Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species
The allocation of non-structural carbohydrates (NSCs) to reserves constitutes an important physiological mechanism associated with tree growth and survival. However, procedures for measuring NSC in plant tissue are expensive and time-consuming. Near-infrared spectroscopy (NIRS) is a high-throughput...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/22591
- Acceso en línea:
- https://doi.org/10.1111/2041-210X.12391
https://repository.urosario.edu.co/handle/10336/22591
- Palabra clave:
- Carbohydrate reserves
Carbon allocation
CARS-PLSR
Multivariate calibration
Spectroscopy
Starch
Sugars
- Rights
- License
- Abierto (Texto Completo)
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a96d9b86-040b-4d84-bf49-93f8d9cc09fb8041617760055c0cee3-186d-4fac-b9b4-f92e7fa6f7be86419a41-4cb5-485c-92b0-9db958c0ecb728eb26f0-45ea-4ad6-8acd-7c37217c28103496ded7-fb3a-4d8d-affa-7ed3f925970ffc8aa420-5591-479d-a94c-ce36b712d94c2020-05-25T23:57:03Z2020-05-25T23:57:03Z2015The allocation of non-structural carbohydrates (NSCs) to reserves constitutes an important physiological mechanism associated with tree growth and survival. However, procedures for measuring NSC in plant tissue are expensive and time-consuming. Near-infrared spectroscopy (NIRS) is a high-throughput technology that has the potential to infer the concentration of organic constituents for a large number of samples in a rapid and inexpensive way based on empirical calibrations with chemical analysis. The main objectives of this study were (i) to develop a general NSC concentration calibration that integrates various forms of variation such as tree species and tissue types and (ii) to identify characteristic spectral regions associated with NSC molecules. In total, 180 samples from different tree organs (root, stem, branch, leaf) belonging to 73 tree species from tropical and temperate biomes were analysed. Statistical relationships between NSC concentration and NIRS spectra were assessed using partial least squares regression (PLSR) and a variable selection procedure (competitive adaptive reweighted sampling, CARS), in order to identify key wavelengths. Parsimonious and accurate calibration models were obtained for total NSC (r2 of 0·91, RMSE of 1·34% in external validation), followed by starch (r2 = 0·85 and RMSE = 1·20%) and sugars (r2 = 0·82 and RMSE = 1·10%). Key wavelengths coincided among these models and were mainly located in the 1740-1800, 2100-2300 and 2410-2490 nm spectral regions. This study demonstrates the ability of general calibration model to infer NSC concentrations across species and tissue types in a rapid and cost-effective way. The estimation of NSC in plants using NIRS therefore serves as a tool for functional biodiversity research, in particular for the study of the growth-survival trade-off and its implications in response to changing environmental conditions, including growth limitation and mortality. © 2015 British Ecological Society.application/pdfhttps://doi.org/10.1111/2041-210X.123912041210Xhttps://repository.urosario.edu.co/handle/10336/22591engBritish Ecological Society1025No. 91018Methods in Ecology and EvolutionVol. 6Methods in Ecology and Evolution, ISSN:2041210X, Vol.6, No.9 (2015); pp. 1018-1025https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941763635&doi=10.1111%2f2041-210X.12391&partnerID=40&md5=f16a70c32ffac83e37b5732df43d5d15Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCarbohydrate reservesCarbon allocationCARS-PLSRMultivariate calibrationSpectroscopyStarchSugarsNear-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree speciesarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Ramirez, Jorge A.Posada Hostettler, Juan Manuel RobertoHanda, I. TanyaHoch, GünterVohland, MichaelMessier, ChristianReu, Björn10336/22591oai:repository.urosario.edu.co:10336/225912022-05-02 07:37:16.29022https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
title |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
spellingShingle |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species Carbohydrate reserves Carbon allocation CARS-PLSR Multivariate calibration Spectroscopy Starch Sugars |
title_short |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
title_full |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
title_fullStr |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
title_full_unstemmed |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
title_sort |
Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species |
dc.subject.keyword.spa.fl_str_mv |
Carbohydrate reserves Carbon allocation CARS-PLSR Multivariate calibration Spectroscopy Starch Sugars |
topic |
Carbohydrate reserves Carbon allocation CARS-PLSR Multivariate calibration Spectroscopy Starch Sugars |
description |
The allocation of non-structural carbohydrates (NSCs) to reserves constitutes an important physiological mechanism associated with tree growth and survival. However, procedures for measuring NSC in plant tissue are expensive and time-consuming. Near-infrared spectroscopy (NIRS) is a high-throughput technology that has the potential to infer the concentration of organic constituents for a large number of samples in a rapid and inexpensive way based on empirical calibrations with chemical analysis. The main objectives of this study were (i) to develop a general NSC concentration calibration that integrates various forms of variation such as tree species and tissue types and (ii) to identify characteristic spectral regions associated with NSC molecules. In total, 180 samples from different tree organs (root, stem, branch, leaf) belonging to 73 tree species from tropical and temperate biomes were analysed. Statistical relationships between NSC concentration and NIRS spectra were assessed using partial least squares regression (PLSR) and a variable selection procedure (competitive adaptive reweighted sampling, CARS), in order to identify key wavelengths. Parsimonious and accurate calibration models were obtained for total NSC (r2 of 0·91, RMSE of 1·34% in external validation), followed by starch (r2 = 0·85 and RMSE = 1·20%) and sugars (r2 = 0·82 and RMSE = 1·10%). Key wavelengths coincided among these models and were mainly located in the 1740-1800, 2100-2300 and 2410-2490 nm spectral regions. This study demonstrates the ability of general calibration model to infer NSC concentrations across species and tissue types in a rapid and cost-effective way. The estimation of NSC in plants using NIRS therefore serves as a tool for functional biodiversity research, in particular for the study of the growth-survival trade-off and its implications in response to changing environmental conditions, including growth limitation and mortality. © 2015 British Ecological Society. |
publishDate |
2015 |
dc.date.created.spa.fl_str_mv |
2015 |
dc.date.accessioned.none.fl_str_mv |
2020-05-25T23:57:03Z |
dc.date.available.none.fl_str_mv |
2020-05-25T23:57:03Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1111/2041-210X.12391 |
dc.identifier.issn.none.fl_str_mv |
2041210X |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/22591 |
url |
https://doi.org/10.1111/2041-210X.12391 https://repository.urosario.edu.co/handle/10336/22591 |
identifier_str_mv |
2041210X |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
1025 |
dc.relation.citationIssue.none.fl_str_mv |
No. 9 |
dc.relation.citationStartPage.none.fl_str_mv |
1018 |
dc.relation.citationTitle.none.fl_str_mv |
Methods in Ecology and Evolution |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 6 |
dc.relation.ispartof.spa.fl_str_mv |
Methods in Ecology and Evolution, ISSN:2041210X, Vol.6, No.9 (2015); pp. 1018-1025 |
dc.relation.uri.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941763635&doi=10.1111%2f2041-210X.12391&partnerID=40&md5=f16a70c32ffac83e37b5732df43d5d15 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
British Ecological Society |
institution |
Universidad del Rosario |
dc.source.instname.spa.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167607188652032 |