Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture

Autores
Laplacette, Celina María; Berone, German Dario; Utsumi, Santiago A.; Insua, Juan Ramón
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Accurate estimation of herbage mass is crucial for managing pastoral livestock systems. The Normalized Difference Vegetation Index (NDVI) from Unmanned Aerial Vehicle (UAV) sensors shows promise for high-resolution estimations of pasture herbage mass, but it is still unknown how this method differs among forage species, seasons, and pasture management practices. A commercial sensor was calibrated to predict herbage mass using NDVI. Additionally, the effect of different forage species, days of regrowth, and nitrogen (N) status on the relationship between NDVI and herbage mass was evaluated. Two pastures of tall wheatgrass (Thinopyrum ponticum) and tall fescue (Festuca arundinacea), divided into 30 and 72 plots, respectively, were assessed during spring and autumn regrowth over two years in Balcarce, Argentina. Doses of 0, 50, and 100 kg N ha−1 were applied to tall wheatgrass, and 0, 50, 100, 200, 400, and 600 kg N ha−1 were applied to tall fescue to create variability in herbage mass and N status. Exponential regression models of herbage mass (y) fitted against NDVI (x) showed an average R2 of 0.83 ± 0.04 and a mean absolute error of 170 ± 60 kg DM ha−1. The relationship between NDVI and herbage mass differed (p ≤ 0.05) between species, seasons, and regrowth stage, but was not influenced by N status (p > 0.05). Results suggest that accurate predictions of herbage mass using NDVI measurements by an UAV require frequent model recalibrations to account for observed differences among forage species, days of regrowth, and years.
EEA Balcarce
Fil: Laplacette, Celina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Laplacette, Celina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Berone, Germán Dario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Berone, Germán Dario. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
Fil: Utsumi, Santiago. New Mexico State University. Department of Animal and Range Sciences; Estados Unidos
Fil: Insúa, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Insúa, Juan. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
Fuente
Agriculture 15 (5) : 492. (March 2025)
Materia
Teledetección
Vehículos Aéreos no Tripulados
Calibración
Pastizales
Índice Normalizado Diferencial de la Vegetación
Remote Sensing
Unmanned Aerial Vehicles
Calibration
Pastures
Normalized Difference Vegetation Index
NDVI
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/21566
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oai_identifier_str oai:localhost:20.500.12123/21566
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spelling Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate PastureLaplacette, Celina MaríaBerone, German DarioUtsumi, Santiago A.Insua, Juan RamónTeledetecciónVehículos Aéreos no TripuladosCalibraciónPastizalesÍndice Normalizado Diferencial de la VegetaciónRemote SensingUnmanned Aerial VehiclesCalibrationPasturesNormalized Difference Vegetation IndexNDVIAccurate estimation of herbage mass is crucial for managing pastoral livestock systems. The Normalized Difference Vegetation Index (NDVI) from Unmanned Aerial Vehicle (UAV) sensors shows promise for high-resolution estimations of pasture herbage mass, but it is still unknown how this method differs among forage species, seasons, and pasture management practices. A commercial sensor was calibrated to predict herbage mass using NDVI. Additionally, the effect of different forage species, days of regrowth, and nitrogen (N) status on the relationship between NDVI and herbage mass was evaluated. Two pastures of tall wheatgrass (Thinopyrum ponticum) and tall fescue (Festuca arundinacea), divided into 30 and 72 plots, respectively, were assessed during spring and autumn regrowth over two years in Balcarce, Argentina. Doses of 0, 50, and 100 kg N ha−1 were applied to tall wheatgrass, and 0, 50, 100, 200, 400, and 600 kg N ha−1 were applied to tall fescue to create variability in herbage mass and N status. Exponential regression models of herbage mass (y) fitted against NDVI (x) showed an average R2 of 0.83 ± 0.04 and a mean absolute error of 170 ± 60 kg DM ha−1. The relationship between NDVI and herbage mass differed (p ≤ 0.05) between species, seasons, and regrowth stage, but was not influenced by N status (p > 0.05). Results suggest that accurate predictions of herbage mass using NDVI measurements by an UAV require frequent model recalibrations to account for observed differences among forage species, days of regrowth, and years.EEA BalcarceFil: Laplacette, Celina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Laplacette, Celina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Berone, Germán Dario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Berone, Germán Dario. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaFil: Utsumi, Santiago. New Mexico State University. Department of Animal and Range Sciences; Estados UnidosFil: Insúa, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Insúa, Juan. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaMDPI2025-03-06T13:53:28Z2025-03-06T13:53:28Z2025-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/21566https://www.mdpi.com/2077-0472/15/5/4922077-0472https://doi.org/10.3390/agriculture15050492Agriculture 15 (5) : 492. (March 2025)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/2019-PE-E1-I007-001, Incremento sostenible de la producción y utilización de pasturas y forrajes conservadosinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:47:10Zoai:localhost:20.500.12123/21566instacron: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 13:47:11.345INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
title Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
spellingShingle Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
Laplacette, Celina María
Teledetección
Vehículos Aéreos no Tripulados
Calibración
Pastizales
Índice Normalizado Diferencial de la Vegetación
Remote Sensing
Unmanned Aerial Vehicles
Calibration
Pastures
Normalized Difference Vegetation Index
NDVI
title_short Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
title_full Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
title_fullStr Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
title_full_unstemmed Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
title_sort Calibration of an Unmanned Aerial Vehicle for Prediction of Herbage Mass in Temperate Pasture
dc.creator.none.fl_str_mv Laplacette, Celina María
Berone, German Dario
Utsumi, Santiago A.
