Sabine J. Seidel

As a crop scientist  with a high level of understanding  of systemic  relationships  in agroecological systems, I have devoted myself to interdisciplinary research in the fields of sustainable crop science, soil science, modeling, climate change protection and adaption, and novel digital tools. My research interests include:

- Development and testing of innovative diverse (organic) cropping systems (e.g. identify promising partners and field designs in intercropping)
- Quantification of ecosystem (dis)services including yield and greenhouse gases (measurements and modelling)
- Model-based improvement of the understanding of (Gx)G×E×M interactions (focus: water, N, roots) in cropping systems
- Identification of promising crop traits and field designs for future climates
- Short- and long-term soil organic carbon, soil water and nutrient dynamics
- Simulation of the water dynamics from the soil through the soil, root, shoot and stomata into the atmosphere using process-based agro-ecosystem models
- Roots: field observations and modelling root growth with focus on the effect of nutrient deficiency and/or drought stress on root growth
- Digital Farming / Development and application of AI tools in agriculture (e.g. detecting pollinators in images and videos), digital twin development

After studying agricultural sciences at the Technical University of Munich and completing my doctorate on crop modelling and irrigation at the Chair of Hydrology at the Technical University of Dresden, I have been a PostDoc at the Institute of Crop Sciences and Resource Conservation, Crop Sciences Group, University of Bonn since 2016. Since May 2020, I am research group leader at the Chair of Crop Science as part of the PhenoRob cluster of excellence (DFG). The research group entitled “Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models” strengthens PhenoRob especially at the interface of crop modeling, ecology, crop and soil science. I actively participate in the PhenoRob cluster of excellence in four out of six core projects. My research within PhenoRob includes 1) data analytics, simulation of sensor signals (sEIT), and process-based forecasting of root and crop growth, soil dynamics and impacts of potential interventions, 2) robot-based selective weeding for improved biodiversity, 3) optimization of crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models (my research group), 4) phenotyping over scales combining destructive on-site measurements such as root and shoot obervations with UAV-based cameras, and 5) non-destructive diagnosis of nutrient deficiencies using deep learning algorithms. Before leading the research group I worked as a PostDoc at the same Chair in the BMBF funded project “Soil3 - Sustainable Subsoil Management” which aims to explore how and to which degree the subsoil can be managed to secure or even increase plant yields by improving the overall nutrient and water use efficiency of crops.
 


1. DFG Excellence cluster PhenoRob  https://www.phenorob.de/

• Junior Research Group leader  in Core Project CP5: New Field Arrangements  (group title: "Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models")

Crop mixtures offer multiple advantages over traditional sole crops, including production of greater yield on a given piece of land, complementary resource use in time and space among different species; reduction of production risk due to complementarity; improved weed suppression; increased N availability for the subsequent crop due to legumes; decreased nitrate leaching by non-legume cover crops; improved soil fertility, soil organic matter content, and carbon sequestration; increased biodiversity, and maintainance and regeneration of ecosystem services. The numerous processes and mechanisms involved in crop mixtures highlight the need to deal with their complexity by combining concepts from diverse disciplines (agronomy, physiology and ecology) and demand for further information on crop species combination, arrangements and proportion as factors that affect mixtures. Crop simulation models are widely recognized as useful tools that examine cause and effect relationships in crop production. Although existing models can simulate interactions, the degree of precision is questionable because of the general poor understanding of system dynamics within mixed cropping systems. The overall objectives of the Research Group are to i) obtain data using classical and new methods and technologies to gain insights into interactions and mechanisms in crop mixtures, ii) develop new and advanced crop models for crop mixtures, iii) determine optimal field arrangements (e.g. species combination, arrangements and proportion) and management (e.g. sowing, fertilization, harvest) in mixtures for a sustainable and climate-resilient crop production by combining highly monitored experiments and models.

