References of "Dardenne, Pierre"
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See detailEstimating daily yield and content of major fatty acids from single milking: First approach
Arnould, Valérie ULg; Froidmont, Eric; Nguyen, Nam et al

Poster (2011, July 11)

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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 detailNear infrared reflectance spectroscopy for estimating soil characteristics valuable in the diagnosis of soil fertility
Genot, Valérie ULg; Colinet, Gilles ULg; Bock, Laurent ULg et al

in Journal of Near Infrared Spectroscopy [=JNRIS] (2011), 19(2), 117-138

Soil fertility diagnostics rely not only upon measurement of available nutrients but also upon the soil’s ability to retain these nutrients. Near-infrared reflectance spectroscopy (NIRS) is a rapid and ... [more ▼]

Soil fertility diagnostics rely not only upon measurement of available nutrients but also upon the soil’s ability to retain these nutrients. Near-infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analytical technique which allows to simultaneously estimate standard soil characteristics and does not require use of chemicals. Previous studies showed that NIRS could be used in local contexts to predict soil properties. The main goal of our research is to build a methodological framework for the use of NIRS at a more global scale. The specific goals of this study were (i) to identify the best spectra treatment and processing –LOCAL versus GLOBAL regression- methods, (ii) to compare NIRS performances to standard chemical protocols and (iii) to evaluate the ability of NIRS to predict soil total organic carbon (TOC), total Nitrogen (TN), clay content and cationic exchange capacity (CEC) for a wide range of soil conditions. We scanned 1,300 samples representative of main soil types of Wallonia under crop, grassland or forest. Various sample preparations were tested prior to NIRS measurements. The most appropriate options were selected according to ANOVA analysis and multiple means comparisons of the spectra principal components. Fifteen pre-treatments were applied to a calibration set and the prediction accuracy was evaluated for GLOBAL and LOCAL modified partial least square (MPLS) regression models. The LOCAL MPLS calibrations showed very encouraging results for all the studied characteristics. On average, for crop soil samples, the prediction coefficient of variation (CVp) was close to 15% for TOC content, 7% for TN content, and 10% for clay content and CEC. The comparisons of repeatability and reproducibility of both NIRS and standard methods showed that NIRS is as reliable as reference methods. Prediction accuracy and technique repeatability allow the use of NIRS within the framework of the soil fertility evaluation and its replacement of standard protocols. LOCAL MPLS can be applied within global datasets, such as the International global soil spectral library. However, the performance of LOCAL MPLS is linked to the number of similar spectra in the dataset and more standard measurements are needed to characterize the least widespread soils. [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 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 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 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 detailFroment 2010 : une réédition de 2006 ?
Sinnaeve, Georges; Gofflot, Sébastien; Chandelier, Anne et al

in Livre Blanc: Céréales - Gembloux - Informations avant les semis (2010, September 09)

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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

Conference (2010, July 14)

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See detailImprovements and validation of mid-infrared predictions of milk fatty acid
Soyeurt, Hélène ULg; McParland, Sinead; Donagh, Berry et al

Conference (2010, July)

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples. The first aim was to improve these predictions by ... [more ▼]

The development of mid-infrared equations to predict the milk fatty acid (FA) content of milk allows prompt analysis of large numbers of samples. The first aim was to improve these predictions by comparing 6 statistical approaches. The second one was to validate the new equations using an independent sample set. The calibration set contained 239 spectrally different Belgian milk samples collected for over 2 years from several cows and breeds. FA were quantified by gas chromatography (GC). Statistical approaches tested were 1) partial least squares regression (PLS), 2) PLS and first derivative, 3) PLS and repeatability file (RF), 4) PLS, first derivative and RF, 5) PLS, second derivative, and 6) PLS, second derivative and RF. This last file contained spectra obtained from the same samples using 5 spectrometers. Cross-validation (CV) used 20 groups from the calibration set. Methods were compared using the ratio of the standard deviation of GC values to the standard error of CV (RPD). An external validation permitted a second comparison and was done using 362 samples collected for one year from multiple breeds and cows in Belgium, Ireland, and Scotland. Different RPD values were obtained by the 6 methods. Generally the equations developed using method 4 gave better results suggesting the adaptation of the methodology to the studied FA. It confirms by the obtained validation coefficients of determination. Highest values were observed for the equations with the highest RPD values except for C18:0. The ability to predict FA using method 4 gave superior results to those shown in previous publications. [less ▲]

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See detailPotential estimation of titratable acidity in cow milk using mid-infrared spectrometry
Colinet, Frédéric ULg; Soyeurt, Hélène ULg; Anceau, Christine ULg et al

Conference (2010, June)

Milk coagulation has a direct effect on cheese yield. Several factors influence the milk coagulation kinetics. In addition to calcium and milk protein concentrations, titratable acidity influences all the ... [more ▼]

Milk coagulation has a direct effect on cheese yield. Several factors influence the milk coagulation kinetics. In addition to calcium and milk protein concentrations, titratable acidity influences all the phases of milk coagulation. The objective of this research was to study the feasibility of prediction of titratable acidity directly in bovine milk using mid-infrared spectrometry. In order to maximize the variability in the measurements of titratable acidity, milk samples were collected on basis of several criteria (e.g. breeds). The titratable acidity was recorded as Dornic degree. All samples were also analyzed by MIR spectrometry. Using partial least squares regressions and first derivative pretreatment of spectral data, a calibration equation was built to predict the Dornic degree in cow milk. First results were promising and showed the potentiality to this calibration. The calibration and cross-validation coefficients of determination were 92.25 and 89.88 %, respectively. Moreover, the ratio of standard error of prediction to standard deviation was 3.13 and permits us to consider the calibration equation as usable in most application such as scientific researches and the screening of the Walloon dairy herd particularly in order to improve the milk coagulation properties. [less ▲]

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See detailPotential estimation of titratable acidity in cow milk using mid-infrared spectrometry
Colinet, Frédéric ULg; Soyeurt, Hélène ULg; Anceau, Christine ULg et al

in ICAR Technical Series (2010), 14

Milk coagulation has a direct effect on cheese yield. Several factors influence the milk coagulation kinetics. In addition to calcium and milk protein concentrations, titratable acidity influences all the ... [more ▼]

Milk coagulation has a direct effect on cheese yield. Several factors influence the milk coagulation kinetics. In addition to calcium and milk protein concentrations, titratable acidity influences all the phases of milk coagulation. The objective of this research was to study the feasibility of prediction of titratable acidity directly in bovine milk using mid-infrared spectrometry. In order to maximize the variability in the measurements of titratable acidity, milk samples were collected on basis of several criteria (e.g. breeds). The titratable acidity was recorded as Dornic degree. All samples were also analyzed by MIR spectrometry. Using partial least squares regressions and first derivative pretreatment of spectral data, a calibration equation was built to predict the Dornic degree in cow milk. First results were promising and showed the potentiality to this calibration. The calibration and cross-validation coefficients of determination were 92.25 and 89.88 %, respectively. Moreover, the ratio of standard error of prediction to standard deviation was 3.13 and permits us to consider the calibration equation as usable in most application such as scientific researches and the screening of the Walloon dairy herd particularly in order to improve the milk coagulation properties. [less ▲]

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See detailImprovement and validation of milk fatty acid predictions using mid-infrared spectrometry
Soyeurt, Hélène ULg; McParland, Sinead; Berry, Donagh et al

in Proceedings of the Bristish Society of Animal Science and the Agricultural Research Forum (2010)

Detailed reference viewed: 28 (3 ULg)