References of "Gengler, Nicolas"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailUsefulness of multi-breed models in genetic evaluation of direct and maternal calving ease in Holstein and Belgian Blue Walloon purebreds and crossbreds
Vanderick, Sylvie ULg; Gillon, Alain; Glorieux, Géry et al

in Livestock Science (2017), 198

The objective of this study was to verify the feasibility of a joint genetic evaluation system for calving ease trait of Belgian Blue (BBB) and Holstein (HOL) Walloon cattle based on data of purebred and ... [more ▼]

The objective of this study was to verify the feasibility of a joint genetic evaluation system for calving ease trait of Belgian Blue (BBB) and Holstein (HOL) Walloon cattle based on data of purebred and crossbred animals. Variance components and derived genetic parameters for purebred BBB and HOL animals were estimated by using single-breed linear animal models. This analysis showed clear genetic differences between breeds. Estimates of direct and maternal heritabilities (± standard error) were 0.34 (±0.02) and 0.09 (±0.01) for BBB, respectively, but only 0.09 (±0.01) and 0.04 (±0.01) for HOL, respectively. Moreover, a significant negative genetic correlation between direct and maternal effects was obtained in both breeds: −0.46 (±0.04) for BBB and −0.29 (±0.11) for HOL. Variance components and derived genetic parameters for purebred BBB and HOL and crossbred BBB ×× HOL cattle were then estimated by using two multi-breed linear animal models: a multi-breed model based on a random regression test-day model (Model MBV), and a multi-breed model based on the random regression multi-breed model (Model MBSM). Both multi-breed models use different functions of breed proportions as random regressions, thereby enabling modelling different additive effects according to animal's breed composition. The main difference between these models is the way in which relationships between breeds are accounted for in the genetic (co)variance structure. Genetic parameters differed between single-breed and multi-breed analysis, but are similar to the literature. For BBB, estimates of direct and maternal heritabilities (±SE) were 0.45 (±0.07) and 0.08 (±0.01) by using Model MBV, and 0.45 (±0.08) and 0.09 (±0.02) for Model MBSM, respectively. For HOL, these estimates were 0.18 (±0.04) and 0.05 (±0.01) using Model MBV, and 0.16 (±0.04) and 0.05 (±0.01) for Model MBSM, respectively. Reliability gains (up to 25%) indicated that the use of crossbred data in the multi-breed models had a positive influence on the estimation of genetic merit of purebred animals. A slight re-ranking of purebred sires and maternal grandsires was observed between single-breed and multi-breed models. Moreover, both multi-breed models can be considered as quasi-equivalent models because they performed almost equally well with respect to MSE and correlations, for purebred and crossbred animals. [less ▲]

Detailed reference viewed: 33 (9 ULg)
Full Text
Peer Reviewed
See detailStudy of the impact of the pregnancy stage on milk composition of primiparous Holstein dairy cows using the mid-infrared spectra of milk
Laine, Aurélie ULg; Bastin, Catherine; Grelet, Clément ULg et al

in Journal of Dairy Science (2016), 100

Changes in milk production traits (i.e., milk yield, fat, and protein contents) with the pregnancy stage are well documented. To our knowledge, the effect of pregnancy on the detailed milk composition has ... [more ▼]

Changes in milk production traits (i.e., milk yield, fat, and protein contents) with the pregnancy stage are well documented. To our knowledge, the effect of pregnancy on the detailed milk composition has not been studied so far. The mid-infrared (MIR) spectrum reflects the detailed composition of a milk sample and is obtained by a nonexhaustive and widely used method for milk analysis. Therefore, this study aimed to investigate the effect of pregnancy on milk MIR spectrum in addition to milk production traits (milk yield, fat, and protein contents). A model including regression on the number of days pregnant was applied on milk production traits (milk yield, fat, and protein contents) and on 212 spectral points from the MIR spectra of 9,757 primiparous Holstein cows from Walloon herds. Effects of pregnancy stage were expressed on a relative scale (effect divided by the squared root of the phenotypic variance); this allowed comparisons between effects on milk traits and on 212 spectral points. Effect of pregnancy stage on production traits were in line with previous studies indicating that the model accounted well for the pregnancy effect. Trends of the relative effect of the pregnancy stage on the 212 spectral points were consistent with known and observed effect on milk traits. The highest effect of the pregnancy was observed in the MIR spectral region from 968 to 1,577 cm−1. For some specific wavenumbers, the effect was higher than for fat and protein contents in the beginning of the pregnancy (from 30 to 90 or 120 d pregnant). In conclusion, the effect of early pregnancy can be observed in the detailed milk composition through the analysis of the MIR spectrum of bovine milk. Further analyses are warranted to explore deeply the use of MIR spectra of bovine milk for breeding and management of dairy cow pregnancy. [less ▲]

