References of "Gengler, Nicolas"
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See detailEuropean TMI estimation
Vanderick, Sylvie ULg; Faux, Pierre ULg; Gengler, Nicolas ULg

Conference given outside the academic context (2011)

Total Merit Indexes (TMI) of 6 national evaluations (France, Germany, Walloon Region of Belgium, Italy, Netherlands and Nordic countries) were available. A principal component analysis was performed on ... [more ▼]

Total Merit Indexes (TMI) of 6 national evaluations (France, Germany, Walloon Region of Belgium, Italy, Netherlands and Nordic countries) were available. A principal component analysis was performed on this data in order to assess the common direction of selection between those 6 countries. Results showed that this methodology was a good basis to define a common european TMI. [less ▲]

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See detailMid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries
Soyeurt, Hélène ULg; Dehareng, ; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2011), 94

Increasing consumer concern exists over the relationship between food composition and human health. Because of the known effects of fatty acids on human health, the development of a quick, inexpensive ... [more ▼]

Increasing consumer concern exists over the relationship between food composition and human health. Because of the known effects of fatty acids on human health, the development of a quick, inexpensive, and accurate method to directly quantify the fatty acid (FA) composition in milk would be valuable for milk processors to develop a payment system for milk pertinent to their customer requirements and for farmers to adapt their feeding systems and breeding strategies accordingly. The aim of this study was (1) to confirm the ability of mid-infrared spectrometry (MIR) to quantify individual FA content in milk by using an innovative procedure of sampling (i.e., samples were collected from cows belonging to different breeds, different countries, and in different production systems); (2) to compare 6 mathematical methods to develop robust calibration equations for predicting the contents of individual FA in milk; and (3) to test interest in using the FA equations developed in milk as basis to predict FA content in fat without corrections for the slope and the bias of the developed equations. In total, 517 samples selected based on their spectral variability in 3 countries (Belgium, Ireland, and United Kingdom) from various breeds, cows, and production systems were analyzed by gas chromatography (GC). The samples presenting the largest spectral variability were used to calibrate the prediction of FA by MIR. The remaining samples were used to externally validate the 28 FA equations developed. The 6 methods were (1) partial least squares regression (PLS); (2) PLS + repeatability file (REP); (3) first derivative of spectral data + PLS; (4) first derivative + REP + PLS; (5) second derivative of spectral data + PLS; and (6) second derivative + REP + PLS. Methods were compared on the basis of the crossvalidation coefficient of determination (R2cv), the ratio of standard deviation of GC values to the standard error of cross-validation (RPD), and the validation coefficient of determination (R2v). The third and fourth methods had, on average, the highest R2cv, RPD, and R2v. The final equations were built using all GC and the best accuracy was observed for the infrared predictions of C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, C18:0, C18:1 trans, C18:1 cis-9, C18:1 cis, and for some groups of FA studied in milk (saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain FA). These equations showed R2cv greater than 0.95. With R2cv equal to 0.85, the MIR prediction of polyunsaturated FA could be used to screen the cow population. As previously published, infrared predictions of FA in fat are less accurate than those developed from FA content in milk (g/dL of milk) and no better results were obtained by using milk FA predictions if no corrections for bias and slope based on reference milk samples with known contents of FA were used. These results indicate the usefulness of equations with R2cv greater than 95% in milk payment systems and the usefulness of equations with R2cv greater than 75% for animal breeding purposes. [less ▲]

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See detailRobustMilk - Développer des outils de sélection pratiques et innovants pour la production de produits laitiers de qualité issus de vaches plus robustes : Sélectionner sur le profil en acides gras du lait
Bastin, Catherine ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in 16ième Carrefour des productions animales: La Filière laitière bovine est-elle durable?, Gembloux, le 2 mars 2011 (2011, March 02)

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See detailEstimation de la quantité journalière grasse du lait à partir d'une seule traite (matin ou soir) des composés fins de la matière grasse du lait
Arnould, Valérie ULg; Froidmont, Eric; Nguyen, Nam et al

in 16ième Carrefour des Productions animales: la filière laitière bovine européenne est-elle durable? (2011, March 02)

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See detailManageMilk - Création d'outils de management innovatifs et pratiques en vue d'améliorer la durabilité de la production laitière et de la qualité des produits laitiers: présentation du projet.
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Stoll, Jean et al

in 16ième Carrefour des Prodcutions animales: La filière laitière bovine européenne est-elle durable? (2011, March 02)

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See detailConservation et valorisation de la Bleue Mixte au travers du projet franco-belge BlueSel
Colinet, Frédéric ULg; Glorieux, Géry; Beguin, Emmanuel et al

Poster (2011, March)

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See detailConservation et valorisation de la Bleue Mixte au travers du projet franco-belge BlueSel
Colinet, Frédéric ULg; Glorieux, Géry; Beguin, Emmanuel et al

in 16ième Carrefour des Productions animales: La filière laitière bovine européenne est-elle durable? (2011, March)

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See detailVariabilité et amélioration des aptitudes à la transformation fermière du lait au travers du projet ProFARMilk
Colinet, Frédéric ULg; Sindic, Marianne ULg; Anceau, Christine ULg et al

in 16ième Carrefour des Productions animales: La filière laitière bovine européenne est-elle durable? (2011, March)

