| Predicting cover crop biomass by lightweight UAS-based RGB and NIR photography: an applied photogrammetric approach L Roth, B Streit Precision Agriculture 19, 93-114, 2018 | 114 | 2018 |
| Extracting leaf area index using viewing geometry effects—A new perspective on high-resolution unmanned aerial system photography L Roth, H Aasen, A Walter, F Liebisch ISPRS Journal of Photogrammetry and Remote Sensing 141, 161-175, 2018 | 88 | 2018 |
| Assessment of multi-image unmanned aerial vehicle based high-throughput field phenotyping of canopy temperature G Perich, A Hund, J Anderegg, L Roth, MP Boer, A Walter, F Liebisch, ... Frontiers in plant science 11, 150, 2020 | 57 | 2020 |
| PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems L Roth, A Hund, H Aasen Plant Methods 14 (1), 1-21, 2018 | 55 | 2018 |
| High-throughput field phenotyping of soybean: Spotting an ideotype L Roth, C Barendregt, CA Bétrix, A Hund, A Walter Remote Sensing of Environment 269, 112797, 2022 | 29 | 2022 |
| Repeated multiview imaging for estimating seedling tiller counts of wheat genotypes using drones L Roth, M Camenzind, H Aasen, L Kronenberg, C Barendregt, KH Camp, ... Plant Phenomics, 2020 | 27 | 2020 |
| Outdoor plant segmentation with deep learning for high-throughput field phenotyping on a diverse wheat dataset R Zenkl, R Timofte, N Kirchgessner, L Roth, A Hund, L Van Gool, A Walter, ... Frontiers in plant science 12, 774068, 2022 | 26 | 2022 |
| Temporal trends in canopy temperature and greenness are potential indicators of late-season drought avoidance and functional stay-green in wheat J Anderegg, H Aasen, G Perich, L Roth, A Walter, A Hund Field Crops Research 274, 108311, 2021 | 21 | 2021 |
| Phenomics data processing: A plot-level model for repeated measurements to extract the timing of key stages and quantities at defined time points L Roth, MX Rodríguez-Álvarez, F van Eeuwijk, HP Piepho, A Hund Field Crops Research 274, 108314, 2021 | 16 | 2021 |
| Rethinking temperature effects on leaf growth, gene expression and metabolism: Diel variation matters L Kronenberg, S Yates, S Ghiasi, L Roth, M Friedli, ME Ruckle, ... Plant, Cell & Environment 44 (7), 2262-2276, 2021 | 15 | 2021 |
| Image-based phenomic prediction can provide valuable decision support in wheat breeding L Roth, D Fossati, P Krähenbühl, A Walter, A Hund Theoretical and Applied Genetics 136 (7), 162, 2023 | 7 | 2023 |
| Phenomics data processing: extracting dose–response curve parameters from high-resolution temperature courses and repeated field-based wheat height measurements L Roth, HP Piepho, A Hund in silico Plants 4 (1), diac007, 2022 | 6 | 2022 |
| Methodological advances, challenges and perspectives in field phenotyping and its application to forage crops A Hund, U Feuerstein, L Roth, N Kirchgessner, H Aasen, B Studer, ... Improving sown grasslands through breeding and management 24, 295-305, 2019 | 3 | 2019 |
| Frost Damage Index: The Antipode of Growing Degree Days F Tschurr, N Kirchgessner, A Hund, L Kronenberg, J Anderegg, A Walter, ... Plant Phenomics 5, 0104, 2023 | 2 | 2023 |
| High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase L Roth, L Kronenberg, H Aasen, A Walter, J Hartung, F van Eeuwijk, ... bioRxiv, 2022.09. 05.506627, 2022 | 2 | 2022 |
| Single image processing in phenotyping with unmanned aerial systems: Taking advantage of multi-view data L Roth, H Aasen, A Walter, F Liebisch Eucarpia Section Biometrics in Plant Breeding, 2018 | 2 | 2018 |
| PhenoFly sample dataset 2: RGB mapping flight at 28 m L Roth ETH Zurich, 2018 | 2 | 2018 |
| Towards Wheat Yield Estimation in Plant Breeding from Inhomogeneous Lidar Point Clouds Using Stochastic Features T Medic, N Manser, N Kirchgessner, L Roth The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2023 | 1 | 2023 |
| Advances in high-throughput crop phenotyping using unmanned aerial vehicles (UAVs) H Aasen, L Roth Advances in plant phenotyping for more sustainable crop production, 179-200, 2022 | 1 | 2022 |
| Development of drone-based phenotyping methodologies to support physiological plant breeding of wheat and soybean L Roth ETH Zurich, 2021 | 1 | 2021 |