Detailed reference viewed: 15 (3 ULg)
See detailNovel innovative possibilities for the dairy industry opened by common format of FT-MIR instruments
Grelet, Clément ULg; Fernandez Pierna, Juan Antonio; Dardenne, Pierre et al

Poster (2016, October)

FT-MIR technology is worldwide used for fast and cost effective determination of major milk components. However, due to the different individual response of each instrument the potential of this ... [more ▼]

FT-MIR technology is worldwide used for fast and cost effective determination of major milk components. However, due to the different individual response of each instrument the potential of this technology is currently underexploited as new tools cannot be easily ported to other instruments. Recently a standardization method was developed in order to harmonize the spectral response format between instruments of different brands and models but also across time for each spectrometer. The method matches monthly the infrared response of all spectrometers on the response of a reference instrument, making all machines talking a common language. The objective is to allow the creation and the use of common, new and innovative concepts by pooling resources and sharing data. Using this method, new tools for analysis of milk quality and milk technological properties have been created and shared within the network, as fatty acids and minerals predictions or milk coagulation properties. New concepts requiring a common spectral format have been developed like the untargeted detection of milk contaminant and abnormal milk or the determination of milk geographic origin. Models in relation with the status of the dairy cow were also created and shared as to predict ketosis, negative energy balance or methane emissions. Therefore models can be developed at one place and deployed within the entire network, in which 90 instruments are currently monthly standardized. [less ▲]

Detailed reference viewed: 18 (2 ULg)
Full Text
Peer Reviewed
See detailEffect of curve traits and Age at first calving on productive life of Holstein primiparous Walloon cows
Grayaa, Marwa; Hammami, Hedi ULg; Hanzen, Christian ULg et al

Poster (2016, September 02)

Detailed reference viewed: 66 (10 ULg)
See detailOptiMIR: Use of MIR spectra to predict multiple cow status as advisory tools for dairy farms
Grelet, Clément ULg; Gengler, Nicolas ULg; Bastin, Catherine et al

Conference (2016, August)

Considering the current increasing of herd size, there is a need for precise and rapid information on individual cow state. Mid infrared (MIR) technology is already used worldwide for milk analysis; it ... [more ▼]

Considering the current increasing of herd size, there is a need for precise and rapid information on individual cow state. Mid infrared (MIR) technology is already used worldwide for milk analysis; it allows rapid and cost effective determination of milk composition. The objective of OptiMIR project was to optimize the use of MIR spectra in order to produce indications on cow status thereby providing advisory tools to dairy farmers. Hence phenotypes of interest were collected in several countries and linked to MIR spectra. Since the OptiMIR network comprised 65 MIR instruments in 6 countries, standardisation of MIR data was necessary, allowing the collation of spectral databases and the use by all milk recording organizations (MRO) of the models developed. Using chemometric tools (like PLS regression), predictive models were developed to provide indicators on fine milk composition, on milk biomarkers of physiological imbalance, and directly on status of the cows. Equations predicting fine milk composition such as fatty acids and minerals were consolidated through the OptiMIR network, providing indirectly information on technological properties of milk and cow status. As biomarker of early physiological imbalance, an equation predicting citrate in milk was developed with good accuracy (R²cv=0.86); and as milk biomarkers of ketosis, BHB and acetone were calibrated with fair results (R²cv=0.63 and 0.67 respectively). Direct classification of spectra regarding low vs high risk of ketosis was also performed (84.5% sensitivity and 84.2% specificity). Direct regressions were realized for various negative energy balance criteria (r from 0.43 to 0.57) and enteric methane (R²cv=0.7). All equations are available to be used by MRO on field and converted into advisory tools for the dairy sector. [less ▲]

Detailed reference viewed: 13 (2 ULg)
Full Text
See detailContribution à l'optimisation technico-économique des élevages laitiers en Wallonie : l'intervalle vêlage
Dalcq, Anne-Catherine ULg; Beckers, Yves ULg; Dogot, Thomas ULg et al

Conference given outside the academic context (2016)

Au cours des dernières décennies, l’intervalle vêlage des vaches laitières a eu tendance à s’allonger au niveau mondial, européen et belge. Les causes sont multiples : évolution du système de production ... [more ▼]

