Spatial frameworks for robust estimation of yield gaps
- Autores
- Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; Grassini, Patricio
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.
Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados Unidos
Fil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países Bajos
Fil: van Loon, Marloes P.. University of Agriculture Wageningen; Países Bajos
Fil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados Unidos - Materia
- NO KEYWORDS
- Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/168531
Ver los metadatos del registro completo
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Spatial frameworks for robust estimation of yield gapsRattalino Edreira, Juan IgnacioAndrade, José FranciscoCassman, Kenneth G.van Ittersum, Martin K.van Loon, Marloes P.Grassini, PatricioNO KEYWORDShttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados UnidosFil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países BajosFil: van Loon, Marloes P.. University of Agriculture Wageningen; Países BajosFil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados UnidosSpringer Nature2021-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/168531Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-7792662-1355CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s43016-021-00365-yinfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s43016-021-00365-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:34:00Zoai:ri.conicet.gov.ar:11336/168531instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:34:00.544CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Spatial frameworks for robust estimation of yield gaps |
title |
Spatial frameworks for robust estimation of yield gaps |
spellingShingle |
Spatial frameworks for robust estimation of yield gaps Rattalino Edreira, Juan Ignacio NO KEYWORDS |
title_short |
Spatial frameworks for robust estimation of yield gaps |
title_full |
Spatial frameworks for robust estimation of yield gaps |
title_fullStr |
Spatial frameworks for robust estimation of yield gaps |
title_full_unstemmed |
Spatial frameworks for robust estimation of yield gaps |
title_sort |
Spatial frameworks for robust estimation of yield gaps |
dc.creator.none.fl_str_mv |
Rattalino Edreira, Juan Ignacio Andrade, José Francisco Cassman, Kenneth G. van Ittersum, Martin K. van Loon, Marloes P. Grassini, Patricio |
author |
Rattalino Edreira, Juan Ignacio |
author_facet |
Rattalino Edreira, Juan Ignacio Andrade, José Francisco Cassman, Kenneth G. van Ittersum, Martin K. van Loon, Marloes P. Grassini, Patricio |
author_role |
author |
author2 |
Andrade, José Francisco Cassman, Kenneth G. van Ittersum, Martin K. van Loon, Marloes P. Grassini, Patricio |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
NO KEYWORDS |
topic |
NO KEYWORDS |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.1 https://purl.org/becyt/ford/4 |
dc.description.none.fl_txt_mv |
Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches. Fil: Rattalino Edreira, Juan Ignacio. Universidad de Nebraska - Lincoln; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Andrade, José Francisco. Universidad de Nebraska - Lincoln; Estados Unidos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cassman, Kenneth G.. Universidad de Nebraska - Lincoln; Estados Unidos Fil: van Ittersum, Martin K.. University of Agriculture Wageningen; Países Bajos Fil: van Loon, Marloes P.. University of Agriculture Wageningen; Países Bajos Fil: Grassini, Patricio. Universidad de Nebraska - Lincoln; Estados Unidos |
description |
Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/168531 Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-779 2662-1355 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/168531 |
identifier_str_mv |
Rattalino Edreira, Juan Ignacio; Andrade, José Francisco; Cassman, Kenneth G.; van Ittersum, Martin K.; van Loon, Marloes P.; et al.; Spatial frameworks for robust estimation of yield gaps; Springer Nature; Nature Food; 2; 10; 10-2021; 773-779 2662-1355 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1038/s43016-021-00365-y info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s43016-021-00365-y |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Springer Nature |
publisher.none.fl_str_mv |
Springer Nature |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.070432 |