References of "Colinet, Frédéric"
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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 detailEarly-programming of dairy cattle, a potential explanation to the adaptation to climate change
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

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

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during ... [more ▼]

Breeding for robustness and considering genotype by environment interaction (G×E) is linked to adaptation. Recently, it has been established that gene expression can be affected by the environment during the embryo development. The concept of early programming has been demonstrated in many settings. This study aimed to assess the impact of thermal stress when dairy cows been conceived on their lifetime performances. Studied traits were milk yield and some novel milk-based biomarkers, fertility (days open), health (somatic cell score and ketosis), and heat tolerance. Data used compromised 905,391 test day of 58,297 cows in parity 1 to 3 for production traits, health and ketosis status, 104,635 records of 48,125 cows for days open, and 399,449 test days recorded (linked with temperature humidity index values, THI) of 28,203 cows for heat tolerance trait. Date of conception was estimated using the next calving date of the cow and subtracting 280 d from the calving interval. Cows being conceived in summer (June- August) were considered as influenced by heat stress (environment 1) and those conceived in winter (December- February) as neutral-thermal conditions (environment 2). G×E was analysed by a multi-trait model for days open in which each of the 3 lactations measured in heat stress and thermo-neutral conditions were considered as separate traits. For the rest of the traits, it was analysed using reaction norm models, in which the trait is considered a function of an environmental descriptor (i.e. THI, days in milk) in the two discrete environments. First results showed that genetic correlations across both early-life defined environments and lactations were substantially lower than unity, implying that effects of genes for cows conceived under neutral-thermal conditions may be different of the effects for the same genes for cows conceived under heat stressed conditions. [less ▲]

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See detailTheoretical basis to extend single-step genomic prediction of dominance in a pig population
REIS MOTA, Rodrigo 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)

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are ... [more ▼]

Single-step methods predict implicitly unknown gene content information of non-genotyped from known gene content for genotyped animals. This theory is well derived in an additive setting. There are reasons not to ignore the dominance context when working with partially genotyped populations. This study addressed several outstanding issues in this context. First, it presented the theoretical basis for dominance single-step genomic best linear unbiased prediction theory. A specific and important issue in all dominance setting is the handling of inbreeding. A total of five dominance single-step inverse matrices were tested and described as C1 to C5 by considering different parameterization (e.g. different ways to account for inbreeding) for pedigree-based and genomic relationships matrices. We simulated genotypes for real crossbred pig population (n=11,943 animals). The SNP effects were assumed to be equal to calculate true dominance values. We added random noise and used them as phenotypes. Accuracy was defined as correlation between true and predicted dominance breeding values. We applied five replicates and estimated accuracies between three situations: all (S1); non-genotyped (S2) and inbred non-genotyped animals (S3). Potential bias of predicted dominance values was assessed by regressing the true dominance values on predicted values. Accuracies of each tested matrix (C1 to C5) were 0.75, 0.33 and 0.35 in average, for S1, S2 and S3, respectively. The matrix C5 better performed and breeding values from C1 and C2 were more biased than those obtained by using C3, C4 and C5. We showed a useful approach to predict dominance gene contents for nongenotyped from genotyped animals. Better matrix compatibility can be obtained by re-scaling the pedigree-based and the genomic relationship matrices to obtain standardized diagonal elements equal to 1 minus the inbreeding coefficient, i.e. the C5 matrix. [less ▲]

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See detailMulti-omics data integration approach for resilience of dairy cattle to heat stress
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

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

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable ... [more ▼]

Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable consequences of future extreme weather scenarios. An example of omics is here epigenomics (e.g. early programming due to heat-stress) allowing new insights to explain biological mechanisms of resilience to HS and G×E interactions. Even if biological mechanisms are complex and still elusive, this study tried to use a holistic approach integrating milk-based biomarkers, climate conditions, and genomics. Data used included 65,907 third-lactation test-day records for production traits (milk, fat and protein yields), specific fatty acids (FA) and metabolites predicted from mid-infrared spectra (C4:0, C18:1cis9, long chain ‘LCFA’, mono- and unsaturated FA ‘MUFA and UFA’, acetone and BHB) of 9,327 Holstein cows. Phenotypes were merged with a temperature humidity index (THI) from public weather stations. For each trait, the response to THI was estimated via days in milk (DIM) × THI combination, and for each cow by using a random regression model with a common threshold of THI=62. The slope (heat tolerance)-to-intercept (general) genetic variance ratios increased as THI increased. They were higher during mid-lactation (140-245 DIM) for C18:1 cis9, acetone, BHB and for production traits, whereas higher in early lactation (≤125 DIM) for C4:0, LCFA, MUFA, and UFA. At extreme high THI scale, slope-to-intercept ratios for C18:1 cis9, MUFA, UFA, and LCFA were 3.8, 3.4, 3.1, 2.8 fold higher than milk yield. These findings indicate that tolerance to HS and traditional production trait responses to THI are marginally related, and changes in milk-based biomarkers under high THI better elucidate physiological and metabolic pathways in HS dairy cows. Ongoing genomic wide association studies will better explain genetic markers unravelling the biological background of resilience to HS. [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 detailGenetic parameters of novel mid-infrared predicted milk traits in three dual-purpose cattle breeds
Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege; Mineur, Axelle ULiege et al

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

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental ... [more ▼]

The objective of this study was to estimate genetic parameters of 39 novel mid-infrared predicted milk traits (e.g. nutritional quality, technological properties, metabolic status, environmental fingerprint) for three dual purpose cattle breeds (i.e. Dual-Purpose Belgian Blue (dpBB), Montbéliarde (MON) and Normande (NOR)), which are also used in organic farming in the Walloon Region of Belgium, as part of the 2-Org-Cows project. Edited data included 21,287, 10,062 and 4,637 first-lactation test-day records collected in the Walloon region of Belgium from 2,988, 1,330 and 621 dpBB, MON and NOR cows, respectively. Genetic parameters were estimated using REML applied to single-trait random regression test-day models for six conventional traits (yields, contents and somatic cell score) and the 39 novel mid-infrared predicted milk traits. Results for conventional traits allowed comparison to literature showing values that were close to the expected ones. For novel traits, comparison with available literature values for Holstein breed showed generally similar estimated heritabilities. Reported average daily heritabilities estimated for the 39 novel traits tended to be higher for dpBB (0.13-0.64) than MON and NOR (0.03-0.60) breeds. Few novel traits showed large differences between breeds except between dpBB and NOR for milk composition traits. However, results for NOR breed have to be taken very carefully given the low number of animals. Even if the used methane prediction equation was not yet validated for these breeds, estimated average daily heritability was moderately high for dpBB (0.41) and MON (0.36) and moderate for NOR (0.23) indicating that this prediction might also be useful in these dual purpose breeds. [less ▲]

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See detailSingle-step genomic analysis of dominance in a crossbred pig population
REIS MOTA, Rodrigo ULiege; Vanderick, Sylvie ULiege; Colinet, Frédéric ULiege et al

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

When all animals are genotyped, developments focused on dominance are well derived. However, this is rare in practice and adaptations are required. The dominant pedigree-based and genomic matrices should ... [more ▼]

