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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/4205
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/4205
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling 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 Técnicas2025-10-22T11:43:20Zoai: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:34982025-10-22 11:43:21.089CONICET 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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score 12.982451

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