10th International Meeting on Plant Breeding

Course Objective

Guide and train researchers, students, breeders, and other interested participants to understand the legal, technical, and administrative foundations of cultivar registration and cultivar protection in Brazil, providing guidance on the requirements, procedures, and documentation needed for the proper submission of applications to the competent authorities.

Syllabus / Main Topics

• Concepts and differences between cultivar registration and cultivar protection.
• Applicable Brazilian legislation and the responsibilities of the competent authorities.
• Technical criteria required for cultivar registration (VCU) and cultivar protection (DUS; DHE in Portuguese).
• Forms and other documents required for submitting applications.
• Procedural flow, deadlines, and fees.
• Common errors and best practices to improve the quality of submitted applications.

Tools / Software

Room equipped with a computer and multimedia projector for the presentation.

Course Objective

To be defined.

Syllabus / Main Topics

To be defined.

Tools / Software

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Course Objective

To enable participants to understand and apply fundamental concepts of Bayesian Inference in the analysis of Genotype × Environment (G×E) interaction, with emphasis on the use of Bayesian models for the estimation of genotypic parameters and posterior-based inference in multi-environment trials using R. The course is structured as a fully hands-on training, with theoretical concepts immediately applied in practice throughout all modules.

Syllabus / Main Topics

• Fundamental concepts of Bayesian Inference (theoretical and applied aspects).
• Prior distributions, likelihood, and posterior distribution (theoretical and applied aspects).
• Bayesian hierarchical models for Genotype × Environment (G×E) interaction analysis (R-based implementation).
• Bayesian reaction norm models for Genotype × Environment (G×E) analysis (R-based implementation).

Tools / Software

• Room equipped with a whiteboard and multimedia projector (datashow).
• Computers or laptops for hands-on activities.
• Use of R software for all statistical analyses.
• Teaching materials, R scripts, example datasets, and any additional resources provided by the instructor.

Syllabus / Main Topics

In this course, we will focus on the fundamentals of applying Genomic Prediction for plant breeding program by fitting several linear mixed models (LMM) using different statistical methodologies. An array of R libraries will be used in this course including BGLR, ASReml-R and rrBLUP. This course will use real datasets and will focus on interpretation of results and discuss practical implications of the use of genomic prediction models in the context of operational breeding programs and their strategies.

Tools / Software

To be defined.