References of "Gengler, Nicolas"
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See detailRelationship between milk composition estimated from mid infrared and methane emissions in dairy cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, F et al

Scientific conference (2012, December 03)

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See detailIntegration/blending of external information into genetic/genomic evaluations
Vandenplas, Jérémie ULg; Gengler, Nicolas ULg

Diverse speeche and writing (2012)

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See detailRelationship matrices and Iterative construction of their inverses
Faux, Pierre ULg; Gengler, Nicolas ULg

Diverse speeche and writing (2012)

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See detailCapitalizing on mid-infrared to improve nutritional and environmental quality of milk
Soyeurt, Hélène ULg; Dehareng, Frédéric; Gengler, Nicolas ULg et al

Conference (2012, November 07)

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See detailDiversité de l’abeille & sélection de souches tolérantes à Varroa destructor
Leclercq, Gil ULg; Francis, Frédéric ULg; Haubruge, Eric ULg et al

Conference given outside the academic context (2012)

Présentation des 2 volets de recherche du projet "Selapis" (D31-1280) : la diversité de l'abeille et la sélection de souches tolérantes au Varroa

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See detailEstimation of genetic parameters for longitudinal measurements of feed intake in Piétrain sire lines
Dufrasne, Marie ULg; Jaspart, Véronique; Wavreille, José et al

Conference (2012, August 30)

The aim of this study was to estimate the genetic parameters for longitudinal measurements of feed intake (FI) in a crossbred population of pigs to develop a genetic evaluation model for the estimation of ... [more ▼]

The aim of this study was to estimate the genetic parameters for longitudinal measurements of feed intake (FI) in a crossbred population of pigs to develop a genetic evaluation model for the estimation of breeding values for FI of Piétrain boars. Data were collected on crossbred pigs in test station in the context of the genetic evaluation system of Piétrain boars in the Walloon Region of Belgium. Trait analyzed was daily FI (DFI). Because there were no facilities to record individual DFI in the Walloon test station, individual DFI were assumed to be the total pen FI divided by the number of pigs per pen. The edited dataset consisted of 3,902 measurements of DFI recorded on 1,975 crossbred pigs from 75 purebred Piétrain sires and 150 Landrace dams from the hyperprolific Landrace K+ line. A random regression animal model with fixed effects of sex and pen, and random effects of additive genetic, permanent environment and residual was developed in this study. Random additive genetic and permanent environment effects were modeled with linear splines with knots located at 75, 100, 175 and 210 d. The mean DFI was 1.979 kg/d with a SD of 0.479 kg/d. Estimated heritability for DFI increased with age from 0.02 at 75 d to 0.30 at 210 d. Estimated genetic correlation between age decreased when age interval increased. These preliminary results are consistent with literature. However, additional research are ongoing to test alternative random regression models that should be better than using splines for longitudinal performance of DFI. Furthermore, genetic relationship between DFI and other production traits, like growth and carcass traits, must be analyzed. [less ▲]

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See detailAlternative single-step type genomic prediction equations
Gengler, Nicolas ULg; Nieuwhof, G.J.; Konstantinov, K.V. et al

Conference (2012, August 28)

Current derivations of single-step equations are based on modified relationships among animals replacing for genotyped animals and on an inverted scale, pedigree based relationships, by modified ones ... [more ▼]

