Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 540945
Title Multi-criteria evaluation of diary cattle feed resources and animal characteristics for nutritive and environmental impacts
Author(s) Lingen, H.J. van; Fadel, J.G.; Bannink, A.; Dijkstra, J.; Tricarico, J.M.; Pacheco, D.; Casper, D.P.; Kebreab, E.
Source Animal (2018). - ISSN 1751-7311 - 11 p.
DOI https://doi.org/10.1017/S1751731118001313
Department(s) Animal Nutrition
WIAS
LR - Animal Nutrition
Publication type Refereed Article in a scientific journal
Publication year 2018
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.
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