References of "Soyeurt, Hélène"
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See detailThe time after feeding alters methane emission kinet- ics in Holstein dry cows fed with various restricted diets
Blaise, Yannick ULiege; Andriamandroso, Andriamasinoro ULiege; Beckers, Yves ULiege et al

in Livestock Science (in press)

This study aims to investigate shifts in methane (CH4) emission in cattle in relation to the time after feeding, diet composition, and feed allowance. Four non-cannulated dry Holstein cows were equipped ... [more ▼]

This study aims to investigate shifts in methane (CH4) emission in cattle in relation to the time after feeding, diet composition, and feed allowance. Four non-cannulated dry Holstein cows were equipped with activity and infrared sensors to monitor feeding behavior and CH4 and carbon dioxide (CO2) levels in the breath, continuously and at a frequency of 4 Hz. The second goal pursued, was to assess the methane emission estimation (CH4, L/h) by the CO2-method based on the ratio between CH4 and CO2 in the exhaled air, using metabolic CO2 as a marker. All cows were fed twice a day at 12 h intervals with contrasting isoenergy diets in a cross-over design: LIN100 diet (5562 VEM, i.e. Voedereenheid Melk, Dutch energy unit for milk production, 1 VEM = 6.9 kJ net energy for lactation) composed of haylage, linseed and wheat, and HAY100 (5367 VEM) diet containing only haylage. After a 2 week adaptation period to the diets, 3 days were required for the measurements and immediately after, two additional experimental treatments were applied by reducing the feed allowance to 70% with the same diets to evaluate the impact of the dry matter intake, yielding the two additional treatments HAY70 and LIN70. In addition, two other rumen-cannulated cows were used to monitor time after feeding short-chain fatty acid concentrations in the rumen. On a daily basis, all indicators (daily CH4:CO2 ratio, eructation frequency and CH4 emission) followed the same trend and showed that cows on a hay-based diet produced more CH4 and feed restriction induced different production levels for the same type of diet. The average CH4 emission for the different diets were 6.86 L/h for HAY100 > 6.25 L/h for HAY70 > 4.26 L/h for LIN100 > 3.97 L/h LIN70 (P < 0.001). The LIN100 diet produced 38% lower daily CH4 emissions than HAY100 and reduced the eructation frequency by 44%. During feeding, the eructation frequency was higher (P<0.001) for HAY than LIN diets. This work underlines the daily CH4 emission dynamics observed using the CH4:CO2 ratio in the cow's exhaled air. Methane emissions (L/h) are strongly influenced by the time after feeding time (P < 0.001). They increased for up to 2 hours after the distribution of the meal, and then decreased until the next meal, with shifts between the maximum and the minimum emission of more than 100% for LIN100 and 22% for HAY100. Consistently, the acetate:proprionate ratio was smaller for the LIN100 diet between 2 to 5 hours after the meal (P < 0.001). [less ▲]

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See detailRelationships between Pb, As, Cr, and Cd in soil and water in agricultural and industrial areas with heavy metals contents from individual cow milks
Zhou, Xuewei; Soyeurt, Hélène ULiege; Zheng, Nan et al

in Journal of Dairy Science (2019, June), 102(1), 190

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See detailLarge scale study of the within and between spatial variability of lead, arsenic, and cadmium contamination of cow milk in China
Zhou, Xuewei ULiege; QU, XUEYIN; ZHENG, NAN et al

in Science of the Total Environment (2019), 650

This large scale study investigated the spatial variability of Pb, As, and Cd contents in raw milk within and between the 10 main milk producing areas in China. A total of 997 raw milk samples were ... [more ▼]

