References of "Soyeurt, Hélène"
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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 ▲]

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See detailComparison of 3 different variable selection strategies to improve the predictions of fatty acid profile in bovine milk by mid-infrared spectrometry
Soyeurt, Hélène ULg; Brostaux, Yves ULg; Dehareng, Frédéric et al

in Journal of Dairy Science (2015), 98(suppl 2), 804

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See detailAssessing resilience of dairy cattle by studying impact of heat stress on predicted feed intake
Vanrobays, Marie-Laure ULg; Hammami, Hedi ULg; Laine, Aurélie ULg et al

in Proceedings of the Third DairyCare Conference 2015 (2015)

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See detailStandardisation of milk MIR spectra, Development of common MIR equations
Grelet, Clément ULg; Fernandez Pierna, Juan Antonio; Dardenne, Pierre et al

Conference (2015)

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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

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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 ▲]

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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)

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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)

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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 ▲]

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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)

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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

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

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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 ▲]

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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)

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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 ▲]

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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 (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 ▲]

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See detailEstimating daily yield and content of major fatty acids from single milking
Arnould, Valérie ULg; Reding, Romain; Delvaux, Charles et al

Poster (2014, February 07)

Reducing the frequency of milk recording and the number of recorded samples per test-day could be a solution in order to reduce costs of official milk recording. However, fewer samples lead to a decrease ... [more ▼]

Reducing the frequency of milk recording and the number of recorded samples per test-day could be a solution in order to reduce costs of official milk recording. However, fewer samples lead to a decrease in the accuracy of predicted daily yields. Unfortunately, the current published equations use the milking interval that is often not available and/or reliable in practice. The first objective of this study was to propose models using easily available traits. Therefore the milking interval was replaced by a combination of data easily recorded by milk recording. The second objective of this study was to enlarge the previous investigations to milk fatty acids (FA) in order to propose a practical method for estimating accurate daily milk, fat and major FA yields from single milking. The fit goodness of proposed models was evaluated based on the correlation values between the estimated and observed daily yields in addition to the calculation of the mean square error. Obtained results are promising. Correlation values were comprised between 96.4% and 97.6% when daily yield were estimated from morning milking, and from 96.9% to 98.3% when daily yield were estimated from evening milking. The combination of records related to lactation stage, month of test, milk yield, and fat could replace the milking interval effect. Because of their simplicity, proposed models would be easy to implement. [less ▲]

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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 ▲]

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