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Statistical analyses of milk traits ...

Hayr, Melanie Kate.

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Statistical analyses of milk traits in the New Zealand dairy cattle population.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical analyses of milk traits in the New Zealand dairy cattle population./
Author:	Hayr, Melanie Kate.
Description:	89 p.
Notes:	Source: Masters Abstracts International, Volume: 53-06.
Contained By:	Masters Abstracts International53-06(E).
Subject:	Animal sciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1567202
ISBN:	9781321269376

Statistical analyses of milk traits in the New Zealand dairy cattle population.
Hayr, Melanie Kate.

Statistical analyses of milk traits in the New Zealand dairy cattle population. - 89 p.

Source: Masters Abstracts International, Volume: 53-06.

Thesis (M.S.)--Iowa State University, 2014.

This item must not be sold to any third party vendors.

Dairy cattle breeding systems have a common goal of improved milk production. Extensive research has been carried out to increase our understanding of the biology behind milk production. This biological information has then been used to improve the prediction of a cow's milk production. This thesis explores two ways in which milk production can be better understood and predicted. The first study investigates whether the sex of the calf that initiates a lactation has an impact on milk yield during that lactation as well as whether the sex of calves in different parities affects milk yield during that lactation. The second study investigates the additive and dominance effects of four quantitative trait nucleotides (QTN) for milk fat yield and evaluates whether including the QTN in genomic prediction analyses as either a random covariate, fixed covariate or fixed class improves estimated breeding values (EBV).

ISBN: 9781321269376Subjects--Topical Terms:

3174829
Animal sciences.

Statistical analyses of milk traits in the New Zealand dairy cattle population.
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020 $a 9781321269376
035 $a (MiAaPQ)AAI1567202
035 $a AAI1567202
040 $a MiAaPQ $c MiAaPQ
100 1 $a Hayr, Melanie Kate. $3 3174869
245 1 0 $a Statistical analyses of milk traits in the New Zealand dairy cattle population.
300 $a 89 p.
500 $a Source: Masters Abstracts International, Volume: 53-06.
500 $a Adviser: Dorian J. Garrick.
502 $a Thesis (M.S.)--Iowa State University, 2014.
506 $a This item must not be sold to any third party vendors.
520 $a Dairy cattle breeding systems have a common goal of improved milk production. Extensive research has been carried out to increase our understanding of the biology behind milk production. This biological information has then been used to improve the prediction of a cow's milk production. This thesis explores two ways in which milk production can be better understood and predicted. The first study investigates whether the sex of the calf that initiates a lactation has an impact on milk yield during that lactation as well as whether the sex of calves in different parities affects milk yield during that lactation. The second study investigates the additive and dominance effects of four quantitative trait nucleotides (QTN) for milk fat yield and evaluates whether including the QTN in genomic prediction analyses as either a random covariate, fixed covariate or fixed class improves estimated breeding values (EBV).
520 $a Calf sex was shown to have an effect on milk yield in each of the first three lactations, with heifer calves resulting in a higher milk yield than bull calves. Some of the effect of calf sex is explained by a greater number of days-in-milk for a cow when a female calf was born, as evidenced by a decrease in the effect of calf sex when days-in-milk was fitted in the model. While days-in-milk explained some of the effect, there was still some effect of calf sex within and across lactations.
520 $a Dominance was observed at the majority of QTN, suggesting that milk fat yield EBV could be improved by the correct modeling of dominance in prediction models. Including QTN in genomic prediction models did not significantly change prediction accuracy, however including QTN significantly decreased bias in many cases, such as when AGPAT6, a QTN with observed over-dominance, was included as a fixed class effect. There was evidence of epistatic interactions between the QTN PLAG1 and AGPAT6, PLAG1 and GHR, and DGAT1 and GHR.
520 $a This thesis shows there is the potential to improve modeling of economically important traits. As data sets get bigger and data collection methods improve, more of the underlying biology will be revealed.
590 $a School code: 0097.
650 4 $a Animal sciences. $3 3174829
650 4 $a Statistics. $3 517247
690 $a 0475
690 $a 0463
710 2 $a Iowa State University. $b Animal Science. $3 1035695
773 0 $t Masters Abstracts International $g 53-06(E).
790 $a 0097
791 $a M.S.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1567202