Search Results - "Confalonieri, R"

CoSMo: A simple approach for reproducing plant community dynamics using a single instance of generic crop simulators by Confalonieri, R.

“…•A new model for plant community dynamics and productivity is presented.•The approach makes use of a single instance of whatever crop simulator.•Species…”
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Comparison of sensitivity analysis techniques: A case study with the rice model WARM by Confalonieri, R., Bellocchi, G., Bregaglio, S., Donatelli, M., Acutis, M.

“…The considerable complexity often included in biophysical models leads to the need of specifying a large number of parameters and inputs, which are available…”
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Comparison of leaf area index estimates by ceptometer and PocketLAI smart app in canopies with different structures by Francone, C., Pagani, V., Foi, M., Cappelli, G., Confalonieri, R.

“…•A recently proposed smartphone app for leaf area index estimation is tested.•The app is compared to the widespread and reliable AccuPAR ceptometer.•The…”
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Model simplification and development via reuse, sensitivity analysis and composition: A case study in crop modelling by Stella, T., Frasso, N., Negrini, G., Bregaglio, S., Cappelli, G., Acutis, M., Confalonieri, R.

“…Crop models, like many representations of environmental processes, tend to be over-parameterised. A redesign of the SUCROS family of crop models, largely…”
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Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods by Confalonieri, R., Foi, M., Casa, R., Aquaro, S., Tona, E., Peterle, M., Boldini, A., De Carli, G., Ferrari, A., Finotto, G., Guarneri, T., Manzoni, V., Movedi, E., Nisoli, A., Paleari, L., Radici, I., Suardi, M., Veronesi, D., Bregaglio, S., Cappelli, G., Chiodini, M.E., Dominoni, P., Francone, C., Frasso, N., Stella, T., Acutis, M.

“…•An app for smartphone for indirect LAI estimates is proposed.•It uses sensors and processing power normally present in modern mobile phones.•The algorithm is…”
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WOFOST-GTC: A new model for the simulation of winter rapeseed production and oil quality by Gilardelli, C., Stella, T., Frasso, N., Cappelli, G., Bregaglio, S., Chiodini, M.E., Scaglia, B., Confalonieri, R.

“…•WOFOST-GTC is a new model to simulate production and oil quality of winter rapeseed.•The dynamic distribution of photosynthetic tissues within the canopy is…”
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A proposal of an indicator for quantifying model robustness based on the relationship between variability of errors and of explored conditions by Confalonieri, R., Bregaglio, S., Acutis, M.

“…The evaluation of biophysical models is usually carried out by estimating the agreement between measured and simulated data and, more rarely, by using indices…”
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Are advantages from the partial replacement of corn with second-generation energy crops undermined by climate change? A case study for giant reed in northern Italy by Cappelli, G., Yamaç, S.S., Stella, T., Francone, C., Paleari, L., Negri, M., Confalonieri, R.

“…Among non-food energy crops, giant reed (Arundo donax L.) represents a promising opportunity to reduce the fossil fuel dependency of Mediterranean countries…”
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Quantifying plasticity in simulation models by Confalonieri, R., Bregaglio, S., Acutis, M.

“…► Plasticity as model aptitude to change parameter relevance under diverse conditions. ► WOFOST was the most plastic. ► Sensitivity analysis demonstrated its…”
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Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean by Richter, G.M., Acutis, M., Trevisiol, P., Latiri, K., Confalonieri, R.

“…Complex crop models with large parameter sets and high temporal resolution need a parsimonious screening method to identify the most important parameters for…”
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A software component implementing a library of models for the simulation of pre-harvest rice grain quality by Cappelli, G., Bregaglio, S., Romani, M., Feccia, S., Confalonieri, R.

“…•Grain quality is key to determine nutritional and economic value of rice production.•We develop a framework-independent software component for rice quality…”
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A generic framework for evaluating hybrid models by reuse and composition – A case study on soil temperature simulation by Donatelli, M., Bregaglio, S., Confalonieri, R., De Mascellis, R., Acutis, M.

“…We evaluate modelling solutions built composing different modelling approaches. Modelling of soil temperature was the case study, evaluating modelling…”
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ISIde: A rice modelling platform for in silico ideotyping by Paleari, L., Bregaglio, S., Cappelli, G., Movedi, E., Confalonieri, R.

