Publications (34)65.83 Total impact
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Article: Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1 - 3.
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ABSTRACT: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents predicted by mid-infrared spectrometry for first-, second- and third-parity Holstein cows. Edited data included records collected in the Walloon region of Belgium from 37 768 cows in parity 1, 22 566 cows in parity 2 and 8221 in parity 3. A total of 69 (23 traits for three parities) single-trait random regression animal test-day models were run. Approximate genetic correlations among traits were inferred from pairwise regressions among estimated breeding values of cow having observations. Heritability and genetic correlation estimates from this study reflected the origins of FA: de novo synthetized or originating from the diet and the body fat mobilization. Averaged daily heritabilities of FA contents in milk ranged between 0.18 and 0.47. Average daily genetic correlations (averaged across days in milk and parities) among groups and individual FA contents in milk ranged between 0.31 and 0.99. The genetic variability of FAs in combination with the moderate to high heritabilities indicated that FA contents in milk could be changed by genetic selection; however, desirable direction of change in these traits remains unclear and should be defined with respect to all issues of importance related to milk FA.Journal of Animal Breeding and Genetics 04/2013; 130(2):118-27. · 1.46 Impact Factor -
Article: Differences in milk fat composition predicted by mid-infrared spectrometry among dairy cattle breeds in the Netherlands.
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ABSTRACT: The aim of this study was to estimate breed differences in milk fatty acid (FA) profile among 5 dairy cattle breeds present in the Netherlands: Holstein-Friesian (HF), Meuse-Rhine-Yssel (MRY), Dutch Friesian (DF), Groningen White Headed (GWH), and Jersey (JER). For this purpose, total fat percentage and detailed FA contents in milk (14 individual FA and 14 groups of FA) predicted from mid-infrared spectra were used. Mid-infrared spectrometry profiles were collected during regular milk recording from a range of herds with different combinations of breeds, including both purebred and crossbred cows. The data set used for the analyses contained 41,404 records from a total of 24,445 cows. In total 7,626 cows were crossbreds belonging to the breeds HF, MRY, DF, GWH, and JER; 1,769 purebreds (≥87.5%) belonging to the breeds MRY, DF, GWH, and JER; and the other 15,050 cows were HF. Breed effects were estimated using a single-trait animal model. The content in milk of short-chain FA C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, and C16:0 was higher for JER and the content in milk of C16:0 was lower for GWH compared with the other breeds; when adjusting for breed differences in fat percentage, however, not all breed differences were significant. Breed differences were also found for cis-9 C14:1, cis-9 C16:1, C18:0, and a number of C18 unsaturated FA. In general, differences in fat composition in milk between HF, MRY, and DF were not significant. Jerseys tended to produce more saturated FA, whereas GWH tended to produce relatively less saturated FA. After adjusting for differences in fat percentage, breed differences in detailed fat composition disappeared or became smaller for several short- and medium-chain FA, whereas for several long-chain unsaturated FA, more significant breed differences were found. This indicates that short- and medium-chain FA are for all breeds more related to total fat percentage than long-chain FA. In conclusion, between breed differences were found in detailed FA composition and content of individual FA. Especially, for FA produced through de novo synthesis (short-chain FA, C12:0, C14:0, and partly C16:0) differences were found for JER and GWH, compared with the breeds HF, MRY, and DF.Journal of Dairy Science 01/2013; · 2.56 Impact Factor -
Article: Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows.
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ABSTRACT: This study investigates the feasibility to predict individual methane (CH4) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH4 emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH4 emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH4 daily emissions ranged from 10.2 to 47.1 g CH4/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH4 data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH4 measurement. The equations were built using Partial Least Squares regression. From the calculated R 2 cv, it appears that the accuracy of CH4 prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH4 emissions gave the best results. The R 2 and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH4/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH4 emission at day 1.5. The lower R 2 (R 2 = 0.76) obtained between FA profile and CH4 emission compared with the one corresponding to the obtained calibration (R 2 c = 0.87) shows the interest to apply directly the developed CH4 equation instead of the use of correlations between FA and CH4. In conclusion, our preliminary results suggest the feasibility of direct CH4 prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH4 emissions at farm level or at the regional scale and it also could be used to identify low-CH4-emitting cows.animal 10/2012; 6(10):1694-701. · 1.74 Impact Factor -
Article: Genetic correlations of days open with production traits and contents in milk of major fatty acids predicted by mid-infrared spectrometry.
