References of "Dardenne, Pierre"
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See detailImprovement of a method to predict individual enteric methane emission of cows from milk MIR spectra
Vanlierde, Amélie ULiege; Dehareng, F.; Froidmont, E. et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August 27)

Besides being a greenhouse gas, enteric methane (CH produced by ruminants during rumination is also associated with the loss of 6 to 12% of gross energy intake. Mitigation of those emissions could be ... [more ▼]

Besides being a greenhouse gas, enteric methane (CH produced by ruminants during rumination is also associated with the loss of 6 to 12% of gross energy intake. Mitigation of those emissions could be based on combined actions on diet, herd management and animal genetics. In order to investigate easily the relationship between these parameters and the CH4 emissions on a large scale, an equation to predict individual enteric CH4 emissions from the whole individual milk mid-infrared (MIR) spectra was developed. To build this equation a total of 452 CHA reference were obtained using the sF6 method. on Jersey, Holstein and Holstein-Jersey crossbred cows. In parallel a 40 ml sample of individual milk was collected at each milking (morning and evening) and was analyzed using MIR spectrometry Then, these spectra were averaged proportionally function of the milk production to have one spectrum for one CH4 ment. Data were collected on 146 different cows (63, 36, 18, 29 a in parity one to fourt, respectively) receiving different diets. The calibration model was developed using Foss wINISI 4 software on spectral data after applying the first derivative and using pLs regression. The CH4 emission prediction (g showed a calibration coefficient of determination (R2c) of 0.76, a cross-validation coefficient of determination (R2cv) and the standard error of calibration was of 62 g/day. Results are very promising and showed the possibility to predict the eructed CH4 from the milk spectra. relationship between measurements and predictions is linear and thereby allowing the distinction between low and high emitting cows. [less ▲]

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULiege; Kandel, Purna Bhadra ULiege; Soyeurt, Hélène ULiege et al

Poster (2013, August 26)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailHerd-test-day variability of methane emissions predicted from milk MIR spectra in Holstein cows
Vanrobays, Marie-Laure ULiege; Kandel, Purna Bhadra ULiege; Soyeurt, Hélène ULiege et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day ... [more ▼]

The aim of this study was to estimate the herd-test-day (HTD) effect on milk yield, fat and protein content, and methane (CH4) emissions of Walloon Holstein first-parity cows. A total of 412,520 test-day records and milk mid-infrared (MIR) spectra of 69,223 cows in 1,104 herds were included in the data set. The prediction equation developed by Vanlierde et al. (Abstract submitted to EAAP 2013; R² of cross-validation=0.70) was applied on the recorded spectral data to predict CH4 emissions (g/d). Daily CH4 emissions expressed in g/kg of milk were computed by dividing CH4 emissions (g/d) by daily milk yield of cows. Several bivariate (a CH4 trait with a production trait) random regression test-day models including HTD and classes of days in milk and age at calving as fixed effects and permanent environment and genetic as random effects were used. HTD solutions of studied traits obtained from these models were studied and presented large deviations (CV=17.54%, 8.93%, 4.68%, 15.51%, and 23.18% for milk yield, fat and protein content, MIR CH4 (g/d), and MIR CH4 (g/kg of milk), respectively) indicating differences among herds, especially for milk yield and CH4 traits. HTD means per month of milk yield and fat and protein contents presented similar patterns within year. The maximum of monthly HTD means corresponded to the spring (pastern release) for milk yield and to the winter for fat and protein contents. The minimum corresponded to the month of November for milk yield and to the summer for the other traits. For MIR CH4 (g/d), monthly HTD means showed similar patterns as fat and protein content within year. MIR CH4 (g/kg of milk) presented maximum values of monthly HTD means in November and minimum values in May. Finally, results of this study showed that HTD effects on milk production traits and on MIR CH4 emissions varied through herds and seasons. [less ▲]

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See detailUse of visible-near infrared spectroscopy to determine cheese properties
Troch, Thibault ULiege; Vanden Bossche, Sandrine; De Bisschop, Céline et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

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See detailMid-infrared prediction of cheese yield from milk and its genetic variability in first-parity cows
Colinet, Frédéric ULiege; Troch, Thibault ULiege; Vanden Bossche, Sandrine et al

in Book of Abstracts of the 64th Annual Meeting of the European Federation of Animal Science (2013, August)

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See detailUse of visible-near infrared spectroscopy to determine cheese properties
Troch, Thibault ULiege; Vanden Bossche, Sandrine; De Bisschop, Céline et al

Poster (2013, August)

