Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System
We developed and tested spectroscopic models derived by partial least squares regression (PLSR) using data from the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) national soil database (NatSoil) and soil samples from the Australian National Soil Archive. Models were con...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/74438 |
| _version_ | 1848763274644946944 |
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| author | Hicks, W. Viscarra Rossel, Raphael Tuomi, S. |
| author_facet | Hicks, W. Viscarra Rossel, Raphael Tuomi, S. |
| author_sort | Hicks, W. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We developed and tested spectroscopic models derived by partial least squares regression (PLSR) using data from the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) national soil database (NatSoil) and soil samples from the Australian National Soil Archive. Models were constructed for 21 soil attributes, and their predictability assessed using the R2, ranged from 0.57 for bicarbonate extractable available phosphorus to 0.92 for the sum of the exchangeable bases. Investigating the spectral library coverage with a suite of 1484 unknown samples from a geochemical survey of Australian catchments, we found that the models could be used to predict many soil attributes in a geographically diverse set of samples. |
| first_indexed | 2025-11-14T11:00:52Z |
| format | Journal Article |
| id | curtin-20.500.11937-74438 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:00:52Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-744382019-08-15T05:25:55Z Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System Hicks, W. Viscarra Rossel, Raphael Tuomi, S. We developed and tested spectroscopic models derived by partial least squares regression (PLSR) using data from the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) national soil database (NatSoil) and soil samples from the Australian National Soil Archive. Models were constructed for 21 soil attributes, and their predictability assessed using the R2, ranged from 0.57 for bicarbonate extractable available phosphorus to 0.92 for the sum of the exchangeable bases. Investigating the spectral library coverage with a suite of 1484 unknown samples from a geochemical survey of Australian catchments, we found that the models could be used to predict many soil attributes in a geographically diverse set of samples. 2015 Journal Article http://hdl.handle.net/20.500.11937/74438 10.1071/SR15171 restricted |
| spellingShingle | Hicks, W. Viscarra Rossel, Raphael Tuomi, S. Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title | Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title_full | Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title_fullStr | Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title_full_unstemmed | Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title_short | Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System |
| title_sort | developing the australian mid-infrared spectroscopic database using data from the australian soil resource information system |
| url | http://hdl.handle.net/20.500.11937/74438 |