Management options for reducing maize yield gaps in contrasting sowing dates

Autores
Vitantonio Mazzini, Lucas N.; Borrás, Lucas; Garibaldi, Lucas Alejandro; Pérez, Diego H.; Gallo, Santiago; Gambin, Brenda L.
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fil: Vitantonio Mazzini, Lucas N. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Vitantonio Mazzini, Lucas N. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Borrás, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Borrás, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.
Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.
Fil: Pérez, Diego H. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.
Fil: Gallo, Santiago. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.
Fil: Gambin, Brenda L. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Gambin, Brenda L. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Optimizing grain production implies defining the best management practices for a set of particular environments. Argentinean farmers in the central temperate region are sowing maize at two contrasting sowing dates (September to October and December), exposing their crops to very different growing environments. We tested the influence of management and environmental variables affecting maize yield at early (ES) or late (LS) sowings. Our objectives were to (i) determine the most relevant management and environmental yield predictors for ES and LS, (ii) quantify the magnitude of their effects, and (iii) explore potential yield increments after optimizing crop management within each sowing. We conducted 91 on-farm multi-environment trials during six years (2010–2016) around the central temperate region, and analyzed 13 management and environmental variables. The most relevant environmental predictors (relative importance > 0.50) for both sowing dates included presence of a water table at sowing, rainfall during the crop cycle, and their interactions. Presence of a water table had a positive or negative effect for ES or LS, respectively. Management yield predictors varied depending on the sowing date. Stand density, N and S availability were important yield predictors at ES, while fungicide use, soil P, and N availability were the most relevant ones at LS. Farmers can increase yield at each sowing date by optimizing these management practices. Optimizing stand density and N availability in ES can have a ∼3,053 kg ha−1 effect, while fungicide use in LS can increase yield by ∼1040 kg ha−1. Determining the adequate sowing date based on the presence of a water table at sowing can have a ∼1000 kg ha−1 effect. Our results described specific management options for reducing yield gaps and optimize maize production across contrasting sowing dates.
Materia
Sowing Date
Water Table
Stand Density
Fertilizer Management
Multi-model Inference
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
RID-UNRN (UNRN)
Institución
Universidad Nacional de Río Negro
OAI Identificador
oai:rid.unrn.edu.ar:20.500.12049/4501
Acceder
id RIDUNRN_8030af7f3891a0c1fc1a69fd8468de0f
oai_identifier_str oai:rid.unrn.edu.ar:20.500.12049/4501
network_acronym_str RIDUNRN
repository_id_str 4369
network_name_str RID-UNRN (UNRN)
spelling Management options for reducing maize yield gaps in contrasting sowing datesVitantonio Mazzini, Lucas N.Borrás, LucasGaribaldi, Lucas AlejandroPérez, Diego H.Gallo, SantiagoGambin, Brenda L.Sowing DateWater TableStand DensityFertilizer ManagementMulti-model InferenceFil: Vitantonio Mazzini, Lucas N. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Vitantonio Mazzini, Lucas N. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Borrás, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Borrás, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.Fil: Pérez, Diego H. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.Fil: Gallo, Santiago. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.Fil: Gambin, Brenda L. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Gambin, Brenda L. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Optimizing grain production implies defining the best management practices for a set of particular environments. Argentinean farmers in the central temperate region are sowing maize at two contrasting sowing dates (September to October and December), exposing their crops to very different growing environments. We tested the influence of management and environmental variables affecting maize yield at early (ES) or late (LS) sowings. Our objectives were to (i) determine the most relevant management and environmental yield predictors for ES and LS, (ii) quantify the magnitude of their effects, and (iii) explore potential yield increments after optimizing crop management within each sowing. We conducted 91 on-farm multi-environment trials during six years (2010–2016) around the central temperate region, and analyzed 13 management and environmental variables. The most relevant environmental predictors (relative importance > 0.50) for both sowing dates included presence of a water table at sowing, rainfall during the crop cycle, and their interactions. Presence of a water table had a positive or negative effect for ES or LS, respectively. Management yield predictors varied depending on the sowing date. Stand density, N and S availability were important yield predictors at ES, while fungicide use, soil P, and N availability were the most relevant ones at LS. Farmers can increase yield at each sowing date by optimizing these management practices. Optimizing stand density and N availability in ES can have a ∼3,053 kg ha−1 effect, while fungicide use in LS can increase yield by ∼1040 kg ha−1. Determining the adequate sowing date based on the presence of a water table at sowing can have a ∼1000 kg ha−1 effect. Our results described specific management options for reducing yield gaps and optimize maize production across contrasting sowing dates.Elseiver2020-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfVitantonio Mazzini, Lucas N., Borrás, Lucas., Garibaldi, Lucas A., Pérez, Diego y et al (2020). Management options for reducing maize yield gaps in contrasting sowing dates. Elseiver; Field Crops Research; 251; 1077790378-42901872-6852https://www.sciencedirect.com/science/article/pii/S0378429019321471?via%3Dihubhttps://rid.unrn.edu.ar/jspui/handle/20.500.12049/4501https://doi.org/10.1016/j.fcr.2020.107779eng251Field Crops Researchinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/reponame:RID-UNRN (UNRN)instname:Universidad Nacional de Río Negro2025-09-11T10:49:12Zoai:rid.unrn.edu.ar:20.500.12049/4501instacron:UNRNInstitucionalhttps://rid.unrn.edu.ar/jspui/Universidad públicaNo correspondehttps://rid.unrn.edu.ar/oai/snrdrid@unrn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:43692025-09-11 10:49:12.576RID-UNRN (UNRN) - Universidad Nacional de Río Negrofalse
dc.title.none.fl_str_mv Management options for reducing maize yield gaps in contrasting sowing dates
title Management options for reducing maize yield gaps in contrasting sowing dates
spellingShingle Management options for reducing maize yield gaps in contrasting sowing dates
Vitantonio Mazzini, Lucas N.