Current derivations of single-step equations are based on modified relationships among animals replacing for genotyped animals and on an inverted scale, pedigree based relationships, by modified ones. These relationships are obtained as linear combination of strictly genomic and pedigree based relationships, therefore implicitly 'weighting' SNP and polygenic effects. Alternative equations were recently proposed deabsorbing the genomic relationships out of the equations. This derivation did not change basic assumptions, but was derived using a matrix of relationship differences. This presentation will show a new and alternative derivation of single-step type genomic prediction equations allowing joint estimation of GEBV and SNP effects based on the partitioning of genetic (co ) variances. The method was derived from a random mixed inheritance model where SNP and residual polygenic effects are jointly modeled. The derived equations were modified to allow non-genotyped animals and to estimate directly and jointly GEBV and SNP effects. Equations resemble superficially recently proposed alternative single-step equations but were derived differently and arc based on completely different assumptions. They also avoid certain issues in dc-absorbing derivation linked to the matrix of relationship differences by using (co ) variances. Several other advantages of the new equations are that weighting of SNP and polygenic effects becomes explicitly and that SNP effects are also estimated. This method makes better use of High-Density SNP panels and can be easily modified to accommodate other genetic effects as major gene effects or copy-number variant based effects. Finally these alternative equations combine advantages of single-step and of explicit SNP effect estimation based methods. Additional research is required to test and validate further the proposed method. [less ▲]

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See detailMid-infrared predictions of fatty acids in bovine milk : final results of the RobustMilk project
Soyeurt, Hélène ULg; McParland, Sinead; Berry, Donagh et al

Poster (2012, August 28)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on ... [more ▼]

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on MIR spectra and FA from multiple countries, production systems, and breeds were used to develop equations to predict milk FA. The calibration set contained 1,776 spectrally different English, Irish, and Belgian milk samples collected for over 6 years. FA were quantified by gas chromatography (GC). Equations were built using partial least squares regression after a first derivative pretreatment applied to the spectral data. The robustness of the developed equations was assessed by cross-validation (CV) using 50 groups from the calibration set. The coefficient of determination (R²) obtained after CV ranged between 0.7101 for the total content of C18:2 and 0.9993 for the saturated FA group. The standard error of CV ranged between 0.0028 and 0.0998 g/dl of milk. Generally, the group or individual FA having the highest content in milk had the highest R²cv. The results obtained in this study confirmed the usefulness of MIR spectra to robustly quantify the FA content of milk permitting the use of these equations by milk laboratories in UK, Belgium or Ireland. Therefore, these equations could be used to develop selection or management tools for dairy farmers in order to improve the nutritional and environmental quality of milk based on the knowledge of the FA composition of their milk. [less ▲]

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See detailMid-infrared prediction of milk titratable acidity and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Vanlierde, Amélie ULg; Vanden Bossche, sandrine ULg et al

Conference (2012, August 27)

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability ... [more ▼]

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability of this trait on a large scale, mid-infrared (MIR) chemometric methods were used to predict TA. A total of 507 milk samples collected in the Walloon Region of Belgium from individual cows were analyzed using a MIR spectrometer. TA was recorded as Dornic degree. An equation to predict TA from milk MIR spectrum was developed using partial least squared regression after a first derivative pre-treatment applied to the spectra to correct the baseline drift. During the calibration process, 45 outliers were detected and removed from the calibration set. The TA mean of the final calibration set was 16.62 (standard deviation (SD) = 1.80). The coefficient of determination (R²) was 0.82 for the calibration with a standard error (SE) of 0.76. A cross-validation (cv) was performed (R²cv = 0.81 with SEcv = 0.80). This equation was then applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated by REML using single-trait random regression animal test-day model. The dataset used included 33,717 records from 9,191 Holstein first-parity cows; the TA mean was 17.05 (SD = 1.35) and TA ranged from 12.83 to 20.87. Estimated daily heritabilities ranged from 0.43 at 5th day in milk to 0.59 at 215th day in milk indicating potential of selection. Further research will study phenotypic and genetic correlations between TA and milk production traits. [less ▲]

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See detailGenetics of the mineral contents in bovine milk predicted by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dehareng, Frédéric; Romnée, Jean-Michel et al

Conference (2012, August 27)

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of ... [more ▼]

