Andreas Hund: Catalogue data in Autumn Semester 2020

Name PD Dr. Andreas Hund
Name variantsAndreas Hund
FieldCrop Science
Address
Professur für Kulturpflanzenwiss.
ETH Zürich, FMG C 25
Eschikon 33
8315 Lindau
SWITZERLAND
Telephone+41 44 632 38 29
E-mailandreas.hund@usys.ethz.ch
URLhttps://kp.ethz.ch/people/person-detail.OTA3Njc=.TGlzdC8xNDQyLDExMzQ4NjQxMzg=.html
DepartmentEnvironmental Systems Science
RelationshipPrivatdozent

NumberTitleECTSHoursLecturers
751-3603-00LCurrent Challenges in Plant Breeding Restricted registration - show details
Number of participants limited to 15.
2 credits2GB. Studer, A. Hund, R. Kölliker
Abstract'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 with students.
The seminar this year will focus on what plant breeding can contribute to mitigate future challenges such as reduced input for plant protection or climate change.
ObjectiveThe educational objectives cover both thematic competences and soft skills:
Thematic competences:
- 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
Soft skills:
- 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
ContentGiven current discussions and efforts towards more sustainable agricultural production systems, we will investigate what plant breeding can contribute i) to reduce the input of plant protection products, ii) to make our crops genetically ready for future climatic conditions and iii) to evaluate what traits might become important in alternative production systems.

On November 6, 2020, from 2 to 5pm, the enrolled students will be introduced to the concept, topic and the lecturers/tutors involved in 'Current challenges in plant breeding'. After an input talk by the lecturers, four to six specific aspects/questions for the above-mentioned topics will be identified and phrased. The tutors and the enrolled students will be assigned to four to six different groups, to critically evaluate one aspect/question. The students, guided by tutors, will prepare a presentation of 15 minutes (plus 5 minutes discussion) covering their specific question/aspect. Participation in this introductory lecture mandatory.

On January 26, 2021, 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. The seminar will be public and serve as annual meeting of the 'Working Group Plant Breeding' from the Swiss Society of Agronomy, bringing together the experts in plant breeding.

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.
Lecture notesno
LiteraturePeer-reviewed research articles, selected according to the selected topic/area.
Prerequisites / NoticeParticipation in the BSc course 'Pflanzenzüchtung' is strongly recommended, a completed course in 'Molecular Plant Breeding' is highly advantageous.
751-3801-00LExperimental Design and Applied Statistics in Agroecosystem Science3 credits2GA. Hund, W. Eugster, C. Grieder, R. Kölliker
AbstractDifferent 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.
ObjectiveStudents 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.
ContentThe 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 notesHandouts will be available (in English)
LiteratureA selection of suggested additional literature, especially for German speaking students will be presented in the introductory lecture.
Prerequisites / NoticeThis 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)