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See detailMid-infrared predictions of lactoferrin content in bovine milk
Soyeurt, Hélène ULg; Bastin, Catherine ULg; Colinet, Frédéric ULg et al

in Journal of Dairy Science (2011), 94(E-suppl.1), 714

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study ... [more ▼]

Lactoferrin (LF) is a glycoprotein present in milk and active in the immune system of cows and humans. Therefore, an inexpensive and rapid analysis to quantify this protein is desirable. A previous study reported the potential to quantify LF from the mid-infrared (MIR) spectrometry from 69 milk samples. Through the European RobustMilk project (www.robustmilk.eu), 3,606 milk samples were collected in Belgium, Ireland, and Scotland from individual cows and analyzed using a MIR MilkoScanFT6000 spectrometer. Milk LF content was quantified using ELISA in duplicate. Average ELISA data with a CV lower than 5% were used. After the detection of spectral and ELISA outliers, the calibration set contained 2,499 samples. An equation to predict LF content from MIR was developed using partial least squared regression. A first derivative pre-treatment of spectra was used to correct the baseline drift. To improve the repeatability of the spectral data, a file which contained the spectra of samples analyzed on 5 spectrometers was used during the calibration. The lactoferrin mean was 159.28 mg/l of milk with a SD of 97.21 mg/l of milk. The calibration (C) coefficient of determination (R2) was equal to 0.73 with a standard error (SE) of calibration of 50.54 mg/l of milk. A cross-validation (CV) was used to assess the robustness of the equation. R2 CV was 0.72 with a SE-CV of 51.16 mg/l of milk. An external validation (V) was conducted on 150 milk samples collected in Belgium. The SE of prediction (SEP) was 59.17 mg/L of milk. The similarity between R2 C and R2CV as well as between SE-C and SE-CV and between SE-CV and SEP confirms the equations developed are robust. The correlation between predicted and measured LF values was 0.71. This lower value compared with the one obtained from the calibration set (0.85) could be explained by the low ELISA reproducibility (16.24% ± 25.51%). If the developed equation is used to clean the validation data set, a total of 16 samples can be deleted. The validation coefficient for these 134 samples increased to 0.82. From these results, the developed equation could be used for screening the dairy cow population for breeding purposes. [less ▲]

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See detailShort communication: estimates of genetic parameters of body condition score in the first 3 lactations using a random regression animal model.
Loker, S.; Bastin, Catherine ULg; Miglior, F. et al

in Journal of Dairy Science (2011), 94(7), 3693-9

The objective of this research was to estimate the genetic parameters of body condition score (BCS) in the first 3 lactations in Canadian Holstein dairy cattle using a multiple-lactation random regression ... [more ▼]

The objective of this research was to estimate the genetic parameters of body condition score (BCS) in the first 3 lactations in Canadian Holstein dairy cattle using a multiple-lactation random regression animal model. Field staff from Valacta milk recording agency (Sainte-Anne-de-Bellevue, QC, Canada) collected BCS from Quebec herds several times throughout each lactation. Approximately 32,000, 20,000, and 11,000 first-, second-, and third-parity BCS were analyzed, respectively, from a total of 75 herds. Body condition score was a moderately heritable trait over the lactation for parity 1, 2, and 3, with average daily heritabilities of 0.22, 0.26, and 0.30, respectively. Daily heritability ranged between 0.14 and 0.26, 0.19 and 0.28, and 0.24 and 0.33 for parity 1, 2, and 3, respectively. Genetic variance of BCS increased with days in milk within lactations. The low genetic variance in early lactation suggests that the evolution of the ability to mobilize tissue reserves in early lactation provided cattle with a major advantage, and is, therefore, somewhat conserved. The increasing genetic variance suggests that more genetic differences were related to how well cows recovered from the negative energy balance state. More specifically, increasing genetic variation as lactation progressed could be a reflection of genetic differences in the ability of cows to efficiently control the rate of mobilization of tissue reserves, which would not be crucial in early lactation. The shape of BCS curves was similar across parities. From first to third parity, differences included the progressively deeper nadir and faster rate of recovery of condition. Daily genetic correlations between parities were calculated from 5 to 305 DIM, and were summed and divided by 301 to obtain average daily genetic correlations. The average daily genetic correlations were 0.84 between parity 1 and 2, 0.83 between parity 1 and 3, and 0.86 between parity 2 and 3. Although not 1, these genetic correlations are still strong, so much of the variation observed in BCS was controlled by the same genes for each of the first 3 lactations. If a genetic evaluation for BCS is developed, regular collection of first-lactation BCS records should be sufficient for genetic evaluation. [less ▲]