When all animals are genotyped, developments focused on dominance are well derived. However, this is rare in practice and adaptations are required. The dominant pedigree-based and genomic matrices should be compatible in scale to be combined. We aimed to show how gene content flows from genotyped to non-genotyped animals. Scenarios where 0% (D), 20% (C20), 40% (C40) 60% (C60), 80% (C80), and 100% (G) of animals were genotyped were assumed in a crossbred pig population. Dominance variances were more sensitive by choosing G rather than D. D and C60 presented the highest dominance variances whereas G showed the lowest. The prediction accuracies increased as the number of genotyped animals increased. C40 provided less inflated dominance breeding values (1.01), and 55% of accuracy. Dominance relationships flew from genotyped to non-genotyped animals but single-step extension might worked because we used an approximation of D where inbreeding is ignored and due to simple family structure in our dataset. Thus, our approach might be useful but is not general as the original derivations of single-step. Genotyping strategies can be optimized based on the proportion of genotyped animals where 40% seemed to be optimal. [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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See detailBayesian single-step genomic evaluations combining local and foreign information in Walloon Holsteins
Colinet, Frédéric ULiege; Vandenplas, J.; Vanderick, Sylvie ULiege et al

in Animal (2017)

Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon ... [more ▼]

Most dairy cattle populations found in different countries around the world are small to medium sized and use many artificial insemination bulls imported from different foreign countries. The Walloon population in the southern part of Belgium is a good example for such a small-scale population. Wallonia has also a very active community of Holstein breeders requesting high level genetic evaluation services. Single-step Genomic BLUP (ssGBLUP) methods allow the simultaneous use of genomic, pedigree and phenotypic information and could reduce potential biases in the estimation of genomically enhanced breeding values (GEBV). Therefore, in the context of implementing a Walloon genomic evaluation system for Holsteins, it was considered as the best option. However, in contrast to multi-step genomic predictions, natively ssGBLUP will only use local phenotypic information and is unable to use directly important other sources of information coming from abroad, for example Multiple Across Country Evaluation (MACE) results as provided by the Interbull Center (Uppsala, Sweden). Therefore, we developed and implemented single-step Genomic Bayesian Prediction (ssGBayes), as an alternative method for the Walloon genomic evaluations. The ssGBayes method approximated the correct system of equations directly using estimated breeding values (EBV) and associated reliabilities (REL) without any explicit deregression step. In the Walloon genomic evaluation, local information refers to Walloon EBV and REL and foreign information refers to MACE EBV and associated REL. Combining simultaneously all available genotypes, pedigree, local and foreign information in an evaluation can be achieved but adding contributions to left-hand and right-hand sides subtracting double-counted contributions. Correct propagation of external information avoiding double counting of contributions due to relationships and due to records can be achieved. This ssGBayes method computed more accurate predictions for all types of animals. For example, for genotyped animals with low Walloon REL (<0.25) without MACE results but sired by genotyped bulls with MACE results, the average increase of REL for the studied traits was 0.38 points of which 0.08 points could be traced to the inclusion of MACE information. For other categories of genotyped animals, the contribution by MACE information was also high. The Walloon genomic evaluation system passed for the first time the Interbull GEBV tests for several traits in July 2013. Recent experiences reported here refer to its use in April 2016 for the routine genomic evaluations of milk production, udder health and type traits. Results showed that the proposed methodology should also be of interest for other, similar, populations. [less ▲]

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See detailGenetic evaluation for birth and conformation traits in dual-purpose Belgian Blue cattle using a mixed inheritance model
REIS MOTA, Rodrigo ULiege; Mayeres, P.; Bastin, Catherine et al

in Journal of Animal Science (2017)

The segregation of the causal mutation (mh) in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing ... [more ▼]

