References of "Gengler, Nicolas"
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See detailEvaluation of Heat Stress Effects on Production Traits and Somatic Cell Score of Holsteins in a Temperate Environment
Hammami, Hedi ULiege; Bormann, Jeanne; M'Hamdi, Naceur et al

in Journal of Dairy Science (2013), 96(3), 1844-1855

This study was aimed to evaluate the degree of thermal stress exhibited by Holsteins under a continental temperate climate. Milk, fat, protein, and somatic cell count test-day records collected between ... [more ▼]

This study was aimed to evaluate the degree of thermal stress exhibited by Holsteins under a continental temperate climate. Milk, fat, protein, and somatic cell count test-day records collected between 2000 and 2011 from 23,963 cows in 604 herds were combined with meteorological data from 14 public weather stations in Luxembourg. Daily values of six different thermal indices (TI) weighted in term of temperature, relative humidity, solar radiation, and wind speed were calculated by averaging hourly TI over 24 hours. Heat stress thresholds were firstly identified by a broken-line regression model. Regression models were thereafter applied to quantify milk production losses due to heat stress. The tipping points at which milk and protein yields declined were effectively identified. For fat yield, no valid threshold was identified for any of the studied TI. Daily fat yields tended to decrease steadily with increasing values of TI. Daily somatic cell scores (SCS) pattern was marked by increased values at both lowest and highest TI ranges with a more pronounced reaction to cold stress for apparent temperature indices. Thresholds differed between TI and traits. For production traits, they ranged from 62 (TI1) to 80 (TI3) for temperature-humidity indices (THI) and from 16 (TI5) to 20 (TI6) for apparent temperature indices. Corresponding SCS thresholds were higher and ranged from 66 (TI1) to 82 (TI3) and from 20 (TI5) to 23 (TI6), respectively. The largest milk decline per unit of mild, moderate, and extreme heat stress levels of 0.164, 0.356, and 0.955 kg, respectively, was observed when using the conventional THI (TI1). The highest yearly milk, fat, and protein losses of 54, 5.7, and 4.2 kg respectively were detected by TI2, the THI index that is adjusted for wind speed and solar radiation. The latter index could be considered as the best indicator of heat stress to be used for forecast and herd management in a first step in temperate regions under anticipated climate changes. [less ▲]

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See detailNeuartige Management Tools für Milchviehbetrieb mittels Spektralanalytik
Arnould, Valérie ULiege; Reding, Romain; Bormann, Jeanne et al

Article for general public (2013)

In den letzten Jahrzenten wurde die Milch- und Fleischproduktion mehr und mehr mit generellen Nachhaltigkeitsfragen in Verbindung gebracht. Sehr oft wird eine bessere Produktionsnachhaltigkeit auch mit ... [more ▼]

In den letzten Jahrzenten wurde die Milch- und Fleischproduktion mehr und mehr mit generellen Nachhaltigkeitsfragen in Verbindung gebracht. Sehr oft wird eine bessere Produktionsnachhaltigkeit auch mit ökonomischen Aspekten verbunden. In der Tat liegt die Kunst der modernen Milchproduktion scheinbar vor allem darin, die Produktion (egal ob tier- oder betriebsindividuell) stetig bei möglichst gleichbleibenden oder gar noch geringeren Kosten zu erhöhen. Daneben ist zu bedenken, dass Konsumenten heutzutage neben preislichen Aspekten sehr oft zusätzlich Gesundheitsaspekte ins Spiel bringen, so dass es für Milchbetriebe nicht unwesentlich ist, die Produktion in gewisser Weise diesen Ansprüchen nach zu gestalten. Glücklicherweise können entscheidende Inhaltsstoffe wie der Milchfettgehalt oder das Fettsäuremuster der Milch durch Managementfaktoren wie Zucht, Selektion, Fütterung und Haltungsbedingungen zum Positiven beeinflusst werden und den Anforderungen der Nachfrageseite besser angepasst werden. Genau bei dieser Problematik liegen die Ansatzpunkte der verschiedenen CONVIS Projekte (QuaM, ManageMILK und OptiMIR) im Bereich Spektralanalysen der Milch. [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 detailSur la voie de l’élevage laitier de précision en Wallonie - 2. ValLait, OptiVal et OptiVal+ : valoriser des données du contrôle des performances
Bastin, Catherine ULiege; Gillon, A.; Massart, X. et al

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

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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 detailL'intérêt des races mixtes dans les systèmes laitiers : enseignements du projet BlueSel
Muchembled, A.; Beguin, E.; Glorieux, G. et al

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

La « Bleue Mixte » (BM) est une race à petit effectif localisée de part et d’autre de la frontière franco-belge. Menacée de disparition, elle bénéficie d’un projet transfrontalier BlueSel soutenu par le ... [more ▼]

