Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance
- Autores
- Durante, Martín; Oesterheld, Martin; Piñeiro, Gervasio; Vassallo, Maria Mercedes
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Assesing forage quantity and quality through remote sensing can facilitate grassland and pasture management. However, the high spatial and temporal variability of canopy conditions may limit the predictive accuracy of models based on reflectance measurements. The objective of this work was to develope this type of models, and to challenge their capacity to predict plant properties under a wide range of environmental conditions. We manipulated Paspalum dilatatum canopies through different stress treatments (flood, drought, nutrient availability, and control) and by artificially varying the amount of senescent biomass. We measured canopy reflectance and constructed simple models, based on either normalized vegetation indices or a few selected wavebands, to estimate biomass and to variables related to forage quality: proportion of photosynthetic vegetation and biomass C:N ratio. General models satisfactorily predicted plants properties for the whole set of environmental conditions, but failed under specific conditions such as drought (for esitmates of plant biomass), fertilization (for estimates of C:N ratio), and different levels of senescent tillers (for estimates of the proportion of photosynthetic vegetation). Where general models failed, specific models, based on different bands, achieved satisfactory accuracy. The generals models performed better when based on a few selected than when based on two-band vegetation indices, having better accuracy (higher R2)and parsimony (lower BIC). However specific models performed similarly for both approaches (similar R2 and BIC). This results indicate that these plant properties can be predicted from reflectance information under a broad range of conditions, but no for some particular conditions, where ancillary data or more complex models are probably needed to increase predictive accuracy.
Fil: Durante, Martín. 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. 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: Piñeiro, Gervasio. 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: Vassallo, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina - Materia
- Forage Quantity And Quality
- Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/4205
Ver los metadatos del registro completo
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Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectanceDurante, MartínOesterheld, MartinPiñeiro, GervasioVassallo, Maria MercedesForage Quantity And Qualityhttps://purl.org/becyt/ford/2.7https://purl.org/becyt/ford/2Assesing forage quantity and quality through remote sensing can facilitate grassland and pasture management. However, the high spatial and temporal variability of canopy conditions may limit the predictive accuracy of models based on reflectance measurements. The objective of this work was to develope this type of models, and to challenge their capacity to predict plant properties under a wide range of environmental conditions. We manipulated Paspalum dilatatum canopies through different stress treatments (flood, drought, nutrient availability, and control) and by artificially varying the amount of senescent biomass. We measured canopy reflectance and constructed simple models, based on either normalized vegetation indices or a few selected wavebands, to estimate biomass and to variables related to forage quality: proportion of photosynthetic vegetation and biomass C:N ratio. General models satisfactorily predicted plants properties for the whole set of environmental conditions, but failed under specific conditions such as drought (for esitmates of plant biomass), fertilization (for estimates of C:N ratio), and different levels of senescent tillers (for estimates of the proportion of photosynthetic vegetation). Where general models failed, specific models, based on different bands, achieved satisfactory accuracy. The generals models performed better when based on a few selected than when based on two-band vegetation indices, having better accuracy (higher R2)and parsimony (lower BIC). However specific models performed similarly for both approaches (similar R2 and BIC). This results indicate that these plant properties can be predicted from reflectance information under a broad range of conditions, but no for some particular conditions, where ancillary data or more complex models are probably needed to increase predictive accuracy.Fil: Durante, Martín. 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. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Piñeiro, Gervasio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Vassallo, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaTaylor & Francis2014-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/4205Durante, Martín; Oesterheld, Martin; Piñeiro, Gervasio; Vassallo, Maria Mercedes; Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance; Taylor & Francis; International Journal of Remote Sensing; 35; 9; 3-2014; 2963-29810143-1161enginfo:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.894658info:eu-repo/semantics/altIdentifier/doi/DOI:10.1080/01431161.2014.894658info:eu-repo/semantics/altIdentifier/issn/0143-1161info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:13:24Zoai:ri.conicet.gov.ar:11336/4205instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:13:25.244CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
title |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
spellingShingle |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance Durante, Martín Forage Quantity And Quality |
title_short |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
