References of "Soyeurt, Hélène"
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See detailEstimating daily yield of major fatty acids from single milking: first approach.
Arnould, Valérie ULg; NGuyen, N. H.; Froidmont et al

in Journal of Dairy Science (2011, July), 94(E-Suppl. 1), 29

Reducing the frequency of milk recording and the number of recorded samples per test-day could be a solution in order to reduce costs of milk recording. However, this solution leads to decrease also the ... [more ▼]

Reducing the frequency of milk recording and the number of recorded samples per test-day could be a solution in order to reduce costs of milk recording. However, this solution leads to decrease also the accuracy of predicting daily yield. According to the literature, several authors have already worked on this problematic. Unfortunately, some effects used in previous studies are not often available or reliable in used databases. This study was aimed to enlarge these investigations to milk fatty acids (FA) production: saturated FA, mono-unsaturated FA, unsaturated FA, medium-chain FA, and long chain FA and to propose a simple, robust and practical method for estimating accurate daily major FA yield from single milking. To do this, five dairy cows were followed between January 2007 and December 2010. FA contents were predicted by mid-infrared spectrometry. The final database contained 1,440 records. The first step was to ensure that used effects were available in most used databases. According to the availability of data, height models were tested to estimate daily yields from both morning and evening milking. These models were compared on the basis of the coefficient of determination values between estimated and observed daily yields and the mean square error. The proposed models included progressively several effects such as the milk yield, the fat and protein content, some classes of stage in lactation, of month of test or of month of calving. As expected, R² values were higher when these effects are introduced in the model and were comprised between 0.87 and 0.88 when daily yield were estimated from morning milking, and from 0.75 and 0.86 when daily yield were estimated from evening milking. It was concluded that the introduction of these effects did highly improve the daily predictability of all trait yield and can partially replace the milking interval effect. It was also observed that daily yields estimated from evening milkings are less accurate than those estimated from morning milkings. Finally, the applied model will depend on the availability of the data and to the convenience of the applied model to the studied population. Keywords: Milk recording, Fatty acids, prediction [less ▲]

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See detailMid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries
Soyeurt, Hélène ULg; Dehareng, ; Gengler, Nicolas ULg et al

in Journal of Dairy Science (2011), 94

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 ... [more ▼]

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 crossvalidation 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. [less ▲]

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See detailRobustMilk - Développer des outils de sélection pratiques et innovants pour la production de produits laitiers de qualité issus de vaches plus robustes : Sélectionner sur le profil en acides gras du lait
Bastin, Catherine ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in 16ième Carrefour des productions animales: La Filière laitière bovine est-elle durable?, Gembloux, le 2 mars 2011 (2011, March 02)

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See detailEstimation de la quantité journalière grasse du lait à partir d'une seule traite (matin ou soir) des composés fins de la matière grasse du lait
Arnould, Valérie ULg; Froidmont, Eric; Nguyen, Nam et al

in 16ième Carrefour des Productions animales: la filière laitière bovine européenne est-elle durable? (2011, March 02)

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See detailManageMilk - Création d'outils de management innovatifs et pratiques en vue d'améliorer la durabilité de la production laitière et de la qualité des produits laitiers: présentation du projet.
Arnould, Valérie ULg; Soyeurt, Hélène ULg; Stoll, Jean et al

in 16ième Carrefour des Prodcutions animales: La filière laitière bovine européenne est-elle durable? (2011, March 02)

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See detailVariabilité et amélioration des aptitudes à la transformation fermière du lait au travers du projet ProFARMilk
Colinet, Frédéric ULg; Sindic, Marianne ULg; Anceau, Christine ULg et al

in 16ième Carrefour des Productions animales: La filière laitière bovine européenne est-elle durable? (2011, March)

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See detailPrediction of individual methane emission by dairy cattle from mid-infrared spectra
Vanlierde, Amélie ULg; Delfosse, Camille; Dehareng, Frédéric et al

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

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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 detailPhenotypic and genetic variability of production traits and milk fatty acid contents across days in milk for Walloon Holstein first-parity cows.
Bastin, Catherine ULg; Gengler, Nicolas ULg; Soyeurt, Hélène ULg

in Journal of Dairy Science (2011), 94(8), 4152-63

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 ... [more ▼]

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. [less ▲]

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See detailPotential of near infrared spectroscopy for on-line analysis at the milking parlour using a fiber-optic probe presentation
Nguyen, Hoang Nam; Dehareng, Frédéric; Hammida, Mohamed et al

in NIR news (2011), 22

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See detailNew method to combine molecular and pedigree relationships
Bömcke, Elisabeth ULg; Soyeurt, Hélène ULg; Szydlowski, Maciej et al

in Journal of Animal Science (2011), 89

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 ... [more ▼]

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. [less ▲]

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See detailAcross breed and country validation of mid-infrared calibration equations to predict milk fat composition
Maurice - Van Eijndhoven, Myrthe; Soyeurt, Hélène ULg; Dehareng, Frédéric et al

in Book of Abstracts of the 62nd Annual Meeting of the European Association for Animal Production (2011)

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