References of "Lewis, E"
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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 detailPrediction of the individual enteric methane emission of dairy cows from milk mid-infrared spectra
Vanlierde, Amélie ULiege; Dehareng, F.; Froidmont, E. et al

in Advances in Animal Biosciences (2013, June)

The livestock sector is considered the largest producer of methane (CH4) from anthropogenic sources, world wide contributing 37% of emissions (FAO, 2006). An important step to study and develop mitigation ... [more ▼]

The livestock sector is considered the largest producer of methane (CH4) from anthropogenic sources, world wide contributing 37% of emissions (FAO, 2006). An important step to study and develop mitigation methods for livestock emissions is to be able to measure them on a large scale. However, it is difficult to obtain a large number of individual CH4 measurements with the currently available techniques (chambers or SF6). The aim of this study was to develop a high throughput tool for determination of CH4 emissions from dairy cows. Anaerobic fermentation of food in the reticulorumen is the basis of enteric CH4 production. End-products of that enteric fermentation can be found in the milk (e.g., volatile fatty acids). Therefore individual enteric CH4 emissions could be quantified from whole milk mid-infrared (MIR) spectra which reflect milk composition and can be obtained at low cost (e.g., national milk recording). Prediction equations of individual CH4 emissions (determined using the SF6 method) from milk MIR spectra have been established (Dehareng et al., 2012; Soyeurt et al., 2013). The results presented here are the improvement of this methodology by using a multiple breed and country approach. [less ▲]

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See detailAvancées dans le développement d’une équation permettant de prédire les émissions de méthane des vaches laitières grâce aux spectres moyens infrarouges du lait Progress in the development of an equation for predicting methane emission from dairy cows using milk mid-infrared spectra
Vanlierde, Amélie ULiege; DEHARENG, F.; FROIDMONT, E. et al

in Rencontres autour des Recherches sur les Ruminants (2013), 20

Le secteur de l'élevage contribue à 37% des émissions de méthane (CH4) d’origine anthropique dans le monde (Steinfeld et al., 2006). Afin de pouvoir étudier ces émissions et ainsi développer des méthodes ... [more ▼]

Le secteur de l'élevage contribue à 37% des émissions de méthane (CH4) d’origine anthropique dans le monde (Steinfeld et al., 2006). Afin de pouvoir étudier ces émissions et ainsi développer des méthodes permettant de les réduire il est nécessaire de pouvoir les mesurer à grande échelle. Dans cette optique, des équations permettant de prédire les émissions individuelles de CH4 directement à partir du spectre laitier mesuré en moyen infrarouge (MIR) ont été établies (Dehareng et al., 2012; Soyeurt et al., 2013). Les avancées de ces équations présentent désormais une approche internationale et multi-race. [less ▲]

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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),

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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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See detailRelationship between milk composition estimated from mid infrared and methane emissions in dairy cows
Kandel, Purna Bhadra ULiege; Vanlierde, Amélie ULiege; Dehareng, F et al

Scientific conference (2012, December 03)

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See detailGenetics and genomics of energy balance measured in milk using mid-infrared spectroscopy
McParland, Sinead; Calus, Mario; Coffey, Mike et al

Poster (2012, August)

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See detailGenetics and genomics of energy balance measured in milk using mid-infrared spectroscopy
McParland, Sinead; Calus, Mario; Coffey, Mike et al

in Book of Abstracts of the 63rd Annual Meeting of the European Federation of Animal Science (2012, August)

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