This large scale study investigated the spatial variability of Pb, As, and Cd contents in raw milk within and between the 10 main milk producing areas in China. A total of 997 raw milk samples were analysed by inductively coupled plasmamass spectrometry (ICP-MS).Mean values of Pb, As, and Cd inmilkwere 1.75 μg/L, 0.31 μg/L, and 0.05 μg/L, respectively. The highest level of Pb and Aswas present in area C, and Cdwas highest in area J. The standard deviation suggested a higher heterogeneity of milk heavy metal contamination within area than between areas. Levels of Pb, As, and Cd showed significant differences between studied areas. The estimated root mean squared standardised error obtained by the cross-validation suggested a differentiated quality of Pb, As, and Cd modelling between areas: the predictions obtainedwere sometimes overestimated or underestimated. These results can be used to define a more appropriate sampling procedure for heavy metal contaminate distribution in rawmilk for improved future control ofmilk contamination by heavymetals in the studied areas. The significant positive correlations between concentrations of Pb-Cd, As-Cd, and Pb-As were observed in nine, six and five areas, respectively. No significant negative correlations were observed. The observed variability of correlation values suggested a different pollution source for Pb, As, and Cd in milk between areas. Further studies are required to clarify the relationships between the contamination of raw milk by heavy metals and the herd environment. [less ▲]

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See detailDetection of plant protein in adulterated milk using nontargeted nano- high- performance liquid chromatography– tandem mass spectroscopy combined with principal component analysis
Yang, Jinhui; Zheng, Nan; Soyeurt, Hélène ULiege et al

in Food Science and Nutrition (2019)

The objective of this study was to detect plant protein adulterated in fluid milk using nano- high- performance liquid chromatography (HPLC)–tandem mass spectroscopy (LC- MS/MS) combined with proteomics ... [more ▼]

The objective of this study was to detect plant protein adulterated in fluid milk using nano- high- performance liquid chromatography (HPLC)–tandem mass spectroscopy (LC- MS/MS) combined with proteomics. Unadulterated milk and samples adulterated with soy protein, pea protein, hydrolyzed wheat protein, and hydrolyzed rice protein were prepared, with plant protein level ranged from 0.5% to 8% in total protein. Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS- PAGE) gels clearly revealed that centrifugation at 20,000 g for 60 min would reduce band intensity of casein and albumin in milk. Results of nano- HPLC- MS/MS indicated the major proteins of soy (β- conglycinin, glycinin), pea (vincilin, convicilin, legumin), and wheat (glutenin and gliadin) in adulterated milks, allowing detection of soy protein and hydrolyzed wheat protein at the level above 0.5% in total protein and pea protein at the level of 2 and 4%. No rice protein was identified in milk samples adulterated with hydrolyzed rice protein. Combined with principal component analysis, nano- HPLC- MS/MS could discriminate all the adulterated samples from authentic milk. This study demonstrated the feasibility of nano- HPLC- MS/MS on the detection of (hydrolyzed) plant protein adulterated in milk. [less ▲]

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See detailCH4 emitted by dairy cows estimated from milk MIR spectra: model based on data collected in 7 countries
Vanlierde, Amélie ULiege; Dehareng, Frédéric; Gengler, Nicolas ULiege et al

in International Conference on Agricultural GHG Emissions and Food Security – Connecting research to policy and practice – Volume of Abstracts (2018, September)

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See detailEffects of inulin supplementation to piglets in the suckling period on growth performance, postileal microbial and immunological traits in the suckling period and three weeks after weaning
Li, Bing ULiege; Schroyen, Martine ULiege; Leblois, Julie ULiege et al

in Archives of Animal Nutrition (2018), 72(6), 425-442

The aim of this study was to investigate the effect of inulin (IN) supplementation to suckling piglets at and 3 weeks post-weaning. A total of 72 newborn piglets were used. Twenty-four piglets per group ... [more ▼]

