PAPER PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Use of spatial analyses for global characterization of wheat-based production systems

作者: D. P. HODSON , J. W. WHITE

DOI: 10.1017/S0021859607006855

关键词:

摘要: CIMMYT (International Maize and Wheat Improvement Centre) other research groups within the Consultative Group for International Agricultural Research (CGIAR) have made major contributions to agricultural development, e.g. underpinning ‘green revolution’, but it is unlikely they will continue making such far-reaching without ability collect, analyse assimilate large amounts of spatially orientated agronomic climatic data. Increasingly, application modern tools technologies are crucial elements in order support enhance effectiveness international research. Bread durum wheats (Triticum aestivum Triticum durum) occupy an estimated 200 million ha globally, grown from sea level over 3500 m asl, equator latitudes above 60 ° N Canada, Europe, Asia. For organizations like CIMMYT, which seek improve wheat production developing world, understanding geographic context priority setting, promoting collaboration, targeting germplasm or management practices specific environments. Increasingly important forecasting how environments, their associated biotic abiotic stress patterns, shift with changing climate patterns. There also a growing need classify environments by combining biophysical criteria socio-economic factors. Geospatial technologies, especially information systems (GIS), playing role each these areas, spatial analysis provides unique insights. Use GIS characterize described, drawing examples at CIMMYT. Since 1980s, programme has classified regions into mega-environments (MEs) based on climatic, edaphic, constraints. Advances disaggregated datasets allow MEs be characterized mapped much more quantitative manner. Parallel advances improving characterizations actual (v. potential) distribution crops, including wheat. The combination improved crop data key high resolutions permits exploring scenarios disease epidemics, as illustrated stem rust race Ug99. Availability describing future conditions may provide insights potential changes coming decades. pressing advance beyond static definitions incorporate temporal aspects define locations terms probability frequency occurrence different environment types. Increased availability near real-time daily weather derived remote sensing should further characterization well permit regional-scale modelling dynamic processes progression water status.

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