The spring semester 2021 will certainly take place online until Easter. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers.

Search result: Catalogue data in Autumn Semester 2016

Agricultural Sciences Bachelor Information
Bachelor Studies (Programme Regulations 2016)
1. Semester
Additional First Year Courses
751-0801-00LBiology I: Laboratory Exercises Information O1 credit2UE. B. Truernit
AbstractPrinciples and methods of light microscopy. Preparation of specimen for microscopy; documentation. Anatomy of seed plants: From cells to organs. Special features of plant cells. Anatomy and function of plant organs. Anatomical adaptations to different environments.
ObjectiveCapability of preparing biological specimen, microscopy and documentation. Understanding the correlation between plant structure and function at the level of organs, tissues and cells.
Awareness of the link between plant anatomy, systematics, physiology, ecology, and development.
ContentBasics of optics. Principles of light microscopy. Microscope parts and their function. Köhler illumination. Optical contrasting methods. Measuring object sizes with the microscope. Preparation of specimen for light microscopy. Plant tissue staining techniques.
Special features of plant cells: Plastids, vacuole, cell wall. Anatomy of seed plants: From cells to organs. Anatomy and function of various plant tissues (epidermis, vascular tissue, wood, etc.). Anatomy and function of different plant organs (root, stem, leaf, flower, fruit, seed). Anatomical adaptations to different environments.
Lecture notesHandouts
LiteratureFor further reading (not obligatory):
Gerhard Wanner: Mikroskopisch-Botanisches Praktikum, Georg Thieme Verlag, Stuttgart.
Prerequisites / NoticeGroups of a maximum of 30 students.
529-0030-00LLaboratory Course: Elementary Chemical TechniquesO3 credits6PN. Kobert, M. Morbidelli, M. H. Schroth, B. Wehrli
AbstractThis practical course provides an introduction to elementary laboratory techniques.
The experiments cover a wide range of techniques, including analytical and synthetic techniques (e. g. investigation of soil and water samples or the preparation of simple compunds). Furthermore, the handling of gaseous substances is practised.
ObjectiveThis course is intended to provide an overview of experimental chemical methods.
The handling of chemicals and proper laboratory techniques represent the main
learning targets. Furthermore, the description and recording of laboratory processes is an essential part of this course.
ContentThe classification and analysis of natural and artificial compounds is a key subject of this
course. It provides an introduction to elementary laboratory techniques, and the experiments cover a wide range of analytic and synthetic tasks:
Selected samples (e.g. soil and water) will be analysed with various methods, such as titrations,
spectroscopy or ion chromatography. The chemistry of aqeous solutions (acid-base equilibria and solvatation or precipitation processes) is studied.
The synthesis of simple inorganic complexes or organic molecules is practised.
Furthermore, the preparation and handling of environmentally relevant gaseous species like carbon dioxide or nitrogen oxides is a central subject of the Praktikum.
Lecture notesThe script will be published on the web.
Details will be provided on the first day of the semester.
LiteratureA thorough study of all script materials is requested before the course starts.
252-0839-00LInformatics Information O2 credits2GL. E. Fässler, M. Dahinden
AbstractStudents learn to apply selected concepts and tools from computer science for working on interdisciplinary projects. The following topics are covered: modeling and simulations, visualizing multi-dimensional data, managing data with lists and tables and with relational databases, introduction to programming, universal methods for algorithm design.
ObjectiveThe students learn to

- choose and apply appropriate tools from computer science,
- process and analyze real-world data from their subject of study,
- handle the complexity of real-world data,
- know universal methods for algorithm design.
Content1. Modeling and simulations
2. Visualizing multidimensional data
3. Data management with lists and tables
4. Data management with a relational database
5. Introduction to macro programming
6. Introduction to programming with Python
Lecture notesAll materials for the lecture are available at
Prerequisites / NoticeThis course is based on application-oriented learning. The students spend most of their time working through projects with data from natural science and discussing their results with teaching assistants. To learn the computer science basics there are electronic tutorials available.
  •  Page  1  of  1