References of "Colinet, Frédéric"
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See detailUtiliser les résultats du contrôle laitier pour améliorer son rendement fromager
Colinet, Frédéric ULg; Troch, Thibault ULg

Conference given outside the academic context (2016)

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See detailCapitalizing in fine milk composition for breeding and management of dairy cows
Gengler, Nicolas ULg; Soyeurt, Hélène ULg; Dehareng, Fréderic et al

in Journal of Dairy Science (2016), 99

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of ... [more ▼]

The challenge of managing and breeding dairy cows is permanently adapting to changing production circumstances under socio-economic constraints. If managing and breeding address different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, and their health, behavior, and well-being as well as their environmental impact and the quality of their products (i.e., milk and subsequently dairy products). Milk composition has been identified as an important source of information because it could reflect, at least partially, all these elements. Major conventional milk components such as fat, protein, urea, and lactose contents are routinely predicted by mid-infrared (MIR) spectrometry and have been widely used for these purposes. But, milk composition is much more complex and other nonconventional milk components, potentially predicted by MIR, might be informative. Such new milk-based phenotypes should be considered given that they are cheap, rapidly obtained, usable on a large scale, robust, and reliable. In a first approach, new phenotypes can be predicted from MIR spectra using techniques based on classical prediction equations. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate) that can be then useful for management and breeding purposes. An innovation was to consider the longitudinal nature of the relationship between the trait of interest and the MIR spectra (e.g., to predict methane from MIR). By avoiding intermediate steps, prediction errors can be minimized when traits of interest (e.g., methane, energy balance, ketosis) are predicted directly from MIR spectra. In a second approach, research is ongoing to detect and exploit patterns in an innovative manner, by comparing observed with expected MIR spectra directly (e.g., pregnancy). All of these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality, and mitigate environmental impact. Under the condition that MIR data are available on a large scale, phenotypes for these traits will allow genetic and genomic evaluations. Introduction of novel traits into the breeding objectives will need additional research to clarify socio-economic weights and genetic correlations with other traits of interest. [less ▲]

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See detailPotential of visible-near infrared spectroscopy for the characterization of butter properties
Troch, Thibault ULg; Baeten, Vincent; Dehareng, Frédéric et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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See detailOn the use of novel milk phenotypes as predictors of difficult-to-record traits in breeding programs
Bastin, Catherine ULg; Colinet, Frédéric ULg; Dehareng, Frédéric et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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See detailGenetic variability of MIR predicted milk technological properties in Walloon dairy cattle
Colinet, Frédéric ULg; Troch, Thibault ULg; Baeten, Vincent et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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See detailGenetic heritage of the Eastern Belgium Red and White breed, an endangered local breed
Colinet, Frédéric ULg; Bouffioux, Aude; Mayeres, Patrick et al

Poster (2015, August)

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See detailOverview of possibilities and challenges of the use of infrared spectrometry in cattle breeding
Gengler, Nicolas ULg; Soyeurt, Hélène ULg; Dehareng, Frédéric et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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See detailGenetic analysis to support the re-establishment of the Kempen breed
François, Liesbeth; Janssens, Steven; Colinet, Frédéric ULg et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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See detailGenetic heritage of the Eastern Belgium Red and White breed, an endangered local breed
Colinet, Frédéric ULg; Bouffioux, Aude; Mayeres, Patrick et al

in Book of Abstracts of the 66th Annual Meeting of the European Federation of Animal Science (2015, August)

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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 detailUnified method to integrate and blend several, potentially related, sources of information for genetic evaluation
Vandenplas, Jérémie ULg; Colinet, Frédéric ULg; Gengler, Nicolas ULg

in Genetics, Selection, Evolution (2014), 46

Background A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For ... [more ▼]

Background A condition to predict unbiased estimated breeding values by best linear unbiased prediction is to use simultaneously all available data. However, this condition is not often fully met. For example, in dairy cattle, internal (i.e. local) populations lead to evaluations based only on internal records while widely used foreign sires have been selected using internally unavailable external records. In such cases, internal genetic evaluations may be less accurate and biased. Because external records are unavailable, methods were developed to combine external information that summarizes these records, i.e. external estimated breeding values and associated reliabilities, with internal records to improve accuracy of internal genetic evaluations. Two issues of these methods concern double-counting of contributions due to relationships and due to records. These issues could be worse if external information came from several evaluations, at least partially based on the same records, and combined into a single internal evaluation. Based on a Bayesian approach, the aim of this research was to develop a unified method to integrate and blend simultaneously several sources of information into an internal genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. Results This research resulted in equations that integrate and blend simultaneously several sources of information and avoid double-counting of contributions due to relationships and due to records. The performance of the developed equations was evaluated using simulated and real datasets. The results showed that the developed equations integrated and blended several sources of information well into a genetic evaluation. The developed equations also avoided double-counting of contributions due to relationships and due to records. Furthermore, because all available external sources of information were correctly propagated, relatives of external animals benefited from the integrated information and, therefore, more reliable estimated breeding values were obtained. Conclusions The proposed unified method integrated and blended several sources of information well into a genetic evaluation by avoiding double-counting of contributions due to relationships and due to records. The unified method can also be extended to other types of situations such as single-step genomic or multi-trait evaluations, combining information across different traits. [less ▲]

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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 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 ▲]

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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 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 ▲]

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See detailNew tools for the dairy sector based on MIR and NIR spectroscopy
Grelet, Clément ULg; Dehareng, Frédéric; Vanlierde, Amélie ULg et al

Conference (2013, November 05)

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

Conference (2013, August 29)

Detailed reference viewed: 35 (17 ULg)