One week intensive course: Experimental design and analysis of field and laboratory trials Africa Uninet Project | Egerton University and BOKU

Target group: students, researchers, extension service, industry, NGOs, etc.

Where:  Egerton University, Njoro, Kenya.

When: March 13-17, 2023

How to register: send filled application form to: gentwork(at)boku.ac.at   before February 20, 2023

Your instructor: Dr. Sebastian Michel; Plant Breeder and Quantitative Geneticist. Lecturer and researcher at the University of Natural Resources and Life Sciences Vienna. ORCID: 0000-0001-6636-2694, more information

For further information please contact:
Dr. Sebastian Michel,  sebastian.michel(at)boku.ac.at
Dr. Mercy Wamalwa,  mercy.wamalwa(at)egerton.ac.ke
 

Course content:

During this lecture you will learn how to use the statistical package R for fitting mixed models and familiarize yourself with the usage of this package.

The following topics will be discussed during the course:

  • Introduction into the R statistical environment (regression analysis, t-test, analysis of variance)

  • Randomized complete block desig (prelude to random blocks)

  • Incomplete block designs (augmented designs, α designs, p-rep,row-column designs)

  • Multi-factorial trial designs (genotype x environment interaction, split-plot designs, strip-plot designs)

Participants will be able to set up a linear mixed model for their designed experiments and can implement such models using statistical packages such as R. Participants will be furthermore able to analyze the data obtained in plant breeding and plant production field and laboratory trials as well as interpret and display the relevant results.

Prerequisites for participation:

  • Basics in Biostatistics (linear regression, analysis of variance)

  • Basic knowledge of biology, plant breeding, plant production, or a related discipline

  • Laptop with an installation the latest versions of R and RStudio (freeware)

 

Acknowledgment:

This course takes place  in the framework of Africa Uninet project  P059: Sustainable networks for using next generation quantitative genetics to modernize breeding programs in Kenya. Gentwork - Genetics and Networks | Kenya - Austria

Downloads