Rice Breeding Course

Research data management is one important area in the responsible conduct of research. Research data management ought to be planned well right from the start of any research project. Researchers must know how to manage their data to ensure that these are well documented and organized systematically. Data management encompasses all phases of the data life cycle starting from research data planning; research data collection, authentication and analysis; data storage, backup and security; and data archival and sharing. Success of a research project is measured not only through its publications, but more importantly by making the data available to the wider community through information databases and archives.

• Introduction to breeding program planning;
• Setting goals and identifying the target environment;
• Information management for pedigree, bulk, and RGA breeding programs;
• Factors affecting the adoption of improved varieties;
• Factors affecting selection response;
• Choosing parents;
• Efficient approaches to pedigree, bulk, and RGA selection;
• Breeding Information Management System (BIMS);
• Managing plant breeding data with the International Rice Information System (IRIS);
• Quality evaluation;
• Screening for biotic stress resistance;
• Screening for abiotic stress tolerance;
• Experimental designs for controlling field variability;
• Multi-environmental trials – design and analysis;
• Participatory varietal selection and participatory plant breeding;
• QTL analysis and molecular marker-aided selection;
• International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA) and worldwide exchange and utilization of rice genetic resources;
• Intellectual property rights/plant variety protection; and
• Development and presentation of action plans for increasing the impact of participants’ programs.