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dc.contributor.author
Pereyra, Valentina M.  
dc.contributor.author
Bastos, Leonardo M.  
dc.contributor.author
Froes de Borja Reis, André  
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Melchiori, Ricardo J. M.  
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Maltese, Nicolás Elías  
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Appelhans, Stefania Carolina  
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Vara Prasad, P. V.  
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Wright, Yancy  
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Brokesh, Edwin  
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Sharda, Ajay  
dc.contributor.author
Ciampitti, Ignacio Antonio  
dc.date.available
2024-01-02T14:48:00Z  
dc.date.issued
2022-10  
dc.identifier.citation
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  
dc.identifier.issn
2045-2322  
dc.identifier.uri
http://hdl.handle.net/11336/222004  
dc.description.abstract
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.  
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application/pdf  
dc.language.iso
eng  
dc.publisher
Nature  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
GLYCINE MAX  
dc.subject
SEEDING RATE  
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UNIFORMITY  
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YIELD ENVIRONMENTS  
dc.subject.classification
Agricultura  
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Agricultura, Silvicultura y Pesca  
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CIENCIAS AGRÍCOLAS  
dc.title
Early-season plant-to-plant spatial uniformity can affect soybean yields  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-01-02T11:45:14Z  
dc.journal.volume
12  
dc.journal.number
1  
dc.journal.pagination
1-10  
dc.journal.pais
Reino Unido  
dc.description.fil
Fil: Pereyra, Valentina M.. Kansas State University; Estados Unidos  
dc.description.fil
Fil: Bastos, Leonardo M.. University of Georgia; Estados Unidos  
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Fil: Froes de Borja Reis, André. State University of Louisiana; Estados Unidos  
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Fil: Melchiori, Ricardo J. M.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Entre Ríos. Estación Experimental Agropecuaria Paraná; Argentina  
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Fil: Maltese, Nicolás Elías. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina  
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Fil: Appelhans, Stefania Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina  
dc.description.fil
Fil: Vara Prasad, P. V.. Kansas State University; Estados Unidos  
dc.description.fil
Fil: Wright, Yancy. No especifíca;  
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Fil: Brokesh, Edwin. Kansas State University; Estados Unidos  
dc.description.fil
Fil: Sharda, Ajay. Kansas State University; Estados Unidos  
dc.description.fil
Fil: Ciampitti, Ignacio Antonio. Kansas State University; Estados Unidos  
dc.journal.title
Scientific Reports  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-022-21385-z  
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info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1038/s41598-022-21385-z