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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

Published on Apr 1, 2007in The Journal of Agricultural Science 1.33
· DOI :10.1017/s0021859607006855
D. P. Hodson1
Estimated H-index: 1
(CGIAR),
J. W. White1
Estimated H-index: 1
Cite
Abstract
SUMMARY CIMMYT (International Maize and Wheat Improvement Centre) and other research groups within the Consultative Group for International Agricultural Research (CGIAR) have made major contributions to agricultural development, e.g. underpinning the ‘ green revolution ’, but it is unlikely they will continue making such far-reaching contributions without the ability to collect, analyse and assimilate large amounts of spatially orientated agronomic and climatic data. Increasingly, application of modern tools and technologies are crucial elements in order to support and enhance the effectiveness of international agricultural research. Bread and durum wheats (Triticum aestivum and Triticum durum) occupy an estimated 200 million ha globally, are grown from sea level to over 3500 m asl, and from the equator to latitudes above 60x N in Canada, Europe, and Asia. For organizations like CIMMYT, which seek to improve wheat production in the developing world, understanding the geographic context of wheat production is crucial for priority setting, promoting collaboration, and targeting germplasm or management practices to specific environments. Increasingly important is forecasting how the environments, and their associated biotic and abiotic stress patterns, shift with changing climate patterns. There is also a growing need to classify production environments by combining biophysical criteria with socio-economic factors. Geospatial technologies, especially geographic information systems (GIS), are playing a role in each of these areas, and spatial analysis provides unique insights. Use of GIS to characterize wheat production environments is described, drawing from examples at CIMMYT. Since the 1980s, the CIMMYT wheat programme has classified production regions into mega-environments (MEs) based on climatic, edaphic, and biotic constraints. Advances in spatially disaggregated datasets and GIS tools allow MEs to be characterized and mapped in a much more quantitative manner. Parallel advances are improving characterizations of the actual (v. potential) distribution of major crops, including wheat. The combination of improved crop distribution data and key biophysical data at high spatial resolutions also permits exploring scenarios for disease epidemics, as illustrated for the stem rust race Ug99. Availability of spatial data describing future climate conditions may provide insights into potential changes in wheat production environments in the coming decades. There is a pressing need to advance beyond static definitions of environments and incorporate temporal aspects to define locations or regions in terms of probability or frequency of occurrence of different environment types. Increased availability of near real-time daily weather data derived from remote sensing should further improve characterization of environments, as well as permit regional-scale modelling of dynamic processes such as disease progression or crop water status.
  • References (23)
  • Citations (29)
Cite
References23
Newest
Published on Jan 1, 2006in Plant Disease 3.58
R. Wanyera15
Estimated H-index: 15
,
Miriam G. Kinyua5
Estimated H-index: 5
+ 1 AuthorsRavi P. Singh61
Estimated H-index: 61
Stem rust resistance in wheat cultivars with Sr31 has been effective and durable worldwide for more than 30 years. Isolates of Puccinia graminis f. sp. tritici with virulence to Sr31 were detected in Uganda in 1999 (1). During 2003 and 2004, a majority of current Kenyan cultivars and a large portion of CIMMYT wheat germplasm with gene Sr31 planted in Kenya were susceptible to stem rust. Six isolates collected during 2004 at different locations in Kenya were tested for virulence on the 16 North A...
Published on Dec 1, 2005in International Journal of Climatology 3.60
Robert J. Hijmans40
Estimated H-index: 40
(Museum of Vertebrate Zoology),
Susan E. Cameron9
Estimated H-index: 9
(UQ: University of Queensland)
+ 2 AuthorsAndy Jarvis35
Estimated H-index: 35
(CIAT: International Center for Tropical Agriculture)
We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpola...
Published on Oct 1, 2005in Food Policy 3.79
Mauricio R. Bellon28
Estimated H-index: 28
(CIMMYT: International Maize and Wheat Improvement Center),
David Hodson16
Estimated H-index: 16
(CIMMYT: International Maize and Wheat Improvement Center)
+ 3 AuthorsYinha Montoya1
Estimated H-index: 1
(CIMMYT: International Maize and Wheat Improvement Center)
Abstract We explore approaches for targeting agricultural research to benefit poor farmers. Using small area estimation methods and spatial analysis, we generated high-resolution poverty maps and combined them with geo-referenced biophysical data relevant to maize-based agriculture in Mexico. We used multivariate classification and cluster analysis to synthesize biophysical data relevant for crop performance with rural poverty data. Results show that the rural poor are concentrated in particular...