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See detailHyperspectral imaging applications in agriculture and agro-food product quality and safety control: A review
Dale, Laura ULiege; Thewis, André ULiege; Boudry, Christelle ULiege et al

in Applied Spectroscopy Reviews (2013), 48(2), 142-159

In this review, various applications of Near Infrared Hyperspectral Imaging (NIR-HSI) in agriculture and in the quality control of agro-food products are presented. NIR-HSI is an emerging technique that ... [more ▼]

In this review, various applications of Near Infrared Hyperspectral Imaging (NIR-HSI) in agriculture and in the quality control of agro-food products are presented. NIR-HSI is an emerging technique that combines classical NIR spectroscopy and imaging techniques in order to simultaneously obtain spectral and spatial information from a field or a sample. The technique is non-destructive, non-polluting, fast and relatively inexpensive per analysis. Currently, its applications in agriculture range from vegetation mapping, crop disease, stress and yield detection to component identification in plants and impurity detection. There is growing interest in HSI for the safety and quality assessment of agro-food products. The applications have been classified from the level of satellite images to the macroscopic, if not, molecular level. [less ▲]

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See detailUse of VIS- and nir-infrared spectroscopy to determine cheese properties
Troch, Thibault ULiege; Vanden Bossche, Sandrine; De Bisschop, Céline et al

Poster (2013, June)

Cheese processing is one of the possibilities of farm diversification. From 30 cow milks were made 60 cheeses on which several parameters were measured and on which NIR spectra were obtained. Our results ... [more ▼]

Cheese processing is one of the possibilities of farm diversification. From 30 cow milks were made 60 cheeses on which several parameters were measured and on which NIR spectra were obtained. Our results show that cheese spectra could be discriminated between different ripening times of cheeses and the access to pasture or not for the animals which had produced the milk from which the cheese was made. Moreover, highly significant correlations were obtained for the color and the texture of cheeses between the values measured in the laboratory and the NIR spectra. [less ▲]

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See detailAnalysis of Soils in Agriculture and Archaeology by NIR Hyperspectral Imaging
Fernandez Pierna, Juan Antonio; Vincke, Damien; Eylenbosch, Damien ULiege et al

Conference (2013, May 23)

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See detailFertilization Effects on the Chemical Composition and In Vitro Organic Matter Digestibility of Semi-natural Meadows as Predicted by NIR Spectrometry
Dale, Laura ULiege; Thewis, André ULiege; Rotar, Ioan et al

in Notulae Botanicae Horti Agrobotanici Cluj-Napoca (2013), 41(1), 42-48

Management of livestock grazing in highly-productive mountain meadows is an important aspect for the economic viability and the environmental impact of a grassland-based farm. The main aim of this study ... [more ▼]

Management of livestock grazing in highly-productive mountain meadows is an important aspect for the economic viability and the environmental impact of a grassland-based farm. The main aim of this study was to build near infrared models to determine the chemical composition and in vitro organic matter digestibility of Romanian meadow forages. The treatments were organic and mineral fertilizer combinations, and forage samples were obtained from three fertilization experiments conducted in the Apuseni Mountains; these samples were analysed using classical and NIR methods. The samples were scanned in the NIR wavelength band. The CRA-W Gembloux ‘local’ calibration models were validated with Romanian meadow forages and then used in order to predict the forage quality of samples. A second objective of the study was to determine the effects of fertilization on forage quality. The results showed a decrease in crude protein content from the NPK treatment (150:75:75), which can be explained by a reduction of Fabaceae plants with this treatment from 17.25% of the populations in the control (semi-natural meadow not fertilized) to 6.25% in the fertilized plots. The decrease in protein content and in vitro organic matter digestibility was related to a reduced Fabaceae presence. Our recommendation is to use mineral fertilization with NPK doses less than 100:50:50 to improve meadow productivity; meanwhile organic fertilization can also be used to complement and maintain biodiversity and forage quality. [less ▲]

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See detailQualité du lait: la Wallonie à la pointe grâce à l’utilisation de la spectrométrie infrarouge
Dehareng, Frédéric; Soyeurt, Hélène ULiege; Gengler, Nicolas ULiege et al

in Carrefour des productions animales: Nouvelles approches pour une optimisation de nos élevages laitiers (2013, February 20)

La spectrométrie infrarouge est utilisée depuis de nombreuses années en Belgique. Les premiers spectromètres utilisés étaient des appareils à filtres, n’utilisant que quelques zones de la plage spectrale ... [more ▼]

