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Effect of including genetic progress in milk yield on evaluating the use of sexed semen and other reproduction strategies in a dairy herd

Published online by Cambridge University Press:  11 July 2011

J. F. Ettema ,
S. Østergaard  and
M. K. Sørensen
J. F. Ettema*
Affiliation:
Faculty of Agricultural Sciences, Department of Animal Health and Bioscience, University of Aarhus, P.O. Box 50, DK-8830 Foulum, Denmark
S. Østergaard
Affiliation:
Faculty of Agricultural Sciences, Department of Animal Health and Bioscience, University of Aarhus, P.O. Box 50, DK-8830 Foulum, Denmark
M. K. Sørensen
Affiliation:
Faculty of Agricultural Sciences, Department of Genetics and Biotechnology, University of Aarhus, P.O. Box 50, DK-8830 Foulum, Denmark Danish Agricultural Advisory Service, Udkærsvej 15, DK-8200 Aarhus N, Denmark
*
†E-mail: [email protected]
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Abstract

The objective of this study was to explore the importance of including genetic progress in milk yield when evaluating different reproductive strategies in a dairy herd by simulation modeling. The model used in this study was SimHerd V, a dynamic and mechanistic Monte Carlo simulation model of a dairy herd including young stock. A daily increasing trend describing genetic milk yield potential of the sire population was included in the model. The inaccuracy of assuming that replacement heifers have the same (milk yield) potential as the cows present in the herd was hereby dealt with. Improving estrus detection rate from 0.45 to 0.80 increased gross margin (GM) per cow-year by €20 when genetic progress was not included in the model. When genetic progress was included in the model, then the same improvement in estrus detection decreased the GM per cow-year by €7.4. This reduced effect was explained by a lower replacement rate in consequence of the improved estrus detection and thereby a slower genetic progress in the herd. There was a reduced effect of including genetic progress on GM when surplus heifers were sold selectively based on breeding values. Repeated insemination with sexed semen on the superior half of all heifers reduced GM by €8 per cow-year when genetic progress was not included and increased the GM by €16 per cow-year when genetic progress was included in the model. Including genetic progress reduced the losses caused by lower conception and estrus detection rates and had a minimal effect with regard to postponing first insemination. This study has proven that it is important to include genetic progress in decisions on reproduction strategies in a dairy herd.

Keywords

simulationdairy herdreproductiongenetic progress
Type
Full Paper
Information
animal , Volume 5 , Issue 12 , 10 November 2011 , pp. 1887 - 1897
Copyright
Copyright © The Animal Consortium 2011

