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Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts

Published online by Cambridge University Press:  24 August 2018

H. J. van Lingen Open the ORCID record for H. J. van Lingen [Opens in a new window] ,
J. G. Fadel ,
A. Bannink Open the ORCID record for A. Bannink [Opens in a new window] ,
J. Dijkstra ,
J. M. Tricarico ,
D. Pacheco ,
D. P. Casper  and
E. Kebreab
H. J. van Lingen
Affiliation:
Department of Animal Science, University of California, Davis, CA 95616, USA
J. G. Fadel
Affiliation:
Department of Animal Science, University of California, Davis, CA 95616, USA
A. Bannink
Affiliation:
Wageningen Livestock Research, Wageningen University & Research, PO Box 338, 6700 AH, Wageningen, the Netherlands
J. Dijkstra
Affiliation:
Animal Nutrition Group, Wageningen University & Research, PO Box 338, 6700 AH, Wageningen, The Netherlands
J. M. Tricarico
Affiliation:
DMI Innovation Center for US Dairy, Rosemont, IL 60018, USA
D. Pacheco
Affiliation:
AgResearch Limited, Grasslands Research Centre, Private Bag 11008, Palmerston North 4442, New Zealand
D. P. Casper
Affiliation:
Furst McNess Company, Freeport, IL61032, USA
E. Kebreab*
Affiliation:
Department of Animal Science, University of California, Davis, CA 95616, USA
*
†E-mail: ekebreab@ucdavis.edu
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Abstract

On-farm nutrition and management interventions to reduce enteric CH4 (eCH4) emission, the most abundant greenhouse gas from cattle, may also affect volatile solids and N excretion. The objective was to jointly quantify eCH4 emissions, digestible volatile solids (dVS) excretion and N excretion from dairy cattle, based on dietary variables and animal characteristics, and to evaluate relationships between these emissions and excreta. Univariate and Bayesian multivariate mixed-effects models fitted to 520 individual North American dairy cow records indicated dry matter (DM) intake and dietary ADF and CP to be the main predictors for production of eCH4 emissions and dVS and N excreta (g/day). Yields (g/kg DM intake) of eCH4 emissions and dVS and N excreta were best predicted by dietary ADF, dietary CP, milk yield and milk fat content. Intensities (g/kg fat- and protein-corrected milk) of eCH4, dVS and N excreta were best predicted by dietary ADF, dietary CP, days in milk and BW. A K-fold cross-validation indicated that eCH4 and urinary N variables had larger root mean square prediction error (RMSPE; % of observed mean) than dVS, fecal N and total N production (on average 24.3% and 26.5% v. 16.7%, 15.5% and 16.2%, respectively), whereas intensity variables had larger RMSPE than production and yields (29.4%, 14.7% and 14.6%, respectively). Univariate and multivariate equations performed relatively similar (18.8% v. 19.3% RMSPE). Mutual correlations indicated a trade-off for eCH4v. dVS yield. The multivariate model indicated a trade-off between eCH4 and dVS v. total N production, yield and intensity induced by dietary CP content.

Keywords

methane emissiondigestible volatile solids excretionnitrogen excretionunivariate and multivariate predictionBayesian analysis
Type
Research Article
Information
animal , Volume 12 , Supplement s2: 10th International Symposium on the Nutrition of Herbivores: Herbivore nutrition supporting sustainable intensification and agro-ecological approaches 2–6th September 2018, Clermont-Ferrand, France , December 2018 , pp. s310 - s320
Copyright
© The Animal Consortium 2018 

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