Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina

Autores
Hall, Antonio Juan; Feoli, Carlos; Ingaramo, Jorge; Balzarini, Mónica Graciela
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000–2007 interval. The estimators were based on comparative yield trial (CYT) data for commercial hybrids, on individual commercial field (ICF) data, and on reporting district (RD) yield information. Contrasts between these estimators led us to prefer the attainable (CYT) yield estimator over the other two. Attainable (CYT) yields ranged from 2.21 to 2.83 t ha−1 across regions. Yield gaps between mean farmer (RD data) and attainable (CYT) yields were computed using best linear unbiased estimator (BLUE) values for both variables obtained using mixed linear models. These gaps were statistically significant (p ≤ 0.05) for all 8 regions and ranged from 0.37 to 1.18 t ha−1 across regions, for a country average of 0.75 t ha−1, equivalent to 41% of the mean country yield of 1.85 t ha−1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2 t ha−1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8 t ha−1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable (CYT) yields were smaller than those between reporting district and attainable (CYT) yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85% across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable (CYT) yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields.
EEA Pergamino
Fil: Hall, Antonio Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires; Argentina
Fil: Feoli, Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Acuerdo Instituto Nacional de Tecnología Agropecuaria (INTA).ASAGIR; Argentina
Fil: Ingaramo, Jorge. Asociación Argentina del Girasol; Argentina
Fil: Balzarini, Monica Graciela. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Departamento de Desarrollo Rural. Area de Estadística y Biometría; Argentina
Fuente
Field Crops Research 143 : 119-129 (March 2013)
Materia
Helianthus Annuus
Rendimiento
Cultivo de Temporal
Sistemas de Cultivo
Indicadores Económicos
Yields
Rainfed Farming
Cropping Systems
Economic Indicators
Yield Gap
Girasol
Argentina
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/5010
Acceder
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oai_identifier_str oai:localhost:20.500.12123/5010
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Gaps between farmer and attainable yields across rainfed sunflower growing regions of ArgentinaHall, Antonio JuanFeoli, CarlosIngaramo, JorgeBalzarini, Mónica GracielaHelianthus AnnuusRendimientoCultivo de TemporalSistemas de CultivoIndicadores EconómicosYieldsRainfed FarmingCropping SystemsEconomic IndicatorsYield GapGirasolArgentinaWe computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000–2007 interval. The estimators were based on comparative yield trial (CYT) data for commercial hybrids, on individual commercial field (ICF) data, and on reporting district (RD) yield information. Contrasts between these estimators led us to prefer the attainable (CYT) yield estimator over the other two. Attainable (CYT) yields ranged from 2.21 to 2.83 t ha−1 across regions. Yield gaps between mean farmer (RD data) and attainable (CYT) yields were computed using best linear unbiased estimator (BLUE) values for both variables obtained using mixed linear models. These gaps were statistically significant (p ≤ 0.05) for all 8 regions and ranged from 0.37 to 1.18 t ha−1 across regions, for a country average of 0.75 t ha−1, equivalent to 41% of the mean country yield of 1.85 t ha−1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2 t ha−1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8 t ha−1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable (CYT) yields were smaller than those between reporting district and attainable (CYT) yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85% across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable (CYT) yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields.EEA PergaminoFil: Hall, Antonio Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires; ArgentinaFil: Feoli, Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Acuerdo Instituto Nacional de Tecnología Agropecuaria (INTA).ASAGIR; ArgentinaFil: Ingaramo, Jorge. Asociación Argentina del Girasol; ArgentinaFil: Balzarini, Monica Graciela. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Departamento de Desarrollo Rural. Area de Estadística y Biometría; ArgentinaElsevier2019-04-30T11:22:57Z2019-04-30T11:22:57Z2013-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://www.sciencedirect.com/science/article/pii/S0378429012001621http://hdl.handle.net/20.500.12123/50100378-4290https://doi.org/10.1016/j.fcr.2012.05.003Field Crops Research 143 : 119-129 (March 2013)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:29:31Zoai:localhost:20.500.12123/5010instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:29:31.443INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
title Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
spellingShingle Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
Hall, Antonio Juan
Helianthus Annuus
Rendimiento
Cultivo de Temporal
Sistemas de Cultivo
Indicadores Económicos
Yields
Rainfed Farming
Cropping Systems
Economic Indicators
Yield Gap
Girasol
Argentina
title_short Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
title_full Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
title_fullStr Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
title_full_unstemmed Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
