References of "Soyeurt, Hélène"
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See detailPotentiel d'utilisation de la spectrometrie moyen infrarouge pour prédire le rendement fromager du lait et étudier sa variabilité génétique
Colinet, Frédéric ULiege; Troch, Thibault ULiege; Abbas, O. et al

in 20èmes Rencontres Recherches Ruminants, Paris, les 4 et 5 Décembre 2013 (2013, December)

Fournir une indication rapide, fiable et bon marché du rendement fromager pour un lait donné, sans devoir appliquer des formules (empiriques ou théoriques) à partir des concentrations préalablement ... [more ▼]

Fournir une indication rapide, fiable et bon marché du rendement fromager pour un lait donné, sans devoir appliquer des formules (empiriques ou théoriques) à partir des concentrations préalablement déterminées pour différents constituants du lait, serait un outil utile et économiquement intéressant tant pour les éleveurs que pour l’industrie laitière. En vue d’étudier la variabilité génétique du rendement fromager à l’échelle du cheptel bovin wallon, des méthodes chimiométriques ont été utilisées afin de développer des équations de prédictions basées sur des spectres moyen infrarouge (MIR) pour les rendements fromagers déterminés en laboratoire et exprimés en frais (RdFF) ou en sec (RdFS). Ceux-ci ont été déterminés sur 258 échantillons de lait analysés en spectrométrie MIR. Les équations de prédiction à partir du spectre MIR du lait ont été développées en utilisant la régression des moindres carrés partiels (PLS) avec une validation croisée interne appliquée sur la dérivée première des spectres MIR. Les coefficients de détermination de validation croisée (R²cv) des équations étaient de 0,81 pour les prédictions du RdFF et de 0,82 pour les celles du RdFS. Les rapports des performances sur les variabilités (RPD) étaient égaux à 2,3. Ces résultats peuvent permettre d’envisager une bonne utilité pratique pour leur prédiction respective, notamment dans le cadre de recherches génétiques. Ces équations ont été appliquées sur la base de données spectrales générée dans le cadre du contrôle laitier wallon. Les composantes de la variance ont été estimées séparément pour le RdFF et le RdFS basées sur un modèle animal « contrôles élémentaires » utilisant des régressions aléatoires. Le jeu de données utilisé comportait 51 537 prédictions pour 7 870 vaches primipares Holstein. Les héritabilités journalières moyennes variaient entre 0,31 (au 5ème jour de lactation (JDL)) et 0,59 (au 279ème JDL) pour le RdFF et entre 0,31 (au 5ème JDL) et 0,57 (au 299ème JDL) pour le RdFS. Ces héritabilités journalières modérées à élevées ont indiqué le potentiel de sélection génétique pour ces deux caractères. [less ▲]

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See detailMid-infrared prediction of cheese yield from milk and its genetic variability in first-parity cows
Colinet, Frédéric ULiege; Troch, Thibault ULiege; Vanden, Bossche et al

Conference (2013, August 29)

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See detailGenetic effects of heat stress on milk yield and MIR predicted methane emissions of Holstein cows
Vanrobays, Marie-Laure ULiege; Gengler, Nicolas ULiege; Kandel, Purna Bhadra ULiege et al

Conference (2013, August 28)

Dairy cows both contribute to and are affected by climate change. Breeding for heat tolerance and reduced methane (CH4) emissions is a key requirement to mitigate interactions between dairy cows and ... [more ▼]

Dairy cows both contribute to and are affected by climate change. Breeding for heat tolerance and reduced methane (CH4) emissions is a key requirement to mitigate interactions between dairy cows and climate change. This study was aimed to estimate genetic variation of milk yield and CH4 emissions over the whole trajectory of temperature humidity index (THI) using a reaction norm approach. A total of 257,635 milk test-day (TD) records and milk mid-infrared (MIR) spectra from 51,782 Holstein cows were used. Data were collected between January 2007 and December 2010 in 983 herds by the Walloon Breeding Association (Ciney, Belgium). The calibration equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the spectral data in order to predict CH4 emissions values (g CH4/d). These values were divided by fat and protein corrected milk yield (FPCM) defining a new CH4 trait (g CH4/kg of FPCM). Daily THI values were calculated using the mean of daily values of dry bulb temperature and relative humidity from meteorological data. Mean daily THI of the previous 3 days before each TD record was used as the THI of reference for that TD. Bivariate (milk yield and a CH4 trait) random regression TD mixed models with random linear regressions on THI values were used. Estimated average daily heritability for milk yield was 0.17 and decreased slightly at extreme THI values. However, heritabilities of MIR CH4 traits increased as THI values increase: from 0.10 (THI=28) to 0.14 (THI=75) for MIR CH4 (g/d) and from 0.14 (THI=28) to 0.21 (THI=75) for MIR CH4 (g/kg of FCPM). Genetic correlations between milk yield and MIR CH4 (g/d) ranged from -0.09 (THI=28) to -0.12 (THI=75) and those between milk yield and MIR CH4 (g/kg of FPCM) from -0.75 (THI=28) to -0.71 (THI=75). These results showed that milk production and CH4 emissions of dairy cows seemed to be influenced by THI. [less ▲]