• Core Project CP3: Putting the Soil-Root Zone into Sustainable Crop Production using Sensor Data and Analytics Algorithm

The accurate quantification of soil-root zone processes for application within yield and efficiency analysis is important to increase crop sustainability while conserving global resources. CP3 will address the task of measuring soil-root zones of crops in the field and in controlled environment rhizotron systems with minimally or non-invasive bespoke sensors and robotics. Sensor data will be ground-truthed at sub-millimeter to meter scales, and aligned with above ground sensor and yield component data and analyses in collaboration with CP1 and CP2. The state-of-the-art root-soil zone models will be used initially to support experimental design and interpretation; however, because these models have limited scope with complex phenomena and 4D data, they will be superseded by novel learning and pattern recognition algorithms from DATA. Using an iterative process of supplying sensor and ground-truthed data to analytics, this project aims to assemble the tools to collect and apply soil-root zone data to crop yield predictions and optimize resource inputs on farms in real time.

2.  BonaRes (BMBF) project Soil3 ("Sustainable Subsoil Management ")  https://www.soil3.de/

We presume that nutrient and water uptake from the subsoil can be elevated at given or even increased crop yields when there are attractive options for the plants to invest into subsoil roots, like low physical resistance for roots, hot spots of high microbially facilitated nutrient supply in the subsoil, as well as plant available subsoil water under conditions of seasonal drought stress in the surface soil. I developed process-based model routines to describe the observed impacts of different subsoil management options (tillage, subsoil amendments, rotations with deep rooting precrops) on plant water and nutrient uptake and on yield at field scale. I will be one of the PIs of this project in the next phase which presumably starts in October 2021.

3.  BLE project MIKODU ("Fruchtfolgen für optimierte Nutzung der Bodenressourcen: Mischanbau allorhizer und homorhizer Arten zur komplementären Durchwurzelung des Ober- und Unterbodens ")

4. BLE project smartMaN2agement  ("Standortdifferenzierte Modellierung der N-Dynamiken zur Verringerung der gasförmigen N-Emissionen und weiterer N-Verluste im Pflanzenbau"). Duration: 2023-2026
The focus of the presented project is on the reduction of N2O and NH3 emissions as well as N leaching through predictable, informed and site-adapted management in crop production. The long-term experiments selected for sampling and informing the modelling cover the most important management measures crop
rotation incl. catch crops, tillage incl. mulching of crops that have high amounts of N, as well as mineral and a wide range of organic fertilisation measures. The consistent focus of the project on modelling, using the extensive data sets already available from the long-term trials for the validation of the models, ensures that
the ambitious goal of a model-based and thus comprehensive evaluation is achieved. Furthermore, within the project period, well-founded statements on the influences of the different farming systems, crop rotations, soil tillage and fertilisation events adapted to the respective location and the respective farming
system are to be derived from this evaluation, regionalised to the federal territory and processed for agricultural practice and consulting.

5. EU project IntercropValueES (duration: 2022-2026)  https://intercropvalues.eu/

The goal of IntercropValueES is to exploit the benefits of intercropping to design productive, diversified, resilient, profitable and environmentally friendly agro-
ecological cropping systems less dependent on external inputs than current systems and acceptable to farmers and actors in the agri-food chain. This goal includes analysing the conditions needed to increase yield and economic performance, but also soil health and ecosystem services (ES), as indicators of the value of intercropping. IntercropValueES will then develop a detailed analysis of lock-ins and levers at the value chain level in order to identify credible solutions that can be adopted by farmers and actors of the value chain. The project will implement a participative and multi-actor approach to overcome such barriers and lock-ins identified by the key actors of the local value-chain by providing multiple services of intercropping.

IntercropValueES  aims to exploit the benefits of intercropping to design and manage productive, diversified, resilient, profitable, environmentally friendly cropping systems acceptable to farmers and actors in the agri-food chain. As a multi-disciplinary and multi-actor project, it brings together scientists and local actors representing the food value chain. It includes 27 participants from 15 countries (3 continents) from a wide diversity of organizations and stakeholders.


