Towards a digital twin for optimal field management

Autor: V. Bloch, T. Palosuo, H. Huitu, A. Ronkainen, J. Backman, K. Pussi, A. Suokannas, M. Pastell

Publikováno v: agriRxiv. 2022

Software for a real-time digital twin of crop production system was developed for supporting farming decisions. Software couples the APSIM crop simulation model with data from precision farming equipment, real-time on-field and remote sensing. A fiel

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::faf32018edd9029a4b5fa99fd403b870
https://doi.org/10.31220/agrirxiv.2022.00165

How well do crop modeling groups predict wheat phenology, given calibration data from the target population?

Autor: Allard de Wit, Emmanuelle Gourdain, Chuang Zhao, Bruno Basso, Tommaso Stella, Sebastian Gayler, Qi Jing, Eric Justes, Marco Moriondo, Arne Poyda, Zvi Hochman, Kurt Christian Kersebaum, Neil M.J. Crout, Eckart Priesack, Niels Schütze, Sabine J. Seidel, T. Palosuo, Heidi Horan, Amit Kumar Srivastava, Amir Souissi, Anne Klosterhalfen, Giacomo Trombi, Gerrit Hoogenboom, Vakhtang Shelia, Tobias K. D. Weber, Evelyn Wallor, Daniel Wallach, Yan Zhu, Mohamed Jabloun, Budong Qian, Cécile Garcia, Johannes Wilhelmus Maria Pullens, Xenia Specka, Benjamin Dumont, Qunying Luo, Jing Wang, Camilla Dibari, Peter J. Thorburn, Roberto Ferrise, Bernardo Maestrini, Jørgen E. Olesen, Afshin Ghahramani, Senthold Asseng, Lutz Weihermüller, Marie Launay, Thomas Gaiser, Thilo Streck, Thomas Wöhling, Liujun Xiao, Henrike Mielenz, Steven Hoek, Mingxia Huang, Samuel Buis, Hasti Nariman Zadeh

Publikováno v: 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, Hoogenboom, G, Horan, H, Huang, M, Jabloun, M, Jing, Q, Justes, E, Kersebaum, K C, 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 K D, Weihermüller, L, de Wit, A, Wöhling, T, Xiao, L, Zhao, C, Zhu, Y & Seidel, S J 2021, ' How well do crop modeling groups predict wheat phenology, given calibration data from the target population? ', European Journal of Agronomy, vol. 124, 126195 . https://doi.org/10.1016/j.eja.2020.126195
Eur. J. Agron. 124:126195 (2021)
European Journal of Agronomy 124 (2021)
European Journal of Agronomy
European Journal of Agronomy, 2021, 124, ⟨10.1016/j.eja.2020.126195⟩
European journal of agronomy 124, 126195-(2021). doi:10.1016/j.eja.2020.126195
European Journal of Agronomy, 124

Plant phenology, which describes the timing of plant development, is a major aspect of plant response to environment and for crops, a major determinant of yield. Since climate change is projected to alter crop phenology worldwide, there is a large ef

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dab2cce551cfb9206c4b19a1aee7942
https://pure.au.dk/portal/da/publications/how-well-do-crop-modeling-groups-predict-wheat-phenology-given-calibration-data-from-the-target-population(a98b7040-5452-4c99-91c0-094e0eb879a3).html

The Hot Serial Cereal Experiment for modeling wheat response to temperature: Field experiments and AgMIP-Wheat multi-model simulations

Autor: Roberto C. Izaurralde, Jakarat Anothai, Andrew J. Challinor, Reimund P. Rötter, Jørgen E. Olesen, Curtis D. Jones, Bing Liu, T. Palosuo, Peter J. Thorburn, Kurt Christian Kersebaum, Mohamed Jabloun, Iwan Supit, Frank Ewert, Mikhail A. Semenov, Margarita Garcia-Vila, Claudio O. Stöckle, Benjamin Dumont, Belay T. Kassie, Jordi Doltra, Christian Biernath, Dominique Ripoche, Giacomo De Sanctis, Enli Wang, Elias Fereres, Bruce A. Kimball, Thilo Streck, Gerard W. Wall, L. A. Hunt, Pierre Stratonovitch, Fulu Tao, Jeffrey W. White, Christoph Müller, Bruno Basso, Senthold Asseng, Katharina Waha, Ann-Kristin Koehler, Andrea Maiorano, Ehsan Eyshi Rezaei, Eckart Priesack, Soora Naresh Kumar, Claas Nendel, Gerrit Hoogenboom, Davide Cammarano, David B. Lobell, Joost Wolf, Pierre Martre, Pramod K. Aggarwal, Garry O'Leary, Zhigan Zhao, Michael J. Ottman, Sebastian Gayler, Yan Zhu

Publikováno v: Open Data J. Agricult. Res. 4, 28-34 (2018)
Open Data Journal for Agricultural Research (4), 28-34. (2018)
Open Data Journal for Agricultural Research
Open Data Journal for Agricultural Research, 2018, 4, pp.28-34. ⟨10.7910/DVN/ECSFZG⟩
ODjAR : open data journal for agricultural research, 4, 28-34
ODjAR : open data journal for agricultural research 4 (2018)

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5bee5664bae6c96042d4081165e82bf
https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=54791

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.