The aim of this study was to investigate the effect of inulin (IN) supplementation to suckling piglets at and 3 weeks post-weaning. A total of 72 newborn piglets were used. Twenty-four piglets per group received different amounts of IN during the suckling period: (a) CON: no IN; (b) IN-0.5: 0.5 g IN/d on the 1st week, 1 g IN/d on the 2nd week, 1.5 g IN/d on the 3rd week and 2 g IN/d on the 4th week, or (c) IN-0.75: 0.75 g IN/d on the 1st week, 1.5 g IN/d on the 2nd week, 2.25 g IN/d on the 3rd week and 3 g IN/d on the 4th week. Starting at 28 d of age, piglets were weaned and received a postweaning diet without inulin during the following 3 weeks. At both 28 d and 49 d of age, piglets were euthanised for sampling. Piglets of group IN-0.5 had the highest body weight starting from the 3rd week (p < 0.05), concomitant with the highest villus height and the ratio of villus height/crypt depth in the jejunum and ileum on both sampling days (p < 0.05). At 28 d of age, an increased concentration of propionate, iso-butyrate or total short chain fatty acids was observed between treatment IN-0.5 and the other groups in the caecum or colon (p < 0.05). Moreover, the relative abundance of Escherichia coli (p = 0.05) and Enterobacteriaceae (p = 0.01) in colonic digesta were reduced in IN-0.5-treated piglets, and in both INsupplemented groups, colonic interleukin-8, tumor necrosis factor- α and toll-like receptor-4 mRNA abundance were decreased compared to the CON group (p < 0.05). However, at 49 d of age, most of these differences disappeared. In conclusion, treatment IN- 0.5 improved during the suckling period of piglets development of intestine, but these beneficial effects were not lasting after weaning, when IN supplementation was terminated. Treatment IN-0.75, however, did not display a prebiotic effect. [less ▲]

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See detailBehavior patterns to the intensification vary differently within dairy producers
Dalcq, Anne-Catherine ULiege; Beckers, Yves ULiege; Wyzen, Benoit et al

Conference (2018, August 27)

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See detailCH4 estimated from milk MIR spectra: model on data from 7 countries and 2 measurement techniques
Vanlierde, Amélie ULiege; Dehareng, Frédéric; Gengler, Nicolas ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Availability of a robust proxy to estimate individual daily methane (CH4) emissions from dairy cows would be valuable especially for large scale studies, for instance with genetic purpose. Milk mid ... [more ▼]

Availability of a robust proxy to estimate individual daily methane (CH4) emissions from dairy cows would be valuable especially for large scale studies, for instance with genetic purpose. Milk mid infrared (MIR) spectroscopy presents potential to meet this aim as spectra can be obtained routinely at reasonable cost through milk recording process. Development of a prediction equation requires as much variability as possible in the reference data set to improve the accuracy and ensure the robustness of the model. So, two datasets including CH4 measurements and corresponding milk MIR spectra have been merged: the first contained 532 data from 156 cows of Ireland and Belgium with CH4 measurements obtained with SF6 tracer technique; the second reached 584 data from 147 cows of Switzerland, United Kingdom, France, Denmark and Germany with CH4 measurements obtained with respiration chambers. In addition to the Partial Least Squares (PLS) equation using the raw CH4 values, a second equation was performed with a reduction of 8% to CH4 values from chambers to evaluate the need to correct the potential method bias in accordance with literature. A 5-group cross-validation was performed to test the robustness of the models. R2 and the standard error of cross-validation were 0.63 and 62 g/day from raw data and 0.65 and 59 g/day when CH4 respiration chamber values were adjusted. This slight improvement due to the adjustment of chamber measurement does not permit to conclude that this correction is needed. The study of residuals showed a non-significant effect due to the CH4 measurement technique. In conclusion this new equation combining CH4 from 2 different techniques covered more variability (cows, diets and country specific information) and shows potential as a proxy especially for genetic evaluation. [less ▲]

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See detailPrediction of test-day body weight from dairy cow characteristics and milk spectra
Soyeurt, Hélène ULiege; Colinet, Frédéric ULiege; Froidmont, E. et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