6. DiARNIKA (Laufzeit: 2024-2027)   https://www.aol.uni-bonn.de/de/forschung/diarnika
 
"Diversifizierter Ackerbau für Risikominderung und nachhaltige Klimaanpassung" 
"Diversified arable farming for risk mitigation and sustainable climate adaptation"
Details and images see also https://www.aol.uni-bonn.de/de/forschung/diarnika

Peer Reviewed Journal Articles:

Behrend, D., Athmann, M., Han, E., Küpper, P. M., Perkons, U., Bauke, S. L., Köpke, U., Kautz, T., Gaiser, T., Seidel, S.J. 202x. Do biopores created by perennial fodder crops improve the growth of subsequent annual crops? A synthesis of multiple field experiments. Field Crops Research 322 (2025) 109687 doi: 10.1016/j.fcr.2024.109687

Seidel, S.J., Ahmadi, S.H., Weihermüller, L., Couëdel, A., Lopez, G., Behrend, D., Kamali, B., Gaiser, T. and Hernández-Ochoa, I.M. 2024. The overlooked effects of environmental impacts on root:shoot ratio in experiments and soil-crop models. Science of the Total Environment (955) 176738 doi: 10.1016/j.scitotenv.2024.176738

Vianna, M., Enders, A., Gaiser, T., Krauss, G., Nguyen, T. H., Rezaei, E.E., Seidel, S.J., Srivastava, A. K., Tewes, A., Webber, H., Ewert, F. The SIMPLACE crop and ecosystem management model. 202x. Book chapter. Publisher: Burleigh Dodds Science Publishing (accepted, in production)

Demie, D.T., Wallach, D., Döring, T.F., Ewert, F., Gaiser, T., Hadir, S., Krauss, G., Paul, M., Hernández-Ochoa, I.M., Vezy, R., Seidel, S.J. 2025. Evaluating a new intercrop model for capturing mixture effects with an extensive intercrop dataset. Agriculture, Ecosystems & Environment, 378  (109302) 

Wallach, D., Buis, S., Seserman, D.-M., Palosuo, T., Thorburn, P., Mielenz, H., Justes, E., Kersebaum, K.-C., Dumont, B., Launay, M. Seidel, S. J. A calibration protocol for soil-crop models. 2024. Environmental Modelling & Software (180), 106147. doi: https://doi.org/10.1016/j.envsoft.2024.106147 

Nguyen, T.H., Lopez, G., Seidel, S.J., Lärm, L., Bauer, F.M., Klotzsche, A., Schnepf, A., Gaiser, T., Hüging, H., Ewert, F.. Multi-year aboveground data of minirhizotron facilities in Selhausen. Sci Data. 2024 Jun 22;11(1):674. doi: 10.1038/s41597-024-03535-2. PMID: 38909019; PMCID: PMC11193711. https://pubmed.ncbi.nlm.nih.gov/38909019/

Drees, L., Demie, D.T., Paul, M.R. Leonhardt, J., Seidel, S.J., Döring, T.F. and Roscher, R. . Data-driven crop growth simulation on time-varying generated images using multi-conditional generative adversarial networks. Plant Methods 20, 93 (2024). doi: 10.1186/s13007-024-01205-3 https://doi.org/10.1186/s13007-024-01205-3
https://plantmethods.biomedcentral.com/articles/10.1186/s13007-024-01205-3

Hadir, S.,Döring, T.F., Justes, E., Demie, D.T., Paul, M., Legner, N., Kemper, R., Gaiser, T., Weedon, O., Ewert, F., Seidel, S.J. Root growth and belowground interactions in spring wheat – faba bean intercrops, 2024. Plant and Soil. doi:10.1007/s11104-024-06742-3  

Hernández-Ochoa, I.M., Gaiser, T., Grahmann, K., Engels, A., Kersebaum, K.-C., Seidel, S.J., Ewert, F. Cross model validation for a diversified cropping system. 2024. European Journal of Agronomy (157). doi: 10.1016/j.eja.2024.127181 

Storm, H., Seidel, S.J., Klingbeil, L., Ewert, F., Vereecken, H., Amelung, W., Behnke, S., Bennewitz, M., Börner, J., Döring, T., Gall, J., Mahlein, A.-K.,  McCool, C., Rascher, U., Wrobel, S., Schnepf, A., Stachniss, C., Kuhlmann, H. 2024. Research priorities to leverage smart digital technologies for sustainable crop production. European Journal of Agronomy (156) 127178 https://doi.org/10.1016/j.eja.2024.127178. 

