References
- ICAR. Milk recording surveys on cow, sheep and goats [Internet]. ICAR; 2017 [cited 2017 Oct 24]. Available from: http://www.icar.org/survey/pages/tables.php
- Inchaisri C, Jorritsma R, Vos PLAM, van der Weijden GC, Hogeveen H. Analysis of the economically optimal voluntary waiting period for first insemination. J Dairy Sci 2011;94:3811-23. https://doi.org/10.3168/jds.2010-3790
- Knight C. Extended lactation: turning theory into reality. Adv Dairy Technol 2005;17:113-23.
- VanRaden PM, Dematawewa CMB, Pearson RE, Tooker ME. Productive life including all lactations and longer lactations with diminishing credits. J Dairy Sci 2006;89:3213-20. https://doi.org/10.3168/jds.S0022-0302(06)72596-6
- Bohmanova J, Miglior F, Jamrozik J. Use of test-day records beyond three hundred five days for estimation of three hundred five-day breeding values for production traits and somatic cell score of Canadian Holsteins. J Dairy Sci 2009;92:5314-25. https://doi.org/10.3168/jds.2009-2280
- Hagiya K, Terawaki Y, Yamazaki T, et al. Relationships between conception rate in Holstein heifers and cows and milk yield at various stages of lactation. Animal 2013;7:1423-8. https://doi.org/10.1017/S1751731113000633
- Haile-Mariam M, Pryce JE. Variances and correlations of milk production, fertility, longevity, and type traits over time in Australian Holstein cattle. J Dairy Sci 2015;98:7364-79. https://doi.org/10.3168/jds.2015-9537
- Interbull. Interbull guidelines for national and international genetic evaluation systems in dairy cattle with focus on production traits. Interbull Bulletin 2001;28:1-27.
- ICAR. ICAR rules, standards and guidelines for dairy production recording. In: International Agreement of Recording Practices, Section 2. Roma, Italy: International Committee on Animal Recording; 2016. p. 25-94.
- Haile-Mariam M, Goddard ME. Genetic and phenotypic parameters of lactations longer than 305 days (extended lactations). Animal 2008;2:325-35.
- Jamrozik J, Schaeffer LR, Dekkers JCM. Genetic evaluation of dairy cattle using test day yields and random regression model. J Dairy Sci 1997;80:1217-26. https://doi.org/10.3168/jds.S0022-0302(97)76050-8
- Jensen J. Genetic evaluation of dairy cattle using test-day models. J Dairy Sci 2001;84:2803-12. https://doi.org/10.3168/jds.S0022-0302(01)74736-4
- Interbull. National genetic evaluation forms provided by countries [Internet]. Interbull; 2017 [cited 2017 Oct 24]. Available from: http://www.interbull.org/ib/geforms
- Kistemaker GJ. The Canadian test day model using Legendre polynomials. Interbull Bulletin 2003;31:202-4.
- Wilmink JBM. Comparison of different methods of predicting 305-day milk yield using means calculated from within-herd lactation curves. Livest Prod Sci 1987;17:1-17. https://doi.org/10.1016/0301-6226(87)90049-2
- Schaeffer LR, Jamrozik J, Kistemaker GJ, Van Doormaal BJ. Experience with a test-day model. J Dairy Sci 2000;83:1135-44. https://doi.org/10.3168/jds.S0022-0302(00)74979-4
- Gernand E, Wassmuth R, von Borstel UU, Konig S. Heterogeneity of variance components for production traits in largescale dairy farms. Livest Sci 2007;112:78-89. https://doi.org/10.1016/j.livsci.2007.01.157
- Yazgan K, Makulska J, Weglarz A, Ptak E, Gierdziewicz M. Genetic relationship between milk dry matter and other milk traits in extended lactations of Polish Holstein cows. Czech J Anim Sci 2010;55:91-104. https://doi.org/10.17221/49/2009-CJAS
- National Livestock Breeding Center. Genetic evaluation for production traits [Internet]. National Livestock Breeding Center; 2018 [cited 2018 Feb 4]. Available from: http://www.nlbc.go.jp/en/sec02.html
- Madsen P, Jensen J. A user's guide to DMU [Internet]. University of Aarhus Research Centre Foulum; 2013 [cited 2017 Oct 24]. Available from: http://dmu.agrsci.dk/DMU/Doc/Current/ dmuv6_guide.5.2.pdf
- SAS Institute Inc. SAS/STAT 14.1 User's guide. Cary, NC, USA: SAS Institute Inc.; 2015.