Projects / Programmes
Comparasion of statistical models for longitudinal data in animal breeding
| Code |
Science |
Field |
Subfield |
| 4.02.00 |
Biotechnical sciences |
Animal production |
|
| Code |
Science |
Field |
| B006 |
Biomedical sciences |
Agronomics |
| B400 |
Biomedical sciences |
Zootechny, animal husbandry, breeding |
longitudinal data, test-day models, random regression, growth, fertility, milk traits, animal breeding
Researchers (11)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
05096 |
MSc Marko Čepon |
Biotechnical sciences |
Researcher |
2004 - 2007 |
458 |
| 2. |
24798 |
Darja Čop |
Biotechnical sciences |
Researcher |
2005 - 2007 |
117 |
| 3. |
05098 |
PhD Peter Dovč |
Biotechnical sciences |
Researcher |
2004 - 2007 |
910 |
| 4. |
02977 |
PhD Franc Habe |
Biotechnical sciences |
Researcher |
2004 |
264 |
| 5. |
08405 |
PhD Marija Klopčič |
Biotechnical sciences |
Researcher |
2004 - 2007 |
698 |
| 6. |
20025 |
PhD Andreja Komprej |
Biotechnical sciences |
Researcher |
2004 - 2007 |
145 |
| 7. |
09755 |
PhD Milena Kovač |
Biotechnical sciences |
Principal Researcher |
2004 - 2007 |
1,193 |
| 8. |
20790 |
MSc Jurij Krsnik |
Biotechnical sciences |
Researcher |
2004 - 2007 |
171 |
| 9. |
19045 |
PhD Špela Malovrh |
Biotechnical sciences |
Researcher |
2004 - 2007 |
871 |
| 10. |
14933 |
PhD Dušan Terčič |
Biotechnical sciences |
Researcher |
2004 - 2007 |
207 |
| 11. |
17514 |
Irena Ule |
|
Technician |
2004 - 2007 |
415 |
Organisations (1)
Abstract
Production functions will be studied for growth traits in pigs and cattle, fertility traits in pigs and small ruminants, and milk traits in cattle and small ruminants. Longitudinal data for mentioned production traits will be modelled by single and multiple trait models as well as random regression models. Furthermore, multiple trait analyses will be applied to more than one trait measured subsequently as for milk traits. In cattle, growth traits described by random regression models will be joined with a set of carcass traits previously selected among traits obtained by carcass dissection. Fertility will be described mainly by litter size changing over parities. Production functions for observed traits are different. Measurements for growth in cattle are taken at different ages, while pigs are weighed six times at well determined ages. Lactation curves in small ruminants have missing observations before weaning of youngs, genetic evaluation is suppose to be ready before mating season and before lactation finishes. In general, test-days are not missing in cattle. Besides changes of overall production level, changes in (co)variance components will be observed over time. The models with random regressions are expected to describe changes of production over time better than other models. At the same time, it allows extraction of genetic values at different production stage. Genetic values may express overall level and rate of change like persistency. Test of animals may be simplified, data records may come from different sources, no precorrections for common age or weight are needed. The importance of regression coefficient will be determined by eigenvalues analyses and tested by appropriate statistical tests. Fixed part of the model will be suggested on the basis of Least Square Methods in SAS, while evaluation of dispersion parameters will be done by VCE 5. PEST will be used for appropriate coding and in part, for genetic evaluation.
