toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Schauberger, B.; Rolinski, S.; Müller, C. doi  openurl
  Title (down) A network-based approach for semi-quantitative knowledge mining and its application to yield variability Type Journal Article
  Year 2016 Publication Environmental Research Letters Abbreviated Journal Environ. Res. Lett.  
  Volume 11 Issue 12 Pages 123001  
  Keywords yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2  
  Abstract Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.  
  Address 2017-04-07  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1748-9326 ISBN Medium Review  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4942  
Permanent link to this record
 

 
Author Gutierrez, L.; Piras, F.; Roggero, P.P. url  doi
openurl 
  Title (down) A global vector autoregression model for the analysis of wheat export prices Type Journal Article
  Year 2015 Publication American Journal of Agricultural Economics Abbreviated Journal American Journal of Agricultural Economics  
  Volume 97 Issue 5 Pages 1494-1511  
  Keywords Global dynamic models; price analysis; wheat market; lagged dependent-variables; commodity-markets; error-correction; food-prices; unit-root; regressors; tests; cointegration; dynamics; time  
  Abstract Food commodity price fluctuations have an important impact on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, and there is an urgent need for appropriate policy responses. Perhaps new approaches are needed to better understand international spill-overs, the feedback between the real and the financial sectors, as well as the link between food and energy prices. In this article, we present the results from a new worldwide dynamic model that provides the short and long-run impulse responses of the international wheat price to various real and financial shocks.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0002-9092 1467-8276 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4658  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: