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Interbull Meeting – Dublin 2007 Genetic Parameters of Butter Hardness Estimated by Test-Day Model Hélène Soyeurt 1,2, F. Dehareng 3, C. Bertozzi 4 & N.

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Presentation on theme: "Interbull Meeting – Dublin 2007 Genetic Parameters of Butter Hardness Estimated by Test-Day Model Hélène Soyeurt 1,2, F. Dehareng 3, C. Bertozzi 4 & N."— Presentation transcript:

1 Interbull Meeting – Dublin 2007 Genetic Parameters of Butter Hardness Estimated by Test-Day Model Hélène Soyeurt 1,2, F. Dehareng 3, C. Bertozzi 4 & N. Gengler 1,5 1 Animal Science Unit, Gembloux Agricultural University, B-5030 Gembloux, Belgium 2 Fond pour la Recherche dans l’Industrie et l’Agriculture (F.R.I.A.), B-1000 Brussels, Belgium 3 Quality Department, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium 4 Research & Development Department, Walloon Breeders Association, B-5590 Ciney, Belgium 5 National Fund for Scientific Research (F.N.R.S.), B-1000 Brussels, Belgium

2 Introduction  Fatty acids (FA) composition influences the technological properties of butter  Already Coulter and Hill (1934) showed breed differences:  Butter of Channel Island was firmer than the one produced by Holstein or Ayrshire cows  Bobe et al. (2003):   UNSAT   spreadable, softer and less adhesive  Phenotypic variation in FA composition among cows fed with the same diet was sufficient to produce butter with different textural properties.

3 Objectives  Estimate the genetic parameters of the hardness of butter and  Estimate its correlations with milk yield, fat and protein contents using a multi-trait random regression test-day model.

4 Materials & Methods  Data:  Cows  85% Holstein in the first lactation  3,853 spectral test-day records Between April 2005 and May 2007 Walloon milk recording MilkoScan FT6000  1,099 cows in 87 herds  Added historical data for cows and herds First lactation test-day milk yields, %FAT, %PROT  Final data: 57,759 test-day records from 7,070 cows

5 Materials & Methods  Prediction of FA:  Soyeurt et al. (2006) : capillary column of 50m length  New calibration equations : capillary column of 100m length R²cv for SAT = 0.97 R²cv for UNSAT = 0.93  Hardness of butter : SAT/UNSAT

6 Materials & Methods  Estimation of (co)variance components:  Multi-trait random regression model: Milk yield, %FAT, %PROT and SAT/UNSAT  Fixed effects: Herd * test day Class of 15 DIM ( 365 were deleted) Class of age (<29 mo, 29-32 mo and  33 mo)  Random effects: Random regressions: –Herd*calving year –Permanent environment –Animal genetic effect Residual effects considered independent

7 Results & Discussion Table 1. Heritability estimates on lactation and average daily heritability values calculated for all studied traits.

8 Results & Discussion Table 2. Phenotypic (above the diagonal) and genetic correlations (below the diagonal) among studied traits. Phenotypic correlation close to 0 suggested no dilution effect Strong negatively genetic correlations with milk yield

9 Results & Discussion Table 2. Phenotypic (above the diagonal) and genetic correlations (below the diagonal) among studied traits. Hardness of butter was affected by milk composition Stronger link between %FAT and SAT/UNSAT

10 Results & Discussion Figure 1. Phenotypic correlations among traits within DIM.  Milk – SAT/UNSAT  Linear increase  Dilution effect  %FAT – SAT/UNSAT  Strong link  Increased when %FAT decreased  %PROT-SAT/UNSAT  Stable

11 Results & Discussion Figure 2. Genetic correlations among traits within DIM.  Higher than phenotypic correlations  Milk – SAT/UNSAT  Dilution effect  %FAT – SAT/UNSAT  Strong link  %PROT-SAT/UNSAT  Stable

12 Conclusion & Perspectives  First results:  Genetic variability of the hardness of butter seemed to exist  Affected by milk production  Influenced by the variation of %FAT but less by the variation of %PROT  Perspectives:  From Sept. 2007, all spectra will be recorded  In a few years, more data will be available for modeling and potential genetic evaluations

13 Thank you for your attention Acknowledgement : Study supported of FRIA through grant scholarship and FNRS through grants F.4552.05 and 2.4507.02 Corresponding author : Hélène Soyeurt Passage des Déportés, 2 5030 Gembloux BELGIUM E-mail : soyeurt.h@fsagx.ac.besoyeurt.h@fsagx.ac.be


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