| Hauptseite > Publikationsdatenbank > Exploring the potential of using GPR to investigate the soil-plant continuumof maize crops > print |
| 001 | 1050413 | ||
| 005 | 20260112202639.0 | ||
| 037 | _ | _ | |a FZJ-2026-00183 |
| 100 | 1 | _ | |a Lärm, Lena |0 P:(DE-Juel1)180553 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a 85.Jahrestagung der Deutschen Geophysikalischen Gesellschaft |c Bochum |d 2025-02-24 - 2025-02-27 |w Germany |
| 245 | _ | _ | |a Exploring the potential of using GPR to investigate the soil-plant continuumof maize crops |
| 260 | _ | _ | |c 2025 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
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| 520 | _ | _ | |a The soil-plant continuum plays a vital role in regulating key processes that impact plant per-formance and agricultural productivity. Understanding these processes is becoming increas-ingly important as climate change affects agricultural systems. Diverging techniques likeagrogeophysics and crop science are currently used to investigate individual components ofthe soil-plant continuum at contrasting scales. However, since these components influenceeach other, integrated methods combining methods like ground penetrating radar (GPR)with root imaging and modelling techniques are needed. First, a study examined the impactof row crops like maize on horizontal variability in GPR-derived permittivities and root vol-ume fraction. Factors like soil type, water treatment, and atmospheric conditions were foundto influence this. A statistical analysis method was developed to visualize the trend-correctedspatial permittivity deviation, allowing correlation between permittivity variability and rootvolume fractions. Second, numerical modeling showed roots had a greater impact on GPRsignals than above-ground shoots. A new approach to derive available soil water was pre-sented, demonstrating that neglecting the root phase in petrophysical mixing models over-estimates soil water content. Third, horizontal crosshole GPR-derived soil water contents werecombined with a hydrological model to estimate soil hydraulic parameters for winter wheat.This sequential hydrogeophysical inversion was first used for a one-dimensional averagedcase, then upscaled to estimate pseudo three-dimensional spatially distributed parametersfor a dual-porosity Mualem-van-Genuchten model. |
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| 536 | _ | _ | |a EXC 2070: PhenoRob - Robotics and Phenotyping for Sustainable Crop Production (390732324) |0 G:(BMBF)390732324 |c 390732324 |x 1 |
| 700 | 1 | _ | |a Bauer, Felix |0 P:(DE-Juel1)186730 |b 1 |u fzj |
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| 700 | 1 | _ | |a Klotzsche, Anja |0 P:(DE-Juel1)129483 |b 8 |u fzj |
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