The segregation of the causal mutation (mh) in the muscular hypertrophy gene in dual-purpose Belgian Blue (dpBB) cattle is considered to result in greater calving difficulty (dystocia). Establishing adapted genetic evaluations might overcome this situation through efficient selection. However, the heterogeneity of dpBB populations at the mh locus implies separating the major gene and other polygenic effects in complex modeling. The use of mixed inheritance models may be an interesting option because they simultaneously assume both influences. A genetic evaluation in dpBB based on a mixed inheritance model was developed for birth and conformation traits: gestation length (GL), calving difficulty (CD), birth weight (BiW), and body conformation score (BC). A total of 27,362 animals having records were used for analyses. The total number of animals in the pedigree used to build the numerator relationship matrix was 62,617. Genotypes at the mh locus were available for 2,671 animals. Missing records at this locus were replaced with genotype probabilities. A total of 13,221 (48.3%) were registered as dpBB, 1,287 (4.7%) as beef Belgian Blue, and 12,854 (47.0%) were unknown. From those 13,221dpBB animals, 650, 849, and 534 had double or single copies or no copy, respectively, of the causal mutation (mh) in the muscular hypertrophy gene, whereas 11,188 had missing genotypes. This heterogeneity at the mh locus may be the reason for high variability in the studied traits, that is, high heritability estimates of 0.33, 0.30, 0.38, and 0.43 for GL, CD, BiW, and BC, respectively. In general, additive (P < 0.05) and dominance (P < 0.001) allele substitution for calves and dams had significant impact for all traits. The moderate coefficient of genetic variation (27.80%) and high direct heritability (0.28) for CD suggested genetic variability in dpBB and possible genetic improvement through selection. This variability has allowed dpBB breeders to successfully apply mass selection in the past. Genetic trend means from 1988 to 2016 showed that sire selection for CD within genotype was progressively applied by breeders. The selection intensity was more important for CD in double-muscled lines than in segregated lines. Our study illustrated the possible confusion caused by the use of major genes in selection and the importance of fitting appropriate models such as mixed inheritance models that combine polygenic and gene content information. [less ▲]

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See detailRelationships between methane emissions and technico-economic data from commercial dairy herds
Delhez, Pauline ULiege; Wyzen, Benoit; Dalcq, Anne-Catherine ULiege et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2017, September 01)

Considering economic and environmental issues is important for the sustainability of dairy farms. Regarding environment, direct methane (CH4) emissions from cows are of increasing concern. Many studies ... [more ▼]

Considering economic and environmental issues is important for the sustainability of dairy farms. Regarding environment, direct methane (CH4) emissions from cows are of increasing concern. Many studies examined CH4 variation factors but often on a low number of experimental cows. Also, few studies linked CH4 to economic aspects of dairy farms. The innovative aim of this study was to highlight technical factors associated with dairy cow CH4 emissions and gain insight into the relationships between CH4 and herd economic results by the use of large scale and on-farm data. A total of 525,697 individual CH4 predictions from milk mid-infrared (MIR) spectra [MIR-CH4 (g/day)] of milk samples collected on 206 farms during the Walloon milk recording were used to create a CH4 proxy at the herd by year (herd*year) level. This proxy was merged with accounting data. This allowed a simultaneous study of CH4 emissions and 56 technico-economic variables for 1,024 herd*year records from 2007 to 2014. Significant effects were detected from ANOVA analyses and correlations (r). MIR-CH4 was weakly linked to technical variables considered individually (r < 0.38), suggesting complex associations between variables. Lower MIR-CH4 was associated with lower fat and protein corrected milk (FPCM) yield (r=0.18), lower milk fat and protein content (r=0.38 and 0.33, respectively), lower quantity of milk produced from forages (r=0.12) and suboptimal reproduction and health performances (e.g. higher calving interval (r=-0.21), higher culling rate (r=-0.15)). On an economic point of view, lower MIR-CH4 was associated with lower gross margin per cow (r=0.19) and per litre FPCM (r=0.09). To conclude, this study suggested that low dairy cow CH4 emissions tended to be associated with suboptimal and also less profitable herd management practices. Further research is needed to confirm and expand on these results. [less ▲]

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See detailUsing milk based biomarkers to monitor the physiological state of dairy cows in large populations
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2017, August 30)

Based on reference data from 6 GplusE project partner farms, several equations were developed to predict milk/ blood based biomarkers from milk mid-infrared spectra (MIR). Additional existing MIR ... [more ▼]

