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Animal : an International Journal of Animal Bioscience
|
October 4, 2012
Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows
F Dehareng, C Delfosse, E Froidmont, et al.
Journal of Dairy Science
|
March 24, 2011
Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries
H Soyeurt, F Dehareng, N Gengler, et al.
Journal of Dairy Science
|
June 25, 2011
The use of mid-infrared spectrometry to predict body energy status of Holstein cows
S McParland, G Banos, E Wall, et al.
Animal : an International Journal of Animal Bioscience
|
November 24, 2017
The feeding system impacts relationships between calving interval and economic results of dairy farms
A-C Dalcq, Y Beckers, P Mayeres, et al.
Journal of Dairy Science
|
November 16, 2006
Variation in fatty acid contents of milk and milk fat within and across breeds
H Soyeurt, P Dardenne, A Gillon, et al.
Journal of Dairy Science
|
November 23, 2020
A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra
H Soyeurt, C Grelet, S McParland, et al.
Journal of Dairy Science
|
August 11, 2006
Estimating fatty acid content in cow milk using mid-infrared spectrometry
H Soyeurt, P Dardenne, F Dehareng, et al.
Methods (San Diego, Calif.)
|
August 9, 2020
Large-scale phenotyping in dairy sector using milk MIR spectra: Key factors affecting the quality of predictions
C Grelet, P Dardenne, H Soyeurt, et al.
Journal of Dairy Science
|
July 4, 2016
Changes throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra
M-L Vanrobays, C Bastin, J Vandenplas, et al.
Journal of Dairy Science
|
September 7, 2023
Imputation of missing milk Fourier transform mid-infrared spectra using existing milk spectral databases: A strategy to improve the reliability of breeding values and predictive models
H Soyeurt, X-L Wu, C Grelet, et al.
Page
of 6
Search research articles
Search
Showing results (31-40 of 53) with videos related to
Sort By:
Page
of 6
Animal : an International Journal of Animal Bioscience
|
October 4, 2012
Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows
F Dehareng, C Delfosse, E Froidmont, et al.
Journal of Dairy Science
|
March 24, 2011
Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries
H Soyeurt, F Dehareng, N Gengler, et al.
Journal of Dairy Science
|
June 25, 2011
The use of mid-infrared spectrometry to predict body energy status of Holstein cows
S McParland, G Banos, E Wall, et al.
Animal : an International Journal of Animal Bioscience
|
November 24, 2017
The feeding system impacts relationships between calving interval and economic results of dairy farms
A-C Dalcq, Y Beckers, P Mayeres, et al.
Journal of Dairy Science
|
November 16, 2006
Variation in fatty acid contents of milk and milk fat within and across breeds
H Soyeurt, P Dardenne, A Gillon, et al.
Journal of Dairy Science
|
November 23, 2020
A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra
H Soyeurt, C Grelet, S McParland, et al.
Journal of Dairy Science
|
August 11, 2006
Estimating fatty acid content in cow milk using mid-infrared spectrometry
H Soyeurt, P Dardenne, F Dehareng, et al.
Methods (San Diego, Calif.)
|
August 9, 2020
Large-scale phenotyping in dairy sector using milk MIR spectra: Key factors affecting the quality of predictions
C Grelet, P Dardenne, H Soyeurt, et al.
Journal of Dairy Science
|
July 4, 2016
Changes throughout lactation in phenotypic and genetic correlations between methane emissions and milk fatty acid contents predicted from milk mid-infrared spectra
M-L Vanrobays, C Bastin, J Vandenplas, et al.
Journal of Dairy Science
|
September 7, 2023
Imputation of missing milk Fourier transform mid-infrared spectra using existing milk spectral databases: A strategy to improve the reliability of breeding values and predictive models
H Soyeurt, X-L Wu, C Grelet, et al.
Page
of 6