References of "Gengler, Nicolas"
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See detailGenetic analysis of longitudinal measurements of feed intake in Piétrain sire lines
Dufrasne, Marie ULg; Jaspart, Véronique; Wavreille, José et al

in Journal of Animal Science (2013), 91(E-Suppl.2), 293

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See detailGenetic analysis of pig survival in a crossbred population
Dufrasne, Marie ULg; Misztal, Ignacy; Tsuruta, Shogo et al

in Journal of Animal Science (2013), 91(E-Suppl.2), 193

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See detailPotential use of mid-infrared milk spectrum in pregnancy diagnosis of dairy cows
Laine, Aurélie ULg; Goubau, Amaury; Dale, Laura-Monica et al

Conference (2013)

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See detailPotential use of mid-infrared milk spectrum in pregnancy diagnosis of dairy cows
Laine, Aurélie ULg; Goubau, Amaury; Dale, Laura-Monica et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013)

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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 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 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, 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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