Bernardo Maestrini

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Researcher DLO, Applied Ecology

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3 Article
1 Conference paper

How well do crop modeling groups predict wheat phenology, given calibration data from the target population?
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. & 34 others, 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., Mar 2021, In: European Journal of Agronomy. 124, 126195.
Research output: Contribution to journal › Article › Academic › peer-review
2 Citations (Scopus)
Multi-model evaluation of phenology prediction for wheat in Australia
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., Hiremath, S., Hoek, S., Horan, H., Hoogenboom, G., Huang, M., Jabloun, M., Jansson, P. E. & 32 others, Jing, Q., Justes, E., Kersebaum, K. C., Launay, M., Lewan, E., Luo, Q., Maestrini, B., Moriondo, M., Olesen, J. E., Padovan, G., Poyda, A., Priesack, E., Pullens, J. W. M., Qian, B., Schütze, N., Shelia, V., Souissi, A., Specka, X., Kumar Srivastava, A., 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., 15 Mar 2021, In: Agricultural and Forest Meteorology. 298, 108289.
Research output: Contribution to journal › Article › Academic › peer-review
Subfield crop yields and temporal stability in thousands of US Midwest fields
Maestrini, B. & Basso, B., 8 May 2021, In: Precision Agriculture.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
Can We Use the Relationship Between Within-Field Elevation and NDVI as an Indicator of Drought-Stress?
Maestrini, B., Brouwer, M., Been, T. & Lotz, L. A. P., 29 Jan 2020, International Symposium on Environmental Software Systems (ISESS 2020): Environmental Software Systems. Data Science in Action. Wageningen: Springer, p. 122-131 (IFIP Advances in Information and Communication Technology ; vol. 554).
Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Academic › peer-review

1 Invited talk
1 Oral presentation

Machine learning surrogates for crop models
Christos Pylianidis (Speaker), Frits van Evert (Contributor), Bernardo Maestrini (Contributor), Sjoukje Osinga (Contributor), Dilli Paudel (Contributor) & Ioannis Athanasiadis (Contributor)
14 Sep 2020 → 18 Sep 2020
Activity: Talk or presentation › Oral presentation › Academic
Metamodels for Crop Growth Models
Bernardo Maestrini (Invited speaker)
11 Nov 2020
Activity: Talk or presentation › Invited talk › Academic

1 Finished

RTM Single Data coherence as a measure of model quality (KB-33-000-016)
Maestrini, B.
1/01/20 → 31/12/20
Project: EZproject

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

Multi-model evaluation of phenology prediction for wheat in Australia

Subfield crop yields and temporal stability in thousands of US Midwest fields

Can We Use the Relationship Between Within-Field Elevation and NDVI as an Indicator of Drought-Stress?

Machine learning surrogates for crop models

Metamodels for Crop Growth Models

RTM Single Data coherence as a measure of model quality (KB-33-000-016)