Experimental Design and Data Analysis of Breeding Trials

Note 1: This course can not be combined in an individual programme with ABG30806 Data Analysis for Plant Breeding and Genetics (DAPAB) and the course MAT33306 Data Science for Plant Breeding and Genetics
Note 2: The period mentioned below is the period in which this course starts. For the exact academic weeks see the courseplanning on www.wur.eu/schedule.
Note 3: This course is offered online and it takes about 20 hours to complete the weekly task. There are assignments with deadlines and non-synchronous interaction with teachers and fellow students. An online exam is offered in the last week.
Note 4: This is an online course, but it can also be followed by on-campus students after consultation of the course coordinator.

In this course, students are taught principles of experimental design of trials and statistical analysis of trial data with a special emphasis to linear and generalized linear methods, mixed models, analysis of multi-environment trials using different statistical methods

• Explain and apply statistical principles underlying experimental designs for breeding trials with respect to randomisation, replication, blocking, experimental units.

• Explain, distinguish and characterise the following experimental designs: completely randomised design (CRD), randomised complete block design (RCB), incomplete block designs (including resolvable designs: lattice designs and alpha designs, row-column designs) and split-plot designs

• Explain and apply linear models, different kinds of generalised linear models (GLM) and mixed models and know the similarities and differences between these

• Explain genotype by environment interaction in multi-environment trials and quantify, test and characterise such interactions using analysis of variance, mixed models, Finlay-Wilkinson regression, AMMI and GGE biplot

• Written test with open questions (100%) The exam is an online remotely proctored exam, where the student should provide a suitable computer and room. The online exam is offered in the last week of course.

MAT25303 Advanced Statistics-DL
PBR60806 Plant Breeding Skills Cluster (DL) - The R module of this course: knowledge of and experience with R and R Studio is needed. The student is expected to be able to modify existing R scripts and to write short scripts to perform analyses.

The exam takes place using Remote Proctoring, which is different than digital examinations on-campus. Students unfamiliar with this system should carefully test it beforehand by following all directions given in the link to the Tryout exam in the pre-exam e-mail.

• Available through the course website.