Published on Sep 1, 2005in Euphytica 1.53
Peter Setimela11
Estimated H-index: 11
(CIMMYT: International Maize and Wheat Improvement Center),
Z. Chitalu1
Estimated H-index: 1
+ 3 AuthorsMarianne Bänziger38
Estimated H-index: 38
(CIMMYT: International Maize and Wheat Improvement Center)
When evaluating genotypes, it is efficient and resourceful to identify similar testing sites and group them according to similarity. Grouping sites ensures that breeders choose as many variable sites as possible to capture the effects of genotype-by-environment (GE) interactions. In order to exploit these interactions and increase testing efficiency and variety selection, it is necessary to group similar environments or mega-environments. The present mega-environments in the Southern African Dev...
Published on Jan 1, 2005in Crop Science 1.64
Carlos M. Löffler4
Estimated H-index: 4
(DuPont Pioneer),
Jun Wei2
Estimated H-index: 2
(DuPont Pioneer)
+ 5 AuthorsMark E. Cooper109
Estimated H-index: 109
(DuPont Pioneer)
The effectiveness of a cultivar evaluation system largely depends on the genetic correlation between genotype performance in multienvironment trials (MET) and in the target population of environments (TPE). Previous classifications of maize (Zea mays L.) environments on the basis of climate and soil did not quantify their impact on the genetic correlations among environments. Consequently, plant breeders have favored classifications based on the similarity ofcultivar discrimination in trials. Ho...
Published on May 1, 2004in Current Opinion in Plant Biology 7.51
David J. Bergvinson20
Estimated H-index: 20
(CIMMYT: International Maize and Wheat Improvement Center),
Silverio García-Lara14
Estimated H-index: 14
(CIMMYT: International Maize and Wheat Improvement Center)
Insects and diseases devour or damage a fifth or more of stored food grains each year in many parts of the world. Modern breeding and genomics promise progress in characterizing the resistance to the pests responsible for these losses that is present in the vast and diverse gene pool of cereals, as well as advances in incorporating this resistance into productive and acceptable crop varieties. The impact of such varieties could be dramatic in developing countries, where grain infestations are mo...
Published on Mar 1, 2004in Global Biogeochemical Cycles 5.73
Billie Leff2
Estimated H-index: 2
(UW: University of Wisconsin-Madison),
Navin Ramankutty56
Estimated H-index: 56
(UW: University of Wisconsin-Madison),
Jonathan A. Foley11
Estimated H-index: 11
(UW: University of Wisconsin-Madison)
[1] Humans have transformed the surface of the planet through agricultural activities, and today, ∼12% of the land surface is used for cultivation and another 22% is used for pastures and rangelands. In this paper, we have synthesized satellite-derived land cover data and agricultural census data to produce global data sets of the distribution of 18 major crops across the world. The resulting data are representative of the early 1990s, have a spatial resolution of 5 min. (∼10 km), and describe t...
Published on Jan 1, 2004
Thomas, Christopher, Aug.1
Estimated H-index: 1
,
Milton Ospina1
Estimated H-index: 1
Measuring Up: The Business Case for GIS offers case studies about companies and government agencies that have implemented GIS solutions to meet business goals and how their successes with this technology measure up in: Saving money and time; Increasing efficiency, accuracy, productivity, communication and collaboration; Generating revenue; Supporting decision making; Aiding budget development; Building information bases; Managing resources; Measuring Up presents 75 articles from 22 business sect...
Published on Jan 1, 2004
Ravi P. Singh1
Estimated H-index: 1
(CGIAR),
H. M. William7
Estimated H-index: 7
(CIMMYT: International Maize and Wheat Improvement Center)
+ 1 AuthorsGarry M. Rosewarne9
Estimated H-index: 9
(CIMMYT: International Maize and Wheat Improvement Center)
The rust diseases of wheat pose a constant threat to sustainable wheat production and thus food security in Asia. If susceptible wheat cultivars are grown, approximately 60 and 40 million hectares could experience periodic epidemics of leaf rust and stripe rust, respectively. Avoiding major rust epidemics in the region is a complex challenge, given that fewer cultivars are being cultivated over large areas, that several of those cultivars are protected by the same resistance genes, and that ther...
Published on Jan 1, 2004
Liangzhi You28
Estimated H-index: 28
,
Stanley Wood1
Estimated H-index: 1
While agricultural production statistics are reported on a geopolitical – often national - basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agro-ecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach tabular crop production statis...
