Early-season plant-to-plant spatial uniformity can affect soybean yields
- Autores
- Pereyra, Valentina M.; Bastos, Leonardo M.; Froes de Borja Reis, André; Melchiori, Ricardo J. M.; Maltese, Nicolás Elías; Appelhans, Stefania Carolina; Vara Prasad, P. V.; Wright, Yancy; Brokesh, Edwin; Sharda, Ajay; Ciampitti, Ignacio Antonio
- Año de publicación
- 2022
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities.
Fil: Pereyra, Valentina M.. Kansas State University; Estados Unidos
Fil: Bastos, Leonardo M.. University of Georgia; Estados Unidos
Fil: Froes de Borja Reis, André. State University of Louisiana; Estados Unidos
Fil: Melchiori, Ricardo J. M.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; Argentina
Fil: Maltese, Nicolás Elías. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina
Fil: Appelhans, Stefania Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina
Fil: Vara Prasad, P. V.. Kansas State University; Estados Unidos
Fil: Wright, Yancy. No especifíca;
Fil: Brokesh, Edwin. Kansas State University; Estados Unidos
Fil: Sharda, Ajay. Kansas State University; Estados Unidos
Fil: Ciampitti, Ignacio Antonio. Kansas State University; Estados Unidos - Materia
-
GLYCINE MAX
SEEDING RATE
UNIFORMITY
YIELD ENVIRONMENTS - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/222004
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Early-season plant-to-plant spatial uniformity can affect soybean yieldsPereyra, Valentina M.Bastos, Leonardo M.Froes de Borja Reis, AndréMelchiori, Ricardo J. M.Maltese, Nicolás ElíasAppelhans, Stefania CarolinaVara Prasad, P. V.Wright, YancyBrokesh, EdwinSharda, AjayCiampitti, Ignacio AntonioGLYCINE MAXSEEDING RATEUNIFORMITYYIELD ENVIRONMENTShttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities.Fil: Pereyra, Valentina M.. Kansas State University; Estados UnidosFil: Bastos, Leonardo M.. University of Georgia; Estados UnidosFil: Froes de Borja Reis, André. State University of Louisiana; Estados UnidosFil: Melchiori, Ricardo J. M.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; ArgentinaFil: Maltese, Nicolás Elías. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Appelhans, Stefania Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Vara Prasad, P. V.. Kansas State University; Estados UnidosFil: Wright, Yancy. No especifíca;Fil: Brokesh, Edwin. Kansas State University; Estados UnidosFil: Sharda, Ajay. Kansas State University; Estados UnidosFil: Ciampitti, Ignacio Antonio. Kansas State University; Estados UnidosNature2022-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/222004Pereyra, Valentina M.; Bastos, Leonardo M.; Froes de Borja Reis, André; Melchiori, Ricardo J. M.; Maltese, Nicolás Elías; et al.; Early-season plant-to-plant spatial uniformity can affect soybean yields; Nature; Scientific Reports; 12; 1; 10-2022; 1-102045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-022-21385-zinfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-21385-zinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:50:11Zoai:ri.conicet.gov.ar:11336/222004instacron: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:34982025-09-03 09:50:11.502CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
title |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
spellingShingle |
Early-season plant-to-plant spatial uniformity can affect soybean yields Pereyra, Valentina M. GLYCINE MAX SEEDING RATE UNIFORMITY YIELD ENVIRONMENTS |
title_short |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
title_full |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
title_fullStr |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
title_full_unstemmed |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
title_sort |
Early-season plant-to-plant spatial uniformity can affect soybean yields |
dc.creator.none.fl_str_mv |
Pereyra, Valentina M. Bastos, Leonardo M. Froes de Borja Reis, André Melchiori, Ricardo J. M. Maltese, Nicolás Elías Appelhans, Stefania Carolina Vara Prasad, P. V. Wright, Yancy Brokesh, Edwin Sharda, Ajay Ciampitti, Ignacio Antonio |
author |
Pereyra, Valentina M. |
author_facet |
Pereyra, Valentina M. Bastos, Leonardo M. Froes de Borja Reis, André Melchiori, Ricardo J. M. Maltese, Nicolás Elías Appelhans, Stefania Carolina Vara Prasad, P. V. Wright, Yancy Brokesh, Edwin Sharda, Ajay Ciampitti, Ignacio Antonio |
author_role |
author |
author2 |
Bastos, Leonardo M. Froes de Borja Reis, André Melchiori, Ricardo J. M. Maltese, Nicolás Elías Appelhans, Stefania Carolina Vara Prasad, P. V. Wright, Yancy Brokesh, Edwin Sharda, Ajay Ciampitti, Ignacio Antonio |
author2_role |
author author author author author author author author author author |
dc.subject.none.fl_str_mv |
GLYCINE MAX SEEDING RATE UNIFORMITY YIELD ENVIRONMENTS |
topic |
GLYCINE MAX SEEDING RATE UNIFORMITY YIELD ENVIRONMENTS |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.1 https://purl.org/becyt/ford/4 |
dc.description.none.fl_txt_mv |
Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities. Fil: Pereyra, Valentina M.. Kansas State University; Estados Unidos Fil: Bastos, Leonardo M.. University of Georgia; Estados Unidos Fil: Froes de Borja Reis, André. State University of Louisiana; Estados Unidos Fil: Melchiori, Ricardo J. M.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; Argentina Fil: Maltese, Nicolás Elías. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Appelhans, Stefania Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina Fil: Vara Prasad, P. V.. Kansas State University; Estados Unidos Fil: Wright, Yancy. No especifíca; Fil: Brokesh, Edwin. Kansas State University; Estados Unidos Fil: Sharda, Ajay. Kansas State University; Estados Unidos Fil: Ciampitti, Ignacio Antonio. Kansas State University; Estados Unidos |
description |
Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10 |
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/11336/222004 Pereyra, Valentina M.; Bastos, Leonardo M.; Froes de Borja Reis, André; Melchiori, Ricardo J. M.; Maltese, Nicolás Elías; et al.; Early-season plant-to-plant spatial uniformity can affect soybean yields; Nature; Scientific Reports; 12; 1; 10-2022; 1-10 2045-2322 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/222004 |
identifier_str_mv |
Pereyra, Valentina M.; Bastos, Leonardo M.; Froes de Borja Reis, André; Melchiori, Ricardo J. M.; Maltese, Nicolás Elías; et al.; Early-season plant-to-plant spatial uniformity can affect soybean yields; Nature; Scientific Reports; 12; 1; 10-2022; 1-10 2045-2322 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-022-21385-z info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-21385-z |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/2.5/ar/ |
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application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Nature |
publisher.none.fl_str_mv |
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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