| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6458924 | Computers and Electronics in Agriculture | 2016 | 4 Pages |
â¢We develop a modelling platform explicitly dedicated to in silico ideotyping studies.â¢Ideotypes can be improved for resistance/tolerance traits to biotic/abiotic stress.â¢Ideotypes are evaluated over entire districts and under climate change scenarios.â¢Results are useful to identify key traits for specific production districts.â¢A case study involving heat stress tolerance illustrates the platform capabilities.
Ecophysiological models can be successfully used to analyze genotype by environment interactions, thus supporting breeders in identifying key traits for specific growing conditions. This is especially true for traits involved with resistance/tolerance to biotic and abiotic stressors, which occurrence can vary greatly both in time and space. However, no modelling tools are available to be used directly by breeders, and this is one of the reasons that prevents an effective integration of modelling activities within breeding programs. ISIde is a software platform specifically designed for district-specific rice ideotyping targeting (i) resistance/tolerance traits and (ii) breeders as final users. Platform usability is guaranteed by a highly intuitive user interface and by exposing to users only settings involved with genetic improvement. Other information needed to run simulations (i.e., data on soil, climate, management) is automatically provided by the platform once the study area, the variety to improve and the climate scenario are selected. Ideotypes indeed can be defined and tested under current and climate change scenario, thus supporting the definition of strategies for breeding in the medium-long term. Comparing the performance of current and improved genotype, the platform provides an evaluation of the yield benefits exclusively due to the genetic improvement introduced. An example of the application of the ISIde platform in terms of functionalities and results that can be achieved is reported by means of a case study concerning the improvement of tolerance to heat stress around flowering in the Oristanese rice district (Italy). The platform is currently available for the six Italian rice districts. However, the software architecture allows its extension to other growing areas - or to additional genotypes - via dedicated tools available at the application page.