Insua, Juan Ramón
author Laplacette, Celina María
author_facet Laplacette, Celina María
Berone, German Dario
Utsumi, Santiago A.
Insua, Juan Ramón
author_role author
author2 Berone, German Dario
Utsumi, Santiago A.
Insua, Juan Ramón
author2_role author
author
author
dc.subject.none.fl_str_mv Teledetección
Vehículos Aéreos no Tripulados
Calibración
Pastizales
Índice Normalizado Diferencial de la Vegetación
Remote Sensing
Unmanned Aerial Vehicles
Calibration
Pastures
Normalized Difference Vegetation Index
NDVI
topic Teledetección
Vehículos Aéreos no Tripulados
Calibración
Pastizales
Índice Normalizado Diferencial de la Vegetación
Remote Sensing
Unmanned Aerial Vehicles
Calibration
Pastures
Normalized Difference Vegetation Index
NDVI
dc.description.none.fl_txt_mv Accurate estimation of herbage mass is crucial for managing pastoral livestock systems. The Normalized Difference Vegetation Index (NDVI) from Unmanned Aerial Vehicle (UAV) sensors shows promise for high-resolution estimations of pasture herbage mass, but it is still unknown how this method differs among forage species, seasons, and pasture management practices. A commercial sensor was calibrated to predict herbage mass using NDVI. Additionally, the effect of different forage species, days of regrowth, and nitrogen (N) status on the relationship between NDVI and herbage mass was evaluated. Two pastures of tall wheatgrass (Thinopyrum ponticum) and tall fescue (Festuca arundinacea), divided into 30 and 72 plots, respectively, were assessed during spring and autumn regrowth over two years in Balcarce, Argentina. Doses of 0, 50, and 100 kg N ha−1 were applied to tall wheatgrass, and 0, 50, 100, 200, 400, and 600 kg N ha−1 were applied to tall fescue to create variability in herbage mass and N status. Exponential regression models of herbage mass (y) fitted against NDVI (x) showed an average R2 of 0.83 ± 0.04 and a mean absolute error of 170 ± 60 kg DM ha−1. The relationship between NDVI and herbage mass differed (p ≤ 0.05) between species, seasons, and regrowth stage, but was not influenced by N status (p > 0.05). Results suggest that accurate predictions of herbage mass using NDVI measurements by an UAV require frequent model recalibrations to account for observed differences among forage species, days of regrowth, and years.
EEA Balcarce
Fil: Laplacette, Celina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Laplacette, Celina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Berone, Germán Dario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Berone, Germán Dario. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
Fil: Utsumi, Santiago. New Mexico State University. Department of Animal and Range Sciences; Estados Unidos
Fil: Insúa, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Insúa, Juan. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
description Accurate estimation of herbage mass is crucial for managing pastoral livestock systems. The Normalized Difference Vegetation Index (NDVI) from Unmanned Aerial Vehicle (UAV) sensors shows promise for high-resolution estimations of pasture herbage mass, but it is still unknown how this method differs among forage species, seasons, and pasture management practices. A commercial sensor was calibrated to predict herbage mass using NDVI. Additionally, the effect of different forage species, days of regrowth, and nitrogen (N) status on the relationship between NDVI and herbage mass was evaluated. Two pastures of tall wheatgrass (Thinopyrum ponticum) and tall fescue (Festuca arundinacea), divided into 30 and 72 plots, respectively, were assessed during spring and autumn regrowth over two years in Balcarce, Argentina. Doses of 0, 50, and 100 kg N ha−1 were applied to tall wheatgrass, and 0, 50, 100, 200, 400, and 600 kg N ha−1 were applied to tall fescue to create variability in herbage mass and N status. Exponential regression models of herbage mass (y) fitted against NDVI (x) showed an average R2 of 0.83 ± 0.04 and a mean absolute error of 170 ± 60 kg DM ha−1. The relationship between NDVI and herbage mass differed (p ≤ 0.05) between species, seasons, and regrowth stage, but was not influenced by N status (p > 0.05). Results suggest that accurate predictions of herbage mass using NDVI measurements by an UAV require frequent model recalibrations to account for observed differences among forage species, days of regrowth, and years.
publishDate 2025
dc.date.none.fl_str_mv 2025-03-06T13:53:28Z
2025-03-06T13:53:28Z
2025-03
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 http://hdl.handle.net/20.500.12123/21566
https://www.mdpi.com/2077-0472/15/5/492
2077-0472
https://doi.org/10.3390/agriculture15050492
url http://hdl.handle.net/20.500.12123/21566
https://www.mdpi.com/2077-0472/15/5/492
https://doi.org/10.3390/agriculture15050492
identifier_str_mv 2077-0472
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repograntAgreement/INTA/2019-PE-E1-I007-001, Incremento sostenible de la producción y utilización de pasturas y forrajes conservados
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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 openAccess
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 MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Agriculture 15 (5) : 492. (March 2025)
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
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score 12.558318

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