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of mid-infrared equations for mineral contents in milk by using an approach combining multiple countries, breeds, and production systems and 2) study of the genetic variability of these traits in the Walloon Holstein dairy cattle. Samples included in the calibration set were collected in Belgium, Luxembourg and France over 5 years. The calibration set included at least 400 samples analyzed by coupled plasma atomic emission spectrometry to quantify the contents of Na, Ca, Mg, P and K. The calibration coefficient of determination ranged between 0.69 for K and 0.93 for Na. The standard error of cross-validation was 63.35, 49.24, 64.33, 7.04, and 93.22 mg/kg of milk for Na, Ca, P, Mg and K. From these results, the quantification of milk minerals by mid-infrared is feasible. These equations were applied to more than 140,000 spectral records collected from 43,797 first parity Holstein cows in 1,233 herds. The variance components were estimated using Gibbs Sampling using single trait random regression models derived from the one used for the Walloon genetic evaluation of milk production traits. First results gave a daily heritability of 0.26 for Na, 0.45 for Ca, 0.48 for P, 0.46 for Mg, and 0.41 for K. Moderate negative genetic correlations were found between Na and the other studied traits. The highest correlation (0.69) was observed between P and Mg. These results confirmed the genetic variability of these traits. Further studies will be conducted to study the relationship between these traits and other traits (e.g., production, health). [less ▲]

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See detailGenetic variance in environmental sensitivity for milk and milk quality in Walloon Holstein cattle
Vandenplas, Jérémie ULg; Bastin, Catherine ULg; Gengler, Nicolas ULg et al

Conference (2012, August 27)

Animals that are robust to environmental changes are desirable in the current dairy industry. This difference in environmental sensitivity can be studied through the heterogeneity of residual variance ... [more ▼]

Animals that are robust to environmental changes are desirable in the current dairy industry. This difference in environmental sensitivity can be studied through the heterogeneity of residual variance while homogeneous residual variance between animals is usually assumed homogeneous in traditional genetic evaluations. The aim of this study was to study genetic heterogeneity of residual variance by the estimation of variance components in residual variance for 5 milk and milk quality traits. 146,027 test-day records from 26,887 Walloon Holstein first-parity cows in 747 herds were available. All cows had at least 3 records and had a known sire. These sires had at least 10 cows with records and each herd x test-day had at least 5 cows. Five traits, milk yield, somatic cell score, and content in milk (g/dL) of oleic acid (C18:1 cis-9), monounsaturated and unsaturated fatty acids, were analyzed separately. Estimation of variance components was performed by running iteratively Expectation Maximization-Restricted Maximum Likelihood algorithm by the implementation of double hierarchical generalized linear models. For all traits, the genetic standard deviation in residual variance (i.e. approximately the genetic coefficient of variation of residual variance) was low and ranged between 0.12 and 0.17. The standard deviations due to herd x test day and permanent environment in residual variance ranged between 0.35 and 0.44 for herd x test-day effect and between 0.55 and 0.96 for permanent environmental effect. This study shows the heterogeneity of residual variance and the existence of some genetic variance in environmental sensitivity for all studied traits in the Walloon Holstein dairy cattle. [less ▲]

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See detailMid-infrared prediction of milk titratable acidity and its genetic variability in first-parity cows
Colinet, Frédéric ULg; Vanlierde, Amélie ULg; Vanden Bossche, sandrine ULg et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability ... [more ▼]

Coagulation of milkhas a direct effect on cheese yield. Among several parameters, titratable acidity of milk (TA) influences all the phases of milk coagulation. In order to study the genetic variability of this trait on a large scale, mid-infrared (MIR) chemometric methods were used to predict TA. A total of 507 milk samples collected in the Walloon Region of Belgium from individual cows were analyzed using a MIR spectrometer. TA was recorded as Dornic degree. An equation to predict TA from milk MIR spectrum was developed using partial least squared regression after a first derivative pre-treatment applied to the spectra to correct the baseline drift. During the calibration process, 45 outliers were detected and removed from the calibration set. The TA mean of the final calibration set was 16.62 (standard deviation (SD) = 1.80). The coefficient of determination (R²) was 0.82 for the calibration with a standard error (SE) of 0.76. A cross-validation (cv) was performed (R²cv = 0.81 with SEcv = 0.80). This equation was then applied on the spectral database generated during the Walloon routine milk recording. The variances components were estimated by REML using single-trait random regression animal test-day model. The dataset used included 33,717 records from 9,191 Holstein first-parity cows; the TA mean was 17.05 (SD = 1.35) and TA ranged from 12.83 to 20.87. Estimated daily heritabilities ranged from 0.43 at 5th day in milk to 0.59 at 215th day in milk indicating potential of selection. Further research will study phenotypic and genetic correlations between TA and milk production traits. [less ▲]