Cited By29
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Published on Apr 1, 2019in Scientia Agricola 1.43
Marcin Studnicki4
Estimated H-index: 4
(Warsaw University of Life Sciences),
Adriana Derejko2
Estimated H-index: 2
(Warsaw University of Life Sciences)
+ 1 AuthorsMichał Kosma1
Estimated H-index: 1
(Warsaw University of Life Sciences)
Published on Apr 1, 2019in Field Crops Research 3.87
Frédéric Baudron15
Estimated H-index: 15
(CIMMYT: International Maize and Wheat Improvement Center),
Alain Ndoli (CIMMYT: International Maize and Wheat Improvement Center)+ 1 AuthorsJoão Vasco Silva5
Estimated H-index: 5
(WUR: Wageningen University and Research Centre)
Abstract As wheat demand is increasing in sub-Saharan Africa (SSA), domestic production is being encouraged. The potential to increase the productivity and profitability of wheat appears large in the region, but little is known about the concrete interventions needed to meet that potential. In this study, we selected a site in Northern Rwanda (representative of the cool humid climatic zone which accounts for most of the spring wheat production of SSA) and analysed the determinants of wheat produ...
Published on Mar 1, 2019in Agricultural and Forest Meteorology 4.19
Kirsten Paff1
Estimated H-index: 1
(UF: University of Florida),
Senthold Asseng42
Estimated H-index: 42
(UF: University of Florida)
Abstract Tef and wheat are staple grains in Ethiopia and are an important part of Ethiopian food security. The DSSAT NWheat and DSSAT Tef models were used to examine the effects of nitrogen fertilizer, planting date, and atmospheric CO 2 on tef and wheat grain yields across four locations in Ethiopia and a 30-year time period. Observed wheat yields were consistently higher than observed tef yields, but the models showed that tef could outproduce wheat in some low yielding scenarios. Wheat yields...
Published on Jan 1, 2019in European Journal of Agronomy 3.38
Alireza Houshmandfar (CSIRO: Commonwealth Scientific and Industrial Research Organisation), Greg J. Rebetzke31
Estimated H-index: 31
(CSIRO: Commonwealth Scientific and Industrial Research Organisation)
+ 1 AuthorsMichael Tausz1
Estimated H-index: 1
(University of Birmingham)
Abstract Grain yield responsiveness to water supply was evaluated in spring wheat ( Triticum aestivum L.) near-isogenic lines (NILs) for presence of the reduced-tillering ‘ tin ’ ( t iller in hibition) gene using boundary-line analysis. Data were collected from multiple seasons at Managed Environment Facilities (MEFs; field experimental facilities to control and target water supply) at three locations across the Australian wheatbelt. The minimum water required to obtain a measurable yield was le...
Published on Nov 1, 2018in Agricultural and Forest Meteorology 4.19
Damien Beillouin1
Estimated H-index: 1
(Université Paris-Saclay),
Marie-Helene Jeuffroy25
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(Université Paris-Saclay),
Arnaud Gauffreteau2
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(Université Paris-Saclay)
Abstract The adaptation of genotypes to environmental conditions is one of the main levers for maintaining an acceptable level of production, both in terms of quality and quantity. To breed suitable genotypes and for the farmers to choose the most adapted one to his farm conditions, the factors affecting production must be precisely characterized. Here, we analyzed the impacts of the climatic factors on winter barley yield in 35 departements (French geographic units) over 25 years, by partial le...
Published on Nov 1, 2017in Environmental Research Letters 6.19
Jesse Tack9
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(KSU: Kansas State University),
Andrew P. Barkley15
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(KSU: Kansas State University),
Nathan P. Hendricks8
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(KSU: Kansas State University)
Temperature increases due to climate change are expected to cause substantial reductions in global wheat yields. However, uncertainty remains regarding the potential role for irrigation as an adaptation strategy to offset heat impacts. Here we utilize over 7000 observations spanning eleven Kansas field-trial locations, 180 varieties, and 29 years to show that irrigation significantly reduces the negative impact of warming temperatures on winter wheat yields. Dryland wheat yields are estimated to...
Published on Nov 1, 2017in Earth System Dynamics Discussions 4.35
Camilla Mathison9
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Chetan Deva3
Estimated H-index: 3
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+ 1 AuthorsAndrew J. Challinor41
Estimated H-index: 41
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Sowing and harvest dates are a significant source of uncertainty within crop models, especially for regions where high-resolution data are unavailable or, as is the case in future climate runs, where no data are available at all. Global datasets are not always able to distinguish when wheat is grown in tropical and subtropical regions, and they are also often coarse in resolution. South Asia is one such region where large spatial variation means higher-resolution datasets are needed, together wi...
Published on Jan 1, 2017in Agronomy Journal 1.80
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Jeffrey W. White40
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Published on Jan 1, 2017in Crop Science 1.64
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José Crossa60
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+ 6 AuthorsRavi P. Singh61
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Published on Jan 1, 2017in Agronomy Journal 1.80
Xingming Zhang4
Estimated H-index: 4
(BNU: Beijing Normal University),
Hao Guo2
Estimated H-index: 2
(BNU: Beijing Normal University)
+ 4 AuthorsJing’ai Wang2
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(BNU: Beijing Normal University)