References of "Soyeurt, Hélène"
     in
Bookmark and Share    
Full Text
See detailGenetic correlations between methane production and milk fatty acid contents of Walloon Holstein cattle throughout the lactation
Vanrobays, Marie-Laure ULg; Vandenplas, Jérémie ULg; Bastin, Catherine ULg et al

Poster (2015, April 16)

Methane (CH4) from ruminal fermentation is the major greenhouse gas produced by dairy cattle which contributes largely to climate change. Production of CH4 also represents losses of gross energy intake ... [more ▼]

Methane (CH4) from ruminal fermentation is the major greenhouse gas produced by dairy cattle which contributes largely to climate change. Production of CH4 also represents losses of gross energy intake. Therefore, there is a growing interest in mitigating these emissions. Acetate and butyrate have common bio-chemical pathways with CH4. Because some milk fatty acids (FA) arise from acetate and butyrate, milk FA are often considered as potential predictors of CH4. However, relationships between these traits remain unclear. Moreover, the evolution of the phenotypic and genetic correlations of CH4 and milk FA across days in milk (DIM) has not been evaluated. The main goal of this study was to estimate genetic correlations between CH4 and milk FA contents throughout the lactation. Calibration equations predicting daily CH4 production (g/d) and milk FA contents (g/100 dL of milk) from milk mid-infrared (MIR) spectra were applied on MIR spectra related to Walloon milk recording. Data included 243,260 test-day records (between 5 and 365 DIM) from 33,850 first-parity Holstein cows collected in 630 herds. Pedigree included 109,975 animals. Bivariate (i.e., CH4 production and one of the FA traits) random regression test-day models were used to estimate genetic parameters of CH4 production and 7 groups of FA contents in milk. Saturated (SFA), short-chain (SCFA), and medium-chain FA (MCFA) showed positive averaged daily genetic correlations with CH4 production (from 0.25 to 0.29). Throughout the lactation, genetic correlations between SCFA and CH4 were low in the beginning of the lactation (0.11 at 5 DIM) and higher at the end of the lactation (0.54 at 365 DIM). Regarding SFA and MCFA, genetic correlations between these groups of FA and CH4 were more stable during the lactation with a slight increase (from 0.23 to 0.31 for SFA and from 0.23 to 0.29 for MCFA, at 5 and 365 DIM respectively). Furthermore, averaged daily genetic correlations between CH4 production and monounsaturated (MUFA), polyunsaturated (PUFA), unsaturated (UFA), and long-chain FA (LCFA) were low (from 0.00 to 0.15). However, these genetic correlations varied across DIM. Genetic correlations between CH4 and MUFA, PUFA, UFA, and LCFA were negative in early lactation (from -0.24 to -0.34 at 5 DIM) and increased afterward to become positive from 15 weeks till the end of the lactation (from 0.14 to 0.25 at 365 DIM). Finally, these results indicate that genetic and, therefore, phenotypic correlations between CH4 production and milk FA vary following lactation stage of the cow, a fact still often ignored when trying to predict CH4 production from FA composition. [less ▲]

Detailed reference viewed: 19 (4 ULg)
Full Text
Peer Reviewed
See detailAssessing variability of literature based methane indicator traits in a large dairy cow population
Kandel, Purna Bhadra ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2015), 19(1), 11-19

Description du sujet. La production laitière est reconnue comme une des sources majeures d’émissions de méthane (CH4). Le recours à un programme de sélection spécifique pourrait être une bonne méthode ... [more ▼]

