3Ps for comparative validation and comprehensive analysis are systematically present, for the first time. Finally, we consider current phenotypic challenges and provide fresh perspectives on future development trends of HT3Ps. This review aims to provide ideas, thoughts, and insights for the optimal selection, exploitation, and utilization of HT3Ps, and thereby pave the way to break through current phenotyping bottlenecks in botany.

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Section: Ht3p For Field Phenotyping In Notoriously Heterogeneous Condmentioning

confidence: 99%

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

Quan

Song

et al. 2021

Front. Bioeng. Biotechnol.

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“…They are used in a broad spectrum of applications from data corrections, filtering and quality assurance, through to increasing ecophysiological understanding from multiple lines of evidence. In addition to previously mentioned integrated proximal systems at flux tower sites, plant phenotyping is a main driver of technical development, evidenced by static tower systems [1] or mobile systems carrying multiple payloads [6,16,68]. Such systems facilitate research into long-term ecosystem dynamics, monitoring environmental change and ecosystem resilience.…”

Section: The Importance Of Multi-sensor -Temporal and -Angular Datamentioning

confidence: 99%

THEMS: an automated thermal and hyperspectral proximal sensing system for canopy reflectance, radiance and temperature

et al. 2020

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Background: Earth Observation 'EO' remote sensing technology development enables original insights into vegetation function and health at ever finer temporal, spectral and spatial resolution. Research sites equipped with monitoring infrastructure such as flux towers operate at a key bridging scale between satellite platform measurements and on-the-ground leaf-level processes. Results: This paper presents the technical details of the design and operation of a proximal observation system 'THEMS' that generates unattended long-term high quality thermal and hyperspectral images of a forest canopy on a short (sub-daily) timescale. The primary purpose of the system is to measure canopy temperature, spectral reflectance and radiance coincident with a highly instrumented flux tower site for benchmarking purposes. Basic system capability is demonstrated through low level data product descriptions of the high-resolution multi-angular imagery and ancillary data streams. The system has been successfully operational for more than 2 years with little to no intervention. Conclusions: These data can then be used to derive remotely sensed proxies of canopy and ecosystem function to study temporal forest dynamics over a wide range of wavelengths, spatial scales (individual trees to canopy), and temporal scales (minutes to multiple years). The multipurpose system is intended to provide unprecedented spatiotemporal ecophysiological insight and to underpin upscaling of remotely sensed dynamic ecosystem water, CO 2 , and energy exchange processes.

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“…For example, the Field Phenotyping Platform (FIP) established at the ETH Zurich uses a suspended cable setup to move sensors over a large experimental field site [84] . Similar setups exist at the University of Nebraska to phenotype maize and soybean cultures [86] . These proximal phenotyping platforms benefit from having multiple mounted sensors capturing phenotypic trait information over a wide range of wavelengths.…”

Section: Introductionmentioning

confidence: 99%

Tackling microbial threats in agriculture with integrative imaging and computational approaches

Singh

Dutta

Puccetti

et al. 2021

Computational and Structural Biotechnology Journal

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NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Cited by 85 publications

References 24 publications

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

THEMS: an automated thermal and hyperspectral proximal sensing system for canopy reflectance, radiance and temperature

Tackling microbial threats in agriculture with integrative imaging and computational approaches

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