References of "Soyeurt, Hélène"
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See detailPhenotypic and genetic variability of methane emissions and milk fatty acid contents of Walloon Holstein dairy cows
Vanrobays, Marie-Laure ULg; Kandel, Purna Bhadra ULg; Soyeurt, Hélène ULg et al

Poster (2013, February 07)

There is a growing interest in reducing methane (CH4) emissions from enteric fermentation of dairy cows because these emissions contribute to climate change and represent losses of gross energy intake for ... [more ▼]

There is a growing interest in reducing methane (CH4) emissions from enteric fermentation of dairy cows because these emissions contribute to climate change and represent losses of gross energy intake for cows. Milk fatty acid (FA) profile is influenced by rumen fermentations. The aim of this study was to estimate phenotypic and genetic variability of enteric CH4 emissions of dairy cows and FA contents of milk. CH4 emissions (g/d) and milk FA contents are predicted from milk mid-infrared (MIR) spectra based on calibration equations developed by Vanlierde et al. (2013) and Soyeurt et al. (2011), respectively. Data included 161,681 records from 22,642 cows in 489 herds. Genetic parameters of MIR CH4 emissions and 7 groups of FA contents in milk were estimated for Walloon Holstein cows in first parity using bivariate (CH4 emission with a FA trait) random regression test-day models. Saturated FA presented higher genetic correlations with MIR CH4 production than unsaturated FA (0.25 vs. 0.10). Genetic correlations with MIR CH4 emissions were higher for short-(SC) and medium-chain (MC) FA (0.24 and 0.23, respectively) than for long-chain (LC) FA (0.13). Phenotypic correlations between MIR CH4 emissions and SC and MC FA were also higher than those between MIR CH4 emissions and LC FA (0.20 vs. -0.08). Finally, results showed that MIR milk FA profile and MIR CH4 emissions are correlated emphasizing indirect link between milk FA and CH4 emissions through rumen metabolism. [less ▲]

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See detailEtude de la variabilité des aptitudes à la transformation laitière en Région wallonne basée sur l'utilisation de la spectrométrie infrarouge
Colinet, Frédéric ULg; Troch, Thibault ULg; Vanden Bossche, S. et al

in 18ième Carrefour des Productions animales : Nouvelles approches pour une optimisation de nos élevages laitiers (2013, February)

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See detailValidation of fatty acid predictions in milk using mid-infrared spectrometry across cattle breeds.
Maurice – Van Eijndhoven, Myrthe; Soyeurt, Hélène ULg; Dehareng, Frédéric et al

in Animal (2013), 7

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See detailGenetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULg; Vanrobays, Marie-Laure ULg; Vanlierde, Amélie ULg et al

in Journal of Dairy Science (2013), 95(E-1), 388

Genetic selection of low methane (CH4) emitting animals is additive and permanent but the difficulties associated with individual CH4 measurement result in a paucity of records required to estimate ... [more ▼]

Genetic selection of low methane (CH4) emitting animals is additive and permanent but the difficulties associated with individual CH4 measurement result in a paucity of records required to estimate genetic variability of CH4 traits. Recently, it was shown that direct quantification of CH4 emissions by mid-infrared spectroscopy (MIR) from milk. The CH4 prediction equation was developed using 452 SF6 CH4 measurements with associated milk spectra and the calibration equation was developed using PLS regression. The obtained SD of predicted CH4 was 126.39 g/day with standard error of cross validation 68.68 g/day and a cross-validation coefficient of determination equal to 70%. The equation was applied on a total of 338,917 spectra obtained from milk samples collected between January 2007 and August 2012 during the Walloon milk recording for first parity Holstein cows. The prediction of MIR CH4 was 547 ± 111 g/d and MIR CH4 g/kg of fat and protein corrected milk (FPCM) was 23.66 ± 8.21.Multi-trait random regression test-day models were used to estimate the genetic variability of MIR predicted CH4 and milk production traits. The heritability, phenotypic and genetic correlations between MIR predicted CH4 traits and milk traits are presented in Table 1. Estimated heritability for CH4 g/day and CH4 g/kg of FPCM were lower than common production traits but would still be useful in breeding programs. While selection for cows emitting lower amounts of MIR predicted CH4 (g/d) would have little effect on milk production traits, selection on MIR predicted CH4 (g/kg of FPCM) would decrease FPCM, fat and protein yields. These genetic parameters of CH4 indicator traits might be entry point for selection that accounts mitigation of CH4 from dairy farming. Table 1. Heritability (diagonal), phenotypic (below the diagonal) and genetic (above the diagonal) correlations between MIR predicted CH4 and production traits Traits MIR CH4 (g/d) MIR CH4 ((g/kg of FPCM) FPCM Fat yield Protein yield MIR CH4 (g/d) 0.11 0.42 0.03 0.19 0.04 MIR CH4 (g/kg of FPCM)0.59 0.18 -0.83 -0.72 -0.77 FPCM -0.02 -0.65 0.20 0.95 0.91 Fat yield 0.01 -0.58 0.76 0.22 0.70 Protein yield -0.01 -0.61 0.78 0.69 0.20 [less ▲]