The knowledge of individual body weight (BW) is a management key in terms of feed efficiency and to assess the environmental footprint of dairy production. From 6 farms, BW were measured on 735 Holstein ... [more ▼]

The knowledge of individual body weight (BW) is a management key in terms of feed efficiency and to assess the environmental footprint of dairy production. From 6 farms, BW were measured on 735 Holstein cows. Daily milk samples were collected on these weighed cows and analysed by mid-infrared spectrometry. The stage and number of lactation were also collated. A spectral cleaning was conducted by calculating GH distances from 17 principal components. Spectra with a GH greater than 3 were discarded. The final dataset contained 720 records. Predicting equations were based on Partial Least Squares regressions. Cross-validation coefficient of determination (R2cv) and root mean square error (RMSEPcv) of the equation including only spectral data were of 0.19 and 65 kg. Then, days in milk, month of test and lactation stage were added. The obtained R2cv and RMSEPcv increased (0.43 and 54 kg). The part of the information derived from the spectral data was equal to 6%. By adding the daily milk yield, the BW prediction was slightly improved and showed a R2cv of 0.45 and a RMSEPcv of 53 kg. The use of Legendre Polynomials to regress the spectral data following the day in milk did not improve the predictability. By deleting samples showing a squared residual higher than its mean + 3 times of its standard deviation, the final equation included 668 samples (93% of the initial set) and had a R2cv of 0.58 and RMSEPcv of 42 kg. A herd cross-validation was then performed to assess the robustness of the developed equation. RMSEPv ranged from 40 to 58 kg. This preliminary study showed the potentiality to predict an indicator of body weight. As this prediction uses easy to record explicative variables and if a larger validation confirmed the obtained results, this prediction equation could be used to develop large scale study about feed efficiency. Moreover, this method allows to consider the past information if spectral data are available. [less ▲]

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See detailPrediction of milk mid-infrared spectrum using mixed test-day models
Delhez, Pauline ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

in Book of Abstracts of the 69th Annual Meeting of the European Federation of Animal Science (2018, August)

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or ... [more ▼]

Mid-infrared (MIR) analysis of milk currently allows the measurement of many variables of interest for the dairy sector related to milk nutritional quality, milk technological properties, cow’s status or environmental fingerprint. The aim of this study was to explore the ability of a test-day model to predict milk MIR spectra, and therefore all the resultant variables, for a future test day of a known cow or for a new cow based on easily known characteristics of cows. This is useful for instance for herd management (e.g. detecting problems, predicting potential of heifers) or to predict future environmental impacts of a dairy herd. A total of 467,496 milk MIR spectra from 53,781 Holstein cows in first lactation were used for the calibration data set. First, 323 wavelengths out of the 1,060 wavelengths of the milk spectra were conserved. This spectral information was reduced by using principal component analysis (PCA). A total of 8 principal components (PC) were kept, representing 99% of the spectral information. Then 8 univariate test-day models including the day in milk, herd×year and herd×month as fixed effects and herd×test date, permanent environment and genetics as random effects were applied for each PC. From the solutions of the models and by using a back reversing operation using eigenvectors of the PCA, the predicted 323 wavelengths of the spectra were re-obtained. The calibration correlations between observed and predicted spectral data ranged from 0.76 to 0.93. Correlations between observed and predicted milk fat and protein contents obtained from the modelled spectra were 0.83 and 0.89, respectively. These findings demonstrate the moderate ability of a test-day model to predict milk MIR spectra. [less ▲]

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See detailDetection of plant protein adulterated in fluid milk using twodimensional gel electrophoresis combined with mass spectrometry
Yang, Jinhui; Zheng, Nan; Yang, Yongxin et al

in Journal of Food Science and Technology (2018), 55(7), 2721-2728

The illegal or unlabelled addition of plant protein in milk can cause serious anaphylaxis. For sustainable food security, it is therefore important to develop a methodology to detect non-milk protein in ... [more ▼]

