Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy

Silicon (Si) is one of the most common elements in the earth bedrock, and its continental cycle is strongly biologically controlled. Yet, research on the biogeochemical cycle of Si in ecosystems is hampered by the time and cost associated with the currently used chemical analysis methods. Here, we a...

Full description

Bibliographic Details
Main Authors: Bråthen, Kari Anne, Ancin-Murguzur, Francisco Javier
Format: Dataset
Language:unknown
Published: DataverseNO 2019
Subjects:
Online Access:https://search.dataone.org/view/sha256:db4e8cd3a3bab2f7ed0031fc8a7ff0ba07080410b126304cbd8ad8d08c5dc355
_version_ 1833938551208673280
author Bråthen, Kari Anne
Ancin-Murguzur, Francisco Javier
author_facet Bråthen, Kari Anne
Ancin-Murguzur, Francisco Javier
author_sort Bråthen, Kari Anne
collection DataverseNO (via DataONE)
description Silicon (Si) is one of the most common elements in the earth bedrock, and its continental cycle is strongly biologically controlled. Yet, research on the biogeochemical cycle of Si in ecosystems is hampered by the time and cost associated with the currently used chemical analysis methods. Here, we assessed the suitability of Near Infrared Reflectance Spectroscopy (NIRS) for measuring Si content in plant tissues. NIR spectra depend on the characteristics of the present bonds between H and N, C and O, which can be calibrated against concentrations of various compounds. Because Si in plants always occurs as hydrated condensates of orthosilicic acid (Si(OH)4), linked to organic biomolecules, we hypothesized that NIRS is suitable for measuring Si content in plants across a range of plant species. We based our testing on 442 samples of 29 plant species belonging to a range of growth forms. We calibrated the NIRS method against a well-established plant Si analysis method by using partial least-squares regression. Si concentrations ranged from detection limit (0.24 ppmSi) to 7.8% Si on dry weight and were well predicted by NIRS. The model fit with validation data was good across all plant species (n = 141, R2 = 0.90, RMSEP = 0.24), but improved when only graminoids were modeled (n = 66, R2 = 0.95, RMSEP = 0.10). A species specific model for the grass Deschampsia cespitosa showed even slightly better results than the model for all graminoids (n = 16, R2 = 0.93, RMSEP = 0.015). We show for the first time that NIRS is applicable for determining plant Si concentration across a range of plant species and growth forms, and represents a time- and cost-effective alternative to the chemical Si analysis methods. As NIRS can be applied concurrently to a range of plant organic constituents, it opens up unprecedented research possibilities for studying interrelations between Si and other plant compounds in vegetation, and for addressing the role of Si in ecosystems across a range of Si research domains.
format Dataset
genre Fennoscandia
genre_facet Fennoscandia
id dataone:sha256:db4e8cd3a3bab2f7ed0031fc8a7ff0ba07080410b126304cbd8ad8d08c5dc355
institution Open Polar
language unknown
op_collection_id dataone:urn:node:DVNO
publishDate 2019
publisher DataverseNO
record_format openpolar
spelling dataone:sha256:db4e8cd3a3bab2f7ed0031fc8a7ff0ba07080410b126304cbd8ad8d08c5dc355 2025-06-03T18:49:43+00:00 Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy Bråthen, Kari Anne Ancin-Murguzur, Francisco Javier 2019-03-08T00:00:00Z https://search.dataone.org/view/sha256:db4e8cd3a3bab2f7ed0031fc8a7ff0ba07080410b126304cbd8ad8d08c5dc355 unknown DataverseNO ecosystem research plant silica concentration Orthosilicic acid Deschampsia cespitosa Fennoscandia plant defense mechanism graminoids Earth and Environmental Sciences calibration Near Infrared Reflectance Spectroscopy (NIRS) Dataset 2019 dataone:urn:node:DVNO 2025-06-03T18:16:48Z Silicon (Si) is one of the most common elements in the earth bedrock, and its continental cycle is strongly biologically controlled. Yet, research on the biogeochemical cycle of Si in ecosystems is hampered by the time and cost associated with the currently used chemical analysis methods. Here, we assessed the suitability of Near Infrared Reflectance Spectroscopy (NIRS) for measuring Si content in plant tissues. NIR spectra depend on the characteristics of the present bonds between H and N, C and O, which can be calibrated against concentrations of various compounds. Because Si in plants always occurs as hydrated condensates of orthosilicic acid (Si(OH)4), linked to organic biomolecules, we hypothesized that NIRS is suitable for measuring Si content in plants across a range of plant species. We based our testing on 442 samples of 29 plant species belonging to a range of growth forms. We calibrated the NIRS method against a well-established plant Si analysis method by using partial least-squares regression. Si concentrations ranged from detection limit (0.24 ppmSi) to 7.8% Si on dry weight and were well predicted by NIRS. The model fit with validation data was good across all plant species (n = 141, R2 = 0.90, RMSEP = 0.24), but improved when only graminoids were modeled (n = 66, R2 = 0.95, RMSEP = 0.10). A species specific model for the grass Deschampsia cespitosa showed even slightly better results than the model for all graminoids (n = 16, R2 = 0.93, RMSEP = 0.015). We show for the first time that NIRS is applicable for determining plant Si concentration across a range of plant species and growth forms, and represents a time- and cost-effective alternative to the chemical Si analysis methods. As NIRS can be applied concurrently to a range of plant organic constituents, it opens up unprecedented research possibilities for studying interrelations between Si and other plant compounds in vegetation, and for addressing the role of Si in ecosystems across a range of Si research domains. Dataset Fennoscandia DataverseNO (via DataONE)
spellingShingle ecosystem research
plant silica concentration
Orthosilicic acid
Deschampsia cespitosa
Fennoscandia
plant defense mechanism
graminoids
Earth and Environmental Sciences
calibration
Near Infrared Reflectance Spectroscopy (NIRS)
Bråthen, Kari Anne
Ancin-Murguzur, Francisco Javier
Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title_full Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title_fullStr Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title_full_unstemmed Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title_short Replication Data for: Determination of plant silicon content with near infrared reflectance spectroscopy
title_sort replication data for: determination of plant silicon content with near infrared reflectance spectroscopy
topic ecosystem research
plant silica concentration
Orthosilicic acid
Deschampsia cespitosa
Fennoscandia
plant defense mechanism
graminoids
Earth and Environmental Sciences
calibration
Near Infrared Reflectance Spectroscopy (NIRS)
topic_facet ecosystem research
plant silica concentration
Orthosilicic acid
Deschampsia cespitosa
Fennoscandia
plant defense mechanism
graminoids
Earth and Environmental Sciences
calibration
Near Infrared Reflectance Spectroscopy (NIRS)
url https://search.dataone.org/view/sha256:db4e8cd3a3bab2f7ed0031fc8a7ff0ba07080410b126304cbd8ad8d08c5dc355