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See detailGenetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1 – 3
Bastin, Catherine ULg; Soyeurt, Hélène ULg; Gengler, Nicolas ULg

in Journal of Animal Breeding & Genetics (2013), 130(2),

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents ... [more ▼]

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents predicted by mid-infrared spectrometry for first-, second- and third-parity Holstein cows. Edited data included records collected in the Walloon region of Belgium from 37 768 cows in parity 1, 22 566 cows in parity 2 and 8221 in parity 3. A total of 69 (23 traits for three parities) single-trait random regression animal test-day models were run. Approximate genetic correlations among traits were inferred from pairwise regressions among estimated breeding values of cow having observations. Heritability and genetic correlation estimates from this study reflected the origins of FA: de novo synthetized or originating from the diet and the body fat mobilization. Averaged daily heritabilities of FA contents in milk ranged between 0.18 and 0.47. Average daily genetic correlations (averaged across days in milk and parities) among groups and individual FA contents in milk ranged between 0.31 and 0.99. The genetic variability of FAs in combination with the moderate to high heritabilities indicated that FA contents in milk could be changed by genetic selection; however, desirable direction of change in these traits remains unclear and should be defined with respect to all issues of importance related to milk FA. [less ▲]

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See detailPhenotyping of robustness and milk quality
Berry, D.P.; McParland, S.; Bastin, Catherine ULg et al

in Advances in Animal Biosciences (2013), 4(3), 600-605

A phenotype describes the outcome of the interacting development between the genotype of an individual and its specific environment throughout life. Animal breeding currently exploits large data sets of ... [more ▼]

A phenotype describes the outcome of the interacting development between the genotype of an individual and its specific environment throughout life. Animal breeding currently exploits large data sets of phenotypic and pedigree information to estimate the genetic merit of animals. Here we describe rapid, low-cost phenomic tools for dairy cattle. We give particular emphasis to infrared spectroscopy of milk because the necessary spectral data are already routinely available on milk samples from individual cows and herds, and therefore the operational cost of implementing such a phenotyping strategy is minimal. The accuracy of predicting milk quality traits from mid-infrared spectroscopy (MIR) analysis of milk, although dependent on the trait under investigation, is particularly promising for differentiating between good and poor-quality dairy products. Many fatty acid concentrations in milk, and in particular saturated fatty acid content, can be very accurately predicted from milk MIR. These results have been confirmed in many international populations. Albeit from only two studied populations investigated in the RobustMilk project, milk MIR analysis also appears to be a reasonable predictor of cow energy balance, a measure of animal robustness; high accuracy of prediction was not expected as the gold standard method of measuring energy balance in those populations was likely to contain error. Because phenotypes predicted from milk MIR are available routinely from milk testing, longitudinal data analyses could be useful to identify animals of superior genetic merit for milk quality and robustness, as well as for monitoring changes in milk quality and robustness because of management, while simultaneously accounting for the genetic merit of the animals. These sources of information can be very valuable input parameters in decision-support tools for both milk producers and processors. [less ▲]

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See detailReview: Milk composition as management tool of sustainability
Arnould, Valérie ULg; Reding, Romain; Bormann, Jeanne et al

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2013), 17(4), 613-621

The main objective of this paper is the use of milk composition data as a management tool. Milk composition, and in particular, milk fat content and fatty acid profiles may be significantly altered due to ... [more ▼]

The main objective of this paper is the use of milk composition data as a management tool. Milk composition, and in particular, milk fat content and fatty acid profiles may be significantly altered due to a variety of factors. These factors are reviewed in the literature; they include diet, animal (genetic) selection, management aspects and animal health. Changes in milk composition can be used as an indicator of the animal’s metabolic status or the efficiency of the feed management system. The advantages of using this kind of data as a management tool would be to allow the early detection of metabolic or management problems. The present review suggests that milk and, especially milk fat composition may be used as a sustainability management tool and as a monitoring and prevention tool for several pathologies or health disorders in dairy cattle. Further, due to the use of MIR technology, these tools may be easily implemented in practice and are relatively cheap. In the field, milk labs or milk recording agencies would be able to alert farmers whenever threshold values for disease were reached, allowing them to improve their dairy production from an economic, ecological and animal (welfare) point of view. [less ▲]

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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)

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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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