Based on reference data from 6 GplusE project partner farms, several equations were developed to predict milk/ blood based biomarkers from milk mid-infrared spectra (MIR). Additional existing MIR prediction equations of milk based biomarkers were included in this study. Data included predicted biomarkers for test-days between the 5th and the 49th DIM in the first 5 lactations of 57,240 Holstein cows. MIR spectra used to predict those biomarkers were collected since 2012 in 461 Belgian commercial farms enrolled in the official Walloon milk recording. Genetic parameters for each trait were estimated using single trait multi-lactation animal linear model. Additionnally bivariate models were used to investigate the genetic associations of MIR predicted milk and blood biomarkers. The lowest heritabilities estimates of 0.14, 0.15, and 0.17 were observed for milk urea, blood urea, and milk β-hydroxybutyrate (BHB) respectively. NEFA, BHB, and IGF-1 in blood have moderate heritability estimates (0.20-0.25). The highest heritabilties (0.31-0.35) concerned milk lactate dehydrogenase (LDH), milk glucose-6-phosphate, and blood glucose. Genetic correlations between lactations were relatively strong (≥0.74) for all indicators. Correlations between first- and later-lactations were the lowest (from 0.74 for blood NEFA to 0.90 for blood glucose). Highest correlations were observed between second- and later lactations (0.86 to 0.97 for milk BHB and milk LDH respectively). Urea and BHB in milk have strong genetic correlations with urea and BHB in blood (0.87 and 0.84 respectively). Additional validation of predictions equations in commercial farms and integration of reference data from other populations were needed, nevertheless first results showed value of these non-invasive biomarkers for routine monitoring and for breeding. [less ▲]

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See detailGenetic analysis of milk MIR predicted blood and milk biomarkers linked to the physiological status
Hammami, Hedi ULiege; Colinet, Frédéric ULiege; Bastin, Catherine et al

in Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science (2017, August)

Based on reference data from 6 GplusE project partner farms, several equations were developed to predict milk/ blood based biomarkers from milk mid-infrared spectra (MIR). Additional existing MIR ... [more ▼]

Based on reference data from 6 GplusE project partner farms, several equations were developed to predict milk/ blood based biomarkers from milk mid-infrared spectra (MIR). Additional existing MIR prediction equations of milk based biomarkers were included in this study. Data included predicted biomarkers for test-days between the 5th and the 49th DIM in the first 5 lactations of 57,240 Holstein cows. MIR spectra used to predict those biomarkers were collected since 2012 in 461 Belgian commercial farms enrolled in the official Walloon milk recording. Genetic parameters for each trait were estimated using single trait multi-lactation animal linear model. Additionnally bivariate models were used to investigate the genetic associations of MIR predicted milk and blood biomarkers. The lowest heritabilities estimates of 0.14, 0.15, and 0.17 were observed for milk urea, blood urea, and milk β-hydroxybutyrate (BHB) respectively. NEFA, BHB, and IGF-1 in blood have moderate heritability estimates (0.20-0.25). The highest heritabilties (0.31-0.35) concerned milk lactate dehydrogenase (LDH), milk glucose-6-phosphate, and blood glucose. Genetic correlations between lactations were relatively strong (≥0.74) for all indicators. Correlations between firstand later-lactations were the lowest (from 0.74 for blood NEFA to 0.90 for blood glucose). Highest correlations were observed between second- and later lactations (0.86 to 0.97 for milk BHB and milk LDH respectively). Urea and BHB in milk have strong genetic correlations with urea and BHB in blood (0.87 and 0.84 respectively). Additional validation of predictions equations in commercial farms and integration of reference data from other populations were needed, nevertheless first results showed value of these non-invasive biomarkers for routine monitoring and for breeding. [less ▲]

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See detailCow milk coagulation: process description, variation factors and evaluation methodologies. A review.
Troch, Thibault ULiege; Lefebure, Emilie ULiege; Baeten, Vincent et al

in Biotechnologie, Agronomie, Société et Environnement (2017), 21

Introduction. For dairy producers who want to transform their milk, the ability of milk to coagulate is an important parameter. It makes it possible to transform milk into cheese. Therefore, it is ... [more ▼]