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References

Abdel-Azim, G, Schnell, S 2007. Genetic impacts of using female-sorted semen in commercial and nucleus herds. Journal of Dairy Science 90, 1554–1563.Google Scholar
Allaire, FR 1981. Economic consequences of replacing cows with genetically improved heifers. Journal of Dairy Science 64, 1985–1995.Google Scholar
Ancker, S, Sloth, KH, Trinderup, M 2008. Stor variation i reproduktionsresultaterne i Danmark (large variation in reproductive results in Denmark). Retrieved June 11, 2009, from http://www.lr.dk/kvaeg/informationsserier/kvaegforsk/1929a.htm?print=yesGoogle Scholar
Appuhamy, JADR, Cassell, BG, Cole, JB 2009. Phenotypic and genetic relationships of common health disorders with milk and fat yield persistencies from producer-recorded health data and test-day yields. Journal of Dairy Science 92, 1785–1795.CrossRefGoogle ScholarPubMed
Arbel, R, Bigun, Y, Ezra, E, Sturman, H, Hojman, D 2001. The effect of extended calving intervals in high lactating cows on milk production and profitability. Journal of Dairy Science 84, 600–608.CrossRefGoogle ScholarPubMed
Chassagne, M, Barnouin, J, Chacornac, JP 1999. Risk factors for stillbirth in holstein heifers under field conditions in france: a prospective survey. Theriogenology 51, 1477–1488.Google Scholar
Danish Cattle Organisation 2007. Årsstatistik Avl (annual breeding statistics) 2006–2007. Rapport 118. Retrieved January 14, 2008, from http://www.landbrugsinfo.dk/kvaeg/avl/avlsanalyser/sider/startside.aspx. 118Google Scholar
Danish Cattle Organisation 2009. Dairy herd budgets. Retrieved January 12, 2010 from http://www.landbrugsinfo.dk/Diverse/KA/Filer/Budgetkalkuler_2009_kvaeg.pdfGoogle Scholar
De Vries, A 2004. Economics of delayed replacement when cow performance is seasonal. Journal of Dairy Science 87, 2947–2958.Google Scholar
De Vries, A, Overton, M, Fetrow, J, Leslie, K, Eicker, S, Rogers, G 2008. Exploring the impact of sexed semen on the structure of the dairy industry. Journal of Dairy Science 91, 847–856.Google Scholar
DeJarnette, JM, Nebel, RL, Meek, J, Wells, J, Marshall, CE 2007. Commercial application of sex-sorted semen in Holstein heifers. Journal of Dairy Science 90 (suppl. 1) 228. (Abstract).Google Scholar
Dematawewa, CMB, Berger, PJ 1998. Genetic and phenotypic parameters for 305-day yield, fertility, and survival in Holsteins. Journal of Dairy Science 81, 2700–2709.Google Scholar
Dijkhuizen, AA, Huirne, RBM, Morris, RS 1997. Economic decision making in animal health management. In Animal health economics (ed. AA Dijkhuizen and RS Morris), pp. 13–24. University of Sydney, Sidney South, Australia.Google Scholar
Enemark, PS 2007. Fakta om kodødelighed (facts on cow mortality). Retrieved October 14, 2010, from http://www.lr.dk/kvaeg/informationsserier/kvaegforsk/1734.htm. Kvæginfo 1734.Google Scholar
Falconer, DS, Mackay, TFC 1996. Selection: the response and its prediction. In Introduction to quantitative genetics (ed. DS Falconer), pp. 184–207. Longmans Green Harlow, Essex.Google Scholar
Galon, N 2010. The use of pedometry for estrus detection in dairy cows in Israel. Journal of Reproduction and Development 56, S48–S52.CrossRefGoogle ScholarPubMed
Ghavi Hossein-Zadeh, N, Nejati-Javaremi, A, Miraei-Ashtiani, SR, Kohram, H 2010. Bio-economic evaluation of the use of sexed semen at different conception rates and herd sizes in Holstein populations. Animal Reproduction Science 121, 17–23.CrossRefGoogle Scholar
Groenendaal, H, Galligan, DT, Mulder, HA 2004. An economic spreadsheet model to determine optimal breeding and replacement decisions for dairy cattle. Journal of Dairy Science 87, 2146–2157.CrossRefGoogle ScholarPubMed
Herrero, M, Fawcett, RH, Dent, JB 1999. Bio-economic evaluation of dairy farm management scenarios using integrated simulation and multiple-criteria models. Agricultural Systems 62, 169–188.Google Scholar
Hohenboken, WD 1999. Applications of sexed semen in cattle production. Theriogenology 52, 1421–1433.Google Scholar
Konig, S, Chang, YM, Borstel, UU, Gianola, D, Simianer, H 2008. Genetic and phenotypic relationships among milk urea nitrogen, fertility, and milk yield in Holstein cows. Journal of Dairy Science 91, 4372–4382.Google Scholar
Kristensen, E, Ostergaard, S, Krogh, MA, Enevoldsen, C 2008. Technical indicators of financial performance in the dairy herd. Journal of Dairy Science 91, 620–631.CrossRefGoogle ScholarPubMed
Lidauer, MJ, Pedersen, J, Pösö, J, Mäntysaari, EA, Stranden, I, Madsen, P, Nielsen, US, Eriksson, JA, Johansson, K, Aamand, GP 2006. Joint Nordic test day model: evaluation model. Interbull open meeting, Kuopio, Finland, June 4–6, 2006.Google Scholar
Marsh, WE, Dijkhuizen, AA, Morris, RS 1987. An economic comparison of four culling decision rules for reproductive failure in United States dairy herds using DairyORACLE. Journal of Dairy Science 70, 1274–1280.Google Scholar
Martinez, ML, Freeman, AE, Berger, PJ 1983. Factors affecting calf livability for Holsteins. Journal of Dairy Science 66, 2400–2407.CrossRefGoogle ScholarPubMed
Meyer, CL, Berger, PJ, Koehler, KJ 2000. Interactions among factors affecting stillbirths in Holstein cattle in the United States. Journal of Dairy Science 83, 2657–2663.Google Scholar
Miglior, F, Muir, BL, Van Doormaal, BJ 2005. Selection indices in Holstein cattle of various countries. Journal of Dairy Science 88, 1255–1263.Google Scholar
Nordic Cattle Genetic Evaluation 2010. Nordic cattle genetic evaluation. Retrieved January 24, 2011, from http://www.nordicebv.info/NR/rdonlyres/92DAA130-5330-401D-A898-56FA003B0300/0/CDEBV2010.pdfGoogle Scholar
Olynk, NJ, Wolf, CA 2007. Expected net present value of pure and mixed sexed semen artificial insemination strategies in dairy heifers. Journal of Dairy Science 90, 2569–2576.Google Scholar
Østergaard, S, Chagunda, MGG, Friggens, NC, Bennedsgaard, TW, Klaas, IC 2005a. A stochastic model simulating pathogen-specific mastitis control in a dairy herd. Journal of Dairy Science 88, 4243–4257.CrossRefGoogle Scholar
Østergaard, S, Friggens, NC, Chagunda, MGG 2005b. Technical and economic effects of an inline progesterone indicator in a dairy herd estimated by stochastic simulation. Theriogenology 64, 819–843.CrossRefGoogle Scholar
Sørensen, JT, Østergaard, S 2003. Economic consequences of postponed first insemination of cows in a dairy cattle herd. Livestock Production Science 79, 145–153.Google Scholar
Thomsen, PT, Østergaard, S, Sørensen, JT, Houe, H 2007. Loser cows in Danish dairy herds: definition, prevalence and consequences. Preventive Veterinary Medicine 79, 116–135.CrossRefGoogle Scholar
Van Arendonk, JAM 1985. Studies on the replacement policies in dairy cattle. II. Optimum policy and influence of changes in production and prices. Livestock Production Science 13, 101–121.Google Scholar
Van Vleck, LD, Everett, RW 1976. Genetic value of sexed semen to produce dairy heifers. Journal of Dairy Science 59, 1802–1807.Google Scholar
Veerkamp, RF, Koenen, EPC, de Jong, G 2001. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models. Journal of Dairy Science 84, 2327–2335.CrossRefGoogle ScholarPubMed
Wilmink, JBM 1987. Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation. Livestock Production Science 16, 335–348.Google Scholar
Windig, JJ, Calus, MPL, Beerda, B, Veerkamp, RF 2006. Genetic correlations between milk production and health and fertility depending on herd environment. Journal of Dairy Science 89, 1765–1775.Google Scholar