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See detailThe use of mid-infrared spectrometry to predict body energy status of Holstein cows
McParland, Sinead; Banos, Giorgios; Wall, Eileen et al

in Journal of Dairy Science (2011), 94

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See detailEffect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations.
Dassonneville, Romain; Brondum, R. F.; Druet, Tom ULg et al

in Journal of Dairy Science (2011), 94(7), 3679-86

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a ... [more ▼]

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data consisted of genotypes of 15,966 European Holstein bulls from the combined EuroGenomics reference population. Genotypes with the low-density chip were created by erasing markers from 50,000-marker data. The studies were performed in the Nordic countries (Denmark, Finland, and Sweden) using a BLUP model for prediction of DGV and in France using a genomic marker-assisted selection approach for prediction of GEBV. Imputation in both studies was done using a combination of the DAGPHASE 1.1 and Beagle 2.1.3 software. Traits considered were protein yield, fertility, somatic cell count, and udder depth. Imputation of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test data. Mean imputation error rates when using national reference animals was 5.5 and 3.9% in the Nordic countries and France, respectively, whereas imputation based on the EuroGenomics reference data set gave mean error rates of 4.0 and 2.1%, respectively. Prediction of GEBV based on genotypes imputed with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected in the French study, and a loss of 0.06 was observed for the mean reliability of DGV in the Nordic study. Consequently, the reliability of DGV using the imputed SNP data was 0.38 based on national reference data, and 0.48 based on EuroGenomics reference data in the Nordic validation, and the reliability of GEBV using the imputed SNP data was 0.41 based on national reference data, and 0.44 based on EuroGenomics reference data in the French validation. [less ▲]

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See detailShort communication: Genetic variation of saturated fatty acids in Holsteins in the Walloon region of Belgium
Arnould, Valérie ULg; Hammami, Hedi ULg; Soyeurt, Hélène ULg et al

in Journal of Dairy Science (2010), 93

Random regression test-day models using Legendre polynomials are commonly used for the estimation of genetic parameters and genetic evaluation for test-day milk production traits. However, some ... [more ▼]

Random regression test-day models using Legendre polynomials are commonly used for the estimation of genetic parameters and genetic evaluation for test-day milk production traits. However, some researchers have reported that these models present some undesirable properties such as the overestimation of variances at the edges of lactation. Describing genetic variation of saturated fatty acids expressed in milk fat might require the testing of different models. Therefore, 3 different functions were used and compared to take into account the lactation curve: (1) Legendre polynomials with the same order as currently applied for genetic model for production traits; 2) linear splines with 10 knots; and 3) linear splines with the same 10 knots reduced to 3 parameters. The criteria used were Akaike’s information and Bayesian information criteria, percentage square biases, and log-likelihood function. These criteria indentified Legendre polynomials and linear splines with 10 knots reduced to 3 parameters models as the most useful. Reducing more complex models using eigenvalues seemed appealing because the resulting models are less time demanding and can reduce convergence difficulties, because convergence properties also seemed to be improved. Finally, the results showed that the reduced spline model was very similar to the Legendre polynomials model. [less ▲]

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See detailHeterogeneity of residuals variances of milk fatty acids in dairy cattle
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Vanderick, Sylvie ULg et al

in Journal of Dairy Science (2010, July), 88(E-Suppl. 2), 744

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore ... [more ▼]

Routine genetic evaluation for milk fatty acids is under development in the Walloon Region of Belgium. The objective of this study was to test the heterogeneity of residual variances and therefore indirectly the potential need to adjust for this heterogeneity if it exists. The residuals were computed as the difference between the observed and the estimated values using a multi-trait random regression test-day model, similar to the Walloon routine model, used for first lactation only milk yield, quantities and percentages of protein (PROT) and fat (FAT), content of saturated fatty acids in milk (g/100g of milk, SAT) and, content of mono-unsaturated fatty acids in milk (g/100g of milk, MONO). Residuals were considered homogeneous inside strata defined, among others, by weeks of lactation, by days in milk and by calendar months of test date. About 6,687,000 records were available for milk yield and for FAT and PROT parameters. For SAT and for MONO, about 184,000 records were available in this database. Means of residuals were stable and close to zero for all traits. Variances were more variable for MONO and SAT than for milk yield, for example. Daily and weekly variances tended to decrease at the end of the lactation (50%). When the variances were computed by month of test date, some variations were observed and some periods of year were more marked. In conclusion, the observed residual variances were less stable for MONO and SAT. We can conclude that introduction for heterogeneous residual variance is more important for the new traits (MONO, SAT) than it was for the old, traditional ones. [less ▲]

