Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen
- Autores
- Lapaz Olveira, Adrián; Castro Franco, Mauricio; Sainz Rozas, Hernan Rene; Carciochi, Walter; Balzarini, Mónica; Avila, Oscar; Ciampitti, Ignacio; Reussi Calvo, Nahuel Ignacio
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Nitrogen (N) nutrition index (NNI) is a reliable indicator of plant N status for field crops, but its determination is both labor- and cost-intensive. The utilization of remote sensing approaches for monitoring N, mainly in relevant crops such as of corn (Zea mays L.), will be critical for enhancing effective use of this nutrient. Therefore, the aim of this study was to assess NNI predicted from optical and C-band Synthetic Aperture Radar (C-SAR) satellite data and available soil N (Nav) at different vegetative growth stages for corn crop. Eleven field studies were conducted in the Pampas region (Argentina), applying five fertilizer N rates (0, 60, 120, 180, and 240 kg N ha−1), all at sowing time. Plant samples were collected at sixth-leaf (V6), tenth-leaf (V10), fourteen-leaf (V14), and flowering (R1). Using linear regression models, NNI was best predicted using only optical satellite data from V6 to V14, and integrating optical with C-SAR plus Nav at R1. The best monitoring model integrated vegetation spectral indices, C-SAR and Nav data at V10 with an adjusted R2 of 0.75 achieved during calibration in the northern Pampa. During validation, it predicted NNI with an RMSE of 0.14 and a MAPE of 12% in the southeastern Pampa. The red-edge spectrum and Local Incidence Angle of C-SAR were necessary to monitor the corn N status via prediction of NNI. Thus, this study provided empirical models to remotely sensed corn N status within fields during vegetative period, serving as a foundational data for guiding future N management.
EEA Balcarce
Fil: Lapaz Olveira, Adrián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
Fil: Lapaz Olveira, Adrián. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.
Fil: Lapaz Olveira, Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Castro Franco, Mauricio. Universidad de los Llanos. Facultad de Ciencias Agropecuarias y Recursos Naturales; Colombia.
Fil: Saínz Rozas, Hernán. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.
Fil: Saínz Rozas, Hernán. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina.
Fil: Carciochi, Walter. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
Fil: Carciochi, Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Balzarini, Mónica. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Balzarini, Mónica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.
Fil: Balzarini, Mónica. Unidad de Fitopatología Y Modelización Agrícola; Argentina.
Fil: Avila, Oscar. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
Fil: Avila, Oscar. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.
Fil: Ciampitti, Ignacio. Kansas State University. Department of Agronomy; Estados Unidos.
Fil: Reussi Calvo, Nahuel. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
Fil: Reussi Calvo, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. - Fuente
- Precision Agriculture : 1-15 (Published: 04 August 2023)
- Materia
-
Maíz
Nitrógeno
Índices de Vegetación
Nutrición
Vigilancia
Satélites
Suelo
Maize
Nitrogen
Vegetation Index
Nutrition
Monitoring
Satellites
Soil - Nivel de accesibilidad
- acceso restringido
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/15248
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Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogenLapaz Olveira, AdriánCastro Franco, MauricioSainz Rozas, Hernan ReneCarciochi, WalterBalzarini, MónicaAvila, OscarCiampitti, IgnacioReussi Calvo, Nahuel IgnacioMaízNitrógenoÍndices de VegetaciónNutriciónVigilanciaSatélitesSueloMaizeNitrogenVegetation IndexNutritionMonitoringSatellitesSoilNitrogen (N) nutrition index (NNI) is a reliable indicator of plant N status for field crops, but its determination is both labor- and cost-intensive. The utilization of remote sensing approaches for monitoring N, mainly in relevant crops such as of corn (Zea mays L.), will be critical for enhancing effective use of this nutrient. Therefore, the aim of this study was to assess NNI predicted from optical and C-band Synthetic Aperture Radar (C-SAR) satellite data and available soil N (Nav) at different vegetative growth stages for corn crop. Eleven field studies were conducted in the Pampas region (Argentina), applying five fertilizer N rates (0, 60, 120, 180, and 240 kg N ha−1), all at sowing time. Plant samples were collected at sixth-leaf (V6), tenth-leaf (V10), fourteen-leaf (V14), and flowering (R1). Using linear regression models, NNI was best predicted using only optical satellite data from V6 to V14, and integrating optical with C-SAR plus Nav at R1. The best monitoring model integrated vegetation spectral indices, C-SAR and Nav data at V10 with an adjusted R2 of 0.75 achieved during calibration in the northern Pampa. During validation, it predicted NNI with an RMSE of 0.14 and a MAPE of 12% in the southeastern Pampa. The red-edge spectrum and Local Incidence Angle of C-SAR were necessary to monitor the corn N status via prediction of NNI. Thus, this study provided empirical models to remotely sensed corn N status within fields during vegetative period, serving as a foundational data for guiding future N management.EEA BalcarceFil: Lapaz Olveira, Adrián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Lapaz Olveira, Adrián. