Influence of soil moisture on near-infrared reflectance spectroscopic measurement of soil properties

dc.contributor.author Chang, Chang-Wen
dc.contributor.author Laird, David
dc.contributor.author Hurburgh, Charles
dc.contributor.author Hurburgh, Charles
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2018-02-18T05:17:29.000
dc.date.accessioned 2020-06-29T22:42:42Z
dc.date.available 2020-06-29T22:42:42Z
dc.date.issued 2005-04-01
dc.description.abstract <p>Near-infrared reflectance spectroscopy (NIRS), a nondestructive analytical technique, may someday be used to rapidly and simultaneously quantify several soil properties in agricultural fields. The objectives of this study were to examine the influence of moisture content on the accuracy of NIRS analysis of soil properties and to assess the robustness of a NIRS multivariate calibration technique. Four hundred agricultural soil samples (<2 mm) from Iowa and Minnesota were studied at two moisture levels: moist and air-dried. The soil properties tested included total C, organic C, inorganic C, total N, CEC, pH, texture, moisture, and potentially mineralizable N. About 70% of the Iowa samples were selected for the calibration set, and the rest of the Iowa samples and all of the Minnesota samples were assigned to validation set I and validation set II, respectively. Calibrations were based on partial least-squares regression (PLSR), using the first differentials of log (1/R) for the 1100 to 2500-nm spectral range. The results for the calibration set and validation set I indicated that NIRS-PLSR was able to predict many soil properties (total C, organic C, inorganic C, total N, CEC, % clay, and moisture) with reasonable accuracy for both the air-dried (R<sup>2</sup> > 0.76) and moist (R<sup>2</sup> > 0.74) soils. The results for validation set II showed that NIRS-PLSR was able to predict some properties of soils (total C, organic C, total N, and moisture content) from a different geographic region, but other soil properties in validation set II were not accurately predicted. Although NIRS-PLSR predictions are slightly more accurate for air-dried soils than for moist soils, the results indicate that the NIRS-PLSR technique can be used for analysis of field moist samples with acceptable accuracy as long as diverse soil samples from the same region are included in the calibration database.</p>
dc.description.comments <p>This article is from <em>Soil Science</em> 170 (2005): 244–255.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/795/
dc.identifier.articleid 2068
dc.identifier.contextkey 9804258
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/795
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/1596
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/795/2005_Chang_InfluenceSoil.pdf|||Sat Jan 15 01:56:29 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.keywords NIRS
dc.subject.keywords near-infrared reflectance spectroscopy
dc.subject.keywords soil testing
dc.subject.keywords precision farming
dc.subject.keywords soil sensing
dc.subject.keywords calibration transfer
dc.subject.keywords moisture
dc.subject.keywords organic carbon
dc.subject.keywords total nitrogen
dc.subject.keywords CEC
dc.title Influence of soil moisture on near-infrared reflectance spectroscopic measurement of soil properties
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 0544d4c0-b52e-42fa-8419-df2d08ad526b
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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