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See detailMarker imputation with low-density marker panels in Dutch Holstein cattle.
Zhang, Zhiyan; Druet, Tom ULg

in Journal of Dairy Science (2010), 93(11), 5487-94

The availability of high-density bovine genotyping arrays made implementation of genomic selection possible in dairy cattle. Development of low-density single nucleotide polymorphism (SNP) panels will ... [more ▼]

The availability of high-density bovine genotyping arrays made implementation of genomic selection possible in dairy cattle. Development of low-density single nucleotide polymorphism (SNP) panels will allow the extension of genomic selection to a larger portion of the population. Prediction of ungenotyped markers, called imputation, is a strategy that allows using the same low-density chips for all traits (and for different breeds). In the present study, we evaluated the accuracy of imputation with low-density genotyping arrays in the Dutch Holstein population. Five different sizes of genotyping arrays were tested, from 384 to 6,000 SNP. According to marker density, the overall allelic imputation error rate obtained with the program DAGPHASE, which relies on linkage disequilibrium and linkage, ranged from 11.7 to 2.0%, and that obtained with the program CHROMIBD, which relies on linkage and the set of all genotyped ancestors, ranged from 10.7 to 3.3%. However, imputation efficiency was influenced by the relationship between low-density and high-density genotyped animals. Animals with both parents genotyped had particularly low imputation error rates: <1% with 1,500 SNP or more. In summary, missing marker alleles can be predicted with 3 to 4% errors with approximately 1 SNP/Mb (approximately 3,000 markers). The CHROMIBD program proved more efficient than DAGPHASE only at lower marker densities or when several genotyped ancestors were available. Future studies are required to measure the effect of these imputation error rates on accuracy of genomic selection with low-density SNP panels. [less ▲]

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See detailImputation of genotypes from different single nucleotide polymorphism panels in dairy cattle.
Druet, Tom ULg; Schrooten, C.; de Roos, A. P. W.

in Journal of Dairy Science (2010), 93(11), 5443-54

Imputation of missing genotypes is important to join data from animals genotyped on different single nucleotide polymorphism (SNP) panels. Because of the evolution of available technologies, economical ... [more ▼]

Imputation of missing genotypes is important to join data from animals genotyped on different single nucleotide polymorphism (SNP) panels. Because of the evolution of available technologies, economical reasons, or coexistence of several products from competing organizations, animals might be genotyped for different SNP chips. Combined analysis of all the data increases accuracy of genomic selection or fine-mapping precision. In the present study, real data from 4,738 Dutch Holstein animals genotyped with custom-made 60K Illumina panels (Illumina, San Diego, CA) were used to mimic imputation of genotypes between 2 SNP panels of approximately 27,500 markers each and with 9,265 SNP markers in common. Imputation efficiency increased with number of reference animals (genotyped for both chips), when animals genotyped on a single chip were included in the training data, with regional higher marker densities, with greater distance to chromosome ends, and with a closer relationship between imputed and reference animals. With 0 to 2,000 animals genotyped for both chips, the mean imputation error rate ranged from 2.774 to 0.415% and accuracy ranged from 0.81 to 0.96. Then, imputation was applied in the Dutch Holstein population to predict alleles from markers of the Illumina Bovine SNP50 chip with markers from a custom-made 60K Illumina panel. A cross-validation study performed on 102 bulls indicated that the mean error rate per bull was approximately equal to 1.0%. This study showed the feasibility to impute markers in dairy cattle with the current marker panels and with error rates below 1%. [less ▲]

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See detailGenetic variability of milk components based on mid-infrared spectral data.
Soyeurt, Hélène ULg; Misztal, I.; Gengler, Nicolas ULg

in Journal of Dairy Science (2010), 93(4), 1722-1728

The aim of this study was to estimate the genetic parameters of the mid-infrared (MIR) milk spectrum represented by 1,060 data points per sample. The dimensionality of traits was reduced by principal ... [more ▼]

