References of "Soyeurt, Hélène"
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See detailMid-infrared predictions of lactoferrin content in bovine milk
Soyeurt, Hélène ULg; Bastin, Catherine ULg; Colinet, Frédéric ULg et al

in Journal of Dairy Science (2011), 94(E-suppl.1), 714

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study ... [more ▼]

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study reported the potential to quantify LF from the mid-infrared (MIR) spectrometry from 69 milk samples. Through the European RobustMilk project (www.robustmilk.eu), 3,606 milk samples were collected in Belgium, Ireland, and Scotland from individual cows and analyzed using a MIR MilkoScanFT6000 spectrometer. Milk LF content was quantified using ELISA in duplicate. Average ELISA data with a CV lower than 5% were used. After the detection of spectral and ELISA outliers, the calibration set contained 2,499 samples. An equation to predict LF content from MIR was developed using partial least squared regression. A first derivative pre-treatment of spectra was used to correct the baseline drift. To improve the repeatability of the spectral data, a file which contained the spectra of samples analyzed on 5 spectrometers was used during the calibration. The lactoferrin mean was 159.28 mg/l of milk with a SD of 97.21 mg/l of milk. The calibration (C) coefficient of determination (R2) was equal to 0.73 with a standard error (SE) of calibration of 50.54 mg/l of milk. A cross-validation (CV) was used to assess the robustness of the equation. R2 CV was 0.72 with a SE-CV of 51.16 mg/l of milk. An external validation (V) was conducted on 150 milk samples collected in Belgium. The SE of prediction (SEP) was 59.17 mg/L of milk. The similarity between R2 C and R2CV as well as between SE-C and SE-CV and between SE-CV and SEP confirms the equations developed are robust. The correlation between predicted and measured LF values was 0.71. This lower value compared with the one obtained from the calibration set (0.85) could be explained by the low ELISA reproducibility (16.24% ± 25.51%). If the developed equation is used to clean the validation data set, a total of 16 samples can be deleted. The validation coefficient for these 134 samples increased to 0.82. From these results, the developed equation could be used for screening the dairy cow population for breeding purposes. [less ▲]

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See detailPhenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows.
Bastin, Catherine ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in Journal of Dairy Science (2011), 94(8), 4152-63

The objective of this study was to assess the phenotypic and genetic variability of production traits and milk fatty acid (FA) contents throughout lactation. Genetic parameters for milk, fat, and protein ... [more ▼]

The objective of this study was to assess the phenotypic and genetic variability of production traits and milk fatty acid (FA) contents throughout lactation. Genetic parameters for milk, fat, and protein yields, fat and protein contents, and 19 groups and individual FA contents in milk were estimated for first-parity Holstein cows in the Walloon Region of Belgium using single-trait, test-day animal models and random regressions. Data included 130,285 records from 26,166 cows in 531 herds. Heritabilities indicated that de novo synthesized FA were under stronger genetic control than FA originating from the diet and from body fat mobilization. Estimates for saturated short- and medium-chain individual FA ranged from 0.35 for C4:0 to 0.44 for C8:0, whereas those for monounsaturated long-chain individual FA were lower (around 0.18). Moreover, de novo synthesized FA were more heritable in mid to late lactation. Approximate daily genetic correlations among traits were calculated as correlations between daily breeding values for days in milk between 5 and 305. Averaged daily genetic correlations between milk yield and FA contents did not vary strongly among FA (around -0.35) but they varied strongly across days in milk, especially in early lactation. Results indicate that cows selected for high milk yield in early lactation would have lower de novo synthesized FA contents in milk but a slightly higher content of C18:1 cis-9, indicating that such cows might mobilize body fat reserves. Genetic correlations among FA emphasized the combination of FA according to their origin: contents in milk of de novo FA were highly correlated with each other (from 0.64 to 0.99). Results also showed that genetic correlations between C18:1 cis-9 and other FA varied strongly during the first 100 d in milk and reinforced the statement that the release of long-chain FA inhibits FA synthesis in the mammary gland while the cow is in negative energy balance. Finally, results showed that the FA profile in milk changed during the lactation phenotypically and genetically, emphasizing the relationship between the physiological status of cow and milk composition. [less ▲]

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See detailPotential of near infrared spectroscopy for on-line analysis at the milking parlour using a fiber-optic probe presentation
Nguyen, Hoang Nam; Dehareng, Frédéric; Hammida, Mohamed et al

in NIR news (2011), 22

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See detailNew method to combine molecular and pedigree relationships
Bömcke, Elisabeth ULg; Soyeurt, Hélène ULg; Szydlowski, Maciej et al

in Journal of Animal Science (2011), 89

Relationship coefficients are traditionally based on pedigree data. Today, with the development of molecular techniques, they are often completely replaced by coefficients calculated from molecular data ... [more ▼]