Description du sujet. La production laitière est reconnue comme une des sources majeures d’émissions de méthane (CH4). Le recours à un programme de sélection spécifique pourrait être une bonne méthode pour optimiser les émissions de méthane par les vaches laitières. Le développement d’un tel programme nécessiterait un nombre important d’enregistrements relatifs aux émissions de méthane. Malheureusement, aucune méthode pratique et bon marché n’existe actuellement pour créer une telle base de données. Cependant, quatre indicateurs CH4 basés sur les quantités en acides gras dans la matière grasse laitière ont été recensés dans la littérature. Objectifs. L’objectif de cette étude est d’utiliser ces indicateurs de la littérature afin d’apprécier la variabilité des émissions de méthane éructées par les vaches laitières. Méthode. Ces indicateurs utilisent les quantités en acides gras obtenues par chromatographie en phase gazeuse. Comme ce type de données n’est pas disponible pour toute la population laitière, un échantillon de 602 analyses chromatographiques a été créé dans cette étude afin de développer une équation de calibrage permettant de prédire les quantités de méthane émises à partir du spectre moyen infrarouge (MIR) du lait qui est disponible pour toutes les vaches étudiées. Ensuite, l’équation de calibrage ainsi obtenue a été appliquée sur 604 028 données spectrales enregistrées entre 2007 et 2011 auprès de 70 872 vaches au cours de leurs trois premières lactations afin de prédire les quantités de méthane émises. Les paramètres génétiques de ces nouveaux indicateurs méthane prédits par MIR ont également été estimés en utilisant un modèle animal de type jour de test avec régressions aléatoires. Résultats. Ces quantités prédites par MIR variaient selon une gamme attendue s’étalant entre 350 ± 40 et 449 ± 65 g par jour. L’émission prédite moyenne de CH4 en g par jour augmentait au début de la lactation, atteignait sa plus haute concentration au pic de lactation et ensuite diminuait jusqu’à la fin de la lactation. Les héritabilités journalières moyennes variaient entre 0,29-0,35 ; 0,26-0,40 et 0,22-0,37 pour les différents indicateurs méthane étudiés au cours des trois premières lactations. Les plus grandes différences entre les valeurs d’élevage estimées pour des taureaux ayant des filles en production émettant le plus et le moins de méthane étaient de 24,18 ; 29,33 et 27,77 kg par lactation pour les trois premières lactations. Des corrélations faiblement négatives ont été observées entre les indicateurs CH4 et la quantité de lait. À l’inverse, des corrélations positives ont été estimées entre ces mêmes indicateurs et les taux en matières grasses et en protéines. Conclusions. Cette étude montre la possibilité de prédire des indicateurs méthane issus de la littérature et utilisant les concentrations en acides gras dans la matière grasse laitière à partir de la spectrométrie MIR. De plus, cette étude suggère également à partir des paramètres génétiques obtenus l’existence d’une variabilité phénotypique et génétique des quantités de méthane éructées par les vaches laitières Holstein. [less ▲]

Detailed reference viewed: 146 (59 ULg)
Full Text
Peer Reviewed
See detailStandardisation of milk MIR spectra, Development of common MIR equations
Grelet, Clément ULg; Fernandez Pierna, Juan Antonio; Dardenne, Pierre et al

Conference (2015)

Detailed reference viewed: 23 (3 ULg)
Full Text
Peer Reviewed
See detailHot topic: Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra
Vanlierde, Amélie; Vanrobays, Marie-Laure ULg; Dehareng, Frédéric et al

in Journal of Dairy Science (2015), In press

Detailed reference viewed: 76 (28 ULg)
Full Text
See detailHow to use ICT to help students to gain in confidence and efficiency in an algorithmic and computer programming course ?
Colaux, Catherine ULg; Soyeurt, Hélène ULg

in INTED2015 Proceedings (2015)

Algorithmic and computer programming in the bachelor’s degree is a course that demands a large involvement of students in performing non-standard exercises. This practical aspect is incompatible with ... [more ▼]

Algorithmic and computer programming in the bachelor’s degree is a course that demands a large involvement of students in performing non-standard exercises. This practical aspect is incompatible with classical ex cathedra course. It is the reason why we implement a blended learning approach much more responsive to students in a bachelor class of Bio Engineering at the Gembloux Agro Bio Tech Faculty (University of Liege, Belgium). This course alternates theoretical classes, take-home lessons with the help of online pedagogical resources and video and debriefing sessions where students have the possibility to benefit from teacher’ support. In doing so, the students are better prepared for the examination. They also gain in confidence and motivation. The teacher no longer simply transmits the knowledge but assists the students in their reflection process and their mastering of programming tools [less ▲]

Detailed reference viewed: 14 (9 ULg)
Full Text
Peer Reviewed
See detailGenetics of beef and milk fatty acid composition
Soyeurt, Hélène ULg; Beitz, Donald

in Garrick, D; Ruvinsky, A (Eds.) The genetics of cattle (2014)

Detailed reference viewed: 60 (34 ULg)
Full Text
See detailInnovative lactation stage specific prediction of CH4 from milk MIR spectra
Vanlierde, Amélie; Vanrobays, Marie-Laure ULg; Dehareng, Frédéric et al

Conference (2014, August 28)

Detailed reference viewed: 61 (37 ULg)
Full Text
See detailUsing milk spectral data for large-scale phenotypes linked to mitigation and efficiency
Soyeurt, Hélène ULg; Vanlierde, Amélie; Vanrobays, Marie-Laure ULg et al

Conference (2014, August 26)

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as ... [more ▼]