The aim of this study was to estimate the genetic parameters of the mid-infrared (MIR) milk spectrum represented by 1,060 data points per sample. The dimensionality of traits was reduced by principal components analysis. Therefore, 46 principal components describing 99.03% of the phenotypic variability were used to create 46 new traits. Variance components were estimated using canonical transformation. Heritability ranged from 0 to 0.35. Twenty-five out of 46 studied traits showed a permanent environment variance greater than genetic variance. Eight traits showed heritability greater than 0.10. Variances of original spectral traits were obtained by back transformation. Heritabilities for each spectral data points ranged from 0.003 to 0.42. In particular, 3 MIR regions showing moderate to high heritability estimates were of potential genetic interest. Heritabilities for specific wave numbers, linked with common milk traits (e.g., lipids, lactose), were similar to those estimated for these traits. This research confirms the genetic variability of the MIR milk spectrum and, therefore, the genetic variation of milk components. The objective of this study was to better understand the genetics of milk composition and, maybe in the future, to select animals to improve milk quality. [less ▲]

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See detailShort communication: Genetic relationship between calving traits and body condition score before and after calving in Canadian Ayrshire second-parity cows.
Bastin, Catherine ULg; Loker, Sarah; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2010), 93(9), 4398-403

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and calving traits (including calving ease and calf survival) for Ayrshire second-parity cows in ... [more ▼]

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and calving traits (including calving ease and calf survival) for Ayrshire second-parity cows in Canada. The use of random regression models allowed assessment of the change of genetic correlation from 100 d before calving to 335 d after calving. Therefore, the influence of BCS in the dry period on subsequent calving could be studied. Body condition scores were collected by field staff several times over the lactation in 101 herds from Quebec and calving records were extracted from the official database used for Canadian genetic evaluation of calving ease. Daily heritability of BCS increased from 0.07 on d 100 before calving to 0.25 at 335 d in milk. Genetic correlations between BCS at different stages ranged between 0.59 and 0.99 and indicated that genetic components for BCS did not change much over lactation. With the exception of the genetic correlation between BCS and direct calving ease, which was low and negative, genetic correlations between BCS and calving traits were positive and moderate to high. Correlations were the highest before calving and decreased toward the end of the ensuing lactation. The correlation between BCS 10 d before calving and maternal calving ease was 0.32 and emphasized the relationship between fat cows before calving with dystocia. Standards errors of the genetic correlations estimates were low. Genetic correlations between BCS and calf survival were moderate to high and favorable. This indicates that cows with a genetically high BCS across lactation would have a greater chance of producing a calf that survived (maternal calf survival) and that they would transmit genes that allow the calf to survive (direct calf survival). [less ▲]

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See detailFeasibility of a genetic evaluation for milk fatty acids in dairy cattle
Soyeurt, Hélène ULg; Arnould, Valérie ULg; Vanderick, Sylvie ULg et al

in Journal of Dairy Science (2010), 93(E-Suppl 1), 744

Recent development of equations based on mid-infrared (MIR) spectrometry for the prediction of milk fatty acid (FA) contents allows their measurement on a large scale during performance recording. The ... [more ▼]

Recent development of equations based on mid-infrared (MIR) spectrometry for the prediction of milk fatty acid (FA) contents allows their measurement on a large scale during performance recording. The objective was to show that a genetic evaluation for milk FA in dairy cattle is feasible in the Walloon region of Belgium and to report first results. Estimated breeding values (EBV) and associated reliabilities (REL) were computed using a multi-trait test-day animal model similar to the one used for the routine genetic evaluation for yield traits. Studied traits were first lactation test-day milk, fat and protein yields, fat (FAT) and protein contents, and content of saturated fatty acids in milk (g/100g of milk, SAT). More than 6,700,000 records were available for common production and content traits and 194,000 records were used for SAT. Used variance components were estimated using REML. The average SAT content was 2.79% with a standard deviation (SD) of 0.50%. A total of 1,707 Holstein bulls used in Walloon Region had REL superior to 0.49 for all studied traits. REL for SAT ranged from 0.53 to 0.99. A total of 1,217 bulls had REL superior to 0.74. SD of EBV for SAT was 0.20%. The maximum and minimum SAT EBV values were 0.89% and -0.69%, respectively. In order to have a direct measure of the part of FAT that is not due to SAT, a new trait (dSAT) was post-evaluated and defined as difference between expected SAT EBV for a given FAT EBV and the estimated EBV for SAT. This new trait can be assumed to be a direct predictor of the content of unsaturated fatty acids in fat. The interest is that this trait cannot be accurately predicted directly by MIR. The maximum and minimum EBV for dSAT for the 1,707 bulls were -0.28% and 0.24%, respectively. Based on these results, a genetic evaluation for milk fatty acids is feasible. In the bull population used recently, a genetic variability for dSAT exists and could be used to improve the milk fat composition. [less ▲]

