Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage
- Autores
- Irisarri, Jorge Gonzalo Nicolás; Durante, Martin; Derner, Justin D.; Oesterheld, Martin; Augustine, David J.
- Año de publicación
- 2022
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.
EEA Concepción del Uruguay
Fil: Irisarri, Jorge Gonzalo Nicolás. Rothamsted Research. Sustainable Agriculture Sciences; Reino Unido
Fil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; Argentina
Fil: Durante, Martin. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; Uruguay
Fil: Derner, Justin D. United States Department of Agriculture-Agricultural Research Service. Rangeland Resources Research Unit; Estados Unidos
Fil: Oesterheld, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Oesterheld, Martin. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Augustine, David J.. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados Unidos - Fuente
- Remote Sensing 14 (4) : 854 (February 2022)
- Materia
-
Forrajes
Teledetección
Proteina Bruta
Evaluación de Riesgos
Pastoreo
Ganado Bovino
Forage
Remote Sensing
Crude Protein
Risk Assessment
Grazing
Cattle - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/11480
Ver los metadatos del registro completo
id |
INTADig_a298db1d1afafb5fb1da05de23fcc0ff |
---|---|
oai_identifier_str |
oai:localhost:20.500.12123/11480 |
network_acronym_str |
INTADig |
repository_id_str |
l |
network_name_str |
INTA Digital (INTA) |
spelling |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe ForageIrisarri, Jorge Gonzalo NicolásDurante, MartinDerner, Justin D.Oesterheld, MartinAugustine, David J.ForrajesTeledetecciónProteina BrutaEvaluación de RiesgosPastoreoGanado BovinoForageRemote SensingCrude ProteinRisk AssessmentGrazingCattleIn the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.EEA Concepción del UruguayFil: Irisarri, Jorge Gonzalo Nicolás. Rothamsted Research. Sustainable Agriculture Sciences; Reino UnidoFil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Durante, Martin. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; UruguayFil: Derner, Justin D. United States Department of Agriculture-Agricultural Research Service. Rangeland Resources Research Unit; Estados UnidosFil: Oesterheld, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Oesterheld, Martin. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Augustine, David J.. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados UnidosMDPI2022-03-23T14:42:39Z2022-03-23T14:42:39Z2022-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/11480https://www.mdpi.com/2072-4292/14/4/8542072-4292https://doi.org/10.3390/rs14040854Remote Sensing 14 (4) : 854 (February 2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo: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)2025-09-29T13:45:30Zoai:localhost:20.500.12123/11480instacron: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 13:45:30.913INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
title |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
spellingShingle |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage Irisarri, Jorge Gonzalo Nicolás Forrajes Teledetección Proteina Bruta Evaluación de Riesgos Pastoreo Ganado Bovino Forage Remote Sensing Crude Protein Risk Assessment Grazing Cattle |
title_short |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
title_full |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
title_fullStr |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
title_full_unstemmed |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
title_sort |
Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage |
dc.creator.none.fl_str_mv |
Irisarri, Jorge Gonzalo Nicolás Durante, Martin Derner, Justin D. Oesterheld, Martin Augustine, David J. |
author |
Irisarri, Jorge Gonzalo Nicolás |
author_facet |
Irisarri, Jorge Gonzalo Nicolás Durante, Martin Derner, Justin D. Oesterheld, Martin Augustine, David J. |
author_role |
author |
author2 |
Durante, Martin Derner, Justin D. Oesterheld, Martin Augustine, David J. |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Forrajes Teledetección Proteina Bruta Evaluación de Riesgos Pastoreo Ganado Bovino Forage Remote Sensing Crude Protein Risk Assessment Grazing Cattle |
topic |
Forrajes Teledetección Proteina Bruta Evaluación de Riesgos Pastoreo Ganado Bovino Forage Remote Sensing Crude Protein Risk Assessment Grazing Cattle |
dc.description.none.fl_txt_mv |
In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle. EEA Concepción del Uruguay Fil: Irisarri, Jorge Gonzalo Nicolás. Rothamsted Research. Sustainable Agriculture Sciences; Reino Unido Fil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; Argentina Fil: Durante, Martin. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; Uruguay Fil: Derner, Justin D. United States Department of Agriculture-Agricultural Research Service. Rangeland Resources Research Unit; Estados Unidos Fil: Oesterheld, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Oesterheld, Martin. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Augustine, David J.. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados Unidos |
description |
In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-23T14:42:39Z 2022-03-23T14:42:39Z 2022-02 |
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/20.500.12123/11480 https://www.mdpi.com/2072-4292/14/4/854 2072-4292 https://doi.org/10.3390/rs14040854 |
url |
http://hdl.handle.net/20.500.12123/11480 https://www.mdpi.com/2072-4292/14/4/854 https://doi.org/10.3390/rs14040854 |
identifier_str_mv |
2072-4292 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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 |
Remote Sensing 14 (4) : 854 (February 2022) 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_ |
1844619163152154624 |
score |
12.559606 |