References of "Dehareng, Frédéric"
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See detailImpact of wheat bran supplementation to sows on their milk quality, their performances and their progeny’s
Leblois, Julie ULg; Bindelle, Jérôme ULg; Dehareng, Frédéric et al

Conference (2016, April 15)

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See detailEarly life programming of pigs' intestinal microbiota, intestinal functioning and hepatic metabolism by maternal wheat bran supplementation
Leblois, Julie ULg; Bindelle, Jérôme ULg; Dehareng, Frédéric et al

Poster (2016, February 05)

The gastrointestinal (GI) microbiota plays many roles on the host’s health, acting as a barrier against pathogens and influencing the development and maturation of the mucosa, important for host’s ... [more ▼]

The gastrointestinal (GI) microbiota plays many roles on the host’s health, acting as a barrier against pathogens and influencing the development and maturation of the mucosa, important for host’s immunity. Microbial colonization occurs pre- and postnatally, via maternal transfer i.e. by milk and by the contact with sows faeces. Hence, the early establishment of a beneficial gastrointestinal microbiota in piglets was investigated by supplementing the sows with wheat bran that we consider as a prebiotic (rich in non-starch polysaccharides). Sows were fed either a wheat bran-enriched diet (25% in gestation, 14% in lactation) either a control diet. Piglets were suckling during 4 weeks, receiving a standard creep feed containing no pre- or probiotic from the second week until weaning. The direct effect of wheat bran on the fecal microbial composition of the sow has been analyzed as well as the chemical composition and immunoglobulins content of the colostrum and milk. Sows and piglets growth performances have been recorded at different time points to verify that wheat bran doesn’t impair performances. At weaning, piglets have been euthanized and the impact of the maternal treatment was investigated at different levels: growth performances, ileal and colonic microbiota, intestinal physiology and immunological response and metabolism. A second animal experiment will be performed next year including a metabolic challenge by giving half of the piglets a high-energy diet post-weaning. [less ▲]

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See detailChemometrics and vibrational spectroscopy for the detection of melamine levels in milk
Fernandez Pierna, Juan; Vincke, Damien; Baeten, Vincent et al

Poster (2016, January 19)

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See detailApplication of a standardisation procedure on an international network of MIR instruments for milk analysis
Grelet, Clément ULg; Fernandez Pierna, Juan A.; Dardenne, Pierre et al

Poster (2016, January)

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See detailUse of a multivariate moving window PCA for the untargeted detection of contaminants in agro-food products, as exemplified by the detection of melamine levels in milk using vibrational spectroscopy.
Fernandez Pierna, Juan A; Vincke, Damien; Baeten, Vincent et al

in Chemometrics and Intelligent Laboratory Systems (2016)

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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 ▲]

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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)

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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)

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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)

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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)

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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)

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See detailQuality Assurance for new analytical parameters, Optimir standardisation of MIR instruments
Grelet, Clément ULg; Fernandez Pierna, Juan; Dardenne, Pierre et al

Conference (2015, June 10)

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See detailGenetic correlations between methane production and milk fatty acid contents of Walloon Holstein cattle throughout the lactation
Vanrobays, Marie-Laure ULg; Vandenplas, Jérémie ULg; Bastin, Catherine ULg et al

Poster (2015, April 16)

Methane (CH4) from ruminal fermentation is the major greenhouse gas produced by dairy cattle which contributes largely to climate change. Production of CH4 also represents losses of gross energy intake ... [more ▼]

Methane (CH4) from ruminal fermentation is the major greenhouse gas produced by dairy cattle which contributes largely to climate change. Production of CH4 also represents losses of gross energy intake. Therefore, there is a growing interest in mitigating these emissions. Acetate and butyrate have common bio-chemical pathways with CH4. Because some milk fatty acids (FA) arise from acetate and butyrate, milk FA are often considered as potential predictors of CH4. However, relationships between these traits remain unclear. Moreover, the evolution of the phenotypic and genetic correlations of CH4 and milk FA across days in milk (DIM) has not been evaluated. The main goal of this study was to estimate genetic correlations between CH4 and milk FA contents throughout the lactation. Calibration equations predicting daily CH4 production (g/d) and milk FA contents (g/100 dL of milk) from milk mid-infrared (MIR) spectra were applied on MIR spectra related to Walloon milk recording. Data included 243,260 test-day records (between 5 and 365 DIM) from 33,850 first-parity Holstein cows collected in 630 herds. Pedigree included 109,975 animals. Bivariate (i.e., CH4 production and one of the FA traits) random regression test-day models were used to estimate genetic parameters of CH4 production and 7 groups of FA contents in milk. Saturated (SFA), short-chain (SCFA), and medium-chain FA (MCFA) showed positive averaged daily genetic correlations with CH4 production (from 0.25 to 0.29). Throughout the lactation, genetic correlations between SCFA and CH4 were low in the beginning of the lactation (0.11 at 5 DIM) and higher at the end of the lactation (0.54 at 365 DIM). Regarding SFA and MCFA, genetic correlations between these groups of FA and CH4 were more stable during the lactation with a slight increase (from 0.23 to 0.31 for SFA and from 0.23 to 0.29 for MCFA, at 5 and 365 DIM respectively). Furthermore, averaged daily genetic correlations between CH4 production and monounsaturated (MUFA), polyunsaturated (PUFA), unsaturated (UFA), and long-chain FA (LCFA) were low (from 0.00 to 0.15). However, these genetic correlations varied across DIM. Genetic correlations between CH4 and MUFA, PUFA, UFA, and LCFA were negative in early lactation (from -0.24 to -0.34 at 5 DIM) and increased afterward to become positive from 15 weeks till the end of the lactation (from 0.14 to 0.25 at 365 DIM). Finally, these results indicate that genetic and, therefore, phenotypic correlations between CH4 production and milk FA vary following lactation stage of the cow, a fact still often ignored when trying to predict CH4 production from FA composition. [less ▲]

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See detailStandardisation of milk mid-infrared spectra from a European dairy network
Grelet, Clément ULg; Fernandez Pierna, Juan Antonio; Dardenne, Pierre et al

in Journal of Dairy Science (2015), 98

http://www.journalofdairyscience.org/article/S0022-0302(15)00091-0/abstract

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See detailComparison of 3 different variable selection strategies to improve the predictions of fatty acid profile in bovine milk by mid-infrared spectrometry
Soyeurt, Hélène ULg; Brostaux, Yves ULg; Dehareng, Frédéric et al

in Journal of Dairy Science (2015), 98(suppl 2), 804

Detailed reference viewed: 19 (1 ULg)