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See detailGenetic relationships between body condition score and reproduction traits in Canadian Holstein and Ayrshire first-parity cows.
Bastin, Catherine ULg; Loker, Sarah; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2010), 93(5), 2215-28

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and reproduction traits for first-parity Canadian Ayrshire and Holstein cows. Body condition ... [more ▼]

The objective of this study was to investigate the genetic relationship between body condition score (BCS) and reproduction traits for first-parity Canadian Ayrshire and Holstein cows. Body condition scores were collected by field staff several times over the lactation in herds from Quebec, and reproduction records (including both fertility and calving traits) were extracted from the official database used for the Canadian genetic evaluation of those herds. For each breed, six 2-trait animal models were run; they included random regressions that allowed the estimation of genetic correlations between BCS over the lactation and reproduction traits that are measured as a single lactation record. Analyses were undertaken on data from 108 Ayrshire herds and 342 Holstein herds. Average daily heritabilities of BCS were close to 0.13 for both breeds; these relatively low estimates might be explained by the high variability among herds and BCS evaluators. Genetic correlations between BCS and interval fertility traits (days from calving to first service, days from first service to conception, and days open) were negative and ranged between -0.77 and -0.58 for Ayrshire and between -0.31 and -0.03 for Holstein. Genetic correlations between BCS and 56-d nonreturn rate at first insemination were positive and moderate. The trends of these genetic correlations over the lactation suggest that a genetically low BCS in early lactation would increase the number of days that the primiparous cow was not pregnant and would decrease the chances of the primiparous cow to conceive at first service. Genetic correlations between BCS and calving traits were generally the strongest at calving and decreased with increasing days in milk. The correlation between BCS at calving and maternal calving ease was 0.21 for Holstein and 0.31 for Ayrshire and emphasized the relationship between fat cows around calving and dystocia. Genetic correlations between calving traits and BCS during the subsequent lactation were moderate and favorable, indicating that primiparous cows with a genetically high BCS over the lactation would have a greater chance of producing a calf that survived (maternal calf survival) and would transmit the genes that allowed the calf to be born more easily (maternal calving ease) and to survive (direct calving ease). [less ▲]

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See detailPotential estimation of major mineral contents in cow milk using mid-infrared spectrometry.
Soyeurt, Hélène ULg; Bruwier, Damien; Romnee, Jean-Michel et al

in Journal of Dairy Science (2009), 92(6), 2444-2454

Milk and dairy products are a major source of minerals, particularly calcium, involved in several metabolic functions in humans. Currently, several dairy products are enriched with calcium to prevent ... [more ▼]

Milk and dairy products are a major source of minerals, particularly calcium, involved in several metabolic functions in humans. Currently, several dairy products are enriched with calcium to prevent osteoporosis. The development of an inexpensive and fast quantitative analysis for minerals is required to offer dairy farmers an opportunity to improve the added value of the produced milk. The aim of this study was to develop 5 equations to measure Ca, K, Mg, Na, and P contents directly in bovine milk using mid-infrared (MIR) spectrometry. A total of 1,543 milk samples were collected between March 2005 and May 2006 from 478 cows during the Walloon milk recording and analyzed by MIR spectrometry. Using a principal component approach, 62 milk samples were selected by their spectral variability and separated in 2 calibration sets. Five outliers were detected and deleted. The mineral contents of the selected samples were measured by inductively coupled plasma atomic emission spectrometry. Using partial least squares combined with a repeatability file, 5 calibration equations were built to estimate the contents of Ca, K, Mg, Na, and P in milk. To assess the accuracy of the developed equations, a full cross-validation and an external validation were performed. The cross-validation coefficients of determination (R(2)cv) were 0.80, 0.70, and 0.79 for Ca, Na, and P, respectively (n = 57), and 0.23 and 0.50 for K and Mg, respectively (n = 31). Only Ca, Na, and P equations showed sufficient R(2)cv for a potential application. These equations were validated using 30 new milk samples. The validation coefficients of determination were 0.97, 0.14, and 0.88 for Ca, Na, and P, respectively, suggesting the potential to use the Ca and P calibration equations. The last 30 samples were added to the initial milk samples and the calibration equations were rebuilt. The R(2)cv for Ca, K, Mg, Na, and P were 0.87, 0.36, 0.65, 0.65, and 0.85, respectively, confirming the potential utilization of the Ca and P equations. Even if new samples should be added in the calibration set, the first results of this study showed the feasibility to quantify the calcium and phosphorus directly in bovine milk using MIR spectrometry. [less ▲]

