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See detailDerivation of a new lamb survival trait for the New Zealand sheep industry
Vanderick, Sylvie ULiege; Auvray, Benoit; Newman, Sheryl-Anne et al

in Journal of Animal Science (2015), 93(8), 3765-3772

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited ... [more ▼]

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited bureau of lamb deaths. This paper reports the decision rules and genetic parameters for a new lamb survival trait for the New Zealand sheep industry. These rules define the new lamb survival trait (NEWSUR) using lamb birth fate (BFATE) codes and the presence/absence of lamb weight measurements. Six univariate animal models were tested and used to estimate variance or covariance components and the resulting direct and maternal heritabilities for NEWSUR. The models differed in the way they adjust for the effect of day of birth, the exclusion or inclusion of a litter (dam/year of birth) random effect and the application or not of a logit transformation of the phenotypes. For both the linear and logistic methods, models including the random effect of litter provided the best fit for NEWSUR according to log-likelihood values. Log-likelihoods for the linear and logistic models cannot be compared, therefore a cross-validation method was used to assess whether the logit transformation was appropriate by analyzing the predictive ability of the models. The mean square errors were slightly lower for the linear compared to the logistic model and therefore the linear model was recommended for industry use. The heritability attributed to direct effects ranged from 2 to 5.5%. A direct heritability of 5.5% resulted from a linear model without litter effect and omitting the effect of day of birth on survival, whereas a direct heritability of 2% resulted from the logistic model fitting a random litter effect. The heritability attributed to maternal genetic effects ranged from 1.9 to 7.7%. A maternal genetic heritability of 7.7% resulted from the logistic model omitting the litter effect, whereas a maternal genetic heritability of 1.9% resulted from the linear model fitting a random litter effect. The addition of the litter random effect decreased the maternal heritabilities substantially in all cases and was recommended for industry use to avoid overestimation of the maternal genetic variance. SIL has implemented NEWSUR and the associated genetic evaluation model based on information described in this paper. Industry wide implementation will enable sheep breeders to produce more accurate genetic evaluations to their commercial clients. [less ▲]

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See detailHot topic: Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra
Vanlierde, Amélie ULiege; Vanrobays, Marie-Laure ULiege; Dehareng, Frédéric et al

in Journal of Dairy Science (2015), 98(8), 5740-5747

The main goal of this study was to develop, apply, and validate a new method to predict an indicator for CH4 eructed by dairy cows using milk mid-infrared (MIR) spectra. A novel feature of this model was ... [more ▼]

The main goal of this study was to develop, apply, and validate a new method to predict an indicator for CH4 eructed by dairy cows using milk mid-infrared (MIR) spectra. A novel feature of this model was the consideration of lactation stage to reflect changes in the metabolic status of the cow. A total of 446 daily CH4 measurements were obtained using the SF6 method on 142 Jersey, Holstein, and Holstein-Jersey cows. The corresponding milk samples were collected during these CH4 measurements and were analyzed using MIR spectroscopy. A first derivative was applied to the milk MIR spectra. To validate the novel calibration equation incorporating days in milk (DIM), 2 calibration processes were developed: the first was based only on CH4 measurements and milk MIR spectra (independent of lactation stage; ILS); the second included milk MIR spectra and DIM information (dependent on lactation stage; DLS) by using linear and quadratic modified Legendre polynomials. The coefficients of determination of ILS and DLS equations were 0.77 and 0.75, respectively, with standard error of calibration of 63 g/d of CH4 for both calibration equations. These equations were applied to 1,674,763 milk MIR spectra from Holstein cows in the first 3 parities and between 5 and 365 DIM. The average CH4 indicators were 428, 444, and 448 g/d by ILS and 444, 467, and 471 g/d by DLS for cows in first, second, and third lactation, respectively. Behavior of the DLS indicator throughout the lactations was in agreement with the literature with values increasing between 0 and 100 DIM and decreasing thereafter. Conversely, the ILS indicator of CH4 emission decreased at the beginning of the lactation and increased until the end of the lactation, which differs from the literature. Therefore, the DLS indicator seems to better reflect biological processes that drive CH4 emissions than the ILS indicator. The ILS and DLS equations were applied to an independent data set, which included 59 respiration chamber measurements of CH4 obtained from animals of a different breed across a different production system. Results indicated that the DLS equation was much more robust than the ILS equation allowing development of indicators of CH4 emissions by dairy cows. Integration of DIM information into the prediction equation was found to be a good strategy to obtain biologically meaningful CH4 values from lactating cows by accounting for biological changes that occur throughout the lactation. [less ▲]

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See detailDescription of the Genetic Evaluation Systems used in the Walloon Region of Belgium
Vanderick, Sylvie ULiege; Bastin, Catherine; Gengler, Nicolas ULiege

E-print/Working paper (2015)

