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http://krishi.icar.gov.in/jspui/handle/123456789/47084
Title: | Development of a hybrid proximal sensing method for rapid identification of petroleum contaminated soils |
Other Titles: | Not Available |
Authors: | Somsubhra Chakraborty, David C. Weindorf, Bin Li, Abdalsamad Abdalsatar Ali Aldabaa, Rakesh Kumar Ghosh, Sathi Paul, Md. NasimAli |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | Ramakrishna Mission Vivekananda University, Kolkata, India ICAR::National Institute of Research on Jute and Allied Fibre Technology |
Published/ Complete Date: | 2015 |
Project Code: | Not Available |
Keywords: | Penalized spline model, Portable X-ray fluorescence spectrometry, Soil petroleum contamination, Random forest, Visible near-infrared diffuse reflectance spectroscopy |
Publisher: | Elsevier |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Using 108 petroleum contaminated soil samples, this pilot study proposed a new analytical approach of combining visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) and portable X-ray fluorescence spectrometry (PXRF) for rapid and improved quantification of soil petroleumcontamination. Results indicated that an advanced fused model where VisNIR DRS spectra-based penalized spline regression (PSR) was used to predict total petroleum hydrocarbon followed by PXRF elemental data-based random forest regression was used to model the PSR residuals, it outperformed (R2 = 0.78, residual prediction deviation (RPD) = 2.19) all other models tested, even producing better generalization than using VisNIR DRS alone (RPD's of 1.64, 1.86, and 1.96 for random forest, penalized spline regression, and partial least squares regression, respectively). Additionally, unsupervised principal component analysis using the PXRF + VisNIR DRS system qualitatively separated contaminated soils from control samples. Capsule: Fusion of PXRF elemental data and VisNIR derivative spectra produced an optimized model for total petroleum hydrocarbon quantification in soils. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Journal |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Science of the Total Environment |
NAAS Rating: | 12.55 |
Volume No.: | 514 |
Page Number: | 399-408 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | http://dx.doi.org/10.1016/j.scitotenv.2015.01.087 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/47084 |
Appears in Collections: | AEng-NINFET-Publication |
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