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ABSTRACT: The objective of this study was to estimate the genetic relationships between days open (DO) and both milk production traits and fatty acid (FA) content in milk predicted by mid-infrared spectrometry. The edited data set included 143,332 FA and production test-day records and 29,792 DO records from 29,792 cows in 1,170 herds. (Co)variances were estimated using a series of 2-trait models that included a random regression for milk production and FA traits. In contrast to the genetic correlations with fat content, those between DO and FA content in milk changed considerably over the lactation. The genetic correlations with DO for unsaturated FA, monounsaturated FA, long-chain FA, C18:0, and C18:1 cis-9 were positive in early lactation but negative after 100 d in milk. For the other FA, genetic correlations with DO were negative across the whole lactation. At 5 d in milk, the genetic correlation between DO and C18:1 cis-9 was 0.39, whereas the genetic correlations between DO and C6:0 to C16:0 FA ranged from -0.37 to -0.23. These results substantiated the known relationship between fertility and energy balance status, explained by the release of long-chain FA in early lactation, from the mobilization of body fat reserves, and the consequent inhibition of de novo FA synthesis in the mammary gland. At 200 d in milk, the genetic correlations between DO and FA content ranged from -0.38 for C18:1 cis-9 to -0.03 for C6:0. This research indicates an opportunity to use FA content in milk as an indicator trait to supplement the prediction of genetic merit for fertility.Journal of Dairy Science 08/2012; 95(10):6113-21. · 2.56 Impact Factor -
Article: Validation of fatty acid predictions in milk using mid-infrared spectrometry across cattle breeds.
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ABSTRACT: The aim of this study was to investigate the accuracy to predict detailed fatty acid (FA) composition of bovine milk by mid-infrared spectrometry, for a cattle population that partly differed in terms of country, breed and methodology used to measure actual FA composition compared with the calibration data set. Calibration equations for predicting FA composition using mid-infrared spectrometry were developed in the European project RobustMilk and based on 1236 milk samples from multiple cattle breeds from Ireland, Scotland and the Walloon Region of Belgium. The validation data set contained 190 milk samples from cows in the Netherlands across four breeds: Dutch Friesian, Meuse-Rhine-Yssel, Groningen White Headed (GWH) and Jersey (JER). The FA measurements were performed using gas-liquid partition chromatography (GC) as the gold standard. Some FAs and groups of FAs were not considered because of differences in definition, as the capillary column of the GC was not the same as used to develop the calibration equations. Differences in performance of the calibration equations between breeds were mainly found by evaluating the standard error of validation and the average prediction error. In general, for the GWH breed the smallest differences were found between predicted and reference GC values and least variation in prediction errors, whereas for JER the largest differences were found between predicted and reference GC values and most variation in prediction errors. For the individual FAs 4:0, 6:0, 8:0, 10:0, 12:0, 14:0 and 16:0 and the groups' saturated FAs, short-chain FAs and medium-chain FAs, predictions assessed for all breeds together were highly accurate (validation R 2 > 0.80) with limited bias. For the individual FAs cis-14:1, cis-16:1 and 18:0, the calibration equations were moderately accurate (R 2 in the range of 0.60 to 0.80) and for the individual FA 17:0 predictions were less accurate (R 2 < 0.60) with considerable bias. FA concentrations in the validation data set of our study were generally higher than those in the calibration data. This difference in the range of FA concentrations, mainly due to breed differences in our study, can cause lower accuracy. In conclusion, the RobustMilk calibration equations can be used to predict most FAs in milk from the four breeds in the Netherlands with only a minor loss of accuracy.animal 07/2012; · 1.74 Impact Factor -
Article: Mid-infrared prediction of lactoferrin content in bovine milk: potential indicator of mastitis.
