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1000 Titel
  • Yield gap analysis of cereals in Europe - Supported by local knowledge
1000 Autor/in
  1. Schils, René |
  2. Kersebaum, Kurt Christian |
  3. Nieróbca, Anna |
  4. Żyłowska, Katarzyna |
  5. Minguez, Inés |
  6. Castaneda Vera, Alba |
  7. Olesen, Jørgen E. |
  8. Sharif, Behzad |
  9. Boogaard, Hendrik |
  10. de Groot, Hugo |
  11. van Bussel, Lenny |
  12. Wolf, Joost |
  13. Rijk, Bert |
  14. van Ittersum, Martin |
1000 Erscheinungsjahr 2015
1000 LeibnizOpen
1000 Publikationstyp
  1. Kongressschrift |
  2. Artikel |
1000 Online veröffentlicht
  • 2015-05-11
1000 Erschienen in
1000 Quellenangabe
  • 5:SP5-57
1000 FRL-Sammlung
1000 Übergeordneter Kongress
1000 Copyrightjahr
  • 2015
1000 Verlagsversion
  • https://ojs.macsur.eu/index.php/Reports/article/view/SP5-57 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The increasing demand for food requires a sustainable intensification of crop production in underperforming areas. Many global and local studies have addressed yield gaps, i.e. the difference between potential or water-limited yields and actual yields. Global studies generally rely on generic models combined with a grid-based approach. Although using a consistent method, it has been shown they are not suitable for local yield gap assessment. Local studies generally exploit knowledge of location-specific conditions and management, but are less comparable across locations due to different methods. To overcome these inconsistencies, the Global Yield Gap Atlas (GYGA, www.yieldgap.org) proposes a consistent bottom-up approach to estimate yield gaps. This paper outlines the implementation of GYGA for estimating yield gaps of cereals across Europe. For each country, climate zones are identified which represent the major growing areas. Within these climate zones, weather stations are selected with >=15 years of daily data. For dominant soil types within a buffer zone around the weather stations, the potential and water-limited yields are simulated with a crop model, using local knowledge on management. Actual yields are derived from sub-national statistics. Yield gaps are scaled up from buffer zones to climate zones and countries. We will present the first results for selected regions in Europe, and discuss methodological issues on location specific weather and upscaling from weather station buffer zones to climate zones and countries. Furthermore we will look ahead at the implementation of the yield gap cross cutting activity (XC9) in MACSUR-2.
1000 Fächerklassifikation (DDC)
1000 DOI 10.4126/FRL01-006413710 |
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-2017-5268|https://orcid.org/0000-0002-3679-8427|https://frl.publisso.de/adhoc/creator/TmllcsOzYmNhLCBBbm5h|https://frl.publisso.de/adhoc/creator/xbt5xYJvd3NrYSwgS2F0YXJ6eW5h|https://frl.publisso.de/adhoc/creator/TWluZ3VleiwgSW7DqXM=|https://frl.publisso.de/adhoc/creator/Q2FzdGFuZWRhIFZlcmEsIEFsYmE=|https://orcid.org/0000-0002-6639-1273|https://frl.publisso.de/adhoc/creator/U2hhcmlmLCBCZWh6YWQ=|https://frl.publisso.de/adhoc/creator/Qm9vZ2FhcmQsIEhlbmRyaWs=|https://frl.publisso.de/adhoc/creator/ZGUgR3Jvb3QsIEh1Z28=|https://orcid.org/0000-0003-3801-9754|https://frl.publisso.de/adhoc/creator/V29sZiwgSm9vc3Q=|https://frl.publisso.de/adhoc/creator/UmlqaywgQmVydA==|https://orcid.org/0000-0001-8611-6781
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1000 Förderprogramm
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1000 Objektart article
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1000 @id frl:6413710.rdf
1000 Erstellt am 2019-04-02T13:50:07.938+0200
1000 Erstellt von 218
1000 beschreibt frl:6413710
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet Thu Jan 30 19:49:35 CET 2020
1000 Objekt bearb. Wed Jun 19 12:18:45 CEST 2019
1000 Vgl. frl:6413710
1000 Oai Id
  1. oai:frl.publisso.de:frl:6413710 |
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