SASA10156U Advanced Quantitative Methods in Herd Management
Volume 2013/2014
Education
MSc Programme in Animal
Science - semi-compulsory
Content
This course is for individuals seeking to
improve their abilities to assemble and use data of animal
performance to enhance rational, quantitative decision making in
animal production. It is a computer intensive course.
Initially, the necessary mathematical and statistical preconditions will be introduced in order to make sure that all students have a basic understanding of topics like vector and matrix operations (i.e., linear algebra), random numbers, Bayes’ theorem, distributions (including multivariate and conditional), etc. The duration of this part is between one and two weeks.
Next, the course provides a comprehensive introduction to advanced quantitative herd management by combining:
- Theory
- Computer applications in order to illustrate theory
- Practical livestock management applications developed in research
The techniques covered in this course have general application in diverse animal production systems. These techniques are applied to an array of management decisions including culling, breeding and mating; feed allocation and slaughter timing; and medical treatment. Specific topics include dynamic monitoring of animal performance and behavior, data filtering, use of state space models, Bayesian networks, decision graphs, linear programming, Markov decision-processes and Monte Carlo simulation.
Initially, the necessary mathematical and statistical preconditions will be introduced in order to make sure that all students have a basic understanding of topics like vector and matrix operations (i.e., linear algebra), random numbers, Bayes’ theorem, distributions (including multivariate and conditional), etc. The duration of this part is between one and two weeks.
Next, the course provides a comprehensive introduction to advanced quantitative herd management by combining:
- Theory
- Computer applications in order to illustrate theory
- Practical livestock management applications developed in research
The techniques covered in this course have general application in diverse animal production systems. These techniques are applied to an array of management decisions including culling, breeding and mating; feed allocation and slaughter timing; and medical treatment. Specific topics include dynamic monitoring of animal performance and behavior, data filtering, use of state space models, Bayesian networks, decision graphs, linear programming, Markov decision-processes and Monte Carlo simulation.
Learning Outcome
After attending the course students
should be able to participate in the development and evaluation of
new tools for management and control taking biological variation
and observation uncertainty into account.
After completing the course, the student should be able to:
Knowledge:
- Describe the methods taught in the course
- Explain the limitations and strengths of the methods in relation to herd management problems.
- Give an overview of typical application areas of the methods.
Skills:
- Construct models to be used for monitoring and decision support in animal production at herd level.
- Apply the software tools used in the course.
Competencies:
- Evaluate methods, models and software tools for herd management.
- Transfer methods to other herd management problems than those discussed in the course.
- Interpret results produced by models and software tools.
After completing the course, the student should be able to:
Knowledge:
- Describe the methods taught in the course
- Explain the limitations and strengths of the methods in relation to herd management problems.
- Give an overview of typical application areas of the methods.
Skills:
- Construct models to be used for monitoring and decision support in animal production at herd level.
- Apply the software tools used in the course.
Competencies:
- Evaluate methods, models and software tools for herd management.
- Transfer methods to other herd management problems than those discussed in the course.
- Interpret results produced by models and software tools.
Literature
Kristensen, A.R., E. Jørgensen and N.
Toft. 2010. Herd Management Science I. Basic concepts. 2010
Edition, University of Copenhagen, Faculty of Life Sciences.
Kristensen, A.R., E. Jørgensen and N. Toft. 2010. Herd Management Science II. Advanced topics. 2010 Edition, University of Copenhagen, Faculty of Life Sciences
Kristensen, A.R. 2010. Herd Management Science. Exercises and supplementary reading. 2010 edition.
Kristensen, A.R., E. Jørgensen and N. Toft. 2010. Herd Management Science II. Advanced topics. 2010 Edition, University of Copenhagen, Faculty of Life Sciences
Kristensen, A.R. 2010. Herd Management Science. Exercises and supplementary reading. 2010 edition.
Academic qualifications
SMAF10070U Statistisk
dataanalyse 2
SMAF10074U Matematik og modeller
SMAF10078U Matematik og optimering
Only one of the courses SMAF10074U and SMAF10078U is required.
SMAF10074U Matematik og modeller
SMAF10078U Matematik og optimering
Only one of the courses SMAF10074U and SMAF10078U is required.
Teaching and learning methods
Lectures, theoretical
exercises, practical computer exercises and report writing. In
connection with lectures, the students are expected to participate
actively in mutual discussions. Throughout the course, t he
application and limitations of the methods taught will be
illustrated by larger examples presented by invited guest lecturers
having used the method in question in research. Lectures will be
supported by theoretical problem solving exercises, and all methods
presented will be supported by computer exercises where the
application of the methods is illustrated. The reports will consist
of answers to selected exercises, evaluation of methods and one or
more simple implementations of methods used to solve management
problems. Reports may be written and handed-in in minor groups of
two or three students.
Remarks
No credit points with
course 260001 Advanced Herd Management (last possible examination
2011/2012).
Workload
- Category
- Hours
- Exam
- 1
- Guidance
- 9
- Lectures
- 54
- Practical exercises
- 18
- Preparation
- 60
- Project work
- 54
- Theory exercises
- 10
- Total
- 206
Sign up
Self Service at
KUnet
Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 minutesAn individual oral examination is held at the end of the course. 30 minutes preparation followed by 30 minutes examination.
- Exam registration requirements
- A precondition for attending exam is that at least 3 of 4 mandatory reports have been handed in and approved.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
More than one internal examiner
Criteria for exam assesment
To achieve the maximum grade of 12, the student shall be
able to:
- Describe the methods taught in the course
- Explain the limitations and strengths of the methods in relation to herd management problems.
- Give an overview of typical application areas of the methods.
- Evaluate methods, models and software tools for herd management.
- Interpret results produced by models and software tools.
- Describe the methods taught in the course
- Explain the limitations and strengths of the methods in relation to herd management problems.
- Give an overview of typical application areas of the methods.
- Evaluate methods, models and software tools for herd management.
- Interpret results produced by models and software tools.
Course information
- Language
- English
- Course code
- SASA10156U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- C
- Course capacity
- No limit
- Study board
- Study Board of Biology and Animal Science
Contracting department
- Department of Large Animal Sciences
Course responsibles
- Anders Ringgaard Kristensen (ark@sund.ku.dk)
Saved on the
18-06-2013