Relationship coefficients are traditionally based on pedigree data. Today, with the development of molecular techniques, they are often completely replaced by coefficients calculated from molecular data. Examples are relationships from microsatellites for biodiversity studies but also genomic relationships from SNP as currently used in genomic prediction of breeding values. There are, however, many situations in which optimal combination of both sources would be the best solutions. Obviously, this is the case for incompletely genotyped populations, but also when pedigree information is sparse. Also, markers, even dense ones, do not reflect the whole genome and therefore give only an incomplete picture of relationships. The main objective of this study was therefore to develop a method to calculate a relationship matrix by the combination of molecular and pedigree data. It will be useful for all situations where pedigree and molecular data are available. In this study, based on simulations of pedigree and marker data, we used partial least squares regression and linear regression to combine total allelic relationship coefficients calculated for each marker with additive relationship coefficients calculated from incomplete pedigree. The results showed that the greatest advantage of this method, compared with the one that replaces a part of the pedigree-based relationship matrix by a genomic relationship matrix, is that adding the partial pedigree data allows for the correction of the molecular coefficient for the ungenotyped part of the genome. [less ▲]

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See detailAcross breed and country validation of mid-infrared calibration equations to predict milk fat composition
Maurice - Van Eijndhoven, Myrthe; Soyeurt, Hélène ULg; Dehareng, Frédéric et al

in Book of Abstracts of the 62nd Annual Meeting of the European Association for Animal Production (2011)

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See detailThe use of mid-infrared spectrometry to predict body energy status of Holstein cows
McParland, Sinead; Banos, Giorgios; Wall, Eileen et al

in Journal of Dairy Science (2011), 94

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See detailIs there value in maintaining small populations ? Example of the Dual-Purpose Belgian Blue breed.
Gengler, Nicolas ULg; Soyeurt, Hélène ULg; Bastin, Catherine ULg et al

in Journal of Dairy Science (2011), 94(E-suppl.1), 664

Current status of thinking on genomic selection in dairy cattle is mostly major breed centric (e.g., Holstein) and only for traditional traits (e.g., milk yields). Once you depart from this, it becomes ... [more ▼]

Current status of thinking on genomic selection in dairy cattle is mostly major breed centric (e.g., Holstein) and only for traditional traits (e.g., milk yields). Once you depart from this, it becomes obvious that different, often related, issues appear (e.g., lack of large training populations, need for expensive recording of new phenotypes). Also, there is an urgent need to rethink issues that are important for sustainability of dairy production (e.g., added value foods, animal robustness). In this context, small populations (breeds/lines) could represent a potential source of extra information to justify their maintenance. As marker densities increase, efficient dissection of different selection histories of divergent breeds or lines, potentially identifying pockets of unexploited variability will increase. A current example from the Belgian (Walloon) perspective is the Dual Purpose (DP) line of the Belgian Blue Breed (BBB), with presently around 4500 breeding females, for historical reason of which only 1500 have good pedigrees, and which is present in Belgium and northern France. Recent research, done on this line, showed its tendency to produce less saturated milk fat and to have better fertility. Results indicated that it could stay competitive in specific markets, especially because of largely increased meat value. Currently, the myostatin mutation is largely used for breeding purposes. To assess the genetic diversity of the breed, recently, over 200 genotypes (SNP50K) for nearly all breeding bulls of the last 20 years became available. HD genotypes should be available in the near future, also allowing to access selection history of this breed as being in between the 2 extreme breeds: Beef BBB (with which it shares a recent history) and Holstein-Friesian (which is related through its geographic proximity over centuries). Finally, genomic selection for DP-BBB will need to consider a single step type approach without the need of reference population and potentially relying heavily on SNP3K of cows, also with the objective to recreate relationships between animals of interest. [less ▲]

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See detailShort communication: Genetic variation of saturated fatty acids in Holsteins in the Walloon region of Belgium
Arnould, Valérie ULg; Hammami, Hedi ULg; Soyeurt, Hélène ULg et al

in Journal of Dairy Science (2010), 93

Random regression test-day models using Legendre polynomials are commonly used for the estimation of genetic parameters and genetic evaluation for test-day milk production traits. However, some ... [more ▼]

Random regression test-day models using Legendre polynomials are commonly used for the estimation of genetic parameters and genetic evaluation for test-day milk production traits. However, some researchers have reported that these models present some undesirable properties such as the overestimation of variances at the edges of lactation. Describing genetic variation of saturated fatty acids expressed in milk fat might require the testing of different models. Therefore, 3 different functions were used and compared to take into account the lactation curve: (1) Legendre polynomials with the same order as currently applied for genetic model for production traits; 2) linear splines with 10 knots; and 3) linear splines with the same 10 knots reduced to 3 parameters. The criteria used were Akaike’s information and Bayesian information criteria, percentage square biases, and log-likelihood function. These criteria indentified Legendre polynomials and linear splines with 10 knots reduced to 3 parameters models as the most useful. Reducing more complex models using eigenvalues seemed appealing because the resulting models are less time demanding and can reduce convergence difficulties, because convergence properties also seemed to be improved. Finally, the results showed that the reduced spline model was very similar to the Legendre polynomials model. [less ▲]

