References of "Gengler, Nicolas"
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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 detailGenetic analysis of heat stress effects on yield traits, udder health, and fatty acids of Walloon Holstein cows
Hammami, Hedi ULg; Vandenplas, Jérémie; Vanrobays, Marie-Laure ULg et al

in Journal of Dairy Science (2015), 98(7), 4956-4968

Genetic parameters that considered tolerance for heat stress were estimated for production, udder health, and milk composition traits. Data included 202,733 test-day records for milk, fat, and protein ... [more ▼]

Genetic parameters that considered tolerance for heat stress were estimated for production, udder health, and milk composition traits. Data included 202,733 test-day records for milk, fat, and protein yields, fat and protein percentages, somatic cell score (SCS), 10 individual milk fatty acids (FA) predicted by mid-infrared spectrometry, and 7 FA groups. Data were from 34,468 first-lactation Holstein cows in 862 herds in the Walloon region of Belgium and were collected between 2007 and 2010. Test-day records were merged with daily temperature-humidity index (THI) values based on meteorological records from public weather stations. The maximum distance between each farm and its corresponding weather station was 21km. Linear reaction norm models were used to estimate the intercept and slope responses of 23 traits to increasing THI values. Most yield and FA traits had phenotypic and genetic declines as THI increased, whereas SCS, C18:0, C18:1 cis-9, and 4 FA groups (unsaturated FA, monounsaturated FA, polyunsaturated FA, and long-chain FA) increased with THI. Moreover, the latter traits had the largest slope-to-intercept genetic variance ratios, which indicate that they are more affected by heat stress at high THI levels. Estimates of genetic correlations within trait between cold and hot environments were generally high (>0.80). However, lower estimates (< = 0.67) were found for SCS, fat yield, and C18:1 cis-9, indicating that animals with the highest genetic merit for those traits in cold environments do not necessarily have the highest genetic merit for the same traits in hot environments. Among all traits, C18:1 cis-9 was the most sensitive to heat stress. As this trait is known to reflect body reserve mobilization, using its variations under hot conditions could be a very affordable milk biomarker of heat stress for dairy cattle expressing the equilibrium between intake and mobilization under warm conditions. [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 detailPotential use of milk based biomarkers to assess and to select for heat tolerance in dairy cattle
Hammami, Hedi ULg; Vandenplas, Jérémie; Vanrobays, Marie-Laure ULg et al

in Proceedings of the second DairyCare Conference 2015 (2015)

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See detailIntegration of external estimated breeding values and associated reliabilities using correlation among traits and effects
Vandenplas, J.; Colinet, Frédéric ULg; Glorieux, G. et al

in Journal of Dairy Science (2015), 98(12), 90449050

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See detailMonitoring the pregnancy status of dairy cows using mid-infrared spectra of milk collected from milk recording
Laine, Aurélie ULg; Dale, Laura-Monica ULg; Bel Mabrouk, Hana ULg et al

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE] (2015), 19(2), 97-124

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See detail7.2. Assessing the pregnancy status of dairy cows by mid-infrared analysis of milk
Laine, Aurélie ULg; Bel Mabrouk, Hana ULg; Dale, Laura-Monica ULg et al

in Precision livestock farming applications (2015)

In dairy cattle, unlike other species, performance recording schemes make it possible to provide advisory tools which integrate information across the whole population. Mid-infrared (MIR) analysis of milk ... [more ▼]