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See detailEstimation of Myostatin gene effects on production traits and fatty acid contents in bovine milk
Vanrobays, Marie-Laure ULg; Bastin, Catherine ULg; Colinet, Frédéric ULg et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

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See detailMid-infrared predictions of fatty acids in bovine milk : final results of the RobustMilk project
Soyeurt, Hélène ULg; McParland, Sinead; Berry, Donagh et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on ... [more ▼]

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples and was one of the aims of the RobustMilk project. Data on MIR spectra and FA from multiple countries, production systems, and breeds were used to develop equations to predict milk FA. The calibration set contained 1,776 spectrally different English, Irish, and Belgian milk samples collected for over 6 years. FA were quantified by gas chromatography (GC). Equations were built using partial least squares regression after a first derivative pretreatment applied to the spectral data. The robustness of the developed equations was assessed by cross-validation (CV) using 50 groups from the calibration set. The coefficient of determination (R²) obtained after CV ranged between 0.7101 for the total content of C18:2 and 0.9993 for the saturated FA group. The standard error of CV ranged between 0.0028 and 0.0998 g/dl of milk. Generally, the group or individual FA having the highest content in milk had the highest R²cv. The results obtained in this study confirmed the usefulness of MIR spectra to robustly quantify the FA content of milk permitting the use of these equations by milk laboratories in UK, Belgium or Ireland. Therefore, these equations could be used to develop selection or management tools for dairy farmers in order to improve the nutritional and environmental quality of milk based on the knowledge of the FA composition of their milk. [less ▲]

Detailed reference viewed: 83 (8 ULg)
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See detailGenetics of the mineral contents in bovine milk predicted by mid-infrared spectrometry
Soyeurt, Hélène ULg; Dehareng, Frédéric; Romnée, Jean-Michel et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of ... [more ▼]

Knowing the contents of minerals in milk like Ca or Na could be interesting to improve the nutritional quality of milk and to assess the animal health status. This study had two aims: 1) development of mid-infrared equations for mineral contents in milk by using an approach combining multiple countries, breeds, and production systems and 2) study of the genetic variability of these traits in the Walloon Holstein dairy cattle. Samples included in the calibration set were collected in Belgium, Luxembourg and France over 5 years. The calibration set included at least 400 samples analyzed by coupled plasma atomic emission spectrometry to quantify the contents of Na, Ca, Mg, P and K. The calibration coefficient of determination ranged between 0.69 for K and 0.93 for Na. The standard error of cross-validation was 63.35, 49.24, 64.33, 7.04, and 93.22 mg/kg of milk for Na, Ca, P, Mg and K. From these results, the quantification of milk minerals by mid-infrared is feasible. These equations were applied to more than 140,000 spectral records collected from 43,797 first parity Holstein cows in 1,233 herds. The variance components were estimated using Gibbs Sampling using single trait random regression models derived from the one used for the Walloon genetic evaluation of milk production traits. First results gave a daily heritability of 0.26 for Na, 0.45 for Ca, 0.48 for P, 0.46 for Mg, and 0.41 for K. Moderate negative genetic correlations were found between Na and the other studied traits. The highest correlation (0.69) was observed between P and Mg. These results confirmed the genetic variability of these traits. Further studies will be conducted to study the relationship between these traits and other traits (e.g., production, health). [less ▲]