La spectrométrie infrarouge est utilisée depuis de nombreuses années en Belgique. Les premiers spectromètres utilisés étaient des appareils à filtres, n’utilisant que quelques zones de la plage spectrale du moyen infrarouge (MIR). La généralisation de ces appareils dans les laboratoires d’analyses laitières a été possible grâce aux nombreux avantages liés à cette technique d’analyse. Ces appareils sont très rapides : ils permettent de mesurer entre 400 et 600 échantillons par heure. Une seule mesure spectrale permet d’estimer simultanément une multitude de paramètres. Cette technique est également précise et robuste, permettant ainsi d’obtenir un niveau de précision équivalent aux méthodes de référence classiques. Enfin, les coûts d’analyse par échantillon restent relativement faibles. Ceci a donc permis d’une part le développement du système de payement du lait actuel qui repose sur un échantillonnage et une mesure systématique de la composition du lait lors de chaque ramassage en ferme et, d’autre part, le développement du contrôle laitier mensuel [less ▲]

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See detailStandardisation of milk MIR spectra: a first step to create new tools of dairy farm management
Grelet, Clément ULiege; Fernandez Pierna, Juan Antonio; Dehareng, Frédéric et al

Conference (2013)

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See detailOptiMIR : de nouveaux outils de management des exploitations laitières grâce au spectre moyen infra-rouge du lait
Grelet, Clément ULiege; Fernandez Pierna, Juan Antonio; Dehareng, Frédéric et al

Conference (2013)

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See detailDevelopment of a method to predict individual enteric methane emissions from cows based on milk mid-infrared spectra
Vanlierde, Amélie ULiege; Froidmont, Eric; Soyeurt, Hélène ULiege et al

in Hassouna, Mélynda; Guingand, Nadine (Eds.) Emissions of Gas and Dust from Livestock (2013)

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See detailGenetic parameters for methane emission predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULiege; Vanrobays, Marie-Laure ULiege; Vanlierde, Amélie ULiege et al

in Advances in Animal Biosciences (2013), 4(2),

N/A

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See detailGenetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows
Kandel, Purna Bhadra ULiege; Vanrobays, Marie-Laure ULiege; Vanlierde, Amélie ULiege et al

in Journal of Dairy Science (2013), 95(E-1), 388

Genetic selection of low methane (CH4) emitting animals is additive and permanent but the difficulties associated with individual CH4 measurement result in a paucity of records required to estimate ... [more ▼]

Genetic selection of low methane (CH4) emitting animals is additive and permanent but the difficulties associated with individual CH4 measurement result in a paucity of records required to estimate genetic variability of CH4 traits. Recently, it was shown that direct quantification of CH4 emissions by mid-infrared spectroscopy (MIR) from milk. The CH4 prediction equation was developed using 452 SF6 CH4 measurements with associated milk spectra and the calibration equation was developed using PLS regression. The obtained SD of predicted CH4 was 126.39 g/day with standard error of cross validation 68.68 g/day and a cross-validation coefficient of determination equal to 70%. The equation was applied on a total of 338,917 spectra obtained from milk samples collected between January 2007 and August 2012 during the Walloon milk recording for first parity Holstein cows. The prediction of MIR CH4 was 547 ± 111 g/d and MIR CH4 g/kg of fat and protein corrected milk (FPCM) was 23.66 ± 8.21.Multi-trait random regression test-day models were used to estimate the genetic variability of MIR predicted CH4 and milk production traits. The heritability, phenotypic and genetic correlations between MIR predicted CH4 traits and milk traits are presented in Table 1. Estimated heritability for CH4 g/day and CH4 g/kg of FPCM were lower than common production traits but would still be useful in breeding programs. While selection for cows emitting lower amounts of MIR predicted CH4 (g/d) would have little effect on milk production traits, selection on MIR predicted CH4 (g/kg of FPCM) would decrease FPCM, fat and protein yields. These genetic parameters of CH4 indicator traits might be entry point for selection that accounts mitigation of CH4 from dairy farming. Table 1. Heritability (diagonal), phenotypic (below the diagonal) and genetic (above the diagonal) correlations between MIR predicted CH4 and production traits Traits MIR CH4 (g/d) MIR CH4 ((g/kg of FPCM) FPCM Fat yield Protein yield MIR CH4 (g/d) 0.11 0.42 0.03 0.19 0.04 MIR CH4 (g/kg of FPCM)0.59 0.18 -0.83 -0.72 -0.77 FPCM -0.02 -0.65 0.20 0.95 0.91 Fat yield 0.01 -0.58 0.76 0.22 0.70 Protein yield -0.01 -0.61 0.78 0.69 0.20 [less ▲]

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