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.Fil: Lapaz Olveira, Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Castro Franco, Mauricio. Universidad de los Llanos. Facultad de Ciencias Agropecuarias y Recursos Naturales; Colombia.Fil: Saínz Rozas, Hernán. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.Fil: Saínz Rozas, Hernán. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina.Fil: Carciochi, Walter. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Carciochi, Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Balzarini, Mónica. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Balzarini, Mónica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Balzarini, Mónica. Unidad de Fitopatología Y Modelización Agrícola; Argentina.Fil: Avila, Oscar. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Avila, Oscar. Agencia Nacional de Promoción Científica y Tecnológica; Argentina.Fil: Ciampitti, Ignacio. Kansas State University. Department of Agronomy; Estados Unidos.Fil: Reussi Calvo, Nahuel. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.Fil: Reussi Calvo, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Springer2023-09-19T16:39:04Z2023-09-19T16:39:04Z2023-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/15248https://link.springer.com/article/10.1007/s11119-023-10054-41573-1618 (online)1385-2256 (print)https://doi.org/10.1007/s11119-023-10054-4Precision Agriculture : 1-15 (Published: 04 August 2023)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/2019-PE-E9-I177-001, Desarrollo y aplicación de tecnologías de mecanización, precisión y digitalización de la Agriculturainfo:eu-repo/semantics/restrictedAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:46:06Zoai:localhost:20.500.12123/15248instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:46:07.105INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
title |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
spellingShingle |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen Lapaz Olveira, Adrián Maíz Nitrógeno Índices de Vegetación Nutrición Vigilancia Satélites Suelo Maize Nitrogen Vegetation Index Nutrition Monitoring Satellites Soil |
title_short |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
title_full |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
title_fullStr |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
title_full_unstemmed |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
title_sort |
Monitoring corn nitrogen nutrition index from optical and synthetic aperture radar satellite data and soil available nitrogen |
dc.creator.none.fl_str_mv |
Lapaz Olveira, Adrián Castro Franco, Mauricio Sainz Rozas, Hernan Rene Carciochi, Walter Balzarini, Mónica Avila, Oscar Ciampitti, Ignacio Reussi Calvo, Nahuel Ignacio |
author |
Lapaz Olveira, Adrián |
author_facet |
Lapaz Olveira, Adrián Castro Franco, Mauricio Sainz Rozas, Hernan Rene Carciochi, Walter Balzarini, Mónica Avila, Oscar Ciampitti, Ignacio Reussi Calvo, Nahuel Ignacio |
author_role |
author |
author2 |
Castro Franco, Mauricio Sainz Rozas, Hernan Rene Carciochi, Walter Balzarini, Mónica Avila, Oscar Ciampitti, Ignacio Reussi Calvo, Nahuel Ignacio |
author2_role |
author author author author author author author |
dc.subject.none.fl_str_mv |
Maíz Nitrógeno Índices de Vegetación Nutrición Vigilancia Satélites Suelo Maize Nitrogen Vegetation Index Nutrition Monitoring Satellites Soil |
topic |
Maíz Nitrógeno Índices de Vegetación Nutrición Vigilancia Satélites Suelo Maize Nitrogen Vegetation Index Nutrition Monitoring Satellites Soil |
dc.description.none.fl_txt_mv |
Nitrogen (N) nutrition index (NNI) is a reliable indicator of plant N status for field crops, but its determination is both labor- and cost-intensive. The utilization of remote sensing approaches for monitoring N, mainly in relevant crops such as of corn (Zea mays L.), will be critical for enhancing effective use of this nutrient. Therefore, the aim of this study was to assess NNI predicted from optical and C-band Synthetic Aperture Radar (C-SAR) satellite data and available soil N (Nav) at different vegetative growth stages for corn crop. Eleven field studies were conducted in the Pampas region (Argentina), applying five fertilizer N rates (0, 60, 120, 180, and 240 kg N ha−1), all at sowing time. Plant samples were collected at sixth-leaf (V6), tenth-leaf (V10), fourteen-leaf (V14), and flowering (R1). Using linear regression models, NNI was best predicted using only optical