Bernardo Maestrini

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6 Article
1 Conference paper

Mixing process-based and data-driven approaches in yield prediction
Maestrini, B., Mimić, G., van Oort, P. A. J., Jindo, K., Brdar, S., van Evert, F. K. & Athanasiados, I., Sep 2022, In: European Journal of Agronomy. 139, 126569.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
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
13 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
9 Citations (Scopus)
Potential utilization of satellite remote sensing for field-based agricultural studies
Jindo, K., Kozan, O., Iseki, K., Maestrini, B., van Evert, F. K., Wubengeda, Y., Arai, E., Shimabukuro, Y. E., Sawada, Y. & Kempenaar, C., 3 Nov 2021, In: Chemical and Biological Technologies in Agriculture. 8, 58.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
4 Citations (Scopus)
Subfield crop yields and temporal stability in thousands of US Midwest fields
Maestrini, B. & Basso, B., 2021, In: Precision Agriculture. 22, 6, p. 1749-1767
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
2 Citations (Scopus)

1 Invited talk
1 Oral presentation

Metamodels for Crop Growth Models
Bernardo Maestrini (Invited speaker)
11 Nov 2020
Activity: Talk or presentation › Invited talk › Academic
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

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

Bernardo Maestrini

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Mixing process-based and data-driven approaches in yield prediction

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

Potential utilization of satellite remote sensing for field-based agricultural studies

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

Metamodels for Crop Growth Models

Machine learning surrogates for crop models

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

Bernardo Maestrini

Fingerprint

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