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ABSTRACT: Lactoferrin (LTF) is a milk glycoprotein favorably associated with the immune system of dairy cows. Somatic cell count is often used as an indicator of mastitis in dairy cows, but knowledge on the milk LTF content could aid in mastitis detection. An inexpensive, rapid and robust method to predict milk LTF is required. The aim of this study was to develop an equation to quantify the LTF content in bovine milk using mid-infrared (MIR) spectrometry. LTF was quantified by enzyme-linked immunosorbent assay (ELISA), and all milk samples were analyzed by MIR. After discarding samples with a coefficient of variation between 2 ELISA measurements of more than 5% and the spectral outliers, the calibration set consisted of 2499 samples from Belgium (n = 110), Ireland (n = 1658) and Scotland (n = 731). Six statistical methods were evaluated to develop the LTF equation. The best method yielded a cross-validation coefficient of determination for LTF of 0.71 and a cross-validation standard error of 50.55 mg/l of milk. An external validation was undertaken using an additional dataset containing 274 Walloon samples. The validation coefficient of determination was 0.60. To assess the usefulness of the MIR predicted LTF, four logistic regressions using somatic cell score (SCS) and MIR LTF were developed to predict the presence of mastitis. The dataset used to build the logistic regressions consisted of 275 mastitis records and 13 507 MIR data collected in 18 Walloon herds. The LTF and the interaction SCS × LTF effects were significant (P < 0.001 and P = 0.02, respectively). When only the predicted LTF was included in the model, the prediction of the presence of mastitis was not accurate despite a moderate correlation between SCS and LTF (r = 0.54). The specificity and the sensitivity of models were assessed using Walloon data (i.e. internal validation) and data collected from a research herd at the University of Wisconsin - Madison (i.e. 5886 Wisconsin MIR records related to 93 mastistis events - external validation). Model specificity was better when LTF was included in the regression along with SCS when compared with SCS alone. Correct classification of non-mastitis records was 95.44% and 92.05% from Wisconsin and Walloon data, respectively. The same conclusion was formulated from the Hosmer and Lemeshow test. In conclusion, this study confirms the possibility to quantify an LTF indicator from milk MIR spectra. It suggests the usefulness of this indicator associated to SCS to detect the presence of mastitis. Moreover, the knowledge of milk LTF could also improve the milk nutritional quality.animal 04/2012; 6(11):1830-8. · 1.74 Impact Factor -
Article: Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows.
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ABSTRACT: This study investigates the feasibility to predict individual methane (CH4) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH4 emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH4 emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH4 daily emissions ranged from 10.2 to 47.1 g CH4/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH4 data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH4 measurement. The equations were built using Partial Least Squares regression. From the calculated R 2 cv, it appears that the accuracy of CH4 prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH4 emissions gave the best results. The R 2 and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH4/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH4 emission at day 1.5. The lower R 2 (R 2 = 0.76) obtained between FA profile and CH4 emission compared with the one corresponding to the obtained calibration (R 2 c = 0.87) shows the interest to apply directly the developed CH4 equation instead of the use of correlations between FA and CH4. In conclusion, our preliminary results suggest the feasibility of direct CH4 prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH4 emissions at farm level or at the regional scale and it also could be used to identify low-CH4-emitting cows.animal 01/2012; 6(10):1694-1701. · 1.74 Impact Factor -
Article: Estimation of genetic parameters for methane indicator traits based on milk fatty acids in dual purpose Belgian Blue cattle.
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ABSTRACT: The genetic parameters of CH4 indicators were estimated by single trait test-day models from 16,825 records collected on Walloon Dual Purpose Belgium Blue cows in their first 3 lactations. Fatty acid based CH4 indicators published in the literature were predicted from milk mid-infrared spectra using 597 calibration samples. For the indicator showing the highest link (R2 =0.88) with SF6 CH4 data, the average daily heritability was 0.21, 0.20 and 0.10 for each lactation, respectively. The sire genetic variability was on average 2.82 kg2 of CH4 per lactation. The genetic difference between the sires having cows eructing higher and lower CH4 was 10 kg of CH4 averaged per lactation. In conclusion, CH4 indicators can be predicted by MIR and the genetic variability of these traits seems to exist.Communications in agricultural and applied biological sciences 01/2012; 77(1):21-5. -
Article: Phenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows.