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See detailGenetic parameters of mastitis-correlated milk components in first parity dairy cows
Gillon, Alain ULg; Bastin, Catherine ULg; Soyeurt, Hélène ULg et al

Conference (2010, August 06)

Ind. of lactoferrin content, ind. of Na content, and lactose content were the three most correlated milk components with somatic cell score among available milk components predicted by mid-infrared ... [more ▼]

Ind. of lactoferrin content, ind. of Na content, and lactose content were the three most correlated milk components with somatic cell score among available milk components predicted by mid-infrared spectrometry on 590,083 test-day records from Walloon Region of Belgium collected between 2007 and 2009. Mean daily heritabilities and mean genetic correlations of these four traits were estimated using Gibbs sampling methodology applied to a multi-trait random regression test-day model with a subset of these records. Mean daily heritabilities of ind. lactoferrin content (0.34), ind. Na content (0.37) and lactose content (0.42) were higher then SCS (0.16) and mean genetic correlations were moderate (from -0.18 to -0.73), showing that these traits could be used together to describe udder health in genetic evaluations instead of SCS alone when clinical mastitis data are not available. [less ▲]

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See detailPredicting Energy Balance Status of Holstein cows using Mid-Infrared Spectral data
Mc Parland, Sinead; Banos, Georgios; Wall, Eileen et al

Conference (2010, August)

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See detailGenetic parameters of mastitis-correlated milk components in first parity dairy cows
Gillon, Alain ULg; Bastin, Catherine ULg; Soyeurt, Hélène ULg et al

in Proceedings of the 9th World Congress on Genetics Applied to Livestock Production (2010, August)

Ind. of lactoferrin content, ind. of Na content, and lactose content were the three most correlated milk components with somatic cell score among available milk components predicted by mid-infrared ... [more ▼]

Ind. of lactoferrin content, ind. of Na content, and lactose content were the three most correlated milk components with somatic cell score among available milk components predicted by mid-infrared spectrometry on 590,083 test-day records from Walloon Region of Belgium collected between 2007 and 2009. Mean daily heritabilities and mean genetic correlations of these four traits were estimated using Gibbs sampling methodology applied to a multi-trait random regression test-day model with a subset of these records. Mean daily heritabilities of ind. lactoferrin content (0.34), ind. Na content (0.37) and lactose content (0.42) were higher then SCS (0.16) and mean genetic correlations were moderate (from -0.18 to -0.73), showing that these traits could be used together to describe udder health in genetic evaluations instead of SCS alone when clinical mastitis data are not available. [less ▲]

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See detailPrediction of individual methane emission by dairy cattle from mid-infrared spectra
Vanlierde, Amélie ULg; Delfosse, Camille; Dehareng, Frédéric et al

Conference (2010, July 14)

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See detailHeterogeneity of residuals variances of milk fatty acids in dairy cattle
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Vanderick, Sylvie ULg et al

in Journal of Dairy Science (2010, July), 88(E-Suppl. 2), 744

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore ... [more ▼]

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore indirectly the potential need to adjust for this heterogeneity if it exists. The residuals were computed as the difference between the observed and the estimated values using a multi-trait random regression test-day model, similar to the Walloon routine model, used for first lactation only milk yield, quantities and percentages of protein (PROT) and fat (FAT), content of saturated fatty acids in milk (g/100g of milk, SAT) and, content of mono-unsaturated fatty acids in milk (g/100g of milk, MONO). Residuals were considered homogeneous inside strata defined, among others, by weeks of lactation, by days in milk and by calendar months of test date. About 6,687,000 records were available for milk yield and for FAT and PROT parameters. For SAT and for MONO, about 184,000 records were available in this database. Means of residuals were stable and close to zero for all traits. Variances were more variable for MONO and SAT than for milk yield, for example. Daily and weekly variances tended to decrease at the end of the lactation (50%). When the variances were computed by month of test date, some variations were observed and some periods of year were more marked. In conclusion, the observed residual variances were less stable for MONO and SAT. We can conclude that introduction for heterogeneous residual variance is more important for the new traits (MONO, SAT) than it was for the old, traditional ones. [less ▲]

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See detailHeterogeneity of residuals variances of milk fatty acids in dairy cattle
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Vanderick, Sylvie ULg et al

Conference (2010, July)

