Mælidagalíkan fyrir íslenska kúastofninn
Many countries utilize random regression (RR) models for genetic evaluation of dairy cows but in Iceland a lactation model is still used. The objective of this study was to investigate the genetics of lactation curves of Icelandic dairy cows and the possible benefits of implementing an RR model for...
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ftskemman:oai:skemman.is:1946/29227 2023-05-15T16:52:48+02:00 Mælidagalíkan fyrir íslenska kúastofninn Test day model for Icelandic dairy cattle Jón Hjalti Eiríksson 1991- Landbúnaðarháskóli Íslands 2017-10 application/pdf http://hdl.handle.net/1946/29227 en eng http://hdl.handle.net/1946/29227 Random regression Somatic cell count Milk yield Genetic progress Mælidagalíkan Frumutala Afurðir Kynbótamat Erfðaframför Thesis Master's 2017 ftskemman 2022-12-11T06:53:35Z Many countries utilize random regression (RR) models for genetic evaluation of dairy cows but in Iceland a lactation model is still used. The objective of this study was to investigate the genetics of lactation curves of Icelandic dairy cows and the possible benefits of implementing an RR model for genetic evaluation in the population. 480,495 test day yields of 33,052 cows were used to estimate genetic parameters for milk yield (MY), fat yield (FY), protein yield (PY) and somatic cell score (SCS) in first three lactations with a RR model based on Legendre polynomials. For comparison 305 day lactation yields (LAC1) were calculated from the same data and genetic parameters estimated with a multitrait model. Parameters for MY, FY and PY using the lactation model currently in use (LAC2) were additionally estimated, one trait, three lactations at a time. Breeding values were estimated using the three models with all available data from the years 1995-2016 and for 24 additional versions of that dataset by eliminating data from the last two to eight years, quarter of a year at a time. Correlation between results using the whole dataset and results using the sub-sets was used as a measure of accuracy of estimated breeding values for bulls in progeny testing with artificial insemination and cows in production. Additive genetic variance was highest in the beginning of lactation for all traits in second and third lactation and FY and SCS in first. Permanent environment variance was highest in the beginning of lactation for all traits. Heritability of daily yields and SCS was lowest in early lactation in all lactations and highest in mid or late lactation. Heritability of first lactation 305 day yields was 0.43, 0.39 and 0.41 for MY, FY and PY, respectively, based on the RR model, 0.41, 0.32 and 0.39 based on LAC1 and 0.31, 0.27 and 0.27 based on LAC2. Heritability of SCS in first lactation was 0.23 according to the RR model but 0.15 using the lactation model. Heritability of persistency of lactation MY, FY and PY was ... Thesis Iceland Skemman (Iceland) |
institution |
Open Polar |
collection |
Skemman (Iceland) |
op_collection_id |
ftskemman |
language |
English |
topic |
Random regression Somatic cell count Milk yield Genetic progress Mælidagalíkan Frumutala Afurðir Kynbótamat Erfðaframför |
spellingShingle |
Random regression Somatic cell count Milk yield Genetic progress Mælidagalíkan Frumutala Afurðir Kynbótamat Erfðaframför Jón Hjalti Eiríksson 1991- Mælidagalíkan fyrir íslenska kúastofninn |
topic_facet |
Random regression Somatic cell count Milk yield Genetic progress Mælidagalíkan Frumutala Afurðir Kynbótamat Erfðaframför |
description |
Many countries utilize random regression (RR) models for genetic evaluation of dairy cows but in Iceland a lactation model is still used. The objective of this study was to investigate the genetics of lactation curves of Icelandic dairy cows and the possible benefits of implementing an RR model for genetic evaluation in the population. 480,495 test day yields of 33,052 cows were used to estimate genetic parameters for milk yield (MY), fat yield (FY), protein yield (PY) and somatic cell score (SCS) in first three lactations with a RR model based on Legendre polynomials. For comparison 305 day lactation yields (LAC1) were calculated from the same data and genetic parameters estimated with a multitrait model. Parameters for MY, FY and PY using the lactation model currently in use (LAC2) were additionally estimated, one trait, three lactations at a time. Breeding values were estimated using the three models with all available data from the years 1995-2016 and for 24 additional versions of that dataset by eliminating data from the last two to eight years, quarter of a year at a time. Correlation between results using the whole dataset and results using the sub-sets was used as a measure of accuracy of estimated breeding values for bulls in progeny testing with artificial insemination and cows in production. Additive genetic variance was highest in the beginning of lactation for all traits in second and third lactation and FY and SCS in first. Permanent environment variance was highest in the beginning of lactation for all traits. Heritability of daily yields and SCS was lowest in early lactation in all lactations and highest in mid or late lactation. Heritability of first lactation 305 day yields was 0.43, 0.39 and 0.41 for MY, FY and PY, respectively, based on the RR model, 0.41, 0.32 and 0.39 based on LAC1 and 0.31, 0.27 and 0.27 based on LAC2. Heritability of SCS in first lactation was 0.23 according to the RR model but 0.15 using the lactation model. Heritability of persistency of lactation MY, FY and PY was ... |
author2 |
Landbúnaðarháskóli Íslands |
format |
Thesis |
author |
Jón Hjalti Eiríksson 1991- |
author_facet |
Jón Hjalti Eiríksson 1991- |
author_sort |
Jón Hjalti Eiríksson 1991- |
title |
Mælidagalíkan fyrir íslenska kúastofninn |
title_short |
Mælidagalíkan fyrir íslenska kúastofninn |
title_full |
Mælidagalíkan fyrir íslenska kúastofninn |
title_fullStr |
Mælidagalíkan fyrir íslenska kúastofninn |
title_full_unstemmed |
Mælidagalíkan fyrir íslenska kúastofninn |
title_sort |
mælidagalíkan fyrir íslenska kúastofninn |
publishDate |
2017 |
url |
http://hdl.handle.net/1946/29227 |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
http://hdl.handle.net/1946/29227 |
_version_ |
1766043228831744000 |