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ABSTRACT: The objective of this study was to assess the phenotypic and genetic variability of production traits and milk fatty acid (FA) contents throughout lactation. Genetic parameters for milk, fat, and protein yields, fat and protein contents, and 19 groups and individual FA contents in milk were estimated for first-parity Holstein cows in the Walloon Region of Belgium using single-trait, test-day animal models and random regressions. Data included 130,285 records from 26,166 cows in 531 herds. Heritabilities indicated that de novo synthesized FA were under stronger genetic control than FA originating from the diet and from body fat mobilization. Estimates for saturated short- and medium-chain individual FA ranged from 0.35 for C4:0 to 0.44 for C8:0, whereas those for monounsaturated long-chain individual FA were lower (around 0.18). Moreover, de novo synthesized FA were more heritable in mid to late lactation. Approximate daily genetic correlations among traits were calculated as correlations between daily breeding values for days in milk between 5 and 305. Averaged daily genetic correlations between milk yield and FA contents did not vary strongly among FA (around -0.35) but they varied strongly across days in milk, especially in early lactation. Results indicate that cows selected for high milk yield in early lactation would have lower de novo synthesized FA contents in milk but a slightly higher content of C18:1 cis-9, indicating that such cows might mobilize body fat reserves. Genetic correlations among FA emphasized the combination of FA according to their origin: contents in milk of de novo FA were highly correlated with each other (from 0.64 to 0.99). Results also showed that genetic correlations between C18:1 cis-9 and other FA varied strongly during the first 100 d in milk and reinforced the statement that the release of long-chain FA inhibits FA synthesis in the mammary gland while the cow is in negative energy balance. Finally, results showed that the FA profile in milk changed during the lactation phenotypically and genetically, emphasizing the relationship between the physiological status of cow and milk composition.Journal of Dairy Science 08/2011; 94(8):4152-63. · 2.56 Impact Factor -
Article: Short communication: influence of the muscle hypertrophy mutation of the myostatin gene on milk production traits and milk fatty acid composition in dual-purpose Belgian Blue dairy cattle.
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ABSTRACT: The objective of this study was to estimate genetic effects for the muscle hypertrophy mutation (mh) of the myostatin gene for conventional milk production traits and for milk fatty acid composition in dual-purpose Belgian Blue dairy cows. For the present study, only cows from a single herd, in which genotype frequencies were as balanced as possible (0.266 for +/+, 0.523 for mh/+, and 0.211 for mh/mh), were chosen to avoid confounding between herd and genotype effects. A total of 109 cows with 3,190 test-day records for fat, protein, and milk yields and 1,064 test-day records for saturated and monounsaturated fatty acids were used for the calculations. Variance component and gene effect estimations were performed via expectation-maximization REML and BLUP methods, respectively, using a multi-trait mixed test-day model with an additional fixed regression on the muscle hypertrophy genotype. Results showed that one copy of the wild-type "+" allele led to a significant additive effect of 26.35 g/d for fat yield. Significant dominance effects of 23.22 g/d for protein yield and 30.28 g/d for fat yield were also observed. In contrast, a nonsignificant trend was observed in favor of lower saturated fatty acid contents in milk for one copy of the mutant "mh" allele. Concerning milk, fat, and protein yields, our results confirmed literature results indicating a superior effect of the "+" allele compared with the mutant allele. Therefore, the selection of the "+" allele has the potential to increase conventional milk production traits in the dual-purpose Belgian Blue breed. However, when focus is given to milk fatty acid profile, a possible antagonistic effect between the benefit of the "+" allele for higher milk production and the "mh" allele for reduced saturated fatty acid content in milk should be confirmed in further studies.Journal of Dairy Science 07/2011; 94(7):3687-92. · 2.56 Impact Factor -
Article: The use of mid-infrared spectrometry to predict body energy status of Holstein cows.
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ABSTRACT: Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application.Journal of Dairy Science 07/2011; 94(7):3651-61. · 2.56 Impact Factor -
Article: Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries.