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore ... [more ▼]

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore indirectly the potential need to adjust for this heterogeneity if it exists. The residuals were computed as the difference between the observed and the estimated values using a multi-trait random regression test-day model, similar to the Walloon routine model, used for first lactation only milk yield, quantities and percentages of protein (PROT) and fat (FAT), content of saturated fatty acids in milk (g/100g of milk, SAT) and, content of mono-unsaturated fatty acids in milk (g/100g of milk, MONO). Residuals were considered homogeneous inside strata defined, among others, by weeks of lactation, by days in milk and by calendar months of test date. About 6,687,000 records were available for milk yield and for FAT and PROT parameters. For SAT and for MONO, about 184,000 records were available in this database. Means of residuals were stable and close to zero for all traits. Variances were more variable for MONO and SAT than for milk yield, for example. Daily and weekly variances tended to decrease at the end of the lactation (50%). When the variances were computed by month of test date, some variations were observed and some periods of year were more marked. In conclusion, the observed residual variances were less stable for MONO and SAT. We can conclude that introduction for heterogeneous residual variance is more important for the new traits (MONO, SAT) than it was for the old, traditional ones. [less ▲]

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See detailFeasibility of a genetic evaluation for milk fatty acids in dairy cattle
Soyeurt, Hélène ULg; Arnould, Valérie ULg; Vanderick, Sylvie ULg et al

Conference (2010, July)

Recent development of equations based on mid-infrared (MIR) spectrometry for the prediction of milk fatty acid (FA) contents allows their measurement on a large scale during performance recording. The ... [more ▼]

Recent development of equations based on mid-infrared (MIR) spectrometry for the prediction of milk fatty acid (FA) contents allows their measurement on a large scale during performance recording. The objective was to show that a genetic evaluation for milk FA in dairy cattle is feasible in the Walloon region of Belgium and to report first results. Estimated breeding values (EBV) and associated reliabilities (REL) were computed using a multi-trait test-day animal model similar to the one used for the routine genetic evaluation for yield traits. Studied traits were first lactation test-day milk, fat and protein yields, fat (FAT) and protein contents, and content of saturated fatty acids in milk (g/100g of milk, SAT). More than 6,700,000 records were available for common production and content traits and 194,000 records were used for SAT. Used variance components were estimated using REML. The average SAT content was 2.79% with a standard deviation (SD) of 0.50%. A total of 1,707 Holstein bulls used in Walloon Region had REL superior to 0.49 for all studied traits. REL for SAT ranged from 0.53 to 0.99. A total of 1,217 bulls had REL superior to 0.74. SD of EBV for SAT was 0.20%. The maximum and minimum SAT EBV values were 0.89% and -0.69%, respectively. In order to have a direct measure of the part of FAT that is not due to SAT, a new trait (dSAT) was post-evaluated and defined as difference between expected SAT EBV for a given FAT EBV and the estimated EBV for SAT. This new trait can be assumed to be a direct predictor of the content of unsaturated fatty acids in fat. The interest is that this trait cannot be accurately predicted directly by MIR. The maximum and minimum EBV for dSAT for the 1,707 bulls were -0.28% and 0.24%, respectively. Based on these results, a genetic evaluation for milk fatty acids is feasible. In the bull population used recently, a genetic variability for dSAT exists and could be used to improve the milk fat composition. [less ▲]

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See detailImprovements and validation of mid-infrared predictions of milk fatty acid
Soyeurt, Hélène ULg; McParland, Sinead; Donagh, Berry et al

Conference (2010, July)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples. The first aim was to improve these predictions by ... [more ▼]

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples. The first aim was to improve these predictions by comparing 6 statistical approaches. The second one was to validate the new equations using an independent sample set. The calibration set contained 239 spectrally different Belgian milk samples collected for over 2 years from several cows and breeds. FA were quantified by gas chromatography (GC). Statistical approaches tested were 1) partial least squares regression (PLS), 2) PLS and first derivative, 3) PLS and repeatability file (RF), 4) PLS, first derivative and RF, 5) PLS, second derivative, and 6) PLS, second derivative and RF. This last file contained spectra obtained from the same samples using 5 spectrometers. Cross-validation (CV) used 20 groups from the calibration set. Methods were compared using the ratio of the standard deviation of GC values to the standard error of CV (RPD). An external validation permitted a second comparison and was done using 362 samples collected for one year from multiple breeds and cows in Belgium, Ireland, and Scotland. Different RPD values were obtained by the 6 methods. Generally the equations developed using method 4 gave better results suggesting the adaptation of the methodology to the studied FA. It confirms by the obtained validation coefficients of determination. Highest values were observed for the equations with the highest RPD values except for C18:0. The ability to predict FA using method 4 gave superior results to those shown in previous publications. [less ▲]

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