Literature DB >> 32480554

The ETH field phenotyping platform FIP: a cable-suspended multi-sensor system.

Norbert Kirchgessner1, Frank Liebisch1, Kang Yu1, Johannes Pfeifer1, Michael Friedli1, Andreas Hund1, Achim Walter1.   

Abstract

Crop phenotyping is a major bottleneck in current plant research. Field-based high-throughput phenotyping platforms are an important prerequisite to advance crop breeding. We developed a cable-suspended field phenotyping platform covering an area of ~1ha. The system operates from 2 to 5m above the canopy, enabling a high image resolution. It can carry payloads of up to 12kg and can be operated under adverse weather conditions. This ensures regular measurements throughout the growing period even during cold, windy and moist conditions. Multiple sensors capture the reflectance spectrum, temperature, height or architecture of the canopy. Monitoring from early development to maturity at high temporal resolution allows the determination of dynamic traits and their correlation to environmental conditions throughout the entire season. We demonstrate the capabilities of the system with respect to monitoring canopy cover, canopy height and traits related to thermal and multi-spectral imaging by selected examples from winter wheat, maize and soybean. The system is discussed in the context of other, recently established field phenotyping approaches; such as ground-operating or aerial vehicles, which impose traffic on the field or require a higher distance to the canopy.

Entities:  

Year:  2016        PMID: 32480554     DOI: 10.1071/FP16165

Source DB:  PubMed          Journal:  Funct Plant Biol        ISSN: 1445-4416            Impact factor:   3.101


  12 in total

1.  A spatio temporal spectral framework for plant stress phenotyping.

Authors:  Raghav Khanna; Lukas Schmid; Achim Walter; Juan Nieto; Roland Siegwart; Frank Liebisch
Journal:  Plant Methods       Date:  2019-02-06       Impact factor: 4.993

Review 2.  Tackling microbial threats in agriculture with integrative imaging and computational approaches.

Authors:  Nikhil Kumar Singh; Anik Dutta; Guido Puccetti; Daniel Croll
Journal:  Comput Struct Biotechnol J       Date:  2020-12-29       Impact factor: 7.271

3.  Population-level deep sequencing reveals the interplay of clonal and sexual reproduction in the fungal wheat pathogen Zymoseptoria tritici.

Authors:  Nikhil Kumar Singh; Petteri Karisto; Daniel Croll
Journal:  Microb Genom       Date:  2021-10

4.  A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data.

Authors:  Diana M Pérez-Valencia; María Xosé Rodríguez-Álvarez; Martin P Boer; Lukas Kronenberg; Andreas Hund; Llorenç Cabrera-Bosquet; Emilie J Millet; Fred A van Eeuwijk
Journal:  Sci Rep       Date:  2022-02-24       Impact factor: 4.379

Review 5.  A Review of High-Throughput Field Phenotyping Systems: Focusing on Ground Robots.

Authors:  Rui Xu; Changying Li
Journal:  Plant Phenomics       Date:  2022-06-16

Review 6.  Exploring and exploiting genetics and genomics for sweetpotato improvement: Status and perspectives.

Authors:  Mengxiao Yan; Haozhen Nie; Yunze Wang; Xinyi Wang; Robert Jarret; Jiamin Zhao; Hongxia Wang; Jun Yang
Journal:  Plant Commun       Date:  2022-05-05

7.  PhenoCams for Field Phenotyping: Using Very High Temporal Resolution Digital Repeated Photography to Investigate Interactions of Growth, Phenology, and Harvest Traits.

Authors:  Helge Aasen; Norbert Kirchgessner; Achim Walter; Frank Liebisch
Journal:  Front Plant Sci       Date:  2020-06-18       Impact factor: 6.627

8.  Outdoor Plant Segmentation With Deep Learning for High-Throughput Field Phenotyping on a Diverse Wheat Dataset.

Authors:  Radek Zenkl; Radu Timofte; Norbert Kirchgessner; Lukas Roth; Andreas Hund; Luc Van Gool; Achim Walter; Helge Aasen
Journal:  Front Plant Sci       Date:  2022-01-04       Impact factor: 5.753

9.  Large-scale field phenotyping using backpack LiDAR and CropQuant-3D to measure structural variation in wheat.

Authors:  Yulei Zhu; Gang Sun; Guohui Ding; Jie Zhou; Mingxing Wen; Shichao Jin; Qiang Zhao; Joshua Colmer; Yanfeng Ding; Eric S Ober; Ji Zhou
Journal:  Plant Physiol       Date:  2021-10-05       Impact factor: 8.340

10.  Resources for image-based high-throughput phenotyping in crops and data sharing challenges.

Authors:  Monica F Danilevicz; Philipp E Bayer; Benjamin J Nestor; Mohammed Bennamoun; David Edwards
Journal:  Plant Physiol       Date:  2021-10-05       Impact factor: 8.340

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