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| Author |
Bojar, W.; Knopik, L.; Zarski, J. |
| Title |
Integrated assessment of business crop productivity and profitability for use in food supply forecasting |
Type |
Report |
| Year |
2014 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
Sp3-7 |
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| Abstract |
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 No Label |
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MA @ admin @ |
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2224 |
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| Author |
Bojar, W.; Knopik, L.; Żarski, J. |
| Title |
Integrated assessment of business crop productivity and profitability for use in food supply forecasting |
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Conference Article |
| Year |
2014 |
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Abbreviated Journal |
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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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MA @ admin @ |
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5090 |
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Bojar, W.; Knopik, L.; Zarski, J. |
| Title |
Application of Markov chains approach for expecting extreme precipitation changes having impact on food supply |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-3 |
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This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label |
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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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MA @ admin @ |
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2193 |
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Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G. |
| Title |
Markov Chain as a Model of Daily Total Precipitation and a Prediction of Future Natural Events |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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Approved |
no |
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MA @ admin @ |
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4911 |
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Bojar, W.; Knopik, L.; Żarski, J.; Sławiński, C.; Baranowski, P.; Żarski, W. |
| Title |
Impact of extreme climate changes on the forecasted agriculture production |
Type |
Journal Article |
| Year |
2014 |
Publication |
Acta Agrophysica |
Abbreviated Journal |
Acta Agrophysica |
| Volume |
21 |
Issue |
4 |
Pages |
415-431 |
| Keywords |
agricultural economics; agriculture; climate change; crop production; integrating assessments |
| Abstract |
The paper presents general characteristics of resources and outputs of agriculture in the Kujawsko-Pomorskie and Lubelskie Regions, based on statistical databases and literature review. Some specific features of the regions, with special consideration for the predicted extreme climate changes, are also included. Next, some statistically significant dependencies between the climatic parameters and yields of selected important crops in the abovementioned regions were worked out on the basis of empirical survey conducted in the University of Technology and Life Sciences, Bydgoszcz, and the Institute of Agrophysics in Lublin. Creating an appropriate method of forecasting long series of ten days without precipitation was necessary to find the desired dependencies. Third, some efforts were taken to make integrated assessments of forecast agricultural outputs influenced by climate extreme phenomena on the basis of the yield-precipitation relations obtained and on the data coming from wide area model regional outputs such as prices of farmland and produce. |
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English |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4619 |
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