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Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations

Hein, Lisa; Sørensen, Lars Peter; Kargo, Morten and Buitenhuis, Albert Johannes (2018) Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations. Journal of Dairy Science, 101 (3), pp. 2148-2157.

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Summary

The objective of this study was to assess the genetic variability of the detailed fatty acid (FA) profiles of Danish Holstein (DH) and Danish Jersey (DJ) cattle populations. We estimated genetic parameters for 11 FA or groups of FA in milk samples from the Danish milk control system between May 2015 and October 2016. Concentrations of different FA and FA groups in milk samples were measured by mid-infrared spectroscopy. Data used for parameter estimation were from 132,732 first-parity DH cows and 21,966 first-parity DJ cows. We found the highest heritabilities for test day measurements in both populations for short-chain FA (DH = 0.16; DJ = 0.16) and C16:0 (DH = 0.14; DJ = 0.16). In DH, the highest heritabilities were also found for saturated FA and monounsaturated FA (both populations: 0.15). Genetic correlations between the fatty acid traits showed large differences between DH and DJ for especially short-chain FA with the other FA traits measured. Furthermore, genetic correlations of total fat with monounsaturated FA, polyunsaturated FA, shortchain FA, and C16:0 differed markedly between DH and DJ populations. In conclusion, we found genetic variation in the mid-infrared spectroscopy-predicted FA and FA groups of the DH and DJ cattle populations. This finding opens the possibility of using genetic selection to change the FA profiles of dairy cattle.


EPrint Type:Journal paper
Subjects: Animal husbandry > Production systems > Dairy cattle
Animal husbandry > Breeding and genetics
Research affiliation: Denmark > AU - Aarhus University
Denmark > SEGES
Denmark > Organic RDD 2 > SOBcows
DOI:10.3168/jds.2017-13225
Deposited By: Hjortø, Line
ID Code:33090
Deposited On:18 May 2018 07:49
Last Modified:18 May 2018 07:49
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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