PNS0222 Spectral techniques for animal, agricultural and veterinary sciences, 4.0 Credits
Pass / Failed
The requirements for attaining different grades are described in the course assessment criteria which are contained in a supplement to the course syllabus. Current information on assessment criteria shall be made available at the start of the course.
Admitted to a postgraduate program in animal science, biology, veterinary medicine,
food science, nutrition, nursing, or related subjects, or to a residency program in veterinary science.
On completion of the course, the student should be able to:
• describe the basic theory behind spectral measurements and potential applications of spectral techniques relevant for applications in animal, agricultural and veterinary sciences.
• conduct basic spectral data acquisition and preprocessing within a relevant context.
• show basic skills for operating spectral data analysis using software provided by SLU e.g Breeze and Evince.
The PhD course includes an introduction to spectral data acquisition and analysis using hand held, laboratory, airborne (drone) and spaceborne (satellite) sensors. Analysis methods include classification and regression chemometric algorithms. Examples of relevant scientific and commercials applications are included, from the animal/plant tissues level to the field plots and landscape levels.
The students will learn basics skills of spectral measurements and analysis (with a focus on the infrared spectral region) through state-of-the-art lectures, demonstrations and practical cases. Apart from these scheduled activities, the students will perform their own studies on suggested literature to improve their understanding of the subject, and a small individual project that will include (i)
spectral data acquisition, (ii) analyze of these data and (iii) a discussion on the obtained results and related limits. Ideally, the students will create their own dataset during the course or import it from their thesis. However, already acquired datasets will be available if necessary.
Lectures will represent a total of approximately 30 hours, demonstrations 10 hours and practical work 30 hours. The students are expected to spend a minimum of 36 hours on their own studies, including their personal project and presentations as a part of the examination.
Formats and requirements for examination
The students will be evaluated through a written report (mini paper) and oral
presentation of their personal project. The students should demonstrate that they understand how
spectral techniques can be used in the context of their research and develop a clear workflow from
the acquisition of the data to their analysis.
Brief description of the course contents and the teaching methods
Teaching is based on lectures, seminars, practical demonstrations, case work (group work) and the student’s own studies outside the scheduled activities.
If the pandemic situation allows it, we will organize study visits to relevant scientific and commercials environments in order to achieve understanding of how the technologies are implemented.
Facilitation for PhD students from different campus
The course will be organised in three intense blocks A, B & C with 3-4 days sessions in Umeå for each. By having blocks of lectures and training the students only need to travel three times. The block design of the schedule also allows them to focus on the subject, which is by nature a complicated matter that needs full attention in order to achieve understanding and practical skills.
If the pandemic situations allows it we recommend that the students travel to Umeå and participates physically in the activities to be able to get hands on experience from instrumentation, data acquisition and processing. However if traveling is restricted we will organize the course according to instructions.
Students will be given reading material and tasks by e-mail prior to and after each of the sessions A, B & C.
Due to the current pandemic context, the students will have the possibility to participate to most of the lectures and some of the demonstrations using video links (e.g. zoom).
Department of Agricultural Research for Northern Sweden