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See detailImprovement of a method to predict individual enteric methane emission of cows from milk MIR spectra
Vanlierde, Amélie ULiege; Dehareng, F.; Froidmont, E. et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August 27)

Besides being a greenhouse gas, enteric methane (CH produced by ruminants during rumination is also associated with the loss of 6 to 12% of gross energy intake. Mitigation of those emissions could be ... [more ▼]

Besides being a greenhouse gas, enteric methane (CH produced by ruminants during rumination is also associated with the loss of 6 to 12% of gross energy intake. Mitigation of those emissions could be based on combined actions on diet, herd management and animal genetics. In order to investigate easily the relationship between these parameters and the CH4 emissions on a large scale, an equation to predict individual enteric CH4 emissions from the whole individual milk mid-infrared (MIR) spectra was developed. To build this equation a total of 452 CHA reference were obtained using the sF6 method. on Jersey, Holstein and Holstein-Jersey crossbred cows. In parallel a 40 ml sample of individual milk was collected at each milking (morning and evening) and was analyzed using MIR spectrometry Then, these spectra were averaged proportionally function of the milk production to have one spectrum for one CH4 ment. Data were collected on 146 different cows (63, 36, 18, 29 a in parity one to fourt, respectively) receiving different diets. The calibration model was developed using Foss wINISI 4 software on spectral data after applying the first derivative and using pLs regression. The CH4 emission prediction (g showed a calibration coefficient of determination (R2c) of 0.76, a cross-validation coefficient of determination (R2cv) and the standard error of calibration was of 62 g/day. Results are very promising and showed the possibility to predict the eructed CH4 from the milk spectra. relationship between measurements and predictions is linear and thereby allowing the distinction between low and high emitting cows. [less ▲]

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULiege; Kandel, Purna Bhadra ULiege; Soyeurt, Hélène ULiege et al

Poster (2013, August 26)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULiege; Kandel, Purna Bhadra ULiege; Soyeurt, Hélène ULiege et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailMid-infrared prediction of cheese yield from milk and its genetic variability in first-parity cows
Colinet, Frédéric ULiege; Troch, Thibault ULiege; Vanden Bossche, Sandrine et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

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See detailGenetic effects of heat stress on milk yield and MIR predicted methane emissions of Holstein cows
Vanrobays, Marie-Laure ULiege; Gengler, Nicolas ULiege; Kandel, Purna Bhadra ULiege et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

Dairy cows both contribute to and are affected by climate change. Breeding for heat tolerance and reduced methane (CH4) emissions is a key requirement to mitigate interactions between dairy cows and ... [more ▼]

Dairy cows both contribute to and are affected by climate change. Breeding for heat tolerance and reduced methane (CH4) emissions is a key requirement to mitigate interactions between dairy cows and climate change. This study was aimed to estimate genetic variation of milk yield and CH4 emissions over the whole trajectory of temperature humidity index (THI) using a reaction norm approach. A total of 257,635 milk test-day (TD) records and milk mid-infrared (MIR) spectra from 51,782 Holstein cows were used. Data were collected between January 2007 and December 2010 in 983 herds by the Walloon Breeding Association (Ciney, Belgium). The calibration equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the spectral data in order to predict CH4 emissions values (g CH4/d). These values were divided by fat and protein corrected milk yield (FPCM) defining a new CH4 trait (g CH4/kg of FPCM). Daily THI values were calculated using the mean of daily values of dry bulb temperature and relative humidity from meteorological data. Mean daily THI of the previous 3 days before each TD record was used as the THI of reference for that TD. Bivariate (milk yield and a CH4 trait) random regression TD mixed models with random linear regressions on THI values were used. Estimated average daily heritability for milk yield was 0.17 and decreased slightly at extreme THI values. However, heritabilities of MIR CH4 traits increased as THI values increase: from 0.10 (THI=28) to 0.14 (THI=75) for MIR CH4 (g/d) and from 0.14 (THI=28) to 0.21 (THI=75) for MIR CH4 (g/kg of FCPM). Genetic correlations between milk yield and MIR CH4 (g/d) ranged from -0.09 (THI=28) to -0.12 (THI=75) and those between milk yield and MIR CH4 (g/kg of FPCM) from -0.75 (THI=28) to -0.71 (THI=75). These results showed that milk production and CH4 emissions of dairy cows seemed to be influenced by THI. [less ▲]