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See detailGenetic parameters for methane indicator traits based on milk fatty acids in cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, Frédéric et al

in Journal of Dairy Science (2012, July 18)

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue ... [more ▼]

Dairy production is pointed out for its large methane emission. Therefore, currently studies of factors affecting emission and methods to abate methane emission are numerous. However, an important issue is the development of easily obtainable indicators, because they would also allow estimating animal genetic variability of methane emission. Recently methane indicators were proposed using gas chromatrography based milk fatty acid composition. We derived these published methane indicators using 1100 calibration samples directly from mid-infrared (MIR).For the published indicator showing the highest relationship (R2 = 0.88) with Sulfur Hexafluoride 6 methane emission data, genetic parameters for this MIR based indicator were estimated by single trait random regression test-day models from 619,272 records collected from 2007 to 2011 on 71,188 Holstein cows in their first three lactations at Walloon region of Belgium. The average daily heritability was 0.35±0.01, 0.35±0.02 and 0.32±0.02 for the first three lactations, respectively. Similarly, the lactation heritability was 0.67±0.02, 0.72±0.03 and 0.62±0.03. As expected, methane production was higher during the peak milk production depicting the normal lactation curve. The largest differences between estimated breeding values (EBV) of sires having cows in production eructing the highest and the lowest methane content was 21.80, 22.75 and 24.89 kg per lactation for the first three parities, the variances of the EBV of the sires with daughters were 10.67, 12.46, 12.18 kg2. Results were similar for other indicators. This study suggested that methane indicator traits can be predicted by MIR. Genetic parameters also indicated a rather high heritability and genetic variability exist for these published indicators and consequently a potential high genetic variability of methane eructation by dairy cows. Therefore, these first finding might open new opportunities for animal selection programs that include the reduction of methane emission. [less ▲]

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See detailGenetic parameters for methane indicator traits based on milk fatty acids in cows
Kandel, Purna Bhadra ULg; Vanlierde, Amélie ULg; Dehareng, Frédéric et al

Conference (2012, July 18)

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See detailExtension of Bayesian procedures to integrate and to blend multiple external information into genetic evaluations
Vandenplas, Jérémie ULg; Gengler, Nicolas ULg

Conference (2012, July 18)

Current genetic evaluations are mostly based on local data, potentially followed by an international second step, as it is performed by INTERBULL (Uppsala, Sweden) for dairy breeds. However, reliability ... [more ▼]

Current genetic evaluations are mostly based on local data, potentially followed by an international second step, as it is performed by INTERBULL (Uppsala, Sweden) for dairy breeds. However, reliability of estimated breeding values (EBV) for animals with few local data may be limited. Furthermore, the current development of genomic selection makes this issue more important and the blending of those multiple sources more necessary. Current methods are based on selection index and Bayesian procedures were proposed for a single external source. The aim of this research was to extend these methods to integrate information from multiple sources outside a given evaluation system, i.e. external information, into this genetic evaluation, i.e. internal evaluation, and to assess its potential to blend multiple sources of information when only external information is available. To allow simplifications of the computational burden and the propagation of all external information through the whole pedigree, all animals were considered as animals associated to external information thanks to the prediction of external information from available one for internal animals, i.e. animals with no external information. Multiple considerations of contributions due to relationships among animals were also taken into account. Two dairy cattle populations were simulated across 5 generations. Internal females were randomly mated with internal and 50 external males. Milk production for the first lactation for each female was simulated in both populations. Results for 100 replicates showed that average rank correlations among Bayesian EBV and EBV based on the joint use of external and internal data were close to 1 for both external and internal animals. The respective correlations for the internal evaluation were equal to 0.54 and 0.95. Mean squared error, expressed as a percentage of the internal mean squared error, was close to 0% for both external and internal animals. Thereby, the Bayesian procedure has the potential to integrate and to blend multiple sources of external information to evaluate animals more reliably. [less ▲]

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