Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean
- Autores
- Salvagiotti, Fernando; Magnano, Luciana; Ortez, Osler; Enrico, Juan Martin; Barraco, Miriam Raquel; Barbagelata, Pedro Anibal; Condori, Alicia Adelina; Di Mauro, Guido; Manlla, Amalia Graciela; Rotundo, Jose Luis; García, Fernando O.; Ferrari, Manuel Carlos; Gudelj, Vicente Jorge; Ciampitti, Ignacio A.
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Estimation of crop nutrient demand, seed nutrient removal, and nutrient use efficiency (yield to nutrient uptake ratio) are crucial for pursuing both balanced nutrition and more sustainable farming systems. However, the estimation of the nutrient requirements as the nutrient uptake per unit of seed yields is impaired in many situations due to the narrow variation of the dataset used to obtain these values or by the overgeneralization of considering a constant value for the nutrient demand at varying yield levels. Past studies focused on other crops and using linear models for estimation of the nutrient requirements, but not yet for soybeans (Glycine max L.). The aims of this research study were to: (i) quantify nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) requirements in soybean and (ii) compare linear and non-linear (spherical) models in their relationship between plant and seed nutrient content all relative to seed yield at varying probabilities utilizing quantile regression. A large dataset from different studies conducted between 2009–2018 period, including data of seed yield, total biomass at physiological maturity, and N, P, K, and S uptake. Soybean seed yield ranged from 955 to 6525 kg ha−1, aboveground biomass from 1990 to 15,814 kg ha−1, and harvest index from 0.16 to 0.57. On average, nutrient uptake was 261 kg N ha−1, 25 kg P ha−1, 133 kg K ha−1, and 16 kg S ha−1 (N:P:K:S ratio = 17:1.6:8.5:1), while nutrient content in seeds averaged 191 kg N ha−1, 17 kg P ha−1, 54 kg K ha−1, and 9 kg S ha−1 (N:P:K:S ratio = 21:1.8:5.8:1). The spherical model described better than the linear model the relationship between plant nutrient uptake or nutrient content in seeds with seed yield in soybean, and thus, nutrient requirements per unit of yield decreased as seed yield increased. A relationship between nutrient internal efficiency and seed yield for the different percentiles as determined by the non-linear quantile regression offered probabilistic values for estimating nutrient uptake in soybean, providing useful information for obtaining more reliable estimates of nutrient balances at the system-level.
EEA Oliveros
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Magnano, Luciana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Ortez, Osler. University of Nebraska-Lincoln. Department of Agronomy and Horticulture; Estados Unidos
Fil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Barraco, Mariam Raquel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria General Villegas; Argentina.
Fil: Barbagelata, Pedro Anibal. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina
Fil: Condori, Alicia Adelina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Di Mauro, Guido. Corteva Agriscience. Predictive Agriculture; Estados Unidos
Fil: Manlla, Amalia Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Rotundo, José Luis. Corteva Agriscience. Predictive Agriculture; Estados Unidos
Fil: García, Fernando O. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
Fil: Ferrari, Manuel Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Gudelj, Vicente Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados Unidos - Fuente
- European Journal of Agronomy 127 : 126289 (July 2021)
- Materia
-
Soja
Nutrientes
Nitrógeno
Fósforo
Potasio
Azufre
Absorción de Sustancias Nutritivas
Soybeans
Nutrients
Nitrogen
Phosphorus
Potassium
Sulphur
Nutrient Uptake - Nivel de accesibilidad
- acceso restringido
- Condiciones de uso
- Repositorio
.jpg)
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/9247
Ver los metadatos del registro completo
| id |
INTADig_6083d903ac358170cda6c80c72ad9023 |
|---|---|
| oai_identifier_str |
oai:localhost:20.500.12123/9247 |
| network_acronym_str |
INTADig |
| repository_id_str |
l |
| network_name_str |
INTA Digital (INTA) |
