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Environmental effects on lactation curves included in a test-day model genetic evaluation

Published online by Cambridge University Press:  01 March 2008

H. Leclerc ,
D. Duclos ,
A. Barbat ,
T. Druet  and
V. Ducrocq
H. Leclerc*
Affiliation:
UR337, Station de Génétique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France
D. Duclos
Affiliation:
UR337, Station de Génétique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France
A. Barbat
Affiliation:
UR337, Station de Génétique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France
T. Druet
Affiliation:
UR337, Station de Génétique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France
V. Ducrocq
Affiliation:
UR337, Station de Génétique Quantitative et Appliquée, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France
*
E-mail: helene.leclerc@jouy.inra.fr
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Abstract

A large number of environmental factors affect the daily milk production of a cow. Lactation curves included in the French test-day model are modelled as a function of days in milk with semi-parametric curves (splines). The proper modelling of environmental effects in the test-day analysis was investigated using test-day records collected from the first three lactations of French Montbéliarde cows from 1988 to 2005. Four lactation-curve effects describing calving month, length of dry period, age at calving and gestation defined within parity-class were fitted. The shape of lactation curves did not depend on year of calving, which can be modelled as a constant over the whole lactation. To reduce computational requirements and time, data were pre-adjusted in a first step for fixed effects with no year interaction, and then used for genetic evaluation. Correlations for each lactation between 305-day estimates of genetic and permanent environment effects computed using pre-adjustment factors obtained at a 4-year interval were virtually one. The use of a two-step procedure had a very limited impact on the estimates of genetic and permanent environment effects. The minimum correlations with values estimated with a one-step procedure were 0.9984 and 0.9974, respectively. The knowledge of systematic environmental effects affecting the cow daily yield through lactation curves offers interesting perspectives to predict future daily milk production.

Keywords

dairy cowsenvironmental factorsgenetic evaluationlactation curvetest-day model
Type
Full Paper
Information
animal , Volume 2 , Issue 3 , March 2008 , pp. 344 - 353
Copyright
Copyright © The Animal Consortium 2008

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References

Bauman, DE, Currie, WB 1980. Partitioning of nutrients during pregnancy and lactation: a review of mechanisms involving homeostasis and homeorhesis. Journal of Dairy Science 63, 1514–1529.CrossRefGoogle ScholarPubMed
Bohmanova J, Miglior F, Kelly M, Kistemaker G and Loker S 2006. Effect of pregnancy on milk yield of Canadian dairy cattle. Retrieved September 17, 2007, from http://www.aps.uoguelph.ca/~jbohmano/publication/report_08.pdfGoogle Scholar
Canavesi F, Biffani S and Nicolazzi EL 2007. Three versus four traits random regression test-day model genetic evaluation for the Holstein breed in Italy. In Proceedings of the 58th Annual Meeting of the European Association for Animal Production, Dublin, 26–29 August, p. 64 (abstract).Google Scholar
Coulon, JB, Pérochon, L, Lescourret, F 1995. Modelling the effect of the stage of pregnancy on dairy cow’s milk yield. Animal Science 60, 401–408.Google Scholar
Danell, B 1982. Studies on lactation yield and individual test-day yields of Swedish dairy cows. I. Environmental influence and development of adjustment factors. Acta Agriculturæ Scandinavica 32, 65–81.Google Scholar
Druet, T, Jaffrézic, F, Boichard, D, Ducrocq, V 2003. Modeling lactation curves and estimation of genetic parameters for first lactation test-day records of French Holstein cows. Journal of Dairy Science 86, 2480–2490.Google Scholar
Druet, T, Jaffrézic, F, Ducrocq, V 2005. Estimation of genetic parameters for test day records of dairy traits in the first three lactations. Genetics Selection Evolution 37, 257–271.CrossRefGoogle ScholarPubMed
Institut de l’Elevage and France Contrôle Laitier 2005. Le règlement technique du contrôle laitier zootechnique des espèces bovine et caprine et annexes. Retrieved April 17, 2007, from http://www.inst-elevage.asso.fr/html1/rubrique.php3?id_rubrique=648Google Scholar
Interbull 2007. Description of National Genetic Evaluation Systems for dairy cattle traits as applied in different Interbull member countries. Retrieved April 17, 2007, from http://www-interbull.slu.se/national_ges_info2/framesida-ges.htmGoogle Scholar
International Committee for Animal Recording 2005. International agreement of recording practices – guidelines approved by the general assembly held in Sousse, Tunisia, June 2004. ICAR, Rome, Italy.Google Scholar
Jensen, J 2001. Genetic evaluation of dairy cattle using test-day models. Journal of Dairy Science 84, 2803–2812.CrossRefGoogle ScholarPubMed
Lidauer, M, Mäntysaari, EA, Strandén, I 2003. Comparision of test-day models for genetic evaluation of production traits in dairy cattle. Livestock Production Science 79, 73–86.CrossRefGoogle Scholar
Louca, A, Legates, JE 1968. Production losses in dairy cattle due to days open. Journal of Dairy Science 51, 573–583.Google Scholar
Mao, IL, Wilton, JW, Freeman, MG 1972. The effect of parity on age adjustment for milk and fat yield. Journal of Dairy Science 55 (Suppl. 1), 716.Google Scholar
Mayeres, P, Stoll, J, Bormann, J, Reents, R, Gengler, N 2004. Prediction of daily milk, fat and protein production by a random regression test-day model. Journal of Dairy Science 87, 1925–1933.CrossRefGoogle ScholarPubMed
Oltenacu, PA, Rounsaville, TR, Milligan, RA, Hintz, RL 1980. Relationship between days open and cumulative milk yield at various intervals from parturition from high and low producing cows. Journal of Dairy Science 63, 1317–1327.Google Scholar
Pérochon, L, Coulon, JB, Lescourret, F 1996. Modelling lactation curves of dairy cows with emphasis on individual variability. Animal Science 63, 189–200.CrossRefGoogle Scholar
Ptak, E, Horst, HS, Schaeffer, LR 1993. Interaction of age and month of calving with year of calving for production traits of Ontario Holsteins. Journal of Dairy Science 76, 3792–3798.Google Scholar
Schaeffer, LR, Henderson, CR 1972. Effects of days dry and days open on Holstein milk production. Journal of Dairy Science 55, 107–112.Google Scholar
Swalve, HH 2000. Theoretical basis and computational methods for different test-day genetic evaluation methods. Journal of Dairy Science 83, 1115–1124.Google Scholar
White, IMS, Thompson, R, Brotherstone, S 1999. Genetic and environmental smoothing of lactation curves with cubic splines. Journal of Dairy Science 82, 632–638.Google Scholar
Wilmink, JBM 1987a. Adjustment of lactation yield for age at calving in relation to level of production. Livestock Production Science 16, 321–334.CrossRefGoogle Scholar
Wilmink, JBM 1987b. Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation. Livestock Production Science 16, 335–348.Google Scholar
Wood, PDP 1969. Factors affecting the shape of the lactation curve in cattle. Animal Production 11, 307–316.Google Scholar