“…•We develop a modelling platform explicitly dedicated to in silico ideotyping studies.•Ideotypes can be improved for resistance/tolerance traits to…”
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District specific, in silico evaluation of rice ideotypes improved for resistance/tolerance traits to biotic and abiotic stressors under climate change scenarios by Paleari, L., Cappelli, G., Bregaglio, S., Acutis, M., Donatelli, M., Sacchi, G. A., Lupotto, E., Boschetti, M., Manfron, G., Confalonieri, R.

“…Using crop models as supporting tools for analyzing the interaction between genotype and environment represents an opportunity to identify priorities within…”
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A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration by Makowski, D., Asseng, S., Ewert, F., Bassu, S., Durand, J.L., Li, T., Martre, P., Adam, M., Aggarwal, P.K., Angulo, C., Baron, C., Basso, B., Bertuzzi, P., Biernath, C., Boogaard, H., Boote, K.J., Bouman, B., Bregaglio, S., Brisson, N., Buis, S., Cammarano, D., Challinor, A.J., Confalonieri, R., Conijn, J.G., Corbeels, M., Deryng, D., De Sanctis, G., Doltra, J., Fumoto, T., Gaydon, D., Gayler, S., Goldberg, R., Grant, R.F., Grassini, P., Hatfield, J.L., Hasegawa, T., Heng, L., Hoek, S., Hooker, J., Hunt, L.A., Ingwersen, J., Izaurralde, R.C., Jongschaap, R.E.E., Jones, J.W., Kemanian, R.A., Kersebaum, K.C., Kim, S.-H., Lizaso, J., Marcaida, M., Müller, C., Nakagawa, H., Naresh Kumar, S., Nendel, C., O’Leary, G.J., Olesen, J.E., Oriol, P., Osborne, T.M., Palosuo, T., Pravia, M.V., Priesack, E., Ripoche, D., Rosenzweig, C., Ruane, A.C., Ruget, F., Sau, F., Semenov, M.A., Shcherbak, I., Singh, B., Singh, U., Soo, H.K., Steduto, P., Stöckle, C., Stratonovitch, P., Streck, T., Supit, I., Tang, L., Tao, F., Teixeira, E.I., Thorburn, P., Timlin, D., Travasso, M., Rötter, R.P., Waha, K., Wallach, D., White, J.W., Wilkens, P., Williams, J.R., Wolf, J., Yin, X., Yoshida, H., Zhang, Z., Zhu, Y.

“…•Statistical models were developed to emulate ensembles of process-based crop models.•They describe the between-crop model variability of the simulated yield…”
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Reimplementation and reuse of the Canegro model: From sugarcane to giant reed by Stella, T., Francone, C., Yamaç, S.S., Ceotto, E., Pagani, V., Pilu, R., Confalonieri, R.

“…•The DSSAT-Canegro model was re-implemented in a framework-independent component.•This reimplementation enhances model reuse and extension.•A new model for…”
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Sensitivity Analysis and Investigation of the Behaviour of the UTOPIA Land-Surface Process Model: A Case Study for Vineyards in Northern Italy by Francone, C., Cassardo, C., Richiardone, R., Confalonieri, R.

“…We used sensitivity-analysis techniques to investigate the behaviour of the land-surface model UTOPIA while simulating the micrometeorology of a typical…”
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A software component to compute agro-meteorological indicators by Confalonieri, R., Bellocchi, G., Donatelli, M.

“…ClimIndices is a software component to compute agro-meteorological indicators on yearly series of daily weather data. The component is released as .NET2…”
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The development of a methodology using fuzzy logic to assess the performance of cropping systems based on a case study of maize in the Po Valley by Carozzi, M., Bregaglio, S., Scaglia, B., Bernardoni, E., Acutis, M., Confalonieri, R.

“…The development of tools for evaluating the sustainability of cropping systems is fundamental to providing reliable information on crop performance. In this…”
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Analysis and modelling of water and near water temperatures in flooded rice ( Oryza sativa L.) by Confalonieri, R., Mariani, L., Bocchi, S.

“…The knowledge of micrometeorological conditions in flooded rice fields is crucial for better modelling the behaviour of the crop in mid and high latitudes,…”
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