Andreas Hund: Catalogue data in Autumn Semester 2018
|Name||PD Dr. Andreas Hund|
|Name variants||Andreas Hund|
Professur für Kulturpflanzenwiss.
ETH Zürich, FMG C 25
|Telephone||+41 44 632 38 29|
|Department||Environmental Systems Science|
|751-3603-00L||Current Challenges in Plant Breeding |
Number of participants limited to 15.
|2 credits||2G||B. Studer, A. Hund, University lecturers|
|Abstract||The seminar 'Current challenges in plant breeding' aims to bring together national and international experts in plant breeding to discuss current activities, latest achievements and future prospective of a selected topic/area in plant breeding.|
The topic this year will be: 'Digital Plant Breeding – Hype or the way forward?'.
|Objective||The educational objectives cover both thematic competences and soft skills:|
- Deepening of scientific knowledge in plant breeding
- Critical evaluation of current challenges and new concepts in plant breeding
- Promotion of collaboration and Master thesis projects with practical plant breeders
- Independent literature research to get familiar with the selected topic
- Critical evaluation and consolidation of the acquired knowledge in an interdisciplinary team
- Establishment of a scientific presentation in an interdisciplinary team
- Presentation and discussion of the teamwork outcome
- Establishing contacts and strengthening the network to national and international plant breeders and scientist
|Content||Interesting topics related to plant breeding will be selected in close collaboration with the working group for plant breeding of the Swiss Society of Agronomy (SSA). For this year, the topic 'Digital Plant Breeding – Hype or the way forward?' was selected. |
In the fall semester (in November 2018), the enrolled students will meet with the lecturers as well as four to six tutors, selected according to their expertise in the selected topic (one afternoon, for about two hours). After an input talk by the lecturers, four to six specific questions/aspects will be identified and phrased. The tutors and the enrolled students will be assigned to four to six different groups, to critically evaluate one question/aspect of the selected topic. The students, guided by tutors, will prepare a presentation of 15 minutes (plus 5 minutes discussion) covering their specific question/aspect. Participation on that afternoon will be mandatory.
On February 1, 2019, a one-day seminar on the selected topic will be organized. The presentations of the students will be complemented with keynote talks from national and international experts, to discuss and critically evaluate the selected topic/area. The seminar will be public and serve as annual meeting of the SSA working group for plant breeding, bringing together the experts in plant breeding. During the reception after the seminar, there will be the opportunity to connect and interact with other seminar participants.
The course is designed for a maximum of 15 Master students and 10 PhD students (advertised and recruited via the Zurich-Basel Plant Science Center). For full and active participation, a total of 2 credit/ECTS points will be provided.
|Literature||Peer-reviewed research articles, selected according to the selected topic/area.|
|Prerequisites / Notice||Participation in the BSc course 'Pflanzenzüchtung' is strongly recommended, a completed course in 'Molecular Plant Breeding' is highly advantageous.|
|751-3801-00L||Experimental Design and Applied Statistics in Agroecosystem Science||3 credits||2G||A. Hund, W. Eugster, C. Grieder, R. Kölliker|
|Abstract||Different experimental designs will be discussed and various statistical tools will be applied to research questions in agroecosystem sciences. Statistical methods range from simple analysis of variance to mixed-models and multivariate statistics. Surveys and manipulative field and laboratory experiments are addressed and students learn to analyse data using a hands-on approach.|
|Objective||Students will know various statistical analyses and their application to science problems in their study area as well as a wide range of experimental design options used in environmental and agricultural sciences. They will practice to use statistical software packages (R), understand pros and cons of various designs and statistics, and be able to statistically evaluate their own results as well as those of published studies.|
|Content||The course program uses a learning-by-doing approach ("hands-on minds-on"). New topics are introduced in the lecture hall, but most of the work is done in the computer lab to allow for the different speeds of progress of the student while working with data and analyzing results. In addition to contact hours exercises must be finalized and handed in for grading. The credit points will be given based on successful assessments of selected exercises.|
The tentative schedule containst the following topics:
Introduction To Experimental Design and Applied Statistics
Introduction to 'R' / Revival of 'R' Skills
Designs of Field and Growth Chamber Experiments
Nonlinear Regression Fits
Multivariate Techniques: Principle Component Analysis, Canonical Correpondence Analysis (CCA), Cluster Analysis
ANOVA using linear and mixed effect models
Error Analysis, Error Propagation and Error Estimation
Introduction to autoregression and autocorrelations in temporal and spatial data and how to consider them in ANOVA-type analysis
This course does not provide the mathematical background that students are expected to bring along when signing up to this course. Alternatively, students can consider some aspects of this course as a first exposure to solutions in experimental design and applied statistics and then deepen their understanding in follow-up statistical courses.
|Lecture notes||Handouts will be available (in English)|
|Literature||A selection of suggested additional literature, especially for German speaking students will be presented in the introductory lecture.|
|Prerequisites / Notice||This course is based on the course Mathematik IV: Statistik, passed in the 2nd year and the Bachelor's course "Wissenschaftliche Datenauswertung und Datenpräsentation" (751-0441-00L)|