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Preprints
https://doi.org/10.5194/egusphere-2024-2082
https://doi.org/10.5194/egusphere-2024-2082
05 Aug 2024
 | 05 Aug 2024

Closing the phenotyping gap with non-invasive belowground field phenotyping

Guillaume Blanchy, Waldo Deroo, Tom De Swaef, Peter Lootens, Paul Quataert, Isabel Roldán-Ruíz, and Sarah Garré

Abstract. Breeding climate-robust crops is one of the needed pathways for adaptation to the changing climate. To speed up the breeding process, it is important to understand how plants react to extreme weather events such as drought or waterlogging in their production environment, i.e. under field conditions in real soils. Whereas a number of techniques exist for above-ground field phenotyping, simultaneous non-invasive belowground phenotyping remains difficult. In this paper, we present the first dataset of the new HYDRAS open access field phenotyping infrastructure, bringing electrical resistivity tomography, alongside drone imagery and environmental monitoring, to a technology readiness level closer to what breeders and researchers need. This paper investigates whether electrical resistivity tomography (ERT) provides sufficient precision and accuracy to distinguish between belowground plant traits of different genotypes of the same crop species. The proof-of-concept experiment was conducted in 2023 with three distinct soybean genotypes known for their contrasting reactions to drought stress. We illustrate how this new infrastructure addresses the issues of depth resolution, automated data processing, and phenotyping indicator extraction. The work shows that electrical resistivity tomography is ready to complement drone-based field phenotyping techniques to accomplish whole plant high-throughput field phenotyping.

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Journal article(s) based on this preprint

24 Jan 2025
Closing the phenotyping gap with non-invasive belowground field phenotyping
Guillaume Blanchy, Waldo Deroo, Tom De Swaef, Peter Lootens, Paul Quataert, Isabel Roldán-Ruíz, Roelof Versteeg, and Sarah Garré
SOIL, 11, 67–84, https://doi.org/10.5194/soil-11-67-2025,https://doi.org/10.5194/soil-11-67-2025, 2025
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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This work uses automated electrical resistivity tomography (ERT) for belowground field...
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