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See detailGenetic variability of the mid-infrared prediction of lactoferrin content in milk for Walloon Holstein first-parity cows
Leclercq, Gil ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg et al

in Livestock Science (2013), 151(2-3), 158-162

The objective of this study was to assess the genetic variability of the mid-infrared prediction of lactoferrin content in milk (pLF) in Holstein first-parity cows. Variance components were estimated by ... [more ▼]

The objective of this study was to assess the genetic variability of the mid-infrared prediction of lactoferrin content in milk (pLF) in Holstein first-parity cows. Variance components were estimated by Average Information Restricted Maximum Likelihood using a single-trait test-day random regression animal model. The dataset included 395,287 test-day records from 67,178 cows in 1190 herds from the Walloon Region of Belgium. Average pLF was 164.89. mg/L and the standard deviation was 76.07. mg/L. Frequency distribution for pLF was slightly asymmetrical, and pLF seemed to increase almost linearly all along the first lactation after a sharp decrease in early lactation. Genetic variance of pLF increased with days in milk within lactation while the permanent environmental variance was the highest in early lactation, then decreased to become lower than genetic variance at 50 days in milk, and finally increased in the last lactation stages. The pLF was a moderately heritable trait. Daily heritability of pLF was the lowest at 5 days in milk (0.19), then increased to reach a maximum at 260 days in milk (0.44), and finally decreased for the last stages of lactation (0.35 at 365 days in milk). Results from this study indicated that pLF is variable and heritable over the lactation and therefore it could be changed by genetic selection. © 2012 Elsevier B.V. [less ▲]

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See detailRelationship between milk composition estimated from mid infrared and methane emissions in dairy cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, F et al

Scientific conference (2012, December 03)

N/A

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See detailCapitalizing on mid-infrared to improve nutritional and environmental quality of milk
Soyeurt, Hélène ULg; Dehareng, Frédéric; Gengler, Nicolas ULg et al

Conference (2012, November 07)

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See detailMid-infrared predictions of fatty acids in bovine milk : final results of the RobustMilk project
Soyeurt, Hélène ULg; McParland, Sinead; Berry, Donagh et al

Poster (2012, August 28)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on ... [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 and was one of the aims of the RobustMilk project. Data on MIR spectra and FA from multiple countries, production systems, and breeds were used to develop equations to predict milk FA. The calibration set contained 1,776 spectrally different English, Irish, and Belgian milk samples collected for over 6 years. FA were quantified by gas chromatography (GC). Equations were built using partial least squares regression after a first derivative pretreatment applied to the spectral data. The robustness of the developed equations was assessed by cross-validation (CV) using 50 groups from the calibration set. The coefficient of determination (R²) obtained after CV ranged between 0.7101 for the total content of C18:2 and 0.9993 for the saturated FA group. The standard error of CV ranged between 0.0028 and 0.0998 g/dl of milk. Generally, the group or individual FA having the highest content in milk had the highest R²cv. The results obtained in this study confirmed the usefulness of MIR spectra to robustly quantify the FA content of milk permitting the use of these equations by milk laboratories in UK, Belgium or Ireland. Therefore, these equations could be used to develop selection or management tools for dairy farmers in order to improve the nutritional and environmental quality of milk based on the knowledge of the FA composition of their milk. [less ▲]

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See detailMid-infrared prediction of milk titratable acidity and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Vanlierde, Amélie ULg; Vanden Bossche, sandrine ULg et al

Conference (2012, August 27)

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability ... [more ▼]

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability of this trait on a large scale, mid-infrared (MIR) chemometric methods were used to predict TA. A total of 507 milk samples collected in the Walloon Region of Belgium from individual cows were analyzed using a MIR spectrometer. TA was recorded as Dornic degree. An equation to predict TA from milk MIR spectrum was developed using partial least squared regression after a first derivative pre-treatment applied to the spectra to correct the baseline drift. During the calibration process, 45 outliers were detected and removed from the calibration set. The TA mean of the final calibration set was 16.62 (standard deviation (SD) = 1.80). The coefficient of determination (R²) was 0.82 for the calibration with a standard error (SE) of 0.76. A cross-validation (cv) was performed (R²cv = 0.81 with SEcv = 0.80). This equation was then applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated by REML using single-trait random regression animal test-day model. The dataset used included 33,717 records from 9,191 Holstein first-parity cows; the TA mean was 17.05 (SD = 1.35) and TA ranged from 12.83 to 20.87. Estimated daily heritabilities ranged from 0.43 at 5th day in milk to 0.59 at 215th day in milk indicating potential of selection. Further research will study phenotypic and genetic correlations between TA and milk production traits. [less ▲]

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See detailGenetics of the mineral contents in bovine milk predicted by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dehareng, Frédéric; Romnée, Jean-Michel et al

Conference (2012, August 27)

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of ... [more ▼]