| spelling |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybeanSalvagiotti, FernandoMagnano, LucianaOrtez, OslerEnrico, Juan MartinBarraco, Miriam RaquelBarbagelata, Pedro AnibalCondori, Alicia AdelinaDi Mauro, GuidoManlla, Amalia GracielaRotundo, Jose LuisGarcía, Fernando O.Ferrari, Manuel CarlosGudelj, Vicente JorgeCiampitti, Ignacio A.SojaNutrientesNitrógenoFósforoPotasioAzufreAbsorción de Sustancias NutritivasSoybeansNutrientsNitrogenPhosphorusPotassiumSulphurNutrient UptakeEstimation of crop nutrient demand, seed nutrient removal, and nutrient use efficiency (yield to nutrient uptake ratio) are crucial for pursuing both balanced nutrition and more sustainable farming systems. However, the estimation of the nutrient requirements as the nutrient uptake per unit of seed yields is impaired in many situations due to the narrow variation of the dataset used to obtain these values or by the overgeneralization of considering a constant value for the nutrient demand at varying yield levels. Past studies focused on other crops and using linear models for estimation of the nutrient requirements, but not yet for soybeans (Glycine max L.). The aims of this research study were to: (i) quantify nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) requirements in soybean and (ii) compare linear and non-linear (spherical) models in their relationship between plant and seed nutrient content all relative to seed yield at varying probabilities utilizing quantile regression. A large dataset from different studies conducted between 2009–2018 period, including data of seed yield, total biomass at physiological maturity, and N, P, K, and S uptake. Soybean seed yield ranged from 955 to 6525 kg ha−1, aboveground biomass from 1990 to 15,814 kg ha−1, and harvest index from 0.16 to 0.57. On average, nutrient uptake was 261 kg N ha−1, 25 kg P ha−1, 133 kg K ha−1, and 16 kg S ha−1 (N:P:K:S ratio = 17:1.6:8.5:1), while nutrient content in seeds averaged 191 kg N ha−1, 17 kg P ha−1, 54 kg K ha−1, and 9 kg S ha−1 (N:P:K:S ratio = 21:1.8:5.8:1). The spherical model described better than the linear model the relationship between plant nutrient uptake or nutrient content in seeds with seed yield in soybean, and thus, nutrient requirements per unit of yield decreased as seed yield increased. A relationship between nutrient internal efficiency and seed yield for the different percentiles as determined by the non-linear quantile regression offered probabilistic values for estimating nutrient uptake in soybean, providing useful information for obtaining more reliable estimates of nutrient balances at the system-level.EEA OliverosFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Magnano, Luciana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Ortez, Osler. University of Nebraska-Lincoln. Department of Agronomy and Horticulture; Estados UnidosFil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Barraco, Mariam Raquel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria General Villegas; Argentina.Fil: Barbagelata, Pedro Anibal. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Condori, Alicia Adelina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Di Mauro, Guido. Corteva Agriscience. Predictive Agriculture; Estados UnidosFil: Manlla, Amalia Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Rotundo, José Luis. Corteva Agriscience. Predictive Agriculture; Estados UnidosFil: García, Fernando O. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaFil: Ferrari, Manuel Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Gudelj, Vicente Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados UnidosElsevier2021-05-03T13:21:42Z2021-05-03T13:21:42Z2021-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/9247https://www.sciencedirect.com/science/article/abs/pii/S11610301210006171161-0301https://doi.org/10.1016/j.eja.2021.126289European Journal of Agronomy 127 : 126289 (July 2021)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/PNCER-022421/AR./Diagnostico, reposición de macronutrientes y tecnología de la fertilización.info:eu-repograntAgreement/INTA/PNCYO-1127033/AR./Manejo nutricional de cereales y oleaginosas para la intensificación sustentable de los sistemas productivosinfo:eu-repo/semantics/restrictedAccess2025-09-04T09:48:52Zoai:localhost:20.500.12123/9247instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:48:53.157INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