Introduction. For dairy producers who want to transform their milk, the ability of milk to coagulate is an important parameter. It makes it possible to transform milk into cheese. Therefore, it is necessary to understand the coagulation process and the techniques to measure it in order to achieve the best transformation performance. The objective of this review is to describe the milk coagulation process, the factors influencing it and the methods for measuring the coagulation of milk at lab level. Literature. The processing of milk into cheese involves three steps: coagulation, dewatering and refining. Coagulation is a key step which involves the use of rennet and depends on several parameters (pH, calcium content, temperature, etc.). Some milks never coagulate. To measure the coagulation ability of milk and identify different parameters in milk coagulation properties, the Formagraph, the computerized renneting meter and the Optigraph have been developed (reference methods). Equations have been developed using infrared spectrometry to predict the parameters obtained by the reference methods. Conclusions. The milk coagulation mechanism is known. However, the issue of non-coagulating milk persists and represents a real challenge in terms of yield. The use of infrared is a faster alternative to reference methods that measure the coagulation properties of milk, but still requires an improvement in prediction equations. [less ▲]

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See detailInnovative database and its potential to realise large scale study to quantify the impact of diet component on CH4 emitted daily by dairy cows
Vanlierde, Amélie ULiege; Boulet, Romain; Colinet, Frédéric ULiege et al

in Proceedings of the 3rd symposium on Emissions of gas and dust from livestock (2017, May)

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See detailAssessing the effect of pregnancy stage on milk composition of dairy cows using mid-infrared spectra
Laine, Aurélie ULiege; Bastin, Catherine; Grelet, Clément ULiege et al

in Journal of Dairy Science (2017), 100(4), 28632876

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 ▲]

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See detailRelationships between methane emissions from dairy cows and farm technico-economic results
Delhez, Pauline ULiege; Wyzen, Benoit; Dalcq, Anne-Catherine ULiege et al

Poster (2017, February 07)

Considering economic and environmental issues is important for the sustainability of dairy farms. Regarding environment, direct methane (CH4) emissions from cows are of increasing concern. Many studies ... [more ▼]

Considering economic and environmental issues is important for the sustainability of dairy farms. Regarding environment, direct methane (CH4) emissions from cows are of increasing concern. Many studies examined CH4 variation factors but often on a low number of experimental cows. Also, few studies linked CH4 to economic aspects of dairy farms. The innovative aim of this study was to highlight technical factors associated with dairy cow CH4 emissions and gain insight into the relationships between CH4 and herd economic results by the use of large scale and on-farm data. A total of 525,697 individual CH4 predictions from milk mid-infrared (MIR) spectra [MIR-CH4 (g/day)] of milk samples collected on 206 farms during the Walloon milk recording were used to create a CH4 proxy at the herd by year (herd*year) level. This proxy was merged with accounting data. This allowed a simultaneous study of CH4 emissions and 56 technico-economic variables for 1,024 herd*year records from 2007 to 2014. Significant effects were detected from ANOVA analyses and correlations (r). MIR-CH4 was weakly linked to technical variables considered individually (r < 0.38), suggesting complex associations between variables. Lower MIR-CH4 was associated with lower fat and protein corrected milk (FPCM) yield (r=0.18), lower milk fat and protein content (r=0.38 and 0.33, respectively), lower quantity of milk produced from forages (r=0.12) and suboptimal reproduction and health performances (e.g. higher calving interval (r=-0.21), higher culling rate (r=-0.15)). On an economic point of view, lower MIR-CH4 was associated with lower gross margin per cow (r=0.19) and per litre FPCM (r=0.09). To conclude, this study suggested that low dairy cow CH4 emissions tended to be associated with suboptimal and also less profitable herd management practices. Further research is needed to confirm and expand on these results. [less ▲]

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