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See detailEstimation of test-day model (co)variance components across breeds using New Zealand dairy cattle data
Vanderick, Sylvie ULg; Harris, Bevin; Pryce, Jenny et al

in Journal of Dairy Science (2009), 92(3), 1240-1252

In New Zealand, a large proportion of cows are currently crossbreds, mostly Holstein-Friesians (HF) x Jersey (JE). The genetic evaluation system for milk yields is considering the same additive genetic ... [more ▼]

In New Zealand, a large proportion of cows are currently crossbreds, mostly Holstein-Friesians (HF) x Jersey (JE). The genetic evaluation system for milk yields is considering the same additive genetic effects for all breeds. The objective was to model different additive effects according to parental breeds to obtain first estimates of correlations among breed-specific effects and to study the usefulness of this type of random regression test-day model. Estimates of (co) variance components for purebred HF and JE cattle in purebred herds were computed by using a single-breed model. This analysis showed differences between the 2 breeds, with a greater variability in the HF breed. (Co) variance components for purebred HF and JE and crossbred HF x JE cattle were then estimated by using a complete multibreed model in which computations of complete across-breed (co)variances were simplified by correlating only eigenvectors for HF and JE random regressions of the same order as obtained from the single-breed analysis. Parameter estimates differed more strongly than expected between the single-breed and multibreed analyses, especially for JE. This could be due to differences between animals and management in purebred and nonpurebred herds. In addition, the model used only partially accounted for heterosis. The multibreed analysis showed additive genetic differences between the HF and JE breeds, expressed as genetic correlations of additive effects in both breeds, especially in linear and quadratic Legendre polynomials (respectively, 0.807 and 0.604). The differences were small for overall milk production (0.926). Results showed that permanent environmental lactation curves were highly correlated across breeds; however, intraherd lactation curves were also affected by the breed-environment interaction. This result may indicate the existence of breed-specific competition effects that vary through the different lactation stages. In conclusion, a multibreed model similar to the one presented could optimally use the environmental and genetic parameters and provide breed-dependent additive breeding values. This model could also be a useful tool to evaluate crossbred dairy cattle populations like those in New Zealand. However, a routine evaluation would still require the development of an improved methodology. It would also be computationally very challenging because of the simultaneous presence of a large number of breeds. [less ▲]

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See detailEstimates of genetic parameters among body condition score and fertility traits in first-parity Canadian cows
Bastin, Catherine ULg; Loker, Sarah; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2009), 92 - E-Suppl 1

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See detailGenetic analysis of lactoferrin content in bovine milk
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2009), 92(5), 2151-2158

Bovine lactoferrin (LF) is mainly present in milk and shows important physiological and biological functions. The aim of this study was to estimate the heritability and correlation values of LF content in ... [more ▼]

Bovine lactoferrin (LF) is mainly present in milk and shows important physiological and biological functions. The aim of this study was to estimate the heritability and correlation values of LF content in bovine milk with different economic traits as milk yield (MY), fat and protein percentages, and somatic cell score (SCS). Variance components of the studied traits were estimated by REML using a multiple-trait mixed model. The obtained heritability (0.22) for LF content predicted using mid-infrared spectrometry (pLF) suggested the possibility of animal selection based on the increase of LF content in milk. The phenotypic and genetic correlation values calculated between pLF and SCS were moderate (0.31 and 0.24, respectively). Furthermore, a preliminary study of bovine LF gene polymorphism effects was performed on the same production traits. By PCR, all exons of the LF gene were amplified and then sequenced. Three new polymorphisms were detected in exon 2, exon 11, and intron 8. We examined the effects of LF gene polymorphisms of exons 2, 4, 9, 11, and 15, and intron 8 on pLF, MY, fat and protein percentages, and SCS. The different observed effects did not reach a significant level probably because of the characteristics of the studied population. However, the results were promising, and LF may be a potential indicator of mastitis. Further studies are necessary to evaluate the effect of genetic selection based on LF content on the improvement of mastitis resistance. [less ▲]