Sowing Date
Water Table
Stand Density
Fertilizer Management
Multi-model Inference
title_short Management options for reducing maize yield gaps in contrasting sowing dates
title_full Management options for reducing maize yield gaps in contrasting sowing dates
title_fullStr Management options for reducing maize yield gaps in contrasting sowing dates
title_full_unstemmed Management options for reducing maize yield gaps in contrasting sowing dates
title_sort Management options for reducing maize yield gaps in contrasting sowing dates
dc.creator.none.fl_str_mv Vitantonio Mazzini, Lucas N.
Borrás, Lucas
Garibaldi, Lucas Alejandro
Pérez, Diego H.
Gallo, Santiago
Gambin, Brenda L.
author Vitantonio Mazzini, Lucas N.
author_facet Vitantonio Mazzini, Lucas N.
Borrás, Lucas
Garibaldi, Lucas Alejandro
Pérez, Diego H.
Gallo, Santiago
Gambin, Brenda L.
author_role author
author2 Borrás, Lucas
Garibaldi, Lucas Alejandro
Pérez, Diego H.
Gallo, Santiago
Gambin, Brenda L.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Sowing Date
Water Table
Stand Density
Fertilizer Management
Multi-model Inference
topic Sowing Date
Water Table
Stand Density
Fertilizer Management
Multi-model Inference
dc.description.none.fl_txt_mv Fil: Vitantonio Mazzini, Lucas N. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Vitantonio Mazzini, Lucas N. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Borrás, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Borrás, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.
Fil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina.
Fil: Pérez, Diego H. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.
Fil: Gallo, Santiago. Asociación Argentina de Consorcios Regionales de Experimentación Agrícola; Argentina.
Fil: Gambin, Brenda L. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Fil: Gambin, Brenda L. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
Optimizing grain production implies defining the best management practices for a set of particular environments. Argentinean farmers in the central temperate region are sowing maize at two contrasting sowing dates (September to October and December), exposing their crops to very different growing environments. We tested the influence of management and environmental variables affecting maize yield at early (ES) or late (LS) sowings. Our objectives were to (i) determine the most relevant management and environmental yield predictors for ES and LS, (ii) quantify the magnitude of their effects, and (iii) explore potential yield increments after optimizing crop management within each sowing. We conducted 91 on-farm multi-environment trials during six years (2010–2016) around the central temperate region, and analyzed 13 management and environmental variables. The most relevant environmental predictors (relative importance > 0.50) for both sowing dates included presence of a water table at sowing, rainfall during the crop cycle, and their interactions. Presence of a water table had a positive or negative effect for ES or LS, respectively. Management yield predictors varied depending on the sowing date. Stand density, N and S availability were important yield predictors at ES, while fungicide use, soil P, and N availability were the most relevant ones at LS. Farmers can increase yield at each sowing date by optimizing these management practices. Optimizing stand density and N availability in ES can have a ∼3,053 kg ha−1 effect, while fungicide use in LS can increase yield by ∼1040 kg ha−1. Determining the adequate sowing date based on the presence of a water table at sowing can have a ∼1000 kg ha−1 effect. Our results described specific management options for reducing yield gaps and optimize maize production across contrasting sowing dates.
description Fil: Vitantonio Mazzini, Lucas N. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.
publishDate 2020
dc.date.none.fl_str_mv 2020-03
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 Vitantonio Mazzini, Lucas N., Borrás, Lucas., Garibaldi, Lucas A., Pérez, Diego y et al (2020). Management options for reducing maize yield gaps in contrasting sowing dates. Elseiver; Field Crops Research; 251; 107779
0378-4290
1872-6852
https://www.sciencedirect.com/science/article/pii/S0378429019321471?via%3Dihub
https://rid.unrn.edu.ar/jspui/handle/20.500.12049/4501
https://doi.org/10.1016/j.fcr.2020.107779
identifier_str_mv Vitantonio Mazzini, Lucas N., Borrás, Lucas., Garibaldi, Lucas A., Pérez, Diego y et al (2020). Management options for reducing maize yield gaps in contrasting sowing dates. Elseiver; Field Crops Research; 251; 107779
0378-4290
1872-6852
url https://www.sciencedirect.com/science/article/pii/S0378429019321471?via%3Dihub
https://rid.unrn.edu.ar/jspui/handle/20.500.12049/4501
https://doi.org/10.1016/j.fcr.2020.107779
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 251
Field Crops Research
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elseiver
publisher.none.fl_str_mv Elseiver
dc.source.none.fl_str_mv reponame:RID-UNRN (UNRN)
instname:Universidad Nacional de Río Negro
reponame_str RID-UNRN (UNRN)
collection RID-UNRN (UNRN)
instname_str Universidad Nacional de Río Negro
repository.name.fl_str_mv RID-UNRN (UNRN) - Universidad Nacional de Río Negro
repository.mail.fl_str_mv rid@unrn.edu.ar
_version_ 1842976458707828736
score 12.993085

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