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Ebrahimi, E.; Manschadi, A.M.; Neugschwandtner, R.W.; Eitzinger, J.; Thaler, S.; Kaul, H.-P. |
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Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria |
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Journal Article |
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2016 |
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Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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154 |
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07 |
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1153-1170 |
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Climate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice. |
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0021-8596 |
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TradeM |
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MA @ admin @ |
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4723 |
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Marton, T. |
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Assessing the impact of agro-climatic factors and farm characteristics on the yield variation of the Norwegian fruit sector |
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Report |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-5 |
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Main drivers of ag. yields:–Technology–R&D (new hybrids etc.)–Weather–Etc.•Common sense and anecdotal observations (remember the Tromsø presentation) revealed extreme events tended to impact wide geographic areas•This was called the «systemic» nature of agriculture No semi-aggregation farm-level•Not the boring corn, maize, wheat fruits•No OLS-like Pearson correlation or functional form approach for conditioning spatial correlations on weather SDM•Finally, if we are smart enough to set the explanatory proxies in a meaningful way presumably we can make the distinction between the effects of, say draught and extreme heat.•And much more in policy relevance |
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MA @ admin @ |
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4857 |
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Savary, S.; Jouanin, C.; Félix, I.; Gourdain, E.; Piraux, F.; Brun, F.; Willocquet, L. |
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Assessing plant health in a network of experiments on hardy winter wheat varieties in France: patterns of disease-climate associations |
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2016 |
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European Journal of Plant Pathology |
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Eur. J. Plant Pathol. |
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146 |
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741-755 |
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Puccinia triticina; Puccinia striiformis; Fusarium graminearum; Fusarium culmorum; Fusarium avenaceum; Blumeria graminis; Zymoseptoria tritici; Categorical data; Risk factor; Multiple pathosystem; Correspondence analysis; Logistic regression |
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A data set generated by a multi-year (2003–2010) and multi-site network of experiments on winter wheat varieties grown at different levels of crop management is analysed in order to assess the importance of climate on the variability of wheat health. Wheat health is represented by the multiple pathosystem involving five components: leaf rust, yellow rust, fusarium head blight, powdery mildew, and septoria tritici blotch. An overall framework of associations between multiple diseases and climate variables is developed. This framework involves disease levels in a binary form (i.e. epidemic vs. non-epidemic) and synthesis variables accounting for climate over spring and early summer. The multiple disease-climate pattern of associations of this framework conforms to disease-specific knowledge of climate effects on the components of the pathosystem. It also concurs with a (climate-based) risk factor approach to wheat diseases. This report emphasizes the value of large scale data in crop health assessment and the usefulness of a risk factor approach for both tactical and strategic decisions for crop health management. |
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0929-1873 1573-8469 |
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CropM |
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CropMwp;wos; ftnot_macsur; |
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MA @ admin @ |
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4755 |
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Mas, K.; Pardo, G.; Galán, E.; del Prado, A. |
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Assessing dairy farm sustainability using whole-farm modelling and life cycle analysis |
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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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259-260 |
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2040-4700 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4863 |
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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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