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dc.contributor.authorHicks, W.
dc.contributor.authorViscarra Rossel, Raphael
dc.contributor.authorTuomi, S.
dc.date.accessioned2019-02-19T04:16:57Z
dc.date.available2019-02-19T04:16:57Z
dc.date.created2019-02-19T03:58:24Z
dc.date.issued2015
dc.identifier.citationHicks, W. and Viscarra Rossel, R. and Tuomi, S. 2015. Developing the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System. Soil Research. 53 (8): pp. 922-931.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/74438
dc.identifier.doi10.1071/SR15171
dc.description.abstract

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.

dc.titleDeveloping the Australian mid-infrared spectroscopic database using data from the Australian Soil Resource Information System
dc.typeJournal Article
dcterms.source.volume53
dcterms.source.number8
dcterms.source.startPage922
dcterms.source.endPage931
dcterms.source.issn1838-675X
dcterms.source.titleSoil Research
curtin.departmentSchool of Molecular and Life Sciences (MLS)
curtin.accessStatusFulltext not available


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