Gorooei, A., Aynehband, A., Behrend, D., Seidel, S.J., Srivastava, A.K., Rahnama, A., Gaiser, T. 2024. Short-Term Response of Soil Organic Carbon Indices to Different Farming Strategies and Crop Rotation Systems in a Semiarid Warm Region. Applied and Environmental Soil Science, doi: 10.1155/2024/8594691

Paul, M.R., Demie, D.T., Seidel, S.J., Döring, T. 2024. Evaluation of multiple spring wheat cultivars in diverse intercropping systems. European Journal of Agronomy (152) 127024

Lärm, L., Bauer, F.M., Hermes, N. et al. Multi-year belowground data of minirhizotron facilities in Selhausen. Sci Data 10, 672 (2023). https://doi.org/10.1038/s41597-023-02570-9 https://www.nature.com/articles/s41597-023-02570-9

Bauke, S. L.; Seidel, S. J.; Athmann, M.; Berns, A. E.; Braun, M.; Gocke, M. I.; Guigue, J.; Kautz, T.; Kögel-Knabner, I.; Ohan, J.; Rillig, M.; Schloter, M.; Schmittmann, O.; Schulz, S.; Uhlig, D.; Schnepf, A. & Amelung, W. Short-term effects of subsoil management by strip-wise loosening and incorporation of organic material. Soil and Tillage Research, 2024, 236, 105936

Gocke, M. I.; Guigue, J.; Bauke, S. L.; Barkusky, D.; Baumecker, M.; Berns, A. E.; Hobley, E.; Honermeier, B.; Kögel-Knabner, I.; Koszinski, S.; Sandhage-Hofmann, A.; Schmidhalter, U.; Schneider, F.; Schweitzer, K.; Seidel, S.; Siebert, S.; Skadell, L. E.; Sommer, M.; von Tucher, S.; Don, A. & Amelung, W. Interactive effects of agricultural management on soil organic carbon accrual: A synthesis of long-term field experiments in Germany, Geoderma, 2023, 438, 116616 

Skadell, L.E., Schneider, F., Gocke, M.I., Guigue, J., Amelung, W., Bauke, S.L., Hobley, E.U., Barkusky, D., Honermeier, B., Kögel-Knabner, I., Schmidhalter, U., Schweitzer, K., Seidel, S.J., Siebert, S., Sommer, M., Vaziritabar, Y., Don, A., 2023. Twenty percent of agricultural management effects on organic carbon stocks occur in subsoils – Results of ten long-term experiments. Agriculture, Ecosystems & Environment : an internat. journal for scientific research on the relationship of agriculture and food production to the biosphere 356. doi: 10.1016/j.agee.2023.108619

Wallach, D., Palosuo, T., Thorburn, P. … Seidel, S. J. Proposal and extensive test of a calibration protocol for crop phenology models. Agron. Sustain. Dev. 43, 46 (2023). doi: 10.1007/s13593-023-00900-0 

Paul, Madhuri Rani; Dereje T Demie; Sabine J. Seidel; Thomas Döring. Effects of spring wheat / faba bean mixtures on early crop development. Plant and Soil. doi: 10.1007/s11104-023-06111-6