title_full |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
title_fullStr |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
title_full_unstemmed |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
title_sort |
Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance |
dc.creator.none.fl_str_mv |
Durante, Martín Oesterheld, Martin Piñeiro, Gervasio Vassallo, Maria Mercedes |
author |
Durante, Martín |
author_facet |
Durante, Martín Oesterheld, Martin Piñeiro, Gervasio Vassallo, Maria Mercedes |
author_role |
author |
author2 |
Oesterheld, Martin Piñeiro, Gervasio Vassallo, Maria Mercedes |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Forage Quantity And Quality |
topic |
Forage Quantity And Quality |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/2.7 https://purl.org/becyt/ford/2 |
dc.description.none.fl_txt_mv |
Assesing forage quantity and quality through remote sensing can facilitate grassland and pasture management. However, the high spatial and temporal variability of canopy conditions may limit the predictive accuracy of models based on reflectance measurements. The objective of this work was to develope this type of models, and to challenge their capacity to predict plant properties under a wide range of environmental conditions. We manipulated Paspalum dilatatum canopies through different stress treatments (flood, drought, nutrient availability, and control) and by artificially varying the amount of senescent biomass. We measured canopy reflectance and constructed simple models, based on either normalized vegetation indices or a few selected wavebands, to estimate biomass and to variables related to forage quality: proportion of photosynthetic vegetation and biomass C:N ratio. General models satisfactorily predicted plants properties for the whole set of environmental conditions, but failed under specific conditions such as drought (for esitmates of plant biomass), fertilization (for estimates of C:N ratio), and different levels of senescent tillers (for estimates of the proportion of photosynthetic vegetation). Where general models failed, specific models, based on different bands, achieved satisfactory accuracy. The generals models performed better when based on a few selected than when based on two-band vegetation indices, having better accuracy (higher R2)and parsimony (lower BIC). However specific models performed similarly for both approaches (similar R2 and BIC). This results indicate that these plant properties can be predicted from reflectance information under a broad range of conditions, but no for some particular conditions, where ancillary data or more complex models are probably needed to increase predictive accuracy. Fil: Durante, Martín. 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. 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: Piñeiro, Gervasio. 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: Vassallo, Maria Mercedes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina |
description |
Assesing forage quantity and quality through remote sensing can facilitate grassland and pasture management. However, the high spatial and temporal variability of canopy conditions may limit the predictive accuracy of models based on reflectance measurements. The objective of this work was to develope this type of models, and to challenge their capacity to predict plant properties under a wide range of environmental conditions. We manipulated Paspalum dilatatum canopies through different stress treatments (flood, drought, nutrient availability, and control) and by artificially varying the amount of senescent biomass. We measured canopy reflectance and constructed simple models, based on either normalized vegetation indices or a few selected wavebands, to estimate biomass and to variables related to forage quality: proportion of photosynthetic vegetation and biomass C:N ratio. General models satisfactorily predicted plants properties for the whole set of environmental conditions, but failed under specific conditions such as drought (for esitmates of plant biomass), fertilization (for estimates of C:N ratio), and different levels of senescent tillers (for estimates of the proportion of photosynthetic vegetation). Where general models failed, specific models, based on different bands, achieved satisfactory accuracy. The generals models performed better when based on a few selected than when based on two-band vegetation indices, having better accuracy (higher R2)and parsimony (lower BIC). However specific models performed similarly for both approaches (similar R2 and BIC). This results indicate that these plant properties can be predicted from reflectance information under a broad range of conditions, but no for some particular conditions, where ancillary data or more complex models are probably needed to increase predictive accuracy. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-03 |
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/11336/4205 Durante, Martín; Oesterheld, Martin; Piñeiro, Gervasio; Vassallo, Maria Mercedes; Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance; Taylor & Francis; International Journal of Remote Sensing; 35; 9; 3-2014; 2963-2981 0143-1161 |
url |
http://hdl.handle.net/11336/4205 |
identifier_str_mv |
Durante, Martín; Oesterheld, Martin; Piñeiro, Gervasio; Vassallo, Maria Mercedes; Estimating forage quantity and quality under different stress and senescent biomass conditions via spectral reflectance; Taylor & Francis; International Journal of Remote Sensing; 35; 9; 3-2014; 2963-2981 0143-1161 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.894658 info:eu-repo/semantics/altIdentifier/doi/DOI:10.1080/01431161.2014.894658 info:eu-repo/semantics/altIdentifier/issn/0143-1161 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844614050994978816 |
score |
13.070432 |