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Bojar, W.; Knopik, L.; Żarski, J. |
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Integrated assessment of business crop productivity and profitability for use in food supply forecasting |
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Conference Article |
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Year |
2014 |
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Climate change suggests long periods without rainfall will occur in the future quite often. Previous approach on dependence crop-yields from size of rain confirms the existence of a statistically significant relation. We built a model describing the amount of precipitation and taking into account periods of drought, using a mixture of gamma distribution and one point-distribution. Parameter estimators were constructed from rainfall data using the method of maximum likelihood. Long series of days or decades of drought allow to determine the probabilities of adverse developments in agriculture as the basis for forecasting crop yields in the future (years 2030, 2050). Forecasted yields can be used for assessment of productivity and profitability of some selected crops in Kujavian-Pomeranian region. Assumptions and parameters of large-scale spatial economic models will be applied to build up relevant solutions. Calculated with this approach output could be useful to expect decrease in agricultural output in the region. It will enable to shape effective agricultural policy to know how to balance food supply and demand through appropriate managing with stored food raw material and/or import/export policies. Used precipitation-yields dependencies method let verify earlier used methodology through comparison of obtained solutions concerning forecasted yields and closed to it uncertainty analysis.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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MA @ admin @ |
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5090 |
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Van den Pol-van Dasselaar, A.; Evers, A.; De Haan, M. |
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Title |
Modelling emissions of greenhouse gases from dairy farms in the Netherlands using DairyWise |
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Conference Article |
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2014 |
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The DairyWise model (Schils et al., 2007) is an empirical model that simulates technical, environmental, and financial processes on a dairy farm. The central component is the FeedSupply model that balances the herd requirements, as generated by the DairyHerd model, and the supply of home-grown feeds, as generated by the crop models for grassland and silage maize. The GrassGrowth model predicts the daily rate of DM accumulation of grass, including several feed quality parameters. Depending on (daily) grazing, the amount of grass silage is calculated which also leads to the purchase (or sale) of roughage. The final output is a farm plan describing cattle performance, crop yield, grazing, feeding, and nutrient flows and the consequences on the environment and economy. The capabilities of DairyWise will be illustrated at the MACSUR meeting in Sassari with results of dairy farming in the Netherlands: farm characteristics, economics, NPK balances and greenhouse gas emissions. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5107 |
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Sandars, D.; Audsley, E.; Holman, I. |
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Predicting the optimum land use at any location for any future scenario (CLIMSAVE/IMPRESSIONS) |
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2014 |
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Given any socio-, techno-, economic scenario and location specific soil and climate scenario, the farm model predicts the most profitable land use at that location. This model is encapsulated within a Europe-wide interactive interface, to allow adaptation and mitigation options to be explored by any user. With 5 climate models and 19 parameters, the user can study the sensitivity of the results to the chosen scenario settings. A scenario’s land use can be classified as intensive arable, intensive grassland, extensive grassland, forestry, or abandoned depending on potential profitability. |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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Call Number |
MA @ admin @ |
Serial |
5113 |
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Author |
Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. |
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Title |
Environmental impacts of grassland management and livestock production |
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Conference Article |
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2014 |
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The potential of grasslands to sequester carbon and provide feed for livestock production depends on the one hand on climatic conditions but secondly on management and grazing pressure. Using a global vegetation model considering different management and grazing options, effects of livestock density on primary productivity can be assessed. It is expected that low animal densities enhance productivity whereas increasing grazing pressure may deteriorate grass plants. Thus, the optimal animal density depend on the specific primary production of the pasture and optimal grazing intensity. Using these optimal grass yields, the impacts of livestock production on resource use is assessed by applying the global land use model MAgPIE. This model integrates a detailed representation of the livestock sector and integrates socio-economic regional information with spatially explicit biophysical data. With scenario analysis we analyze the impact of livestock production on future deforestation and land use. Our results indicate that the reduction of animal derived calory demand has a huge potential to spare land for nature and reduce deforestation. On the supply side, feeding efficiency gains can help to decrease demand for land and overall biomass requirements. |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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no |
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Call Number |
MA @ admin @ |
Serial |
5078 |
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Author |
Özkan, Ṣ.; Bonesmo, H.; Østerås, O.; Harstad, O.M. |
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Title |
Effect of Increased Somatic Cell Count and Replacement Rate on Greenhouse Gas Emissions in Norwegian Dairy Herds |
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Conference Article |
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Year |
2014 |
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Dairy sector contributes around 4% of global greenhouse gas (GHG) emissions, of which 2/3 and 1/3 are attributed to milk and meat production, respectively. The main GHGs released from dairy farms are methane, nitrous oxide and carbon dioxide. The increased trend in emissions has stimulated research evaluating alternative mitigation options. Much of the work to date has focused on animal breeding, dietary factors and rumen manipulation. There have been little studies assessing the impact of secondary factors such as animal health on emissions at farm level. Production losses associated with udder health are significant. Somatic cell count (SCC) is an indicator on udder health. In Norway, around 45, 60 and 70% of cows in a dairy herd at first, second and third lactation are expected to have SCC of 50,000 cells/ml and above. Another indirect factor is replacement rate. Increasing the replacement rate due to health disorders, infertility and reduced milk yield is likely to increase the total farm emissions if the milking heifer replacements are kept in the herd. In this study, the impact of elevated SCC (200,000 cells/ml and above) and replacement rate on farm GHG emissions was evaluated. HolosNor, a farm scale model adapting IPCC methodology was used to estimate net farm GHG emissions. Preliminary results indicate an increasing trend in emissions (per kg milk and meat) as the SCC increases. Results suggest that animal health should be considered as an indirect mitigation strategy; however, further studies are required to enable comparisons of different farming systems. |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Notes |
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Approved |
no |
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Call Number |
MA @ admin @ |
Serial |
5075 |
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