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AbioticDamage

AbioticDamage
AbioticDamage is a software component implementing models for the impact of temperature shocks, atmospheric ozone concentration, frost, salinity and lodging on crops productivity


Product Manager: Roberto Confalonieri
Online Code doc: http://download.cassandralab.com/abioticdamage/abioticdamage_codedoc/UNIMI.AbioticDamage_codedoc.html
Online Help: http://download.cassandralab.com/abioticdamage/abioticdamage_help/Abstract.html
Application file: request a download link providing your email below.
2019 - Crop Science, 59, 1155-1164.
Analysis and modelling of processes involved with salt tolerance and rice.
Tartarini, S., Paleari, L., Movedi, E., Sacchi, G.A., Nocito, F.F., Confalonieri, R.
2019 - Agricultural Systems, 168, 181-190
A high-resolution, integrated system for rice yield forecasting at district level.
Pagani, V., Guarneri, T., Busetto, L., Ranghetti, L., Boschetti, M., Movedi, E., Campos-Taberner, M., Garcia-Haro, F.J., Katsantonis, D., Stavrakoudis, D., Ricciardelli, E., Romano, F., Holecz, F., Collivignarelli, F., Granell, C., Casteleyn, S., Confalonieri, R.
2019 - Scientific Reports, 9, 9258
Quantifying uncertainty due to stochastic weather generators in climate change impact studies
Vesely, F.M., Paleari, L., Movedi, E., Bellocchi, G., Confalonieri, R.
2018 - Ecological Modelling, 368, 1-14.
Sensitivity of WOFOST-based modelling solutions to crop parameters under climate change.
Gilardelli, C., Confalonieri, R., Cappelli, G., Bellocchi, G.
2017 - European Journal of Agronomy, 89, 97-106
Improving cereal yield forecast in Europe - the impact of weather extremes.
Pagani, V., Guarneri, T., Fumagalli, D., Movedi, E., Testi, L., Klein, T., Calanca, P., Villalobos, F., Lopez-Bernal, A., Niemeyer, S., Bellocchi, G., Confalonieri, R.
2017 - Scientific Reports, 7:14858
Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments.
Hasegawa, T., Li, T., Yin, X., Zhu, Y., Boote, K., Baker, J. ... Confalonieri, R. ... Wallach, D., Wang, Y., Wilson, L.T., Yang, L., Yang, Y., Yoshida, H., Zhang, Z., Zhu, J.
2017 - Agricultural Systems, 154, 45-52
Forecasting sugarcane yields using agro-climatic indicators and Canegro model: a case study in the main production region in Brazil.
Pagani, V., Stella, T., Guarneri, T., Finotto, G., van den Berg, M., Marin, F.R., Acutis, M., Confalonieri, R.
2017 - Global Change Biology, 23, 4651-4662.
Surfing parameter hyperspaces under climate change scenarios to design future rice ideotypes.
Paleari, L., Movedi, E., Cappelli, G., Wilson, L.T., Confalonieri, R.
2017 - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10, 5423-5441.
Downstream services for rice crop monitoring in Europe: from regional to local scale.
Busetto, L., Casteleyn, S., Granell, C., Pepe, M., Crema, A., Barbieri, M., Campos-Taberner, M., Casa, R., Collivignarelli, F., Confalonieri, R., García-Haro, J. ... Movedi, E., Nutini, F. ... Boschetti, M.
2016 - Computers and Electronics in Agriculture, 128, 46-49
ISIde: a rice modelling platform for in silico ideotyping.
Paleari, L., Bregaglio, S., Cappelli, G., Movedi, E., Confalonieri, R.
2016 - Environmental Modelling & Software, 85, 332-341
A taxonomy-based approach to shed light on the babel of mathematical models for rice simulations.
Confalonieri, R., Bregaglio, S., Adam, M., Ruget, F., Li, T., Hasegawa, T., Yin, X., Zhu, Y., Boote, K., Buis, S., Fumoto, T., Gaydon, D., Lafarge, T., Marcaida, M., Nakagawa, H., Ruane, A.C., Singh, B., Singh, U., Tang, L., Tao, F., Fugice, J., Yoshida, H., Zhang, Z., Wilson, L.T., Baker, J., Yang, Y., Masutomi, Y., Wallach, D., Acutis, M., Bouman, B.
2015 - Climatic Change, 132, 661-675
District specific, in silico evaluation of rice ideotypes improved for resistance/tolerance traits to biotic and abiotic stressors under climate change scenarios.
Paleari, L., Cappelli, G., Bregaglio, S., Acutis, M., Donatelli, M., Sacchi, G.A., Lupotto, E., Boschetti, M., Manfron, G., Confalonieri, R.
2015 - Agricultural and Forest Meteorology, 214-215, 483-493
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration.
Makowski, D., Asseng, S., Ewert, F., ... , Confalonieri, R., ... , Zhu, Y.
2015 - Biomass & Bioenergy, 80, 85-93
Are advantages from partial replacement of corn with second generation energy crops undermined by climate change? A case study for giant reed in Northern Italy
Cappelli, G., Yamaç, S.S., Stella, T., Francone, C., Paleari, L., Negri, M., Confalonieri, R.
European Commission Joint Research Centre AGRI4CAST
http://mars.jrc.ec.europa.eu/mars/About-us/AGRI4CAST
 
INRA - Institut national de la recherche agronomique
www.inra.fr
 
CREA
www.crea.gov.it
 

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  • About Cassandra

    • Cassandra is a research group at the University of Milan. Main research lines deal with the analysis of biophysical systems aimed at developing software solutions for agro-environmental studies, ranging from smart apps to complex systems for large area applications targeting crop monitoring, yield forecast, early warning, in silico ideotyping.

      @ 2014-2020 Cassandra


  • Programma di Sviluppo Rurale

    • Il Gruppo di ricerca CassandraLab partecipa ad una iniziativa realizzata nell’ambito del Programma Regionale di Sviluppo Rurale 2014 - 2020 (FEASR).

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