satellite data from V6 to V14, and integrating optical with C-SAR plus Nav at R1. The best monitoring model integrated vegetation spectral indices, C-SAR and Nav data at V10 with an adjusted R2 of 0.75 achieved during calibration in the northern Pampa. During validation, it predicted NNI with an RMSE of 0.14 and a MAPE of 12% in the southeastern Pampa. The red-edge spectrum and Local Incidence Angle of C-SAR were necessary to monitor the corn N status via prediction of NNI. Thus, this study provided empirical models to remotely sensed corn N status within fields during vegetative period, serving as a foundational data for guiding future N management. EEA Balcarce Fil: Lapaz Olveira, Adrián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Fil: Lapaz Olveira, Adrián. Agencia Nacional de Promoción Científica y Tecnológica; Argentina. Fil: Lapaz Olveira, Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Castro Franco, Mauricio. Universidad de los Llanos. Facultad de Ciencias Agropecuarias y Recursos Naturales; Colombia. Fil: Saínz Rozas, Hernán. Agencia Nacional de Promoción Científica y Tecnológica; Argentina. Fil: Saínz Rozas, Hernán. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Innovación para la Producción Agropecuaria y el Desarrollo Sostenible; Argentina. Fil: Carciochi, Walter. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Fil: Carciochi, Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Balzarini, Mónica. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: Balzarini, Mónica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina. Fil: Balzarini, Mónica. Unidad de Fitopatología Y Modelización Agrícola; Argentina. Fil: Avila, Oscar. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Fil: Avila, Oscar. Agencia Nacional de Promoción Científica y Tecnológica; Argentina. Fil: Ciampitti, Ignacio. Kansas State University. Department of Agronomy; Estados Unidos. Fil: Reussi Calvo, Nahuel. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Fil: Reussi Calvo, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. |
description |
Nitrogen (N) nutrition index (NNI) is a reliable indicator of plant N status for field crops, but its determination is both labor- and cost-intensive. The utilization of remote sensing approaches for monitoring N, mainly in relevant crops such as of corn (Zea mays L.), will be critical for enhancing effective use of this nutrient. Therefore, the aim of this study was to assess NNI predicted from optical and C-band Synthetic Aperture Radar (C-SAR) satellite data and available soil N (Nav) at different vegetative growth stages for corn crop. Eleven field studies were conducted in the Pampas region (Argentina), applying five fertilizer N rates (0, 60, 120, 180, and 240 kg N ha−1), all at sowing time. Plant samples were collected at sixth-leaf (V6), tenth-leaf (V10), fourteen-leaf (V14), and flowering (R1). Using linear regression models, NNI was best predicted using only optical satellite data from V6 to V14, and integrating optical with C-SAR plus Nav at R1. The best monitoring model integrated vegetation spectral indices, C-SAR and Nav data at V10 with an adjusted R2 of 0.75 achieved during calibration in the northern Pampa. During validation, it predicted NNI with an RMSE of 0.14 and a MAPE of 12% in the southeastern Pampa. The red-edge spectrum and Local Incidence Angle of C-SAR were necessary to monitor the corn N status via prediction of NNI. Thus, this study provided empirical models to remotely sensed corn N status within fields during vegetative period, serving as a foundational data for guiding future N management. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-09-19T16:39:04Z 2023-09-19T16:39:04Z 2023-08 |
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/20.500.12123/15248 https://link.springer.com/article/10.1007/s11119-023-10054-4 1573-1618 (online) 1385-2256 (print) https://doi.org/10.1007/s11119-023-10054-4 |
url |
http://hdl.handle.net/20.500.12123/15248 https://link.springer.com/article/10.1007/s11119-023-10054-4 https://doi.org/10.1007/s11119-023-10054-4 |
identifier_str_mv |
1573-1618 (online) 1385-2256 (print) |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repograntAgreement/INTA/2019-PE-E9-I177-001, Desarrollo y aplicación de tecnologías de mecanización, precisión y digitalización de la Agricultura |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess 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 |
restrictedAccess |
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 |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
Precision Agriculture : 1-15 (Published: 04 August 2023) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
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INTA Digital (INTA) |
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INTA Digital (INTA) |
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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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