For over ten years now, due to the regionalization of agriculture in Belgium, the Walloon Region has fully developed and still develops its own genetic and genomic evaluation systems. The aim is to allow ... [more ▼]

For over ten years now, due to the regionalization of agriculture in Belgium, the Walloon Region has fully developed and still develops its own genetic and genomic evaluation systems. The aim is to allow breeders of this region to be able to use tools adapted to their specific needs. Since 2002, genetic evaluation systems for production and conformation traits have been routinely used. Likewise, genetic evaluation system for udder health (using somatic cell scores) has been routinely used since 2003, as well as for longevity since 2005, for female fertility since 2007, and for body condition score since 2010. Finally, calving ease has been evaluated by genetic evaluation system in routine since 2013. Therefore, these genetic evaluation systems allow the Walloon Region of Belgium to participate to the international MACE evaluations performed by INTERBULL for all traits nationally evaluated. Moreover, since July 2013, genomic evaluation systems have been used in routine for most of these traits, thus enabling the Walloon Region of Belgium to participate to the international genomic evaluations (GMACE) performed by INTERBULL. The purpose of this document is to give a synthesis of the systems developed and used to evaluate the Walloon dairy cattle. [less ▲]

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See detailGenetic variability of MIR predicted milk technological properties in Walloon dairy cattle
Colinet, Frédéric ULiege; Troch, Thibault ULiege; 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 detailPotential of visible-near infrared spectroscopy for the characterization of butter properties
Troch, Thibault ULiege; 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 ULiege; Colinet, Frédéric ULiege; 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 detailOverview of possibilities and challenges of the use of infrared spectrometry in cattle breeding
Gengler, Nicolas ULiege; Soyeurt, Hélène ULiege; 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 analysis to support the re-establishment of the Kempen breed
François, Liesbeth; Janssens, Steven; Colinet, Frédéric ULiege 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 heritage of the Eastern Belgium Red and White breed, an endangered local breed
Colinet, Frédéric ULiege; Bouffioux, Aude; Mayeres, Patrick 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 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 ULiege; 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 ▲]

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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 ULiege; Brostaux, Yves ULiege; Dehareng, Frédéric et al

in Journal of Animal Science (2015, July 15), 93/98(Suppl. s3/ Suppl. 2), 804

Mid-infrared (MIR) spectrometry is used to provide phenotypes related to the milk composition. Foss spectrum contains 1,060 datapoints. The number of reference values required to build a calibration ... [more ▼]

Mid-infrared (MIR) spectrometry is used to provide phenotypes related to the milk composition. Foss spectrum contains 1,060 datapoints. The number of reference values required to build a calibration equation is often lower than the spectral variables mainly due to the cost of chemical analysis. Problems of collinearity and overfitting appear when this high dimensional data set is used. This research will study the interest of using variable selection (VS) approach before the use of partial least square regression (PLS). The data set included 1,236 milk spectra related to their fatty acid (FA) contents. Saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), short chain (SCFA), medium chain (MCFA), and long chain FA (LCFA) were studied. The data set was randomly divided in 3 groups which were used to create 3 calibration and validation data sets. Three different VS methods were compared. The first strategy was based on the part of trait variability explained by each considered variables (R2VS). The second method was based on the regression coefficient estimated after PLS procedure divided by the standard deviation of the considered spectral variable (BSVS). The third strategy permitted to underline the uninformative variables which were the ones having the lowest ratio of average regression coefficient to their corresponding standard deviation estimated after a leave-one out cross-validation (UVEVS). For UVEVS and BSVS, the cutoff was determined from the known uninformative region of MIR milk spectrum. The cutoff for R2VS was determined by testing different thresholds ranged between 5 and 40%. The most interesting cutoff for R2VS was 25%. The worst results in terms of validation root mean square error of prediction (RMSEPv) were obtained using a full PLS (i.e., without VS). The maximum difference (g/dl of milk) of RMSEPv obtained from the full PLS and from the PLS using selected variables were 0.156 for SFA, 0.139 for MUFA, 0.011 for PUFA, 0.025 for SCFA, 0.164 for MCFA, and 0.188 for LCFA. R2VS gave the best results for all studied traits followed by UVEVS and then BSVS. In conclusion, the use of VS improved significantly the performance of FA MIR equations. [less ▲]

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See detailDo milk spectrometry phenotypes have a role to play in dairy fertility and health programs?
Bastin, Catherine ULiege; Theron, Léonard ULiege; Laine, Aurélie ULiege et al

in Journal of Animal Science (2015, July 12), 93/98(Suppl. s3/ Suppl. 2), 5

Genetic selection allows for permanent improvement of dairy cow fertility and health. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10). Hence, indicators have ... [more ▼]