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ABSTRACT: Increasing consumer concern exists over the relationship between food composition and human health. Because of the known effects of fatty acids on human health, the development of a quick, inexpensive, and accurate method to directly quantify the fatty acid (FA) composition in milk would be valuable for milk processors to develop a payment system for milk pertinent to their customer requirements and for farmers to adapt their feeding systems and breeding strategies accordingly. The aim of this study was (1) to confirm the ability of mid-infrared spectrometry (MIR) to quantify individual FA content in milk by using an innovative procedure of sampling (i.e., samples were collected from cows belonging to different breeds, different countries, and in different production systems); (2) to compare 6 mathematical methods to develop robust calibration equations for predicting the contents of individual FA in milk; and (3) to test interest in using the FA equations developed in milk as basis to predict FA content in fat without corrections for the slope and the bias of the developed equations. In total, 517 samples selected based on their spectral variability in 3 countries (Belgium, Ireland, and United Kingdom) from various breeds, cows, and production systems were analyzed by gas chromatography (GC). The samples presenting the largest spectral variability were used to calibrate the prediction of FA by MIR. The remaining samples were used to externally validate the 28 FA equations developed. The 6 methods were (1) partial least squares regression (PLS); (2) PLS+repeatability file (REP); (3) first derivative of spectral data+PLS; (4) first derivative+REP+PLS; (5) second derivative of spectral data+PLS; and (6) second derivative+REP+PLS. Methods were compared on the basis of the cross-validation coefficient of determination (R2cv), the ratio of standard deviation of GC values to the standard error of cross-validation (RPD), and the validation coefficient of determination (R2v). The third and fourth methods had, on average, the highest R2cv, RPD, and R2v. The final equations were built using all GC and the best accuracy was observed for the infrared predictions of C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, C18:0, C18:1 trans, C18:1 cis-9, C18:1 cis, and for some groups of FA studied in milk (saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain FA). These equations showed R2cv greater than 0.95. With R2cv equal to 0.85, the MIR prediction of polyunsaturated FA could be used to screen the cow population. As previously published, infrared predictions of FA in fat are less accurate than those developed from FA content in milk (g/dL of milk) and no better results were obtained by using milk FA predictions if no corrections for bias and slope based on reference milk samples with known contents of FA were used. These results indicate the usefulness of equations with R2cv greater than 95% in milk payment systems and the usefulness of equations with R2cv greater than 75% for animal breeding purposes.Journal of Dairy Science 04/2011; 94(4):1657-67. · 2.56 Impact Factor -
Article: New method to combine molecular and pedigree relationships.
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ABSTRACT: Relationship coefficients are traditionally based on pedigree data. Today, with the development of molecular techniques, they are often completely replaced by coefficients calculated from molecular data. Examples are relationships from microsatellites for biodiversity studies but also genomic relationships from SNP as currently used in genomic prediction of breeding values. There are, however, many situations in which optimal combination of both sources would be the best solutions. Obviously, this is the case for incompletely genotyped populations, but also when pedigree information is sparse. Also, markers, even dense ones, do not reflect the whole genome and therefore give only an incomplete picture of relationships. The main objective of this study was therefore to develop a method to calculate a relationship matrix by the combination of molecular and pedigree data. It will be useful for all situations where pedigree and molecular data are available. In this study, based on simulations of pedigree and marker data, we used partial least squares regression and linear regression to combine total allelic relationship coefficients calculated for each marker with additive relationship coefficients calculated from incomplete pedigree. The results showed that the greatest advantage of this method, compared with the one that replaces a part of the pedigree-based relationship matrix by a genomic relationship matrix, is that adding the partial pedigree data allows for the correction of the molecular coefficient for the ungenotyped part of the genome.Journal of Animal Science 11/2010; 89(4):972-8. · 2.10 Impact Factor -
Article: Short communication: Genetic variation of saturated fatty acids in Holsteins in the Walloon region of Belgium.
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ABSTRACT: 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.Journal of Dairy Science 09/2010; 93(9):4391-7. · 2.56 Impact Factor -
Article: Genetic variability of milk components based on mid-infrared spectral data.
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ABSTRACT: 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.Journal of Dairy Science 04/2010; 93(4):1722-8. · 2.56 Impact Factor -
Article: Accessing genotype by environment interaction using within- and across-country test-day random regression sire models.