The illegal or unlabelled addition of plant protein in milk can cause serious anaphylaxis. For sustainable food security, it is therefore important to develop a methodology to detect non-milk protein in milk products. This research aims to differentiate milk adulterated with plant protein using two-dimensional gel electrophoresis (2-DE) coupled with mass spectrometry. According to the protein spots highlighted on the gel of adulterated milk,b-conglycinin and glycinin were detected in milk adulterated with soy protein, while legumin, vicilin, and convicilin indicated the addition of pea protein, and b-amylase and serpin marked wheat protein. These results suggest that a 2-DE-based protein profile is a useful method to identify milk adulterated with soy and pea protein, with a detection limit of 4% plant protein in the total protein. [less ▲]

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See detailContamination and spatial distribution of Pb, As and Cd contents in Chinese cow raw milk
Zhou, Xuewei; Qu, Xuyin; Zheng, Nan et al

in Journal of Dairy Science (2018, June), 101(2), 249-250

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See detailMilk phenomics to advice dairy farmers: Present and prospects
Soyeurt, Hélène ULiege

Conference (2018, May)

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See detailMilk biomarkers to evaluate health status of mammary gland in high producing dairy cattle
Marchitelli, Cinzia; Signorelli, Federica; Napolitano, Francesco et al

Conference (2018, March)

For several decades, in many countries, the focus of dairy industry has been on maximizing milk yield, leading to the deterioration of most functional traits. The high producing dairy cows may be affected ... [more ▼]

For several decades, in many countries, the focus of dairy industry has been on maximizing milk yield, leading to the deterioration of most functional traits. The high producing dairy cows may be affected by mastitis, lameness, cystic ovarian disease, displaced abomasum, ketosis, metritis, milk fever and retained placenta. The new approach to solve these diseases is to detect them at earliest stage, utilizing predictive milk biomarkers. The aim of this study was to discover potential biomarkers in milk to evaluate health status of mammary gland. This work is organized within the FP7 EU funded project GplusE. A total of 241 dairy cows from 6 experimental herds in Denmark, Ireland, United Kingdom, Italy, Belgium and Germany are involved. Milk samples were collected at 7, 14 and 21 days post partum. Lactose, fat, protein content, SCC, β-hydroxybutyrate, isocitrate, urea, uric acid, glucose, glucose-6-phosphate, lactate dehydrogenase (LHD) and N-acetyl-β-d-glucosaminidase (NAGase) were determined. Furthermore, individual milk MIR spectra were collected at the same DIM, and prediction equations were used to predict mineral and fatty acid contents. Cows were assigned to three groups on the basis of milk SCC values (cells/mL): LOW (≤ 100,000) in at least two out of the three milk sampling, INTERMEDIATE (101≤SCC≤400), HIGH (≥ 401,00). Mammary gland status was monitored during trial period by veterinarian control. Milk parameters were analysed by PROC GLM model in SAS to determinate and compare mean among different lactation day and between the three groups. A canonical discriminant analysis was performed by CANDISC procedure in SAS to obtain new variables that distinguish three health status. Mineral and lactose contents, NAGase, and LDH activity, some fatty acid contents were significantly different between 7vs14vs21 days post partum and in HIGH vs LOW cows. Two new canonical functions that group some of milk parameters (Fat, Na, K, C:16, C18:2, SFA, MCFA, ω6) distinguished LOW vs INTERMEDIATE vs HIGH cows. The sample sizes may constraint, but the identified milk biomarkers will be tested and validated in thousands of cows within the GplusE project. These new milk biomarkers could be use by farmers for an early detection of diseases. [less ▲]

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See detailCombining heterogeneous across-country data for prediction of enteric methane from proxies in dairy cattle
Negussie, E.; Gonzàlez Recto, O.; de Haas, Y. et al

in Proceedings of the World Congress on Genetics Applied to Livestock Production (2018, February)

