| Records |
| Author |
Sinabell, F.; Brouwer, F. |
| Title |
TradeM synergies with AGMIP |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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Issue |
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Pages |
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Abstract  |
The AgMIP network started activities on intercomparison of global economic modelling at a time when MACSUR was not yet established. The achievements made so far are highly relevant for TradeM and several partners (Wageningen University, IIASA, PIK, University Bonn) are in both networks. The MOU between MACSUR and AGMIP established formal links between the two projects and TradeM is activley working on establishing further collaboration. Preparations are underway to bring together researchers of both networks in a joint workshop to be held in Austria, September 2014. The topic will be on issues related to linking local and regional models with global ones. TradeM will actively contribute to the workshop and will host a one-day side-event. |
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Original Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
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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 |
| Call Number |
MA @ admin @ |
Serial |
5136 |
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| Author |
Yin, X.G.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.H.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Rotter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.J.; Olesen, J.E.; Yin, X.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Roetter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.-J.; Olesen, J.E. |
| Title |
Performance of process-based models for simulation of grain N in crop rotations across Europe |
Type |
Journal Article |
| Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
| Volume |
154 |
Issue |
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Pages |
63-77 |
| Keywords |
Calibration, Crop model, Crop rotation, Grain N content, Model evaluation, Model initialization; Climate-Change; Winter-Wheat; Nitrogen-Fertilization; Agroecosystem; Models; Multimodel Ensembles; Yield Response; Use Efficiency; Soil-Moisture; Oilseed Rape; Elevated Co2 |
| Abstract |
The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordewn vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena saliva L.), winter rye (Secale cereale L.), pea (Piswn sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism. |
| Address |
2017-06-12 |
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English |
Summary Language |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0308-521x |
ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4963 |
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| Author |
Van Oosten, M.J.; Sharkhuu, A.; Batelli, G.; Bressan, R.A.; Maggio, A. |
| Title |
The Arabidopsis thaliana mutant air1 implicates SOS3 in the regulation of anthocyanins under salt stress |
Type |
Journal Article |
| Year |
2013 |
Publication |
Plant Molecular Biology |
Abbreviated Journal |
Plant Mol. Biol. |
| Volume |
83 |
Issue |
4-5 |
Pages |
405-415 |
| Keywords |
Anthocyanins/analysis/*metabolism; Arabidopsis/drug effects/*genetics/physiology/radiation effects; Arabidopsis Proteins/*genetics/metabolism; Basic-Leucine Zipper Transcription Factors/*genetics/metabolism; Flavonoids/metabolism; *Gene Expression Regulation, Plant; Light; Mutagenesis, Insertional; Phenotype; Plant Roots/drug effects/genetics/physiology/radiation effects; Plant Shoots/drug effects/genetics/physiology/radiation effects; Real-Time Polymerase Chain Reaction; Sodium Chloride/pharmacology; Stress, Physiological |
| Abstract |
The accumulation of anthocyanins in plants exposed to salt stress has been largely documented. However, the functional link and regulatory components underlying the biosynthesis of these molecules during exposure to stress are largely unknown. In a screen of second site suppressors of the salt overly sensitive3-1 (sos3-1) mutant, we isolated the anthocyanin-impaired-response-1 (air1) mutant. air1 is unable to accumulate anthocyanins under salt stress, a key phenotype of sos3-1 under high NaCl levels (120 mM). The air1 mutant showed a defect in anthocyanin production in response to salt stress but not to other stresses such as high light, low phosphorous, high temperature or drought stress. This specificity indicated that air1 mutation did not affect anthocyanin biosynthesis but rather its regulation in response to salt stress. Analysis of this mutant revealed a T-DNA insertion at the first exon of an Arabidopsis thaliana gene encoding for a basic region-leucine zipper transcription factor. air1 mutants displayed higher survival rates compared to wild-type in oxidative stress conditions, and presented an altered expression of anthocyanin biosynthetic genes such as F3H, F3’H and LDOX in salt stress conditions. The results presented here indicate that AIR1 is involved in the regulation of various steps of the flavonoid and anthocyanin accumulation pathways and is itself regulated by the salt-stress response signalling machinery. The discovery and characterization of AIR1 opens avenues to dissect the connections between abiotic stress and accumulation of antioxidants in the form of flavonoids and anthocyanins. |
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English |
Summary Language |
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0167-4412 1573-5028 |
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Article |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4616 |
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| Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
| Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
Type |
Journal Article |
| Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
| Volume |
81 |
Issue |
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Pages |
236-249 |
| Keywords |
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 |
| Abstract |
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. |
| Address |
2016-10-31 |
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English |
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0040-1625 |
ISBN |
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Article |
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CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4789 |
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| Author |
Vilvert, E.; Lana, M.; Zander, P.; Sieber, S. |
| Title |
Multi-model approach for assessing the sunflower food value chain in Tanzania |
Type |
Journal Article |
| Year |
2018 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
| Volume |
159 |
Issue |
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Pages |
103-110 |
| Keywords |
Sunflower; Food value chain; Modelling; Tanzania; Food security; Systems Simulation; Crop Model; Agricultural Systems; Farming Systems; Yield Response; Land-Use; Water; Aquacrop; Security; Stics |
| Abstract |
Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC. |
| Address |
2018-01-25 |
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English |
Summary Language |
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Original Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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0308-521x |
ISBN |
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Conference |
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| Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5187 |
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