References of "Gengler, Nicolas"
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See detailPotential of mid-infrared spectrum of milk to detect changes in the physiological status of dairy cows
Laine, Aurélie ULg; Goubau, Amaury; Hammami, Hedi ULg et al

in Journal of Dairy Science (2013)

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See detailGenetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULg; Vanrobays, Marie-Laure ULg; Vanlierde, Amélie 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 detailEstimation of dominance variance with sire-dam subclass effects in a crossbred population of pigs
Dufrasne, Marie ULg; Jaspart, Véronique; Wavreille, José et al

in Book of Abstract of the 64th Annual Meeting of the European Association of Animal Science (2013)

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See detailGenetics of body energy status of Holstein cows predicted by mid-infrared spectrometry
Bastin, Catherine ULg; Berry, D.; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2013), 96(E-Suppl. 1),

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See detailGenetic parameters for methane emission predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULg; Vanrobays, Marie-Laure ULg; Vanlierde, Amélie et al

in Advances in Animal Biosciences (2013)

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See detailGenetic parameters for methane emission predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULg; Vanrobays, Marie-Laure ULg; Vanlierde, Amélie et al

in Advances in Animal Biosciences (2013), 4(2),

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See detailGenetic variability of the mid-infrared prediction of lactoferrin content in milk for Walloon Holstein first-parity cows
Leclercq, Gil ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg et al

in Livestock Science (2013), 151(2-3), 158-162

The objective of this study was to assess the genetic variability of the mid-infrared prediction of lactoferrin content in milk (pLF) in Holstein first-parity cows. Variance components were estimated by ... [more ▼]

The objective of this study was to assess the genetic variability of the mid-infrared prediction of lactoferrin content in milk (pLF) in Holstein first-parity cows. Variance components were estimated by Average Information Restricted Maximum Likelihood using a single-trait test-day random regression animal model. The dataset included 395,287 test-day records from 67,178 cows in 1190 herds from the Walloon Region of Belgium. Average pLF was 164.89. mg/L and the standard deviation was 76.07. mg/L. Frequency distribution for pLF was slightly asymmetrical, and pLF seemed to increase almost linearly all along the first lactation after a sharp decrease in early lactation. Genetic variance of pLF increased with days in milk within lactation while the permanent environmental variance was the highest in early lactation, then decreased to become lower than genetic variance at 50 days in milk, and finally increased in the last lactation stages. The pLF was a moderately heritable trait. Daily heritability of pLF was the lowest at 5 days in milk (0.19), then increased to reach a maximum at 260 days in milk (0.44), and finally decreased for the last stages of lactation (0.35 at 365 days in milk). Results from this study indicated that pLF is variable and heritable over the lactation and therefore it could be changed by genetic selection. © 2012 Elsevier B.V. [less ▲]

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See detailRelationship between milk composition estimated from mid infrared and methane emissions in dairy cows
Kandel, Purna Bhadra ULg; Vanlierde, A; 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 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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