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Bio-economic model to evaluate twinning rate using sexed embryo transfer in dairy herds

Published online by Cambridge University Press:  13 June 2011

N. Ghavi Hossein-Zadeh ,
A. Nejati-Javaremi ,
S. R. Miraei-Ashtiani ,
H. Kohram  and
M. Honarvar
N. Ghavi Hossein-Zadeh*
Affiliation:
Department of Animal Science, Faculty of Agriculture, University of Guilan, PO Box: 41635-1314, Rasht, Iran
A. Nejati-Javaremi
Affiliation:
Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, PO Box: 31587-77871, Karaj, Iran
S. R. Miraei-Ashtiani
Affiliation:
Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, PO Box: 31587-77871, Karaj, Iran
H. Kohram
Affiliation:
Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, PO Box: 31587-77871, Karaj, Iran
M. Honarvar
Affiliation:
Department of Animal Science, Faculty of Agriculture, Azad University of Shahriar Shahr-e-Qods, Iran
*
†E-mail: [email protected] or [email protected]
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Abstract

A stochastic bio-economic model has been used to determine the effects of new reproductive technologies over a 15-year period. A strategy of using conventional artificial insemination (AI) or embryo transfer (ET) using two sex-controlled embryos at different conception rates (CRs) and herd sizes resulted in a 24 state model. The genetic means of AI population increased over the years, and the genetic means of milk production for all of the embryo strategies were greater than those of AI. In addition, the genetic means of milk yield using different embryo-based scenarios in the expanding herds were greater than those for the fixed herds. The net profit of using sexed ET in the expanding herds was greater (P < 0.05) than that of fixed size herds. In general, there was a roughly consistent trend in net profit per cow for sexed ET strategies in the expanding herds over the years, but there was an increasing trend in net profit per cow for sexed ET strategies in the fixed herds over the years. Medium to high CRs for ET and the use of sex-controlled embryo systems, especially for induction of twin births to produce dairy replacements, will be critical elements of a system that produces significant numbers of female calves. The greater number of female calves produced in the sex-controlled scenarios allows the farmer to select animals with the best genetic potential as dairy replacement heifers; therefore, the rate of genetic gain increased in the dairy herd. Results of sensitivity analyses showed that a significant decrease in the production costs and increase in the ET performance are essential for embryo-based technologies to be profitable.

Keywords

sexed embryoartificial inseminationtwinningbio-economic modelmilk yield
Type
Full Paper
Information
animal , Volume 5 , Issue 11 , 26 September 2011 , pp. 1705 - 1719
Copyright
Copyright © The Animal Consortium 2011