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of mid-infrared equations for mineral contents in milk by using an approach combining multiple countries, breeds, and production systems and 2) study of the genetic variability of these traits in the Walloon Holstein dairy cattle. Samples included in the calibration set were collected in Belgium, Luxembourg and France over 5 years. The calibration set included at least 400 samples analyzed by coupled plasma atomic emission spectrometry to quantify the contents of Na, Ca, Mg, P and K. The calibration coefficient of determination ranged between 0.69 for K and 0.93 for Na. The standard error of cross-validation was 63.35, 49.24, 64.33, 7.04, and 93.22 mg/kg of milk for Na, Ca, P, Mg and K. From these results, the quantification of milk minerals by mid-infrared is feasible. These equations were applied to more than 140,000 spectral records collected from 43,797 first parity Holstein cows in 1,233 herds. The variance components were estimated using Gibbs Sampling using single trait random regression models derived from the one used for the Walloon genetic evaluation of milk production traits. First results gave a daily heritability of 0.26 for Na, 0.45 for Ca, 0.48 for P, 0.46 for Mg, and 0.41 for K. Moderate negative genetic correlations were found between Na and the other studied traits. The highest correlation (0.69) was observed between P and Mg. These results confirmed the genetic variability of these traits. Further studies will be conducted to study the relationship between these traits and other traits (e.g., production, health). [less ▲]

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See detailMid-infrared prediction of milk titratable acidity and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Vanlierde, Amélie ULg; Vanden Bossche, sandrine ULg et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability ... [more ▼]

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability of this trait on a large scale, mid-infrared (MIR) chemometric methods were used to predict TA. A total of 507 milk samples collected in the Walloon Region of Belgium from individual cows were analyzed using a MIR spectrometer. TA was recorded as Dornic degree. An equation to predict TA from milk MIR spectrum was developed using partial least squared regression after a first derivative pre-treatment applied to the spectra to correct the baseline drift. During the calibration process, 45 outliers were detected and removed from the calibration set. The TA mean of the final calibration set was 16.62 (standard deviation (SD) = 1.80). The coefficient of determination (R²) was 0.82 for the calibration with a standard error (SE) of 0.76. A cross-validation (cv) was performed (R²cv = 0.81 with SEcv = 0.80). This equation was then applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated by REML using single-trait random regression animal test-day model. The dataset used included 33,717 records from 9,191 Holstein first-parity cows; the TA mean was 17.05 (SD = 1.35) and TA ranged from 12.83 to 20.87. Estimated daily heritabilities ranged from 0.43 at 5th day in milk to 0.59 at 215th day in milk indicating potential of selection. Further research will study phenotypic and genetic correlations between TA and milk production traits. [less ▲]

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See detailEstimation of Myostatin gene effects on production traits and fatty acid contents in bovine milk
Vanrobays, Marie-Laure ULg; Bastin, Catherine ULg; Colinet, Frédéric ULg et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

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See detailGenetics and genomics of energy balance measured in milk using mid-infrared spectroscopy
McParland, Sinead; Calus, Mario; Coffey, Mike et al

Poster (2012, August)

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See detailGenetics and genomics of energy balance measured in milk using mid-infrared spectroscopy
McParland, Sinead; Calus, Mario; Coffey, Mike et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

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See detailDifferences in bovine milk fat composition among dairy breeds in The Netherlands
Maurice-Van eijndhoven, Myrthe; Bovenhuis, Henk; Soyeurt, Hélène ULg et al

Conference (2012, August)

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See detailDifferences in bovine milk fat composition among dairy breeds in The Netherlands
Maurice-Van Eijndhoven, Myrthe; Bovenhuis, Henk; Soyeurt, Hélène ULg et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

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See detailMid-infrared predictions of fatty acids in bovine milk : final results of the RobustMilk project
Soyeurt, Hélène ULg; McParland, Sinead; Berry, Donagh et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on ... [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 and was one of the aims of the RobustMilk project. Data on MIR spectra and FA from multiple countries, production systems, and breeds were used to develop equations to predict milk FA. The calibration set contained 1,776 spectrally different English, Irish, and Belgian milk samples collected for over 6 years. FA were quantified by gas chromatography (GC). Equations were built using partial least squares regression after a first derivative pretreatment applied to the spectral data. The robustness of the developed equations was assessed by cross-validation (CV) using 50 groups from the calibration set. The coefficient of determination (R²) obtained after CV ranged between 0.7101 for the total content of C18:2 and 0.9993 for the saturated FA group. The standard error of CV ranged between 0.0028 and 0.0998 g/dl of milk. Generally, the group or individual FA having the highest content in milk had the highest R²cv. The results obtained in this study confirmed the usefulness of MIR spectra to robustly quantify the FA content of milk permitting the use of these equations by milk laboratories in UK, Belgium or Ireland. Therefore, these equations could be used to develop selection or management tools for dairy farmers in order to improve the nutritional and environmental quality of milk based on the knowledge of the FA composition of their milk. [less ▲]

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See detailGenetics of the mineral contents in bovine milk predicted by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dehareng, Frédéric; Romnée, Jean-Michel et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of ... [more ▼]