Enders, A., Vianna, M., Gaiser, T., Krauss, G., Webber, H., Srivastava, A.K.,, Seidel, S.J., Tewes, A., Rezaei, E.E., Ewert, F., SIMPLACE – A versatile modelling and simulation framework for sustainable crops and agroecosystems, in silico Plants, 2023;, diad006, https://doi.org/10.1093/insilicoplants/diad006Christopher Just, Martin Armbruster, Dietmar Barkusky, Michael Baumecker, Michael Diepolder, Thomas F. Döring, Lorenz Heigl, Bernd Honermeier, Melkamu Jate, Ines Merbach, Constanze Rusch, David Schubert, Franz Schulz, Kathlin Schweitzer, Sabine Seidel, Michael Sommer, Heide Spiegel, Ulrich Thumm, Peer Urbatzka, Jörg Zimmer, Ingrid Kögel-Knabner, Martin Wiesmeier, Soil organic carbon sequestration in agricultural long-term field experiments as derived from particulate and mineral-associated organic matter, Geoderma (434:116472) doi: 10.1016/j.geoderma.2023.116472.  

Khatab Abdalla, Thomas Gaiser, Sabine Julia Seidel, Johanna Pausch. 2023. Soil organic carbon and nitrogen in aggregates in response to over seven decades of farmyard manure application. Journal of Plant Nutrition and Soil Science 2023 (1-6) doi: 10.1002/jpln.202300062 
Shahin Solgi, Seyed Hamid Ahmadi, Sabine J. Seidel. Remote sensing of canopy water status of the irrigated winter wheat fields and the paired anomaly analyses on the spectral vegetation indices and grain yields. Agricultural Water Management. 2023 (280): 108226. doi: 10.1016/j.agwat.2023.108226 

Lopez, G., Ahmadi, S.H., Amelung, W., Athmann, M., Ewert, F., Gaiser, T., Gocke, M.I., Kautz, T., Postma, J., Rachmilevitch, S., Schaaf, G., Schnepf, A., Stoschus, A., Watt, M., Yu, P. and Seidel, S.J. Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops. Frontiers in Plant Science. 2023.13:1067498. doi: 10.3389/fpls.2022.1067498

Feike, Til, Frei, Michael, Germeier, Christoph, Herrmann, Antje, Hülsbergen, Kurt-Jürgen, Kaul, Hans-Peter, Komainda, Martin, Kottmann, Lorenz, Möller, Kurt, Nendel, Claas, Pasda, Gregor, Pekrun, Carola, Seidel, Sabine, Stützel, Hartmut and Wrage-Mönnig, Nicole. “Wissenschaftliche Grundlagen zum Strategiediskurs für einen nachhaltigen Pflanzenbau” Die Bodenkultur: Journal of Land Management, Food and Environment, vol.73, no.3, 2022, pp.153-192. doi: 10.2478/boku-2022-0011

Abdalla, K., Sun, Y., Zarebanadkouki, M., Gaiser, T., Seidel, S. and Pausch, J. Long-term continuous farmyard manure application increases soil carbon when combined with mineral fertilizers due to lower priming effects, Geoderma. 2022. 116216. https://doi.org/10.1016/j.geoderma.2022.116216

Hernández-Ochoa, I.M., Gaiser, T., Kersebaum, KC. Webber, H., Seidel, S.J., Grahmann, K. and Ewert, F. Model-based design of crop diversification through new field arrangements in spatially heterogeneous landscapes. A review. Agron. Sustain. Dev. 42, 74. 2022. https://doi.org/10.1007/s13593-022-00805-4

Seidel, S. J.,  Thomas Gaiser, Amit Kumar Srivastava,  Daniel Leitner,  Oliver Schmittmann, Miriam Athmann, Timo Kautz, Julien Guigue, Frank Ewert and Andrea Schnepf. Simulating root growth as a function of soil strength and yield with a field-scale crop model coupled with a 3D architectural root model. 2022. Frontiers in Plant Science, doi: 10.3389/fpls.2022.865188

Demie, D.T., Döring, T.F., Finckh, M.R., Van Der Werf, W., Enjalbert, J., Seidel, S. J. Mixture x Genotype
Effects in Cereal/Legume Intercropping: A Review. 2022. Frontiers in Plant Science, doi: 10.3389/fpls.2022.846720

