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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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2016 |
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Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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7 |
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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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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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2016 |
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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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MA @ admin @ |
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4932 |
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Banse, M. |
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Title |
Halftime in MACSUR – what have we learned and what comes next |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-2 |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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no |
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Call Number |
MA @ admin @ |
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2192 |
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Banse, M. |
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What drives meat consumption? Combining cross-country analysis with an applied trade model |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-3 |
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In a cross country analysis using national data for both OECD and developing countries, we estimate a regression model with different coefficients for different drivers for per capita meat consumption. The model contains data from approximately 125 countries (depending on the variables included) on meat consumption and production, relative size of agricultural area and pasture and meadows, PPP adjusted consumer prices for meat (and for food as control variable), PPP adjusted GNI per capita, HDI, degree of urbanisation, religion and geographical/cultural belonging.A regression analysis has been conducted, using OLS with data from 2011 and an aggregation of all meat types as the dependent variable. In the results all of the mentioned variables have a significant impact on meat consumption.Based on a first scenario analysis which has been presented on a TradeM Workshop of MACSUR in September 2014, this paper will extend the approach of an estimated cross-country analysis to improve the demand elasticities in the MAGNET model for meat and meat products. Further other demand determining factors of meat consumption, e.g. behavioural change towards less meat consumption (vegetarian or vegan) derived from the regression analysis will be fed into the MAGNET model. This extended approach will help to analyse the resulting market effects of a changing demand pattern for meat. MAGNET will provide insights in consequences on supply and international trade for meat and meat products.The aim of this combined approach is to further explore the relationship between production and consumption, and to what extent the one is driving the other. Based on the application of the panel data method for a detailed demand analysis with the combination of the feedback from the supply and trade side based on the MAGNET model we will be able to provide a tool which is able to address the important questions of demand responses under different adaptation or mitigation strategies towards clime change, such as tax measures like fat taxes. This extended tool also contributes to an improved decision making process of policy makers under different options to respond to climate change issues – not only with regard to the supply side of agricultural production but also to the consumption side. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2118 |
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Banse, M. |
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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 – Introduction |
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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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SP6-1 |
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MACSUR’s aims•To analyze the effects of climate change for farming conditions in European regions •To identify risks for farmers, to jointly develop mitigation and adaptation options•To analyze consequences of mitigation and adaptation for farming competitiveness, the environment and rural developmentMACSUR’S mission •improve and integratemodels – crop and livestock production, farms, and national & international agri-food markets•demonstrate integration and links – models for selected farming systems and regions •provide hands-on training- young and experienced researchers in integrative modelingProgramme of the workshop•Presentation of current achievements—Regional Pilots on climate adaptation —EU-level assessments •Intensive discussion with all participants—What are your knowledge needs ?—What can MACSUR-2 contribute ?—How to collaborate ?—Next steps of interaction 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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MA @ admin @ |
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2082 |
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