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See detailQualité du lait: la Wallonie à la pointe grâce à l’utilisation de la spectrométrie infrarouge
Dehareng, Frédéric; Soyeurt, Hélène ULiege; Gengler, Nicolas ULiege et al

in Carrefour des productions animales: Nouvelles approches pour une optimisation de nos élevages laitiers (2013, February 20)

La spectrométrie infrarouge est utilisée depuis de nombreuses années en Belgique. Les premiers spectromètres utilisés étaient des appareils à filtres, n’utilisant que quelques zones de la plage spectrale ... [more ▼]

La spectrométrie infrarouge est utilisée depuis de nombreuses années en Belgique. Les premiers spectromètres utilisés étaient des appareils à filtres, n’utilisant que quelques zones de la plage spectrale du moyen infrarouge (MIR). La généralisation de ces appareils dans les laboratoires d’analyses laitières a été possible grâce aux nombreux avantages liés à cette technique d’analyse. Ces appareils sont très rapides : ils permettent de mesurer entre 400 et 600 échantillons par heure. Une seule mesure spectrale permet d’estimer simultanément une multitude de paramètres. Cette technique est également précise et robuste, permettant ainsi d’obtenir un niveau de précision équivalent aux méthodes de référence classiques. Enfin, les coûts d’analyse par échantillon restent relativement faibles. Ceci a donc permis d’une part le développement du système de payement du lait actuel qui repose sur un échantillonnage et une mesure systématique de la composition du lait lors de chaque ramassage en ferme et, d’autre part, le développement du contrôle laitier mensuel [less ▲]

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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 ULiege; Kandel, Purna Bhadra ULiege; Soyeurt, Hélène ULiege 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 ULiege; Troch, Thibault ULiege; 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 ULiege; Dehareng, Frédéric et al

in Animal (2013), 7

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See detailAvancées dans le développement d’une équation permettant de prédire les émissions de méthane des vaches laitières grâce aux spectres moyens infrarouges du lait Progress in the development of an equation for predicting methane emission from dairy cows using milk mid-infrared spectra
Vanlierde, Amélie ULiege; DEHARENG, F.; FROIDMONT, E. et al

in Rencontres autour des Recherches sur les Ruminants (2013), 20

Le secteur de l'élevage contribue à 37% des émissions de méthane (CH4) d’origine anthropique dans le monde (Steinfeld et al., 2006). Afin de pouvoir étudier ces émissions et ainsi développer des méthodes ... [more ▼]

Le secteur de l'élevage contribue à 37% des émissions de méthane (CH4) d’origine anthropique dans le monde (Steinfeld et al., 2006). Afin de pouvoir étudier ces émissions et ainsi développer des méthodes permettant de les réduire il est nécessaire de pouvoir les mesurer à grande échelle. Dans cette optique, des équations permettant de prédire les émissions individuelles de CH4 directement à partir du spectre laitier mesuré en moyen infrarouge (MIR) ont été établies (Dehareng et al., 2012; Soyeurt et al., 2013). Les avancées de ces équations présentent désormais une approche internationale et multi-race. [less ▲]

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See detailDevelopment of a method to predict individual enteric methane emissions from cows based on milk mid-infrared spectra
Vanlierde, Amélie ULiege; Froidmont, Eric; Soyeurt, Hélène ULiege et al

in Hassouna, Mélynda; Guingand, Nadine (Eds.) Emissions of Gas and Dust from Livestock (2013)

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

in Advances in Animal Biosciences (2013), 4(2),

N/A

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