Au cours des dernières décennies, l’intervalle vêlage des vaches laitières a eu tendance à s’allonger au niveau mondial, européen et belge. Les causes sont multiples : évolution du système de production laitière, augmentation du niveau de production,… Les conséquences sont nombreuses également mais se traduisent-elles par un impact économique pour l’éleveur laitier ? La recherche présentée aujourd’hui se base sur près de 1800 bilans comptables de 400 exploitations laitières, fournis par le service technico-économique de l’Association Wallonne de l’Elevage, entre 2007 et 2014, pour déterminer l’impact économique de la durée de l’intervalle vêlage et définir l’optimum technico-économique de ce paramètre de management. Faut-il garder en tête « le veau par vache et par an » ou est-il intéressant économiquement d’allonger la période entre deux vêlages pour une même vache ? L’étude révèle qu’il y a bien une relation entre l’intervalle vêlage et les résultats économiques d’une exploitation. De plus, il n’y aurait pas un seul optimum d’intervalle vêlage mais plusieurs, dépendant du type d’exploitation et plus particulièrement du mode d’alimentation. L’optimum de l’intervalle vêlage a tendance à être plus court pour les exploitations à alimentation plutôt intensive et plus long pour les exploitations à alimentation plutôt extensive. Cependant il ne s’agit que de tendances observées, un travail plus approfondi doit encore être réalisé pour confirmer ces tendances et définir des objectifs plus précis à poursuivre pour maximiser la rentabilité de son exploitation. [less ▲]

Detailed reference viewed: 141 (7 ULg)
Full Text
Peer Reviewed
See detailModeling heat stress under different environmental conditions
Carabano, Maria-Jesus; Logar, Betka; Bormann, Jeanne et al

in Journal of Dairy Science (2016)

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at ... [more ▼]

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across three European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat and protein test day data from official milk recording for years 1999 to 2010 in four Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO) and Southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature and humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) in SLO and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units towards larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared to quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70 - 0.80) than for SPA (0.83 - 0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA. [less ▲]

Detailed reference viewed: 132 (25 ULg)
Full Text
Peer Reviewed
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 ▲]

Detailed reference viewed: 60 (25 ULg)
Full Text
Peer Reviewed
See detailMilk biomarkers to detect ketosis and negative energy balance using MIR spectrometry
Grelet, Clément ULg; Bastin, Catherine ULg; Gelé, Marine et al

Conference (2015, September 02)

Detailed reference viewed: 46 (15 ULg)
Full Text
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)

Detailed reference viewed: 36 (9 ULg)
Full Text
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)

Detailed reference viewed: 27 (5 ULg)
Full Text
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)

Detailed reference viewed: 48 (14 ULg)
Full Text
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)

Detailed reference viewed: 46 (9 ULg)
Full Text
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)

Detailed reference viewed: 21 (1 ULg)
Full Text
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)

Detailed reference viewed: 23 (3 ULg)
Full Text
Peer Reviewed
See detailPredictions of Daily Milk and Fat Yields, Major Groups of Fatty Acids, and C18:1 cis-9 from Single Milking Data without a Milking Interval
Arnould, Valérie ULg; Reding, Romain; Bormann, Jeanne et al

in Animals (2015), 5(3), 643-661

Reducing the frequency of milk recording would help reduce the costs of official milk recording. However, this approach could also negatively affect the accuracy of predicting daily yields. This problem ... [more ▼]

Reducing the frequency of milk recording would help reduce the costs of official milk recording. However, this approach could also negatively affect the accuracy of predicting daily yields. This problem has been investigated in numerous studies. In addition, published equations take into account milking intervals (MI), and these are often not available and/or are unreliable in practice. The first objective of this study was to propose models in which the MI was replaced by a combination of data easily recorded by dairy farmers. The second objective was to further investigate the fatty acids (FA) present in milk. Equations to predict daily yield from AM or PM data were based on a calibration database containing 79,971 records related to 51 traits [milk yield (expected AM, expected PM, and expected daily); fat content (expected AM, expected PM, and expected daily); fat yield (expected AM, expected PM, and expected daily; g/day); levels of seven different FAs or FA groups (expected AM, expected PM, and expected daily; g/dL milk), and the corresponding FA yields for these seven FA types/groups (expected AM, expected PM, and expected daily; g/day)]. These equations were validated using two distinct external datasets. The results obtained from the proposed models were compared to previously published results for models which included a MI effect. The corresponding correlation values ranged from 96.4% to 97.6% when the daily yields were estimated from the AM milkings and ranged from 96.9% to 98.3% when the daily yields were estimated from the PM milkings. The simplicity of these proposed models should facilitate their use by breeding and milk recording organizations. [less ▲]

Detailed reference viewed: 36 (9 ULg)