Large-scale measurement of enteric methane (CH4) from individual animals is a prerequisite for estimation of genetic parameters and prediction of breeding values. Direct measurement of individual CH4 ... [more ▼]

Large-scale measurement of enteric methane (CH4) from individual animals is a prerequisite for estimation of genetic parameters and prediction of breeding values. Direct measurement of individual CH4 emissions is logistically demanding and expensive, and correlated traits (proxies) or models can be used instead as a means to predict emissions. However, most predictive models tend to be specific and are valid mainly within the circumstances under which they were developed. Robust prediction models that work across countries and production environments may be built by combining heterogeneous data from several sources. However, combining heterogeneous individual animal observations on CH4 proxies from several sources is challenging and reports are scant in the literature. The main objective of this study was to combine heterogeneous individual animal observations on CH4 proxies to develop robust enteric CH4 prediction models. Data on dairy cattle CH4 emissions and related proxies from 16 herds were made available by 13 research centers across 9 European countries within the Methagene EU COST Action FA1302 consortium on “Large-scale methane measurements on individual ruminants for genetic evaluations”. After a thorough editing and harmonization, the final dataset comprised 48,804 observations from 2,391 cows. Random Forest (RF) models were used to predict CH4 emissions and to estimate the relative importance of proxies for across-country predictions. Principal component analysis (PCA) was used to detect potential data stratifications. Milk yield, milk fat, DIM, BW, herd and country of origin appeared to be the most relevant proxies in the prediction model. An overall prediction accuracy of 0.81 was estimated from the combined heterogeneous data. This study is a first attempt to develop methods and approaches tocombine heterogeneous individual animal data on proxies for CH4 to build robust models for prediction of CH4 emissions across diverse production systems and environments. The methodology outlined here can be extended to combining heterogeneous data, pedigree information and genome-wide dense marker information for estimation of genetic parameters and prediction of breeding values for traits related to dairy system CH4 emissions. [less ▲]

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See detailThe feeding system impacts relationships between calving interval and economic results of dairy farms
Dalcq, Anne-Catherine ULiege; Beckers, Yves ULiege; Mayeres, Patrick et al

in Animal (2017)

The calving interval (CI) can potentially impact the economic results of dairy farms. This study highlighted the most profitable CI and innovated by describing this optimum as a function of the feeding ... [more ▼]

The calving interval (CI) can potentially impact the economic results of dairy farms. This study highlighted the most profitable CI and innovated by describing this optimum as a function of the feeding system of the farm. On-farm data were used to represent real farm conditions. A total of 1832 accounts of farms recorded from 2007 to 2014 provided economic, technical and feeding information per herd and per year. A multiple correspondence analysis created four feeding groups: extensive, low intensive, intensive and very intensive herds. The gross margin and some of its components were corrected to account for the effect of factors external to the farm, such as the market, biological status, etc. Then the corrected gross margin (cGMc) and its components were modelled by CI parameters in each feeding system by use of GLM. The relationship between cGMc and the proportion of cows with CI<380 days in each feeding group showed that keeping most of the cows in the herd with CI near to 1 year was not profitable for most farms (for the very intensive farms there was no effect of the proportion). Moreover, a low proportion of cows (0% to 20%) with a near-to-1-year CI was not profitable for the extensive and low intensive farms. Extending the proportion of cows with CI beyond 459 days until 635 days (i.e. data limitation) caused no significant economic loss for the extensive and low intensive farms, but was not profitable for the intensive and very intensive farms. Variations of the milk and feeding components explained mainly these significant differences of gross margin. A link between the feeding system and persistency, perceptible in the milk production and CI shown by the herd, could explain the different relationships observed between the extent of CI and the economic results in the feeding groups. This herd-level study tended to show different economic optima of CI as a function of the feeding system. A cow-level study would specify these tendencies to give CI objectives to dairy breeders as a function of their farm characteristics. [less ▲]

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