Nguyen, T. H., Langensiepen, M., Hüging, H., Gaiser, T., Seidel, S. J. and Ewert, F. Expansion and evaluation of two coupled root-shoot models in simulating CO2 and H2O fluxes and growth of maize. 2021. Vadose Zone Journal  doi: 10.1002/vzj2.20181

Wallach, D., Palosuo, T., Thorburn, P., Hochman, Z., Gourdain, E., Andrianasolo, F., Asseng, S., Basso, B., Buis, S., Crout, N., Dibari, C., Dumont, B., Ferrise, R., Gaiser, T., Garcia, C., Gayler, S., Ghahramani, A., Hiremath, S., Hoek, S., Horan, H., Hoogenboom, G., Huang, M., Jabloun, M., Jansson, P.-E., Jing, Q., Justes, E., Kersebaum, K.C., Klosterhalfen, A., Launay, M., Lewan, E., Luo, Q., Maestrini, B., Mielenz, H., Moriondo, M., Nariman Zadeh, H., Padovan, G., Olesen, J.E., Poyda, A., Priesack, E., Pullens, J.W.M., Qian, B., Schütze, N., Shelia, V., Souissi, A., Specka, X., Srivastava, A.K., Stella, T., Streck, T., Trombi, G., Wallor, E., Wang, J., Weber, T.K.D., Weihermüller, L., de Wit, A., Wöhling, T., Xiao, L., Zhao, C., Zhu, Y., Seidel, S.J., The chaos in calibrating crop models: lessons learned from a multi-model calibration exercise, Environmental Modelling and Software. 2021 (145), 105206. https://doi.org/10.1016/j.envsoft.2021.105206.

Seidel, S.J., Gaiser, T., Ahrends, H.E., Hüging, H., Siebert, S., Bauke, S.L., Gocke, M.I., Koch, M., Schweitzer, K. Schaaf, G., Ewert, F. Crop response to P fertilizer omission under a changing climate – experimental and modeling results over 115 years of a long-term fertilizer experiment. Field Crops Research. 2021 (268) 108174. doi: 10.1016/j.fcr.2021.108174

Hadir, S., Gaiser, T., Hüging, H., Athmann, M., Pfarr, D., Kemper, R., Ewert, F., Seidel, S. J. Sugar beet shoot and root phenotypic plasticity to nitrogen, phosphorus, potassium and lime omission. Agriculture 2021. 11, 21. doi: 10.3390/agriculture1101002

Wallach, D., Palosuo, T., Thorburn, P., Hochman, Z., Andrianasolo, F., Asseng, S., Basso, B., Buis, S., Crout, N., Dumont, B., Ferrise, R., Gaiser, T., Gayler, S., Hireman, S., Hoek, S., Horan, H., Hoogenboom, G., Huang, M., Jabloun, M., Jasson, P.-E., Jing, Q., Justes, E., Kersebaum, C.K., Launay, M., Lewan, E., Luo, Q., Maestrini, B., Moriondo, M., Padovan, G., Olesen, J.E., Poyda, A., Priesack, E., Pullens, J.W.M, Qian, B., Schütze, N., Shelia, V., Souissi, A., Specka, X., Srivastava, A.K., Stella, T., Streck, T., Trombi, G., Wallor, E., Wang, J., Weber, T.H.D., Weihermüller, L., de Wit, A., Wöhling, T., Xiao, L., Zhao, C., Zhu, Y., Seidel, S. J. Multi-model evaluation of phenology prediction for wheat in Australia. Agricultural and Forest Meteorology. 2021 (298-299) 108289. doi: 10.1016/j.agrformet.2020.108289

