RiceQuality (Cappelli et al., 2014) is a software component implementing models to simulate various aspects of rice quality:
- amylose content,
- protein content,
- lipids content,
- starch content,
- viscosity profile,
- chalkiness,
- cracking,
- head rice yield.
Alternate approaches for the simulation of the same quality property are included, to allow users to select the most suitable for specific modelling studies.
The component is used within the WARM 2 application.

RiceQuality 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 documentation of code and algorithms, as well as sample projects showing how to use the component and how to link it with others for, e.g., crop growth and development.


Cappelli, G., Bregaglio, S., Romani, M., Feccia, S., Confalonieri, R., 2014. A software component implementing a library of models for the simulation of pre-harvest rice grain quality. Comput. Electron. Agr. 104, 18-24.

Product Manager: Roberto Confalonieri
Online Code doc: http://download.cassandralab.com/ricequality/ricequality_codedoc/RiceQualityCodedoc.html
Online Help: http://download.cassandralab.com/ricequality/ricequality_help/UNIMI.Cassandra.RiceQuality.html
Application file: request a download link providing your email below.

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.

CNR - Consiglio Nazionale delle Ricerche
International Rice Research Institute