↓ Skip to main content

Determination of plant silicon content with near infrared reflectance spectroscopy

Overview of attention for article published in Frontiers in Plant Science, September 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
92 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Determination of plant silicon content with near infrared reflectance spectroscopy
Published in
Frontiers in Plant Science, September 2014
DOI 10.3389/fpls.2014.00496
Pubmed ID
Authors

Adriaan Smis, Francisco Javier Ancin Murguzur, Eric Struyf, Eeva M. Soininen, Juan G. Herranz Jusdado, Patrick Meire, Kari Anne Bråthen

Abstract

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, R (2) = 0.90, RMSEP = 0.24), but improved when only graminoids were modeled (n = 66, R (2) = 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, R (2) = 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
Sweden 1 1%
Australia 1 1%
Unknown 89 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 18%
Student > Ph. D. Student 15 16%
Student > Master 11 12%
Student > Doctoral Student 7 8%
Student > Bachelor 6 7%
Other 16 17%
Unknown 20 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 36%
Earth and Planetary Sciences 8 9%
Environmental Science 6 7%
Engineering 5 5%
Chemistry 5 5%
Other 11 12%
Unknown 24 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 October 2014.
All research outputs
#14,784,344
of 25,374,917 outputs
Outputs from Frontiers in Plant Science
#6,903
of 24,598 outputs
Outputs of similar age
#127,249
of 263,254 outputs
Outputs of similar age from Frontiers in Plant Science
#68
of 216 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,598 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,254 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.