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Dumont, B., Basso, B., Leemans, V., Bodson, B., Destain, J. - P., & Destain, M. - F. (2013). Yield variability linked to climate uncertainty and nitrogen fertilisation. In J. V. Stafford (Ed.), (pp. 427–434). Precision Agriculture ‘13. 9th ECPA – European Conference on Precision Agriculture, 7-11 June 2013, Lleida, Spain. Springer.
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Dumont, B., Basso, B., Leemans, V., Destain, J. P., Bodson, B., & Destain, M. - F. (2013). Yield variability linked to climate uncertainty and nitrogen fertilisation..
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Dumont, B., Basso, B., Destain, J. - P., Bodson, B., & Destain, M. - F. (2014). A Comparison of Optimal Nitrogen Fertilisation Strategies Using Current and Future Stochastically Generated Climatic Conditions..
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Roggero, P. P., Pulina, A., Baldoni, G., Basso, B., Berti, A., Orlandini, S., et al. (2014). IC-FAR: Linking Long Term Observatories with Crop Systems Modeling For a better understanding of Climate Change Impact, and Adaptation Strategies for Italian Cropping Systems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The IC-FAR project (2013-2016), funded by the Italian ministry of University, Research and Education, aims to use datasets from 16 Italian long term agronomic experiments (LTEs) to assess the reliability of different cropping system models over a range of Mediterranean environments and cropping systems. The selected models will be used for scenario and uncertainty analyses vs near-future climate change. The LTEs are located in seven sites: Turin, Padua, Bologna, Ancona, Pisa, Perugia, Foggia. The project’s is linked to international projects such as MACSUR, AgMIP, ANAEE, ESFRI and GRA, and has model developer teams as associate partners. IC-FAR is structured in five WPs. WP1 is focused on building a common dataset and sampling protocols. The field data will be implemented in the WP2 to calibrate, validate and assess the performances of different models across Italian environments. An uncertainty analysis will be performed in relation to the model types, cropping system typologies and climate scenarios (WP3). WP4 and WP5 are focused on capacity building on modeling and on dissemination, including networking with other European LTE platforms (WP4), and to the project coordination (WP5). The next step of IC-FAR will be the design and realization of a special issue summarizing a selection of the most important results from the LTEs, that will be the starting point towards the full implementation of the data sharing policy of this project.
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Sándor, R., Ehrhardt, F., Basso, B., Bellocchi, G., Bhatia, A., Brilli, L., et al. (2016). C and N models Intercomparison – benchmark and ensemble model estimates for grassland production. Advances in Animal Biosciences, 7(03), 245–247.
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