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Author Rusu, T.; Moraru, P.I. url  openurl
  Title Impact of climate change on crop land and technological recommendations for the main crops in Transylvanian Plain, Romania Type Journal Article
  Year 2015 Publication Romanian Agricultural Research Abbreviated Journal Romanian Agricultural Research  
  Volume 32 Issue Pages 103-111  
  Keywords climate change monitoring; temperature regimes; soil moisture; adaptation technologies; transylvanian plain; agriculture; france; precipitation; circulation; adaptation; models  
  Abstract The Transylvanian Plain (TP) is an important agricultural production area of Romania that is included among the areas with the lowest potential of adapting to climate changes in Europe. Thermal and hydric regime monitoring is necessary to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data regarding ground temperature at 3 depths (10, 30, 50 cm), humidity at a depth of 10 cm, air temperature (at 1 m) and precipitation. For agricultural crops, the periods of drought and extreme temperatures require specific measures of adaptation to climate changes. During the growing season of crops in the spring (April – October) in the south-eastern, southern, and eastern escarpments, precipitation decreased by 43.8 mm, the air temperature increased by 0.37 degrees C, and the ground temperature increased by 1.91 degrees C at a depth of 10 cm, 2.22 degrees C at a depth of 20 cm and 2.43 degrees C at a depth of 30 cm compared with values recorded for the northern, north-western or western escarpments. Water requirements were ensured within an optimal time frame for 58.8-62.1% of the spring row crop growth period, with irrigation being necessary to guarantee the optimum production potential. The biologically active temperature recorded in the TP demonstrates the need to renew the division of the crop areas reported in the literature.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1222-4227 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4650  
Permanent link to this record
 

 
Author Ramirez-Villegas, J.; Watson, J.; Challinor, A.J. url  doi
openurl 
  Title Identifying traits for genotypic adaptation using crop models Type Journal Article
  Year 2015 Publication Journal of Experimental Botany Abbreviated Journal J. Experim. Bot.  
  Volume 66 Issue 12 Pages 3451-3462  
  Keywords Adaptation, Physiological/*genetics; Crops, Agricultural/*genetics; Environment; Genotype; *Models, Theoretical; *Quantitative Trait, Heritable; Climate change; crop models; genotypic adaptation; ideotypes; impacts  
  Abstract Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0022-0957 1460-2431 ISBN Medium Review  
  Area Expedition Conference  
  Notes (up) CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4645  
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Author Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F. url  doi
openurl 
  Title Bayesian methods for predicting LAI and soil water content Type Journal Article
  Year 2014 Publication Precision Agriculture Abbreviated Journal Precision Agric.  
  Volume 15 Issue 2 Pages 184-201  
  Keywords crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state  
  Abstract LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1385-2256 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4629  
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Author Refsgaard, J.C.; Arnbjerg-Nielsen, K.; Drews, M.; Halsnaes, K.; Jeppesen, E.; Madsen, H.; Markandya, A.; Olesen, J.E.; Porter, J.R.; Christensen, J.H. url  doi
openurl 
  Title The role of uncertainty in climate change adaptation strategies – a Danish water management example Type Journal Article
  Year 2013 Publication Mitigation and Adaptation Strategies for Global Change Abbreviated Journal Mitig. Adapt. Strateg. Glob. Change  
  Volume 18 Issue 3 Pages 337-359  
  Keywords Climate change; Adaptation; Uncertainty; Risk; Water sectors; Multi-disciplinary; change impacts; global change; winter-wheat; models; scenarios; ensembles; denmark; vulnerability; community; knowledge  
  Abstract We propose a generic framework to characterize climate change adaptation uncertainty according to three dimensions: level, source and nature. Our framework is different, and in this respect more comprehensive, than the present UN Intergovernmental Panel on Climate Change (IPCC) approach and could be used to address concerns that the IPCC approach is oversimplified. We have studied the role of uncertainty in climate change adaptation planning using examples from four Danish water related sectors. The dominating sources of uncertainty differ greatly among issues; most uncertainties on impacts are epistemic (reducible) by nature but uncertainties on adaptation measures are complex, with ambiguity often being added to impact uncertainties. Strategies to deal with uncertainty in climate change adaptation should reflect the nature of the uncertainty sources and how they interact with risk level and decision making: (i) epistemic uncertainties can be reduced by gaining more knowledge; (ii) uncertainties related to ambiguity can be reduced by dialogue and knowledge sharing between the different stakeholders; and (iii) aleatory uncertainty is, by its nature, non-reducible. The uncertainty cascade includes many sources and their propagation through technical and socio-economic models may add substantially to prediction uncertainties, but they may also cancel each other. Thus, even large uncertainties may have small consequences for decision making, because multiple sources of information provide sufficient knowledge to justify action in climate change adaptation.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1381-2386 1573-1596 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4613  
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Author Rötter, R.P.; Höhn, J.G.; Fronzek, S. doi  openurl
  Title Projections of climate change impacts on crop production – a global and a Nordic perspective Type Journal Article
  Year 2012 Publication Acta Agriculturae Scandinavica, Section A – Animal Science Abbreviated Journal Acta Agriculturae Scandinavica, Section A – Animal Science  
  Volume 62 Issue Pages 166-180  
  Keywords climate change; impact projection; food production; uncertainty; crop simulation model; food security; integrated assessment; winter-wheat; scenarios; agriculture; adaptation; temperature; models; yield; scale  
  Abstract Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few known unknowns’ affecting crop impact projections.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0906-4702, 1651-1972 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4591  
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