Document Type : Research Paper

Authors

1 Department of Animal Sciences, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

2 Department of Animal Science, Faculty of Agriculture, Isfahan University of Technology, Isfahan-Iran

3 Department of Animal Science, Faculty of Agricultura, Bu-Ali Sina University, Hamedan, Iran.

Abstract

The aim of this study was to estimate the economic values for residual feed intake and some production and performance traits in Iranian Holstein dairy cow. For this purpose, trait by trait or multiple traits of bio-economic modeling along with production and economic data were used. These data were collected from seven large herds of dairy cows in 2020. The economic values of the residual feed intake was calculated in four different age groups. The diets of different groups were formulated using CNCPS software. Index economic weights (multiplication of the economic values by discounted genetic expressions, in Rial and one cow per year) on average at the level of the studied farms were estimated to be IRR 14280 per kg of milk yield; IRR 291060 per kg of fat yield; IRR 232260 per kg of protein yield; IRR - 790860 per kg of residual feed intake; IRR 702588 per month of longevity and IRR- 113820 per day of days open. The sensitivity analysis showed that the price of concentrate ingredients has a greater effect on the economic value of the residual feed intake than of forage ingredients. In the genetic- economic analysis, the milk production with a relative emphasis of 50 percent was the most important trait in the breeding of Iranian dairy cows, while the relative emphasis on feed efficiency was only about 5 percent. The results of this research provide valuable information for economic values of traits that can be used to complete the national selection index and cost-benefit analysis.

Keywords

  1. Bauman DE, McCutcheon SN, Steinhour WD, Eppard PJ and Sechen SJ (1985) Sources of variation and prospects for improvement of productive efficiency in the dairy cow. A review Journal of Animal Science, 60: 583-592.
  2. ByrneTJ, Santos BFS, Amer pr, Martin-Collado D, Pryce JE and Axford M (2016) New breeding objectives and selection indices for the Australian dairy industry. Journal of Dairy Science, 99: 1-22.
  3. Connor E.E (2015) Invited review: Improving feed efficiency in dairy production: challenges and possibilities. Animal, 9: 395-408.
  4. Difford GF, Lovendahl P, Veerkamp RF, Bovenhuis H, Visker MHPW, Lassen J and de Haas Y (2019) Can greenhouse gases in breath be used to genetically improve feed efficiency of dairy cows?. Journal of Dairy Science, 103 (3): 2019-16966.
  5. Ghiasi H, Nejati-Javaremi A, Pakdel A and Gonzalez-Recio O (2013) Selection strategies for fertility traits of Holstein cows in Iran. Livestock, 152: 11-15.
  6. Gonzalez-recio O, Coffey MP and Pryce JE (2014) On the value of the phenotypes in the genomic era. On the value of the phenotypes in the genomic era, 97: 7905-7915.
  7. Groen AF (1989) Cattle breeding goals and production circumstanc- es. PhD Thesis. Wageningen Agricultural University, Wageningen, the Netherlands.
  8. Hazel LN and Lush JL (1942) The efficiency of three methods of selection. Journal of Heredity, 33: 393-399.

 

  1. Hietala P, Wolfová M, Wolf J, Kantanen J and Juga J (2014) Economic values of production and functional traits, including residual feed intake, in Finnish milk production. Journal of Dairy Science, 97: 1092-1106.
  2. Kokko P (2017) Towards more profitable and sustainable milk and beef production system. University of Helsinki, Ph.D. Dissertation.
  3. Krupova Z, Krupa, E, Michalickova M, Wolfova M and KasardaR (2016) Economic values for health and feed efficiency traits of dual-purpose cattle in marginal areas. Journal of Dairy Science, 99: 644-656.
  4. Manzanilla-Pech CIV, Verkeekamp, RF, Templeman RJ, van Pelt ML, Weigel KA, VanderHaar M, Lawlor TJ, Spurlock DM, Armentano LE, Staples CR, Hanigan M and De Haas Y (2016) Genetic parameters between feed- intake-related traits and conformation in 2 separate dairy populations-the Netherlands and United States. Journal of Dairy Science, 99: 443-457.
  5. McGilliard ML, Swisher JM and James RE (1983) Grouping lactating cows by nutritional requirements for feeding. Journal of Dairy Science, 663: 1084-1093.
  6. NRC I (2001) Nutrient requirements of dairy cattle. National Research Council 519.
  7. Pryce J, Gonzalez-Recio O, Nieuwhof G, Wales W, Coffey M, Hayes B and Goddard M (2015) Hot topic: Definition and implementation of a breeding value for feed efficiency in dairy cows. Journal of Dairy Science, 98: 7340-7350.
  8. Pryce JE, Coffey MP and Simm G (2001) The relationship between body condition score and reproductive performance. Journal of Dairy Science, 84: 1508-1515.
  9. Sadeghi-Sefidmazgi A, Moradi-Shahrbabak M, Nejati-Javaremi A, Miraei-Ashtiani SR and Amer PA (2012) Breeding objectives for Holstein dairy cattle in Iran. Journal of Dairy Science, 95: 3406-3418.
  10. Stephansen RB, Lassen J, Ettema JF, Sørensen LP and Kargo M (2021) Economic value of residual feed intake in dairy cattle breeding goals. Livestock Science, 21: 1871-1413.
  11. Thoma G, Popp J, Nutter D, Shonnard D, Ulrich R, Matlock M, Ulrich R, Kellogg W, Soo Kim D, Neiderman Z, Kemper N, East E and Adom F (2013) Greenhouse gas emissions from milk production and consumption in the United States. International Dairy Journal, 31: S3-S14.
  12. Vallimont JE, Dechow CD, Daubert JM, Dekleva MW, Blum JW, Barlieb CM, Liu W, Varga GA, Heinrichs AJ and Baumrucker CR (2011) Short communication: Heritability of gross feed efficiency and associations with yield, intake, residual intake, body weight, and body condition score in 11 commercial Pennsylvania tie stalls. Journal of Dairy Science, 94: 2108- 2113.
  13. VanRaden PM (2004) Invited Review: Selection on Net Merit to Improve Lifetime Profit. Journal of Dairy Science, 87: 3125-3131.
  14. Veerkamp RF, Simm G and Oldham JD (1994) Effects of interaction between genotype and feeding system on milk production, feed intake, efficiency and body tissue mobiliza- tion in dairy cows. Livestock Production Science, 39(3): 229-241.
  15. Williams CB and Oltenacu PA (1992) Evaluation of criteria used to group lactating cows using a dairy production model. On the value of the phenotypes in the genomic era. Journal of Dairy Science, 75: 155-160.
  16. Yan T, Gordon FJ, Agnew RE, Porter MG and Patterson DC (1997) The metabolisable energy requirement for maintenance and the efficiency of utilisation of metabolisable energy for lactation by dairy cows offered grass silage-based diets. Livestock Production Science, 51: 141-150.