Genetic selection allows for permanent improvement of dairy cow fertility and health. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10). Hence, indicators have been proven as useful in the prediction of genetic merit for direct fertility and health traits as long as they are easier to measure, heritable, and genetically correlated. Considering that changes in (fine) milk composition over the lactation reflects the physiological status of the cow, the mid-infrared (MIR) analysis of milk opens the door to a whole new range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most of them being related to negative postpartum energy balance and body fat mobilization (e.g., fat to protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acids traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub-)clinical ketosis has been related to milk-based phenotypes such as fatty acids and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk were demonstrated as useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worth considering. It includes traits related to the disease response of the cow (e.g., lactoferrin), to the reduced secretory activity (e.g., lactose) and to the alteration of blood-milk barrier (e.g., minerals, citrate). Moreover, direct MIR-prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies. [less ▲]

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See detailCapitalizing on fine milk composition for breeding and management of dairy cows
Gengler, Nicolas ULiege; Soyeurt, Hélène ULiege; Dehareng, Frédéric et al

in Journal of Animal Science (2015, July 12), 93/ 98(Suppl. s3/ Suppl. 2), 4

Management and breeding of dairy cows face the challenge of permanently adapting to changing production circumstances under socioeconomic constraints. If management and breeding addresses different ... [more ▼]

Management and breeding of dairy cows face the challenge of permanently adapting to changing production circumstances under socioeconomic constraints. If management and breeding addresses different timeframes of action, both need relevant phenotypes that allow for precise monitoring of the status of the cows, their products (i.e., milk and subsequently dairy products), their behavior and their environmental impact. Milk composition has been identified as an important source of information since it could reflect, at least partially, all these elements. Major 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 components 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 classical prediction equation based techniques. This method was used successfully for many novel traits (e.g., fatty acids, lactoferrin, minerals, milk technological properties, citrate), that can then be 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., ketosis) are predicted directly from MIR spectra. In a second approach, in an innovative manner, patterns detected by comparing observed from expected MIR spectra can be used directly. All these traits can then be used to define best practices, adjust feeding and health management, improve animal welfare, improve milk quality and limit 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 correlation with other traits of interest. [less ▲]

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See detailInnovative Combination of all Sources of Information for Production Traits in Slovenian Brown Swiss
Vandenplas, J.; Spehar, M.; Potocnik, K. et al

in Interbull Bulletin (2015, July 09), 49

Slovenian Brown Swiss is a small population with genetic improvement based on its own breeding program supplemented with imports from other populations. Routine national genetic evaluations for milk, fat ... [more ▼]

Slovenian Brown Swiss is a small population with genetic improvement based on its own breeding program supplemented with imports from other populations. Routine national genetic evaluations for milk, fat, and protein yields are computed from all available national phenotypic and pedigree data. At an international level, a Multiple Across Country Evaluation (MACE) is performed by Interbull to aggregate estimated breeding values (EBV) for international sires across different populations into a single Slovenian ranking. Additionally, a genomic evaluation for many sires is now routinely computed at an international level through the InterGenomics (IG) project. Phenotypes used for this genomic evaluation are deregressed MACE EBV which generate genomically enhanced EBV (GEBV) for all genotyped sires. However, national evaluations are not influenced by these international evaluations and, therefore, may be less accurate and even biased because foreign data used to select foreign sires are not used at the national level. Therefore, an integration of international evaluations back into the national evaluations is required to use the available information in an optimal way for both bulls and cows. The aim of this study was to assess the potential of an innovative Bayesian approach, based on a single-step genomic Best Linear Unbiased Prediction, that combines national data for milk, fat and protein yields with the IG genotypes and information (i.e., GEBV and reliabilities). Because IG information considers genotypes and also MACE information, which also includes national information, double-counting of contributions due to records and due to relationships had to be considered. The integration of IG genotypes and information showed an increase of reliability for the three traits, especially for all IG sires. For example, for IG sires with progeny with national records, the integration led to an average increase of reliability of > 0.10 points for milk yield, in comparison to their average national reliability. For the IG sires without progeny with national records, an average increase of reliability of >0.74 points was observed for the same trait. An average increase of reliability of > 0.05 points was also observed for animals with a reliability <0.30 and sired by genotyped IG sires and with progeny with records. Finally, this approach has the potential to simultaneously combine national data and IG genotypes and information. Furthermore, while it was not implemented in this study, this approach has the advantage to allow the consideration of genotypes of other non-IG animals (e.g., cows). [less ▲]

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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 ULiege; Vandenplas, Jérémie; Bastin, Catherine ULiege et al

in Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment (2015, April 16), 19(2), 117

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-1) and milk FA contents (g.100 dl-1 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 seven 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 detailGenetic correlations between methane production and milk fatty acid contents of Walloon Holstein cattle throughout the lactation
Vanrobays, Marie-Laure ULiege; Vandenplas, Jérémie ULiege; Bastin, Catherine ULiege 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 detailSystème d'évaluations génomiques des bovins laitiers en Wallonie (Belgique)
Colinet, Frédéric ULiege; Vandenplas, Jérémie; Vanderick, Sylvie ULiege et al

Computer development (2015)

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