| dc.title.none.fl_str_mv |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| title |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| spellingShingle |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean Salvagiotti, Fernando Soja Nutrientes Nitrógeno Fósforo Potasio Azufre Absorción de Sustancias Nutritivas Soybeans Nutrients Nitrogen Phosphorus Potassium Sulphur Nutrient Uptake |
| title_short |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| title_full |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| title_fullStr |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| title_full_unstemmed |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| title_sort |
Estimating nitrogen, phosphorus, potassium, and sulfur uptake and requirement in soybean |
| dc.creator.none.fl_str_mv |
Salvagiotti, Fernando Magnano, Luciana Ortez, Osler Enrico, Juan Martin Barraco, Miriam Raquel Barbagelata, Pedro Anibal Condori, Alicia Adelina Di Mauro, Guido Manlla, Amalia Graciela Rotundo, Jose Luis García, Fernando O. Ferrari, Manuel Carlos Gudelj, Vicente Jorge Ciampitti, Ignacio A. |
| author |
Salvagiotti, Fernando |
| author_facet |
Salvagiotti, Fernando Magnano, Luciana Ortez, Osler Enrico, Juan Martin Barraco, Miriam Raquel Barbagelata, Pedro Anibal Condori, Alicia Adelina Di Mauro, Guido Manlla, Amalia Graciela Rotundo, Jose Luis García, Fernando O. Ferrari, Manuel Carlos Gudelj, Vicente Jorge Ciampitti, Ignacio A. |
| author_role |
author |
| author2 |
Magnano, Luciana Ortez, Osler Enrico, Juan Martin Barraco, Miriam Raquel Barbagelata, Pedro Anibal Condori, Alicia Adelina Di Mauro, Guido Manlla, Amalia Graciela Rotundo, Jose Luis García, Fernando O. Ferrari, Manuel Carlos Gudelj, Vicente Jorge Ciampitti, Ignacio A. |
| author2_role |
author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Soja Nutrientes Nitrógeno Fósforo Potasio Azufre Absorción de Sustancias Nutritivas Soybeans Nutrients Nitrogen Phosphorus Potassium Sulphur Nutrient Uptake |
| topic |
Soja Nutrientes Nitrógeno Fósforo Potasio Azufre Absorción de Sustancias Nutritivas Soybeans Nutrients Nitrogen Phosphorus Potassium Sulphur Nutrient Uptake |
| dc.description.none.fl_txt_mv |
Estimation of crop nutrient demand, seed nutrient removal, and nutrient use efficiency (yield to nutrient uptake ratio) are crucial for pursuing both balanced nutrition and more sustainable farming systems. However, the estimation of the nutrient requirements as the nutrient uptake per unit of seed yields is impaired in many situations due to the narrow variation of the dataset used to obtain these values or by the overgeneralization of considering a constant value for the nutrient demand at varying yield levels. Past studies focused on other crops and using linear models for estimation of the nutrient requirements, but not yet for soybeans (Glycine max L.). The aims of this research study were to: (i) quantify nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) requirements in soybean and (ii) compare linear and non-linear (spherical) models in their relationship between plant and seed nutrient content all relative to seed yield at varying probabilities utilizing quantile regression. A large dataset from different studies conducted between 2009–2018 period, including data of seed yield, total biomass at physiological maturity, and N, P, K, and S uptake. Soybean seed yield ranged from 955 to 6525 kg ha−1, aboveground biomass from 1990 to 15,814 kg ha−1, and harvest index from 0.16 to 0.57. On average, nutrient uptake was 261 kg N ha−1, 25 kg P ha−1, 133 kg K ha−1, and 16 kg S ha−1 (N:P:K:S ratio = 17:1.6:8.5:1), while nutrient content in seeds averaged 191 kg N ha−1, 17 kg P ha−1, 54 kg K ha−1, and 9 kg S ha−1 (N:P:K:S ratio = 21:1.8:5.8:1). The spherical model described better than the linear model the relationship between plant nutrient uptake or nutrient content in seeds with seed yield in soybean, and thus, nutrient requirements per unit of yield decreased as seed yield increased. A relationship between nutrient internal efficiency and seed yield for the different percentiles as determined by the non-linear quantile regression offered probabilistic values for estimating nutrient uptake in soybean, providing useful information for obtaining more reliable estimates of nutrient balances at the system-level. EEA Oliveros Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Magnano, Luciana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Ortez, Osler. University of Nebraska-Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Barraco, Mariam Raquel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria General Villegas; Argentina. Fil: Barbagelata, Pedro Anibal. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina Fil: Condori, Alicia Adelina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Di Mauro, Guido. Corteva Agriscience. Predictive Agriculture; Estados Unidos Fil: Manlla, Amalia Graciela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Rotundo, José Luis. Corteva Agriscience. Predictive Agriculture; Estados Unidos Fil: García, Fernando O. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Ferrari, Manuel Carlos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina Fil: Gudelj, Vicente Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina Fil: Ciampitti, Ignacio A. Kansas State University. Department of Agronomy; Estados Unidos |
| description |
Estimation of crop nutrient demand, seed nutrient removal, and nutrient use efficiency (yield to nutrient uptake ratio) are crucial for pursuing both balanced nutrition and more sustainable farming systems. However, the estimation of the nutrient requirements as the nutrient uptake per unit of seed yields is impaired in many situations due to the narrow variation of the dataset used to obtain these values or by the overgeneralization of considering a constant value for the nutrient demand at varying yield levels. Past studies focused on other crops and using linear models for estimation of the nutrient requirements, but not yet for soybeans (Glycine max L.). The aims of this research study were to: (i) quantify nitrogen (N), phosphorus (P), potassium (K), and sulfur (S) requirements in soybean and (ii) compare linear and non-linear (spherical) models in their relationship between plant and seed nutrient content all relative to seed yield at varying probabilities utilizing quantile regression. A large dataset from different studies conducted between 2009–2018 period, including data of seed yield, total biomass at physiological maturity, and N, P, K, and S uptake. Soybean seed yield ranged from 955 to 6525 kg ha−1, aboveground biomass from 1990 to 15,814 kg ha−1, and harvest index from 0.16 to 0.57. On average, nutrient uptake was 261 kg N ha−1, 25 kg P ha−1, 133 kg K ha−1, and 16 kg S ha−1 (N:P:K:S ratio = 17:1.6:8.5:1), while nutrient content in seeds averaged 191 kg N ha−1, 17 kg P ha−1, 54 kg K ha−1, and 9 kg S ha−1 (N:P:K:S ratio = 21:1.8:5.8:1). The spherical model described better than the linear model the relationship between plant nutrient uptake or nutrient content in seeds with seed yield in soybean, and thus, nutrient requirements per unit of yield decreased as seed yield increased. A relationship between nutrient internal efficiency and seed yield for the different percentiles as determined by the non-linear quantile regression offered probabilistic values for estimating nutrient uptake in soybean, providing useful information for obtaining more reliable estimates of nutrient balances at the system-level. |
| publishDate |
2021 |
| dc.date.none.fl_str_mv |
2021-05-03T13:21:42Z 2021-05-03T13:21:42Z 2021-07 |
| 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/20.500.12123/9247 https://www.sciencedirect.com/science/article/abs/pii/S1161030121000617 1161-0301 https://doi.org/10.1016/j.eja.2021.126289 |
| url |
http://hdl.handle.net/20.500.12123/9247 https://www.sciencedirect.com/science/article/abs/pii/S1161030121000617 https://doi.org/10.1016/j.eja.2021.126289 |
| identifier_str_mv |
1161-0301 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repograntAgreement/INTA/PNCER-022421/AR./Diagnostico, reposición de macronutrientes y tecnología de la fertilización. info:eu-repograntAgreement/INTA/PNCYO-1127033/AR./Manejo nutricional de cereales y oleaginosas para la intensificación sustentable de los sistemas productivos |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
| eu_rights_str_mv |
restrictedAccess |
| 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 |
European Journal of Agronomy 127 : 126289 (July 2021) 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 |
| _version_ |
1842341386847780864 |
| score |
12.623145 |