Wallach, D., Palosuo, T., Thorburn, P., Gourdain, E., Asseng, S., Basso, B., Buis, S., Crout, N., Dibari, C., Dumont, B., Ferrise, R., Gaiser, T., Garcia, C., Gayler, S., Ghahramani, A., Hochman, Z., Hoek, S., Horan, H., Hoogenboom, G., Huang, M., Jabloun, M., Jing, Q., Justes, E., Kersebaum, C.K., Klosterhalfen, A., Launay, M., Luo, Q., Maestrini, B., Mielenz, H., Moriondo, M., Nariman Zadeh, H., Olesen, J.E., Poyda, A., Priesack, E., Pullens, J.W.M, Qian, B., Schütze, N., Shelia, V., Souissi, A., Specka, X., Srivastava, A.K., Stella, T., Streck, T., Trombi, G., Wallor, E., Wang, J., Weber, T.H.D., Weihermüller, L., de Wit, A., Wöhling, T., Xiao, L., Zhao, C., Zhu, Y., Seidel, S. J. How well do crop modeling groups predict wheat phenology, given calibration data from the target population? European Journal of Agronomy. 2021 (124) 126195. doi: 10.1016/j.eja.2020.126195

Ahrends, H., Eugster, W., Siebert, S., Ewert, F., Rezaei, E., Hüging, H., Döring, T., Rueda-Ayala, V., Seidel, S., Gaiser, T. 2020. Nutrient supply affects the stability of major European crops -a 50-year study. Environmental Research Letters. 2021 (16). doi: 10.1088/1748-9326/abc849

Yi, J., Krusenbaum, L., Unger, P., Hüging, H., Seidel, S., Schaaf, G. and Gall J. Deep learning for non-invasive diagnosis of nutrient deficiencies in sugar beet using RGB images. Sensors. 2020, 20(20), 5893. doi:10.3390/s20205893 
see video at DIGICROP2020 conference. link

Ittner, S., Gerdes, H., Athmann, M., Bauke, S. L., Gocke, M., Guigue, J., Jaiswal, S., Kautz, T., Schmittmann, O., Schulz, S., Seidel, S. J. 2020. The impact of subsoil management on the delivery of ecosystem services. BonaRes Series. DOI: 10.20387/bonares-bszh-qbkn

Seidel, S.J., Gaiser, T., Kautz, T., Bauke, S.L., Amelung, W., Barfus, K., Ewert, F. and Athmann, M. Estimation of the impact of precrops and climate variability on soil depth-differentiated spring wheat growth and water, nitrogen and phosphorus uptake. Soil and Tillage Research. 2019, (195) 104427. doi: 10.1016/j.still.2019.104427

Kumar, A., Shahbaz, M., Koirala, M., Blagodatskaya, E., Seidel, S.J., Kuzyakov, Y. and Pausch, J. Root trait plasticity and plant nutrient acquisition in phosphorus limited soil. J. Plant Nutr. Soil Sci. 2019. doi: 10.1002/jpln.201900322

Koch, M., Guppy, Ch., Amelung, W., Gypser, S., Bol, R., Seidel, S., Siebers, N. Insights into 33phosphorus utilization from Fe- and Al-hydroxides in Luvisol and Ferralsol subsoils. Soil Research. 2019, 57(5) 447-458. doi: 10.1071/SR18223

Seidel, S. J., Barfus, K., Gaiser, T., Nguyen, T. H. and Lazarovitch, N. The influence of climate variability, soil conditions and sowing date on simulation-based crop coefficient curves and irrigation water demand. Agricultural Water Management. 2019 (221) 73-83. doi: 10.1016/j.agwat.2019.02.007

Maharjana, G. R., Prescher, A.-K., Nendel, C., Ewert, F., Mboh, C. M., Gaiser, T. and Seidel, S. J. Approaches to model the impact of tillage implements on soil physical and nutrient properties in different agro-ecosystem models. Soil and Tillage Research. 2018 (180) 210-221. doi: 10.1016/j.still.2018.03.009

Seidel, S. J., Palosuo, T., Thorburn, P. and D. Wallach. Towards improved calibration of crop models – where are we now and where should we go? European Journal of Agronomy 94:25-35, 2018. doi: 10.1016/j.eja.2018.01.006 link

A. Hartmann, J. Simunek, M. Kwame Aidoo, S. J. Seidel and N. Lazarovitch. Implementation and Application of a Root Growth Module in HYDRUS. Vadose Zone Journal, 2017. doi: 10.2136/vzj2017.02.0040

