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van Lingen, H.J.; Plugge, C.M.; Fadel, J.G.; Kebreab, E.; Bannink, A.; Dijkstra, J. |
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Title |
Correction: Thermodynamic Driving Force of Hydrogen on Rumen Microbial Metabolism: A Theoretical Investigation |
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Miscellaneous |
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2016 |
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PLoS One |
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PLoS One |
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11(12) |
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12 |
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e0168052 |
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[This corrects the article DOI: 10.1371/journal.pone.0161362.]. |
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1932-6203 |
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LiveM, ftnotmacsur |
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MA @ admin @ |
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5020 |
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Bannink, A.; Dijkstra, J. |
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Title |
Effects of roughage characteristics on enteric methane emission in dairy cows |
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Journal Article |
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Year |
2016 |
Publication |
Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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Volume |
7 |
Issue |
03 |
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229-230 |
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2040-4700 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4875 |
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Kipling, R.P.; Bannink, A.; Özkan Gülzari, Ş.; Van Middelkoop, J. |
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Title |
Editorial |
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Journal Article |
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Year |
2016 |
Publication |
Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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7(03) |
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03 |
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223 |
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2040-4700 |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
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4878 |
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Scollan, N.; Bannink, A.; Kipling, R.; Saetnan, E.; Van Middelkoop, J. |
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Title |
Livestock and feed production, especially dairy and beef |
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Conference Article |
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2015 |
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FACCE MACSUR Reports |
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6 |
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Sp6-3 |
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Improving health and welfare is an important adaptation and mitigation strategyDeveloping process based modelling, responsive to adaptationLinks to climate and land use change modelling are essential Livestock systems likely to be hit hardest by climate changeNeed to develop animal health models that respond to adaptation by farmersBringing together direct and indirect impacts of climate change vitalAdaptation and mitigation need to be considered and modelled togetherLinking models across scales is important to support policy decisionsLearning between sectors carries potential for novel solutions and methodological advancesEffective communication of outcomes to stakeholders (how?) No Label |
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Brussels |
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Climate-change impacts on farming systems in the next decades: Why worry when you have CAP? A FACCE MACSUR workshop for policymakers |
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no |
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MA @ admin @ |
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2084 |
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Bannink, A.; van Lingen, H.J.; Ellis, J.L.; France, J.; Dijkstra, J. |
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Title |
The contribution of mathematical modeling to understanding dynamic aspects of rumen metabolism |
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Journal Article |
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Year |
2016 |
Publication |
Frontiers in Microbiology |
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Frontiers in Microbiology |
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7 |
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1820 |
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lactating dairy-cows; milk urea concentration; fatty-acid production; ruminal fermentation; mechanistic model; holstein cows; beef-cattle; stoichiometric parameters; methane production; feeding frequency |
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All mechanistic rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interactions between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e., with new characteristics from the perspective of whole rumen function) in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen pH is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA), and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and their role in VFA absorption needs to be better represented in models that aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more to microbial metabolism. For rumen model construction, data on rumen microbiomes are preferably coupled with knowledge consolidated in rumen models instead of relying on correlations with rather general aspects of treatment or animal. This helps to prevent the disregard of basic principles and underlying mechanisms of whole rumen function. |
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2017-01-06 |
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English |
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1664-302x |
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LiveM, ft_MACSUR |
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no |
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Call Number |
MA @ admin @ |
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4932 |
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