La « Bleue Mixte » (BM) est une race à petit effectif localisée de part et d’autre de la frontière franco-belge. Menacée de disparition, elle bénéficie d’un projet transfrontalier BlueSel soutenu par le programme européen INTERREG IV et les autorités françaises et wallonnes. L’objectif de ce projet est d’assurer la conservation, la sélection et la promotion de la BM. L’un des volets du programme a consisté à étudier la rentabilité économique des troupeaux BM. Il s’est appuyé sur un réseau de 16 fermes de références mis en place fin 2008 jusque mi 2012. La collecte des données techniques et économiques sur les 4 années comptables de 2007 à 2010 a reposé sur la méthodologie mise en oeuvre au sein du dispositif français des Réseaux d’élevage. Les exploitations BM ont été regroupées selon deux systèmes, herbivore et polyculture-élevage, et comparées aux exploitations laitières Prim’Holstein (PH) du Réseau d’élevage de Nord-Picardie. Les résultats démontrent la capacité des éleveurs de vaches BM à obtenir de bonnes performances économiques malgré de plus faibles productivité laitière (4225 l/VL) et taux (3,70 % de MG et 3,22 % de protéines), et un moindre prix du lait, grâce notamment à une conduite de troupeaux bien maîtrisée, des surfaces fourragères très bien valorisées, et la mixité lait-viande très affirmée de la race qui atténue les fluctuations du prix du lait. En système herbivore, les exploitations BM s’avèrent économes et autonomes avec une excellente valorisation des prairies. En système de polyculture-élevage, les troupeaux sont conduits de façon à peine plus intensive qu’en système herbivore, contrairement aux troupeaux PH. [less ▲]

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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 detailUse of automated systems for recording of direct and indirect data with special emphasis on the use of MIR milk spectra (OptiMIR project)
Gengler, Nicolas ULiege; Berry, D. P.; Bastin, Catherine

in Challenges and benefits of health data recording in the context of food chain quality, management and breeding. (2013)

A current tendency in developing tools to support farm management is to make use of advanced sensors closely associated to animals, facilitating the collection of large quantities of data ideally at a low ... [more ▼]

A current tendency in developing tools to support farm management is to make use of advanced sensors closely associated to animals, facilitating the collection of large quantities of data ideally at a low cost without perturbing the animal itself. On a dairy farm level, sensors measuring milk conductivity or pedometers measuring mobility are often cited as examples. This introduces the concept of "precision livestock farming" where a given "bioresponse" captured by a "biosensor" allows the creation of feedback to adjust the "bioprocess". Such on-farm systems are often restricted to a given farm and they are mostly strictly separated from standard performance recording systems. In dairy cows, a particular rich source of information to detect a "bioresponse" is milk and its (fine) composition. Standard milk analysis undertaken in milk recording schemes by mid infrared spectroscopy (MIR) generates spectral data that reflects the milk characteristics. Therefore, spectral data directly reflects the metabolic (e.g., energy balance) and health (e.g., udder health) status of the cow. The use of MIR spectral data to predict fine milk components (e.g., fatty acids) is now becoming commonplace. However the use of MIR spectral data could provide an even more direct method to assess the "bioresponse" in relation to health, fertility, feeding, milk quality and even rejection of pollutants. For this reason, 12 EU milk recording organizations and milk laboratories together with 6 EU research groups have joined forces to develop the North-West Europe INTERREG IVB Project OptiMIR (www.optimir.eu). As a first step to use spectral data for developing decision support tools, the project includes the development of methods to standardize spectral data generated by various apparatuses in different laboratories. Through the OptiMIR project, health indicator traits from milk analysis either through the prediction of milk components (i.e. lactoferrin) or through the direct assessment of the health status of the cow (i.e. clinical mastitis) will become available. These data can then be generated in routine milk recording and can be stored in a central database. Because generating MIR data at the on-farm level is still difficult and expensive, the use of near infrared (NIR) spectroscopy is currently also under investigation by other groups. For a comprehensive use of fine milk composition, as for other automated sensors, the optimum would be a close and bi-directional interaction between in-line on-farm systems and central databases in order to contribute to the successful implementation of powerful health monitoring systems and decision support tools. [less ▲]

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See detailDistributed computing as a new opportunity for stakeholders in dairy cattle management and breeding
Gengler, Nicolas ULiege

in Berckmans, D; Vandermeulen, J (Eds.) Precision Livestock Farming ‘13 (2013)

Currently the uses of on-farm computers and of centralized performance-recording based tools are considered as two opposite models for dairy management. However, dividing the problem into complementary ... [more ▼]

Currently the uses of on-farm computers and of centralized performance-recording based tools are considered as two opposite models for dairy management. However, dividing the problem into complementary tasks, each of which is optimally solved, is an opportunity that should also be considered by stakeholders. recent development solved data exchange issues allowing the use of adapted distributed computing algorithms. as example milk yield and composition are given. Different research projects and several commercial companies are focussing on the development of on-farm tools, mostly near infrared (nir) based, other projects are developing and implementing tools based on mid infrared (mir), available only through performance recording.Both are complementary, as nir based measurements are easier and less expensive, available at every milking, but mir based measurements are more precise, however only obtained every 4 weeks. numerous advantages arise when combining both types of measurements. it will be shown that statistical theory exists to base advanced modelling on, using optimally the longitudinal data generated by this type of setting. this will open different novel opportunities to optimize currently used on-farm and off-farm management and breeding tools. [less ▲]

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See detailOptiMIR : de nouveaux outils de management des exploitations laitières grâce au spectre moyen infra-rouge du lait
Grelet, Clément ULiege; Fernandez Pierna, Juan Antonio; Dehareng, Frédéric et al

Conference (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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See detailSystème d'évaluations génétiques des verrats Piétrain en croisement en Wallonie
Dufrasne, Marie ULiege; Gengler, Nicolas ULiege

Conference given outside the academic context (2013)

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See detailEvaluations génétiques des verrats Piétrain en croisement en Wallonie
Dufrasne, Marie ULiege; Gengler, Nicolas ULiege

Conference given outside the academic context (2013)

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