title_sort Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina
dc.creator.none.fl_str_mv Hall, Antonio Juan
Feoli, Carlos
Ingaramo, Jorge
Balzarini, Mónica Graciela
author Hall, Antonio Juan
author_facet Hall, Antonio Juan
Feoli, Carlos
Ingaramo, Jorge
Balzarini, Mónica Graciela
author_role author
author2 Feoli, Carlos
Ingaramo, Jorge
Balzarini, Mónica Graciela
author2_role author
author
author
dc.subject.none.fl_str_mv Helianthus Annuus
Rendimiento
Cultivo de Temporal
Sistemas de Cultivo
Indicadores Económicos
Yields
Rainfed Farming
Cropping Systems
Economic Indicators
Yield Gap
Girasol
Argentina
topic Helianthus Annuus
Rendimiento
Cultivo de Temporal
Sistemas de Cultivo
Indicadores Económicos
Yields
Rainfed Farming
Cropping Systems
Economic Indicators
Yield Gap
Girasol
Argentina
dc.description.none.fl_txt_mv We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000–2007 interval. The estimators were based on comparative yield trial (CYT) data for commercial hybrids, on individual commercial field (ICF) data, and on reporting district (RD) yield information. Contrasts between these estimators led us to prefer the attainable (CYT) yield estimator over the other two. Attainable (CYT) yields ranged from 2.21 to 2.83 t ha−1 across regions. Yield gaps between mean farmer (RD data) and attainable (CYT) yields were computed using best linear unbiased estimator (BLUE) values for both variables obtained using mixed linear models. These gaps were statistically significant (p ≤ 0.05) for all 8 regions and ranged from 0.37 to 1.18 t ha−1 across regions, for a country average of 0.75 t ha−1, equivalent to 41% of the mean country yield of 1.85 t ha−1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2 t ha−1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8 t ha−1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable (CYT) yields were smaller than those between reporting district and attainable (CYT) yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85% across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable (CYT) yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields.
EEA Pergamino
Fil: Hall, Antonio Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires; Argentina
Fil: Feoli, Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Acuerdo Instituto Nacional de Tecnología Agropecuaria (INTA).ASAGIR; Argentina
Fil: Ingaramo, Jorge. Asociación Argentina del Girasol; Argentina
Fil: Balzarini, Monica Graciela. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Departamento de Desarrollo Rural. Area de Estadística y Biometría; Argentina
description We computed three estimators of attainable yield for each of between 5 and 8 rainfed sunflower-growing regions of Argentina using between 5 and 9 years of data over the 2000–2007 interval. The estimators were based on comparative yield trial (CYT) data for commercial hybrids, on individual commercial field (ICF) data, and on reporting district (RD) yield information. Contrasts between these estimators led us to prefer the attainable (CYT) yield estimator over the other two. Attainable (CYT) yields ranged from 2.21 to 2.83 t ha−1 across regions. Yield gaps between mean farmer (RD data) and attainable (CYT) yields were computed using best linear unbiased estimator (BLUE) values for both variables obtained using mixed linear models. These gaps were statistically significant (p ≤ 0.05) for all 8 regions and ranged from 0.37 to 1.18 t ha−1 across regions, for a country average of 0.75 t ha−1, equivalent to 41% of the mean country yield of 1.85 t ha−1. We also used CYT data to examine the issue of recurrent, albeit infrequent, reports of unusually high yields. Mean yields for the top decile of comparative yield trial data ranged from 3.2 to 4.2 t ha−1 across regions, and the highest yields for this decile in any of the years of record ranged from 3.9 to 4.8 t ha−1 across regions. Individual commercial field yields were available for 5 regions. Gaps between BLUEs for this variable and attainable (CYT) yields were smaller than those between reporting district and attainable (CYT) yields, but were nevertheless significant in all 5 regions. A notable feature of reporting district, individual field, and yield trial data was their variability. At reporting district level within regions, contributions of spatial and temporal variability were roughly similar. The mean relative contribution of the trial effect to non-error variance of the CYT data exceeded 85% across regions, dominating the contributions of genotype and of genotype by trial effects. We conclude that the magnitude of mean farmer/attainable (CYT) yield gaps for this crop in Argentina justifies further research aimed at reducing regional gaps; and that CYT data can be used to generate an appropriate benchmark for attainable yields.
publishDate 2013
dc.date.none.fl_str_mv 2013-03-01
2019-04-30T11:22:57Z
2019-04-30T11:22:57Z
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 https://www.sciencedirect.com/science/article/pii/S0378429012001621
http://hdl.handle.net/20.500.12123/5010
0378-4290
https://doi.org/10.1016/j.fcr.2012.05.003
url https://www.sciencedirect.com/science/article/pii/S0378429012001621
http://hdl.handle.net/20.500.12123/5010
https://doi.org/10.1016/j.fcr.2012.05.003
identifier_str_mv 0378-4290
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Field Crops Research 143 : 119-129 (March 2013)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.712165

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