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as methane emission (CH4), dry matter intake (DMI) and feed efficiency (FE); however they are available on a small scale. Researches showed that CH4 could be predicted from milk mid-infrared (MIR) spectra, allowing large-scale recording at low cost. The main objective of this study was to show, using a modelling approach, that DMI and FE could be derived from milk MIR spectra. For that, knowledge of body weight (BW) is required; however it was unknown in this study. Derived procedure was based on milk yield and composition, MIR CH4, and modelled standard animal requirements, allowing the prediction of expected BW. An external validation was conducted based on 91 actual records. 95% confidence limit for the difference ranged between -0.66 and 18.84 kg for BW, from -0.02 to 0.26 kg/day for DMI, and from -0.02 to 0.002 kg of fat corrected milk/kg DM for FE. Root mean square errors were 39.66 kg, 0.56 kg/d, and 0.03 kg/DM for the 3 studied traits. P-value for the t-test was not significant for BW and DMI. This suggests the possibility to obtain expected BW and therefore DMI from MIR spectra. Single trait animal test-day models used 1,291,850 records to assess the variability of studied traits. Significant variations were observed for the lactation stage, parity, genetics, and age. These findings were in agreement with the literature except for early lactation. This suggests in conclusion that the MIR information gave similar results for DMI and CH4 for the major part of lactation. The use of this novel method to predict expected BW offers new possibilities interesting for the development of genomic and genetic tools. [less ▲]

Detailed reference viewed: 25 (5 ULg)
Full Text
See detailCreation of universal MIR calibration by standardization of milk spectra: example of fatty acids
Grelet, Clément ULg; Fernandez Pierna, Juan; Soyeurt, Hélène ULg et al

Poster (2014, August 25)

Detailed reference viewed: 56 (13 ULg)
Full Text
See detailUsing milk spectral data for large-scale phenotypes linked to mitigation and efficiency
Soyeurt, Hélène ULg; Vanlierde, Amélie; Vanrobays, Marie-Laure ULg et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as ... [more ▼]

Even if producing milk efficiently has always been a major concern for producers, the direct environmental impact of their cows is becoming a novel one. Traits linked to this issue were identified as methane emission (CH4), dry matter intake (DMI) and feed efficiency (FE); however they are available on a small scale. Researches showed that CH4 could be predicted from milk mid-infrared (MIR) spectra, allowing large-scale recording at low cost. The main objective of this study was to show, using a modelling approach, that DMI and FE could be derived from milk MIR spectra. For that, knowledge of body weight (BW) is required; however it was unknown in this study. Derived procedure was based on milk yield and composition, MIR CH4, and modelled standard animal requirements, allowing the prediction of expected BW. An external validation was conducted based on 91 actual records. 95% confidence limit for the difference ranged between -0.66 and 18.84 kg for BW, from -0.02 to 0.26 kg/day for DMI, and from -0.02 to 0.002 kg of fat corrected milk/kg DM for FE. Root mean square errors were 39.66 kg, 0.56 kg/d, and 0.03 kg/DM for the 3 studied traits. P-value for the t-test was not significant for BW and DMI. This suggests the possibility to obtain expected BW and therefore DMI from MIR spectra. Single trait animal test-day models used 1,291,850 records to assess the variability of studied traits. Significant variations were observed for the lactation stage, parity, genetics, and age. These findings were in agreement with the literature except for early lactation. This suggests in conclusion that the MIR information gave similar results for DMI and CH4 for the major part of lactation. The use of this novel method to predict expected BW offers new possibilities interesting for the development of genomic and genetic tools. [less ▲]

Detailed reference viewed: 11 (0 ULg)
Full Text
See detailInnovative lactation stage specific prediction of CH4 from milk MIR spectra
Vanlierde, Amélie; Vanrobays, Marie-Laure ULg; Dehareng, Frédéric et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

Detailed reference viewed: 22 (6 ULg)
Full Text
Peer Reviewed
See detailConsequences of Selection for Environmental Impact Traits in Dairy Cows
Kandel, Purna Bhadra ULg; Vanderick, Sylvie ULg; Vanrobays, Marie-Laure ULg et al

in Proceedings, 10th World Congress of Genetics Applied to Livestock Production (2014, August)

Genetic selection programs aiming to mitigate methane (CH4) emissions require the estimation of genetic correlations with other production and economical traits and predicted selection response. CH4 ... [more ▼]

Genetic selection programs aiming to mitigate methane (CH4) emissions require the estimation of genetic correlations with other production and economical traits and predicted selection response. CH4 intensity was predicted from Mid-infrared spectra of milk samples from Holstein cows. Genetic correlations between CH4 intensity and milk yield (MY) was -0.68, fat yield (FY) -0.13, protein yield (PY) -0.47, somatic cell score (SCS) 0.07, longevity 0.05, fertility 0.31, body condition score (BCS) 0.17. Adding 25% relative weight on CH4 intensity to the current Walloon selection index, the response to selection would reduce CH4 intensity by 24%, increase MY by 30%, FY by 17%, PY by 29%, SCS by -14%, longevity by 24% but also reduce fertility by 11% and BCS by 13%. In conclusion, environmental traits can be added without jeopardizing production traits, but energy balance related traits have to be protected. [less ▲]