F. Schneider, A, Don, I. Hennings, O. Schmittmann and S. J. Seidel. The effect of deep tillage on crop yield – What do we really know? Soil and Tillage Research 174:193-204, 2017. doi: 10.1016/j.still.2017.07.005

S. J. Seidel, S. Werisch, N. Schütze, and H. Laber. Impact of irrigation on plant growth and development of white cabbage. Agricultural Water Management 187:99–111, 2017. doi: 10.1016/j.agwat.2017.03.011

Durand, J.-L., K. Delusca, K. Boote, J. Lizaso, R. Manderscheid, H.J. Weigel, A.C. Ruane, C. Rosenzweig, J. Jones, L. Ahuja, S. Anapalli, B. Basso, C. Baron, P. Bertuzzi, C. Biernath, D. Derying, F. Ewert, T. Gaiser, S. Gayler, F. Heinlein, K.C. Kersebaum, Soo-Hyung Kim, C. Müller, C. Nendel, A. Olioso, E. Priesack, J. R. Villegas, D. Ripoche, R. P. Rötter, S. J. Seidel, A. Srivastava, F. Tao, D. Timlin, T. Twine, E. Wang, H. Webber, Z. Zhao. How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield? European Journal of Agronomy, 67-75, 2018. doi: 10.1016/j.eja.2017.01.002.

S. J. Seidel, S. Rachmilevitch, N. Schütze and N. Lazarovitch. Modelling the impact of drought and heat stress on common bean with two different photosynthesis model approaches. Environmental Modelling \& Software 81:111-121, 2016. doi: 10.1016/j.envsoft.2016.04.001.

S. J. Seidel, S. Werisch, K. Barfus, M. Wagner, N. Schütze, and H. Laber. Field evaluation of irrigation scheduling strategies using a mechanistic crop growth model. Irrigation and Drainage. 65(2):214-223, 2016.doi: 10.1002/ird.1942. link ( Winner of the ‘Best Paper Award 2017’ of the ICID Journal)

M. Wagner, S. J. Seidel, S. Werisch, K. Barfuss and N. Schütze. Integrierte Modellierung von Wasserdargebot und Wassernachfrage am Beispiel der Bewässerungslandwirtschaft in Sachsen [Integrated modelling of water supply and water demand using the example of irrigation farming in Saxony]. Hydrologie und Wasserbewirtschaftung. 1(60):22-37, 2016. doi: 10.5675/HyWa\_2016,1\_2.

M. Wagner, S. J. Seidel and N. Schütze. Irrigation water demand of common bean on field and regional scale under varying climatic conditions. Meteorologische Zeitschrift, 2015. doi: 10.1127/metz/2014/0698.

S. J. Seidel, N. Schütze, M. Fahle, J.-C. Mailhol, and P. Ruelle. Optimal irrigation scheduling, irrigation control and drip line layout to increase water productivity and profit in subsurface drip irrigated agriculture. Irrigation and Drainage, 64:501-518, 2015. doi: 10.1002/ird.1926.

S. Kloss, J. Grundmann, S. J. Seidel, S. Werisch, J. Trümmer, U. Schmidhalter, and  N. Schütze. Investigation of deficit irrigation strategies combining SVAT-modeling, optimization and experiments. Environmental Earth Sciences, 72(12):1866-6280, 2014. doi: 10.1007/s12665-014-3463-7.

S. Walser, N. Schütze, M. Guderle, S. Liske, and U. Schmidhalter. Evaluation of the  transferability of a SVAT model? Results from field and greenhouse applications. Irrigation and Drainage, 60(S1):59-70, 2011. doi: 10.1002/ird.669.

J.C. Mailhol, P. Ruelle, S. Walser, N. Schütze, and C. Dejean. Analysis of AET and  yield predictions under surface and buried drip irrigation systems using the Crop Model PILOTE and Hydrus-2D. Agricultural Water Management, 98(6):1033-1044, 2011. doi: 10.1016/j.agwat.2011.01.014