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Sandars, L.; Audsley, E. |
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Title |
Optimal Land-use Future Scenarios Nordic Area |
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2014 |
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Trade M |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, Hurdalsjøen, Norway, 2014-11-25 to 2014-11-27 |
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MA @ admin @ |
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2785 |
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Bressan, R.A.; Park, H.C.; Orsini, F.; Oh, D.-ha; Dassanayake, M.; Inan, G.; Yun, D.-J.; Bohnert, H.J.; Maggio, A. |
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Title |
Biotechnology for mechanisms that counteract salt stress in extremophile species: a genome-based view |
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Journal Article |
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2013 |
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Plant Biotechnology Reports |
Abbreviated Journal |
Plant Biotechnol. Rep. |
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7 |
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1 |
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27-37 |
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Thellungiella; Extremophile species; Genome sequences; Abiotic stress; protection; Biotechnology potential; arabidopsis-thaliana; thellungiella-halophila; salinity stress; whole-genome; gene-expression; water-content; model system; tolerance; halophytes |
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Molecular genetics has confirmed older research and generated new insights into the ways how plants deal with adverse conditions. This body of research is now being used to interpret stress behavior of plants in new ways, and to add results from most recent genomics-based studies. The new knowledge now includes genome sequences of species that show extreme abiotic stress tolerances, which enables new strategies for applications through either molecular breeding or transgenic engineering. We will highlight some physiological features of the extremophile lifestyle, outline emerging features about halophytism based on genomics, and discuss conclusions about underlying mechanisms. |
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1863-5466 1863-5474 |
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Review |
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CropM |
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MA @ admin @ |
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4483 |
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Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
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Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
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Journal Article |
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2014 |
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Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
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81 |
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236-249 |
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Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
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2016-10-31 |
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0040-1625 |
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CropM |
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MA @ admin @ |
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4789 |
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Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Müller, C. |
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Title |
Forecasting technological change in agriculture—An endogenous implementation in a global land use model |
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Journal Article |
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Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
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81 |
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236-249 |
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Technological change; Land use; Agricultural productivity; Land use intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
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► Endogenous technological change in an economic land use model ► Estimation of yield elasticity with respect to investments in technological change ► Projections of future agricultural productivity rates ► Validation with observed data and historic trends ► Trade-off between required technological change and forest protection objectives Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. |
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0040-1625 |
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CropM |
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MA @ admin @ |
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4518 |
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Author |
Dumont, B.; Basso, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium |
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Journal Article |
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2016 |
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Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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79 |
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184-196 |
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Tactical nitrogen management; Climatic variability; Probability risk; assessment; LARS-WG; Crop model; STICS; stics crop model; generic model; simulation; yield; water; soil; fertilizer; behavior; climate; maize |
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Future progress in wheat yield will rely on identifying genotypes & management practices better adapted to the fluctuating environment Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic & environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 & 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers. (C) 2016 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4749 |
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