Detailed reference viewed: 34 (13 ULg)
Full Text
See detailCreation of universal MIR calibration by standardization of milk spectra: example of fatty acids
Grelet, Clément; Fernandez Pierna, Juan; Soyeurt, Hélène ULg et al

in Book of abstracts of the 65th annual meeting of the European Federation of Animal Science (2014, August)

Detailed reference viewed: 31 (7 ULg)
Full Text
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 (2014, February 17)

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 ▲]

Detailed reference viewed: 16 (0 ULg)
Full Text
See detailConsequences of Selection for Environmental Impact Trait in Dairy Cows
Kandel, Purna Bhadra ULg; Vanderick, Sylvie ULg; Vanrobays, Marie-Laure ULg et al

Scientific conference (2014, February 07)

Environmental sustainability is gaining importance in dairy industry due to enteric methane (CH4) emission from dairy cows. We predicted CH4 indicator trait (CH4 intensity: CH4 g/kg of milk) from Mid ... [more ▼]

Environmental sustainability is gaining importance in dairy industry due to enteric methane (CH4) emission from dairy cows. We predicted CH4 indicator trait (CH4 intensity: CH4 g/kg of milk) from Mid-infrared spectra of milk samples and recorded milk yield. Genetic correlations between CH4 intensity and milk production traits were estimated on Holstein cows from correlations of estimated breeding values. Genetic correlations between CH4 intensity and milk yield (MY) was -0.67, fat yield (FY) -0.13, protein yield (PY) -0.46, somatic cell score (SCS) 0.02, longevity -0.07, fertility 0.31, body condition score (BCS) 0.27 and average of confirmation traits -0.23. Currently, there is no CH4 emission trait in genetic evaluation selection index. Putting an hypothetical 25% weight on CH4 intensity on current Walloon genetic evaluation selection index and proportional reduction on other selection traits, the response to selection will be reduction of CH4 emission intensity by 24%, increase in MY by 30%, FY by 17%, PY by 29%, SCS by -15%, longevity by 24%, fertility by -11%, BCS by -13% and conformation traits by 24%. In conclusion, introduction of environmental traits in current selection index will affect selection responses. As there is no economic value of these traits presently alternative methods like putting correlated traits with clear economic value (e.g. feed efficiency) in the selection objective could generate appropriate index weights. [less ▲]

Detailed reference viewed: 71 (30 ULg)
Full Text
See detailPotentiel d'utilisation de la spectrometrie moyen infrarouge pour prédire le rendement fromager du lait et étudier sa variabilité génétique
Colinet, Frédéric ULg; Troch, Thibault ULg; Abbas, O. et al

Conference (2013, December 04)

Providing a quick, reliable and cheap indication of the expected cheese yield for a milk sample by avoiding (empirical or theoretical) formulas based on previously determined milk constituents would be an ... [more ▼]

Providing a quick, reliable and cheap indication of the expected cheese yield for a milk sample by avoiding (empirical or theoretical) formulas based on previously determined milk constituents would be an economically valuable tool useful for farmers and the dairy industry. In order to study the genetic variability of cheese yield on a large scale, mid-infrared (MIR) chemometric methods were used to predict fresh or dry Individual Laboratory Cheese Yield (RdFF and RdFS, respectively). RdFF and RdFS were determined on a total of 258 milks samples also analyzed by a MIR spectrometer. Equations to predict RdFF and RdFS from milk MIR spectra were developed using partial least square regression (PLS) after first derivative pre-traitment applied to the spectra. The cross-validation coefficients of determination (R²cv) of the two equations were equal to 0.81 for the prediction of RdFF and 0.82 for the prediction RdFS. The ratios of performance to deviation (RPD) of the two equations were both equal to 2.3. Therefore, these results suggest a practical utility of these two equations, i.e. for genetic research. Both equations were applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated using univariate random regressions animal test-day model. The dataset included 51 537 predicted records from 7 870 Holstein first-parity cows. Estimated daily heritabilities ranged from 0.31 (at 5th day in milk (DIM)) to 0.59 (at 279th DIM) for RdFF and from 0.31 (at 5th DIM) to 0.57 (at 299th DIM) for RdFS. Those moderate to high daily heritabilities indicated potential of selection for both traits. [less ▲]

Detailed reference viewed: 45 (15 ULg)
Full Text
Peer Reviewed
See detailPotentiel d'utilisation de la spectrometrie moyen infrarouge pour prédire le rendement fromager du lait et étudier sa variabilité génétique
Colinet, Frédéric ULg; Troch, Thibault ULg; 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 ▲]

Detailed reference viewed: 42 (10 ULg)