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See detailOptiMIR- Développement et mise en place d'outils innovants de gestion des troupeaux et de conseil personnalisé pour une meilleure durabilité du secteur laitier
Hammami, Hedi ULg; Massart, Xavier; Bertozzi, Carlo et al

in 16ème Carrefour des Productions animales: La filière laitière bovine européenne est-elle durable? (2011, March)

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See detailLa génomique bovine laitière en Région Wallonne : état des lieux
Colinet, Frédéric ULg; Gengler, Nicolas ULg; Hubin, Xavier et al

Conference given outside the academic context (2011)

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See detailUsing test station and on-farm data for the genetic evaluation of Piétrain boars used on Landrace sows for growth performance
Dufrasne, Marie ULg; Rustin, Maité; Jaspart, Véronique et al

in Journal of Animal Science (2011), 89

The aim of this study was to develop a new genetic evaluation model to estimate the genetic merit of boars for growth based on 1) performance of their crossbred progeny fattened in the test station and 2 ... [more ▼]

The aim of this study was to develop a new genetic evaluation model to estimate the genetic merit of boars for growth based on 1) performance of their crossbred progeny fattened in the test station and 2) their own performance or those of relatives from the on-farm testing system. The model was a bivariate random regression animal model with linear splines and was applied to Piétrain boars from the Walloon Region of Belgium mated with Landrace sows. Data contained 1) 12,610 BW records from the test station collected on 1,435 crossbred pigs from Piétrain boars and Landrace sows, and 2) 52,993 BW records from the on-farm testing system collected on 50,670 pigs with a breed composition of at least 40% Piétrain or Landrace. Since 2007, 56 Piétrain boars have been tested in the station. Data used to estimate variance components and breeding values were standardized for the age to take into account heterogeneity of variances and then pre-adjusted at 210 d of age to put all records on the same scale. Body weight records from the test station and from the on-farm testing system were considered as 2 different traits. The heterosis effect was modeled as fixed regression on the heterozygosity coefficient. As all test station animals were similarly crossbred, smaller variation in heterozygosity caused the sampling error of the regression estimate at 210 d to be larger in the test station than in on-farm data with estimates of 28.35 ± 14.55 kg and 9.02 ± 0.67 kg, respectively. Therefore, the most likely reason for the large differences in estimates was sampling. Heritability estimates ranged from 0.37 to 0.60 at 210 and 75 d, respectively, for test station BW and from 0.42 to 0.60 at 210 d and 175 d, respectively, for on-farm BW. Genetic correlation decreased when the age interval between records increased, and were greater between ages for test station than for on-farm data. Genetic correlations between test station and on-farm BW at the same age were high: 0.90 at 175 d and 0.85 at 210 d. For the 56 boars tested in the station, the average reliability of their EBV for ADG between 100 and 210 d was improved from 0.60 using only test station data to 0.69 using jointly test station and on-farm data. Based on these results, the new model developed was considered as a good method of detection of differences in growth potential of Piétrain boars based on test station and on-farm data. [less ▲]

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See detailMid-infrared predictions of lactoferrin content in bovine milk
Soyeurt, Hélène ULg; Bastin, Catherine ULg; Colinet, Frédéric ULg et al

in Journal of Dairy Science (2011), 94(E-suppl.1), 714

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study ... [more ▼]

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study reported the potential to quantify LF from the mid-infrared (MIR) spectrometry from 69 milk samples. Through the European RobustMilk project (www.robustmilk.eu), 3,606 milk samples were collected in Belgium, Ireland, and Scotland from individual cows and analyzed using a MIR MilkoScanFT6000 spectrometer. Milk LF content was quantified using ELISA in duplicate. Average ELISA data with a CV lower than 5% were used. After the detection of spectral and ELISA outliers, the calibration set contained 2,499 samples. An equation to predict LF content from MIR was developed using partial least squared regression. A first derivative pre-treatment of spectra was used to correct the baseline drift. To improve the repeatability of the spectral data, a file which contained the spectra of samples analyzed on 5 spectrometers was used during the calibration. The lactoferrin mean was 159.28 mg/l of milk with a SD of 97.21 mg/l of milk. The calibration (C) coefficient of determination (R2) was equal to 0.73 with a standard error (SE) of calibration of 50.54 mg/l of milk. A cross-validation (CV) was used to assess the robustness of the equation. R2 CV was 0.72 with a SE-CV of 51.16 mg/l of milk. An external validation (V) was conducted on 150 milk samples collected in Belgium. The SE of prediction (SEP) was 59.17 mg/L of milk. The similarity between R2 C and R2CV as well as between SE-C and SE-CV and between SE-CV and SEP confirms the equations developed are robust. The correlation between predicted and measured LF values was 0.71. This lower value compared with the one obtained from the calibration set (0.85) could be explained by the low ELISA reproducibility (16.24% ± 25.51%). If the developed equation is used to clean the validation data set, a total of 16 samples can be deleted. The validation coefficient for these 134 samples increased to 0.82. From these results, the developed equation could be used for screening the dairy cow population for breeding purposes. [less ▲]

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