Fourier Transformed Infrared (FTIR) Spectroscopy Data for Soil Carbon, Extractable Carbon, Changes in Soil FTIR Spectra, FTIR Data Clustering & Discriminant Analysis
Here we report on a rapid, high throughput approach using fingerprint Fourier transformed infrared (FTIR) spectroscopy and chemometric modeling. Fingerprint FTIR incorporates all information embedded within the FTIR spectrum, thus producing a biogeochemical or ecological “fingerprint” of the soil. This methodology was applied in a highly disturbed forest ecosystem over a 19-year sampling period to detect, via spectral analysis, changes in dynamic soil properties (e.g., soil organic matter and reactive mineralogy) that can indicate changes in soil quality. Two chemometric statistical techniques (i.e., hierarchical clustering analysis [HCA] and discriminate analysis of principal components [DAPC]) were evaluated for interpreting and quantifying similarities/dissimilarities between samples utilizing the entire FTIR spectra from each sample.
This dataset is associated with the following publication:
Maynard, J., and M. Johnson. Applying fingerprint Fourier transformed infrared spectroscopy and chemometrics to assess soil ecosystem disturbance and recovery. JOURNAL OF SOIL AND WATER CONSERVATION. Soil and Water Conservation Society, 73(4): 443-451, (2018).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
]
|
| contactPoint |
{
"fn": "Mark Johnson",
"hasEmail": "mailto:johnson.markg@epa.gov"
}
|
| description | Here we report on a rapid, high throughput approach using fingerprint Fourier transformed infrared (FTIR) spectroscopy and chemometric modeling. Fingerprint FTIR incorporates all information embedded within the FTIR spectrum, thus producing a biogeochemical or ecological “fingerprint” of the soil. This methodology was applied in a highly disturbed forest ecosystem over a 19-year sampling period to detect, via spectral analysis, changes in dynamic soil properties (e.g., soil organic matter and reactive mineralogy) that can indicate changes in soil quality. Two chemometric statistical techniques (i.e., hierarchical clustering analysis [HCA] and discriminate analysis of principal components [DAPC]) were evaluated for interpreting and quantifying similarities/dissimilarities between samples utilizing the entire FTIR spectra from each sample. This dataset is associated with the following publication: Maynard, J., and M. Johnson. Applying fingerprint Fourier transformed infrared spectroscopy and chemometrics to assess soil ecosystem disturbance and recovery. JOURNAL OF SOIL AND WATER CONSERVATION. Soil and Water Conservation Society, 73(4): 443-451, (2018). |
| distribution |
[
{
"title": "Maynard and Johnson 2018_JSWC_Data.xlsx",
"mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502535/Maynard%20and%20Johnson%202018_JSWC_Data.xlsx"
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|
| identifier | https://doi.org/10.23719/1502535 |
| keyword |
[
"Discriminant analysis",
"FTIR",
"Forest soil",
"Soil carbon",
"Terrain analysis",
"redundancy analysis",
"remote sensing",
"spatial variability",
"system recovery",
"variation partitioning"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2018-06-08 |
| programCode |
[
"020:000"
]
|
| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
}
}
}
|
| references |
[
"https://doi.org/10.2489/jswc.73.4.443"
]
|
| rights |
null
|
| title | Fourier Transformed Infrared (FTIR) Spectroscopy Data for Soil Carbon, Extractable Carbon, Changes in Soil FTIR Spectra, FTIR Data Clustering & Discriminant Analysis |
