Diseases


Diseases
Diseases is a software component implementing models to estimate the impacts of disease epidemics on plant growth and yield. It consists of four modules providing a generic frame to simulate disease development: disease progress, inoculum pressure (initial conditions), impacts on plants, and agricultural management impact on pathogen populations. Contrarily to Blast (specific for rice blast disease), the models implemented in Diseases can be parameterized/extended for potentially all diseases, regardless they refer to herbaceous or tree species.

The component is distributed free of charge for non-commercial purposes with a dedicated software development kit (SDK), and can be used by modellers and developers in their own applications. SDK includes code and algorithms documentations and sample projects illustrating how to use Diseases and to link it to other components for, e.g., crop growth and development.


Product Manager: Marco Foi
Online Code doc: http://download.cassandralab.com/diseases/diseases_codedoc/Diseases_codedoc.html
Online Help: http://download.cassandralab.com/diseases/diseases_help/Abstract.html
Application file: request a download link providing your email below.


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.

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 - 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.

2016 - European Journal of Agronomy, 76, 107-117
Coupling a generic disease model to the WARM rice simulator to assess leaf and panicle blast impacts in temperate climate.
Bregaglio, S., Titone, P., Cappelli, G., Tamborini, L., Mongiano, G., Confalonieri, R.

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.

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.






Conserve Italia
www.conserveitalia.it
 
LAORE Sardegna
www.sardegnaagricoltura.it/assistenzatecnica/laore/
 
ERSAF Regione Lombardia
www.ersaf.lombardia.it
 
European Commission Joint Research Centre AGRI4CAST
http://mars.jrc.ec.europa.eu/mars/About-us/AGRI4CAST
 
CREA
www.crea.gov.it
 
CNR - Consiglio Nazionale delle Ricerche
www.cnr.it
 
DTN
www.dtn.com
 
International Rice Research Institute
http://irri.org/
 
SupAgro
en.montpellier-supagro.fr