In dairy cattle, unlike other species, performance recording schemes make it possible to provide advisory tools which integrate information across the whole population. Mid-infrared (MIR) analysis of milk provides a spectrum for each individual cow’s milk sample. The MIR spectrum represents the whole milk composition and can be used to assess the status of the animal (e.g. health, pregnancy, feeding). The main objective of the European project OptiMIR (INTERREG IVB North West Europe Programme) is to develop innovative advisory tools based on the MIR data collected by milk recording organizations. One of the objectives is to develop a tool to assess the pregnancy status of cows. The tool uses an innovative comparison of observed spectra with expected spectra predicted from a set of spectra with a known cow status, in this case open. Development was carried out using Walloon milk recording data. A training dataset (348,191 spectral data from 49,849 cows) was used to obtain residual spectra (i.e. difference between observed and expected spectra). Based on the fact that the pregnancy status of all cows was known, a predictive discriminant function was constructed using 7,524 residual spectra randomly selected from the initial dataset. The discriminant function was then applied to the rest of the dataset (24,278 residual spectra) for validation. When considering the period from 21 to 50 days after insemination, the error rate was about 7.5 with a specificity of 95.3 and a sensitivity of 87.2\%. These results showed a high potential for directly using the MIR spectrum of milk to detect a change in the pregnancy status of dairy cows. This methodology can also be applied to predict other types of physiological status changes (e.g. udder health related) and can be used on other types of biomarker data (i.e. collected from on-farm sensors). Similarly, integration of on-farm information on expected pregnancy status could improve the off-farm tool presented here. [less ▲]

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See detailDerivation of a new lamb survival trait for the New Zealand sheep industry
Vanderick, Sylvie ULg; Auvray, Benoit; Newman, Sheryl-Anne et al

in Journal of Animal Science (2015), 93

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited ... [more ▼]

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited bureau of lamb deaths. This paper reports the decision rules and genetic parameters for a new lamb survival trait for the New Zealand sheep industry. These rules define the new lamb survival trait (NEWSUR) using lamb birth fate (BFATE) codes and the presence/absence of lamb weight measurements. Six univariate animal models were tested and used to estimate variance or covariance components and the resulting direct and maternal heritabilities for NEWSUR. The models differed in the way they adjust for the effect of day of birth, the exclusion or inclusion of a litter (dam/year of birth) random effect and the application or not of a logit transformation of the phenotypes. For both the linear and logistic methods, models including the random effect of litter provided the best fit for NEWSUR according to log-likelihood values. Log-likelihoods for the linear and logistic models cannot be compared, therefore a cross-validation method was used to assess whether the logit transformation was appropriate by analyzing the predictive ability of the models. The mean square errors were slightly lower for the linear compared to the logistic model and therefore the linear model was recommended for industry use. The heritability attributed to direct effects ranged from 2 to 5.5%. A direct heritability of 5.5% resulted from a linear model without litter effect and omitting the effect of day of birth on survival, whereas a direct heritability of 2% resulted from the logistic model fitting a random litter effect. The heritability attributed to maternal genetic effects ranged from 1.9 to 7.7%. A maternal genetic heritability of 7.7% resulted from the logistic model omitting the litter effect, whereas a maternal genetic heritability of 1.9% resulted from the linear model fitting a random litter effect. The addition of the litter random effect decreased the maternal heritabilities substantially in all cases and was recommended for industry use to avoid overestimation of the maternal genetic variance. SIL has implemented NEWSUR and the associated genetic evaluation model based on information described in this paper. Industry wide implementation will enable sheep breeders to produce more accurate genetic evaluations to their commercial clients. [less ▲]

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See detailInvited review: overview of new traits and phenotyping strategies in dairy cattle with a focus on functional traits
Egger-Danner, C.; Cole, J. B.; Pryce, J. E. et al

in animal (2015), 9

ABSTRACT For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in ... [more ▼]

ABSTRACT For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm include, for example, slaughter houses (meat composition and quality) and veterinary labs (specific pathogens, viral loads). At the farm level, many data are available from automated and semi-automated milking and management systems. Electronic devices measuring physiological status or activity parameters can be used to predict events such as oestrus, and also behavioural traits. Challenges concerning the predictive biology of indicator traits or standardization need to be solved. To develop effective selection programmes for new traits, the development of large databases is necessary so that high-reliability breeding values can be estimated. For expensive-to-record traits, extensive phenotyping in combination with genotyping of females is a possibility. [less ▲]

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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

Detailed reference viewed: 112 (46 ULg)