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of mid-infrared equations for mineral contents in milk by using an approach combining multiple countries, breeds, and production systems and 2) study of the genetic variability of these traits in the Walloon Holstein dairy cattle. Samples included in the calibration set were collected in Belgium, Luxembourg and France over 5 years. The calibration set included at least 400 samples analyzed by coupled plasma atomic emission spectrometry to quantify the contents of Na, Ca, Mg, P and K. The calibration coefficient of determination ranged between 0.69 for K and 0.93 for Na. The standard error of cross-validation was 63.35, 49.24, 64.33, 7.04, and 93.22 mg/kg of milk for Na, Ca, P, Mg and K. From these results, the quantification of milk minerals by mid-infrared is feasible. These equations were applied to more than 140,000 spectral records collected from 43,797 first parity Holstein cows in 1,233 herds. The variance components were estimated using Gibbs Sampling using single trait random regression models derived from the one used for the Walloon genetic evaluation of milk production traits. First results gave a daily heritability of 0.26 for Na, 0.45 for Ca, 0.48 for P, 0.46 for Mg, and 0.41 for K. Moderate negative genetic correlations were found between Na and the other studied traits. The highest correlation (0.69) was observed between P and Mg. These results confirmed the genetic variability of these traits. Further studies will be conducted to study the relationship between these traits and other traits (e.g., production, health). [less ▲]

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See detailGenetic parameters for methane indicator traits based on milk fatty acids in cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, Frédéric et al

in Journal of Dairy Science (2012, July 18)

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue ... [more ▼]

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue is the development of easily obtainable indicators, because they would also allow estimating animal genetic variability of methane emission. Recently methane indicators were proposed using gas chromatrography based milk fatty acid composition. We derived these published methane indicators using 1100 calibration samples directly from mid-infrared (MIR).For the published indicator showing the highest relationship (R2 = 0.88) with Sulfur Hexafluoride 6 methane emission data, genetic parameters for this MIR based indicator were estimated by single trait random regression test-day models from 619,272 records collected from 2007 to 2011 on 71,188 Holstein cows in their first three lactations at Walloon region of Belgium. The average daily heritability was 0.35±0.01, 0.35±0.02 and 0.32±0.02 for the first three lactations, respectively. Similarly, the lactation heritability was 0.67±0.02, 0.72±0.03 and 0.62±0.03. As expected, methane production was higher during the peak milk production depicting the normal lactation curve. The largest differences between estimated breeding values (EBV) of sires having cows in production eructing the highest and the lowest methane content was 21.80, 22.75 and 24.89 kg per lactation for the first three parities, the variances of the EBV of the sires with daughters were 10.67, 12.46, 12.18 kg2. Results were similar for other indicators. This study suggested that methane indicator traits can be predicted by MIR. Genetic parameters also indicated a rather high heritability and genetic variability exist for these published indicators and consequently a potential high genetic variability of methane eructation by dairy cows. Therefore, these first finding might open new opportunities for animal selection programs that include the reduction of methane emission. [less ▲]

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See detailGenetic parameters for methane indicator traits based on milk fatty acids in cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, Frédéric et al

Conference (2012, July 18)

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See detailEffect of milk recording schemes on milk and milk components genetic parameters in Luxembourg
Arnould, Valérie ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

Conference (2012, July 18)

A particularity of the Luxembourg milk recording is the use of different schemes. Two principal schemes are applied: the scheme “S” applied on 69.1% of the total herds (n=712) and consisting in one ... [more ▼]

A particularity of the Luxembourg milk recording is the use of different schemes. Two principal schemes are applied: the scheme “S” applied on 69.1% of the total herds (n=712) and consisting in one proportionate sample of all daily milkings, and the scheme “T” (21.6% of the total herds) which consists in one sample of only one milking (morning or evening milking) (and alternating milking time from month to month). The problematic is that application of different schemes could influence the milk components (protein and fat yield) and the milk fat components (saturated and unsaturated groups of fatty acids) genetic parameters estimation and to prevent all comparisons between dairy population under different milk recording schemes. A total of 47,613 and 44,833 test-day records were obtained, respectively for schemes “S” and “T” from Holstein cows in first lactation in Luxembourg dairy herds. The used model included as fixed effects: herd x date of test, class of age, and month x year. Random effects were permanent environmental, additive genetics, and residual effects. The main objective of this work is to study the effect the choice of milk recording schemes (“S” or “T” schemes) on milk yield and milk components genetic parameters. A solution could be to add a fixed effect taking in account the milking time. The second objective is to study the effect of milking time (morning or evening) on genetic parameters estimated in the case of scheme “T”. According to the results, genetic parameters were statistically different between the schemes “S” and “T” for milk yield (P value < 0.0001). Further, the classifications of bulls according to their breeding values were very different when values were estimated on basis of scheme “S” or “T” (Spearman correlation value of 0.51 for milk yield for example). In conclusion, using several milk recording schemes do not allow any comparison of genetic parameters between dairy cattle’s. [less ▲]

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