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ABSTRACT: First-lactation test-day (TD) milk records of Luxembourg and Tunisian Holsteins were analysed for evidence of genotype by environment interaction (G x E). The joint data included 730 810 TD records of 87 734 cows and 231 common sires. Random regression TD sire models with fourth-order Legendre polynomials were used to estimate genetic parameters via within- and across-country analyses. Daily heritability estimates of milk yield from within-country analysis were between 0.11 and 0.32, and 0.03 and 0.13 in Luxembourg and Tunisia, respectively. Heritability estimates for 305-day milk yield and persistency (defined as the breeding value for milk yield on DIM 280 minus the breeding value on DIM 80) were lower for Tunisian Holsteins compared with the Luxembourg population. Specifically, heritability for 305-day milk yield was 0.16 for within- and 0.11 for across-country analyses for Tunisian Holsteins and 0.38 for within- and 0.40 for across-country analyses for Luxembourg Holsteins. Heritability for apparent persistency was 0.02 for both within- and across-country analyses for Tunisian Holsteins and 0.08 for within- and 0.09 for across-country analyses for Luxembourg Holsteins. Genetic correlations between the two countries were 0.50 for 305-day milk yield and 0.43 for apparent persistency. Moreover, rank correlations between the estimated breeding values of common sires for 305-day milk yield and persistency, estimated separately in each country, were low. Low genetic correlations are evidence for G x E for milk yield production while low rank correlations suggest different rankings of sires in both environments. Results from this study indicate that milk production of daughters of the same sires depends greatly on the production environment and that importing high merit semen for limited input systems might not be an effective strategy to improve milk production.Journal of Animal Breeding and Genetics 10/2009; 126(5):366-77. · 1.46 Impact Factor -
Article: Environmental sensitivity for milk yield in Luxembourg and Tunisian Holsteins by herd management level.
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ABSTRACT: Milk production data of Luxembourg and Tunisian Holstein cows were analyzed using herd management (HM) level. Herds in each country were clustered into high, medium, and low HM levels based on solutions of herd-test-date and herd-year of calving effects from national evaluations. Data from both populations included 730,810 test-day (TD) milk yield records from 87,734 first-lactation cows. A multi-trait, random regression TD model was used to estimate (co)variance components for milk yield within and across country HM levels. Additive genetic and permanent environmental variances of TD milk yields varied with management level in Tunisia and Luxembourg. Additive variances were smaller across HM levels in Tunisia than in Luxembourg, whereas permanent environmental variances were larger in Tunisian HM levels. Highest heritability estimates of 305-d milk yield (0.41 and 0.21) were found in high HM levels, whereas lowest estimates (0.31 and 0.12, respectively) were associated with low HM levels in both countries. Genetic correlations among Luxembourg HM levels were >0.96, whereas those among Tunisian HM levels were below 0.80. Respective rank orders of sires ranged from 0.73 to 0.83 across Luxembourg environments and from 0.33 to 0.42 across Tunisian HM levels indicating high re-ranking of sires in Tunisia and only a scaling effect in Luxembourg. Across-country environment analysis showed that estimates of genetic variance in the high, medium, and low classes of Tunisian environments were 45, 69, and 81% lower, respectively, than the estimate found in the high Luxembourg HM level. Genetic correlations among 305-d milk yields in Tunisian and Luxembourg HM environments ranged from 0.39 to 0.79. The largest estimated genetic correlation was found between the medium Luxembourg and high Tunisian HM levels. Rank correlations for common sires' estimated breeding values among HM environments were low and ranged from 0.19 to 0.39, implying the existence of genotype by environment interaction. These results indicate that daughters of superior sires in Luxembourg have their genetic expression for milk production limited under Tunisian environments. Milk production of cows in the medium and low Luxembourg environments were good predictors of that of their paternal half-sisters in the high Tunisian HM level. Breeding decisions in low-input Tunisian environment should utilize semen from sires with daughters in similar production environments rather than semen of bulls proven in higher management levels.Journal of Dairy Science 09/2009; 92(9):4604-12. · 2.56 Impact Factor -
Article: Modeling milk urea of Walloon dairy cows in management perspectives.
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ABSTRACT: 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.Journal of Dairy Science 08/2009; 92(7):3529-40. · 2.56 Impact Factor -
Article: Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry.
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ABSTRACT: 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.Journal of Dairy Science 07/2009; 92(6):2444-54. · 2.56 Impact Factor -
Article: Genetic analysis of lactoferrin content in bovine milk.
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ABSTRACT: 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.Journal of Dairy Science 06/2009; 92(5):2151-8. · 2.56 Impact Factor
Top co-authors
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Institutions
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2010–2013
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University of Liège
Liège, WAL, Belgium
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2008–2012
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Walloon Agricultural Research Centre CRA-W
Gembloux, WAL, Belgium
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2011
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TEAGASC - The Agriculture and Food Development Authority
- Grange Animal & Grassland Research and Innovation Centre
Carlow, L, Ireland (Republic of Ireland)
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