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References

Allore, HG, Schruben, LW, Erb, HN, Oltenacu, PA 1998. Design and validation of a dynamic discrete event stochastic simulation model of mastitis control in dairy herds. Journal of Dairy Science 81, 703–717.CrossRefGoogle ScholarPubMed
Beerepoot, GMM, Dykhuzen, AA, Nielen, M, Schukken, YH 1992. The economics of naturally occurring twinning in dairy cattle. Journal of Dairy Science 75, 1044–1051.CrossRefGoogle ScholarPubMed
Britt, JH, Scott, RG, Armstrong, JD, Whitacre, MD 1986. Determinants of estrous behavior in lactating Holstein cows. Journal of Dairy Science 69, 2195–2202.CrossRefGoogle ScholarPubMed
Buoen, LC, Zhang, TQ, Wever, AF, Ruth, GR 1992. Non-freemartin rate in Holstein heterosexual twins. American Association of Bovine Practitioners Conference 1, 300–303.CrossRefGoogle Scholar
Cady, RA, Van Vleck, LD 1978. Factors affecting twinning and effects of twinning in Holstein dairy cattle. Journal of Animal Science 46, 950–956.CrossRefGoogle Scholar
Caraviello, DZ, Wiegel, KA, Fricke, PM, Wiltbank, MC, Florent, MJ, Cook, NB, Nordlund, KV, Zwald, NR, Rawson, CL 2006. Survey of management practices on reproductive performance of dairy cattle on large US commercial farms. Journal of Dairy Science 89, 4723–4735.CrossRefGoogle ScholarPubMed
Colleau, JJ 1992. Combining embryo sexing and cloning in closed mixed MOET for selection in dairy cattle. Genetics Selection Evolution 24, 345–361.CrossRefGoogle 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
Dohoo, IR 1993. Monitoring livestock health and production: service – epidemiology's last frontier? Preventive Veterinary Medicine 18, 43–52.Google Scholar
Faber, DC, Ferré, LB 2004. Advancements in reproductive technology in cattle. Proceedings of Beef Improvement Federation. Retrieved June 4, 2011, from http://www.beefimprovement.org/proceedings/04proceedings/faber.pdf.Google Scholar
Fricke, PM 2001. Review: twinning in dairy cattle. Professional Animal Scientist 17, 61–67.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N 2010a. The effect of twinning on milk yield, dystocia, calf birth weight and open days in Holstein dairy cows of Iran. Journal of Animal Physiology and Animal Nutrition 94, 780–787.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N 2010b. Evaluation of the genetic trend of milk yield in the multiple ovulation and embryo transfer populations of dairy cows, using stochastic simulation. Comptes Rendus Biologies 333, 710–715.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N, Nejati-Javaremi, A, Miraei-Ashtiani, SR, Kohram, H 2008. An observational analysis of twin births, calf stillbirth, calf sex ratio, and abortion in Iranian Holsteins. Journal of Dairy Science 91, 4198–4205.CrossRefGoogle Scholar
Ghavi Hossein-Zadeh, N, Nejati-Javaremi, A, Miraei-Ashtiani, SR, Kohram, H 2009. Estimation of variance components and genetic trends for twinning rate in Holstein dairy cattle of Iran. Journal of Dairy Science 92, 3411–3421.Google Scholar
Ghavi Hossein-Zadeh, N, Nejati-Javaremi, A, Miraei-Ashtiani, SR, Kohram, H 2010. Bioeconomic 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.Google Scholar
Herd, RM, Bootle, BW, Parfett, DC 1993. An economic evaluation of traditional, twinning and sex-controlled systems of beef production in southern Australia. Australian Journal of Agricultural Research 44, 1541–1556.Google Scholar
Honarvar, M, Nejati Javaremi, A, Miraei Ashtiani, SR, Dehghan Banadaky, M 2010. Effect of length of productive life on genetic trend of milk production and profitability: a simulation study. African Journal of Biotechnology 9, 3000–3010.Google Scholar
Imke, JM, De Boer, IJM, Van Arendonk, JAM 1994. Market share for semen and cloned embryos in dairy herds. Journal of Dairy Science 77, 3691–3703.Google Scholar
Jeon, GJ, Mao, LL, Jensen, J, Ferris, TA 1990. Stochastic modeling of multiple ovulation and embryo transfer breeding schemes in small closed dairy cattle populations. Journal of Dairy Science 73, 938–1944.CrossRefGoogle ScholarPubMed
Korver, S, Van Arendonk, JAM, Koops, WJ 1985. A function for live-weight change between two calvings in dairy cattle. Animal Production 40, 233–241.Google Scholar
Kosgey, IS, Kahi, AK, Van Arendonk, JA 2005. Evaluation of closed adult nucleus multiple ovulation and embryo transfer and conventional progeny testing breeding schemes for milk production in tropical crossbred cattle. Journal of Dairy Science 88, 1582–1594.CrossRefGoogle ScholarPubMed
Macmillan, KL, Henry, RI, Taufa, VK, Phillips, P 1990. Calving patterns in seasonal dairy herds. New Zealand Veterinary Journal 38, 151–155.Google Scholar
National Research Council 2001. Nutrient requirements of dairy cattle, 7th edition. National Academy of Sciences, Washington, DC.Google Scholar
Nebel, RL, Jobst, SM 1998. Evaluation of systematic breeding programs for lactating dairy cows: a review. Journal of Dairy Science 81, 1169–1174.CrossRefGoogle ScholarPubMed
Olds, D, Cooper, T, Thrift, FA 1979. Relationship between milk yield and fertility in dairy cattle. Journal of Dairy Science 62, 1140–1144.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Olynk, NJ, Wolf, CA 2008. Economic analysis of reproductive management strategies on US commercial dairy farms. Journal of Dairy Science 91, 4082–4091.Google Scholar
Peixoto, MGCD, Verneque, RS, Teodoro, RL, Penna, VM, Martinez, ML 2006. Genetic trend for milk yield in Guzerat herds participating in progeny testing and MOET nucleus schemes. Genetics and Molecular Research 5, 454–465.Google ScholarPubMed
Reneau, JK, Kinsel, ML (ed. WD Herd Health) 2001. Record systems and herd monitoring in production-oriented health and management programs in food producing animals. Saunders Company, Philadelphia, PA.Google Scholar
SAS Institute 2002. User's guide: statistics, version 9.1 Edition. SAS Inst., Inc., Cary, NC.Google Scholar
JrSeidel, GE 2003. Economics of selecting for sex: the most important genetic trait. Theriogenology 59, 585–598.Google Scholar
Silva del Río, N, Stewart, S, Rapnicki, P, Chang, YM, Fricke, PM 2007. An observational analysis of twin births, calf sex ratio, and calf mortality in Holstein dairy cattle. Journal of Dairy Science 90, 1255–1264.Google Scholar
Smeaton, DC, Vivanco, WH 2001. Potential benefits from new reproductive technologies in commercial dairy herds a case study simulation. Proceeding of New Zealand Society of Animal Production 61, 199–202.Google Scholar
Smeaton, DC, Vivanco, WH 2002. Profitability of the use of new reproductive technologies in beef production systems. Proceeding of New Zealand Society of Animal Production 62, 133–137.Google Scholar
Smeaton, DC, Harris, BL, Xu, ZZ, Vivanco, WH 2003. Factors affecting commercial application of embryo technologies in New Zealand: modelling approach. Theriogenology 59, 617–634.CrossRefGoogle ScholarPubMed
Tian, YQ, McCall, DG, McMillan, WH 1999. The potential for use of surplus dairy herd reproductive capacity for beef production. New Zealand Journal of Agricultural Research 42, 405–414.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.CrossRefGoogle Scholar
Wood, PDP 1967. Algebraic model of the lactation curve in cattle. Nature 216, 164–165.Google Scholar
Yates, CM, Rehman, T, Chamberlain, AT 1996. Evaluation of the potential effects of embryo transfer on milk production on commercial dairy herds: the development of a Markov chain model. Agricultural systems 50, 65–79.Google Scholar