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See detailGenetic variability of test-day stearoyl coenzyme-A desaturase 9 activity
Arnould, Valérie ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in Journal of Dairy Science (2009), 92(E-suppl.1), 353-354

Milk fatty acid (FA) profile is far from the optimal fat composition in regards to human health. Different natural sources of variation such as feeding or genetics could be used to modify the contents of ... [more ▼]

Milk fatty acid (FA) profile is far from the optimal fat composition in regards to human health. Different natural sources of variation such as feeding or genetics could be used to modify the contents of unsaturated fatty acids. The impact of feeding is well described; however, genetics effects on the milk FA composition are not well studied. Increasing the unsaturated fatty acids contents of bovine milk could have the potential to raise the nutritive and therapeutic values of dairy products. The stearoyl Coenzyme-A desaturase 9 (delta-9) gene was identified as a potential functional candidate gene affecting milk fat composition in dairy cattle. The objective of this research was to study the genetic variability on this enzyme activity across lactations. A total of 199,977 test-day records were obtained from 29,603 Holstein cows in first lactation, 154,267 records from 23,453 Holstein cows in second lactation, and 173,244 records from 75,887 Holstein cows in third and later lactations. The used model was a multiple-trait random regressions test-day model. Fixed effects were: herd × date of test, and class of age. Random effects were: herd × year of calving, permanent environmental, additive genetic, and residual effects. The studied traits were milk yield, protein content, percentage of fat, monounsaturated fatty acids estimated by mid-infrared spectrometry, and the ratios reflecting the delta-9 activity. Obtained heritability estimates of delta-9 as well as the genetic and phenotypic correlations varied across lactations. These results suggest potential improvements of milk fat composition based on delta-9 activity using animal selection and appropriate management practices. [less ▲]

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See detailModeling milk urea of Walloon dairy cows in management perspectives.
Bastin, Catherine ULg; Laloux, Laurent; Gillon, Alain ULg et al

in Journal of Dairy Science (2009), 92(7), 3529-40

The aim of this study was to develop an adapted random regression test-day model for milk urea (MU) and to study the possibility of using predictions and solutions given by the model for management ... [more ▼]

The aim of this study was to develop an adapted random regression test-day model for milk urea (MU) and to study the possibility of using predictions and solutions given by the model for management purposes. Data included 607,416 MU test-day records of first-lactation cows from 632 dairy herds in the Walloon Region of Belgium. Several advanced features were used. First, to detect the herd influence, the classical herd x test-day effect was split into 3 new effects: a fixed herd x year effect, a fixed herd x month-period effect, and a random herd test-day effect. A fixed time period regression was added in the model to take into account the yearly oscillations of MU on a population scale. Moreover, first autoregressive processes were introduced and allowed us to consider the link between successive test-day records. The variance component estimation indicated that large variance was associated with the random herd x test-day effect (48% of the total variance), suggesting the strong influence of herd management on the MU level. The heritability estimate was 0.13. By comparing observed and predicted MU levels at both the individual and herd levels, target ranges for MU concentrations were defined to take into account features of each cow and each herd. At the cow level, an MU record was considered as deviant if it was <200 or >400 mg/L (target range used in the field) and if the prediction error was >50 mg/L (indicating a significant deviation from the expected level). Approximately 7.5% of the MU records collected between June 2007 and May 2008 were beyond these thresholds. This combination allowed for the detection of potentially suspicious cows. At the herd level, the expected MU level was considered as the sum of the solutions for specific herd effects. A herd was considered as deviant from its target range when the prediction error was greater than the standard deviation of MU averaged by herd test day. Results showed that 6.7% of the herd test-day MU levels between June 2007 and May 2008 were considered deviant. These deviations seemed to occur more often during the grazing period. Although theoretical considerations developed in this study should be validated in the field, this research showed the potential use of a test-day model for analyzing functional traits to advise dairy farmers. [less ▲]

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