Sabine J. Seidel

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 ")

Peer Reviewed Journal Articles:

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. Frontiers in Plant Science (accepted, in production)

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