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@ARTICLE{Stumpe:17682,
author = {Stumpe, B. and Weihermüller, L. and Marschner, B.},
title = {{S}ample preparation and selection for qualitative and
quantitative analyses with mid-infrared reflectance
spectroscopy},
journal = {European journal of soil science},
volume = {62},
issn = {1351-0754},
address = {Oxford [u.a.]},
publisher = {Wiley-Blackwell},
reportid = {PreJuSER-17682},
pages = {849 - 862},
year = {2011},
note = {Record converted from VDB: 12.11.2012},
abstract = {Mid-infrared spectroscopy (MIRS) is a well-established
analytical tool for qualitative and quantitative analysis of
soil samples. However, effects of soil sample grinding
procedures on the prediction accuracy of MIR models and on
qualitative spectral information have not been well
investigated and, in consequence, not standardized up to
now. Further, the effects of soil sample selection on the
accuracy of MIR prediction models has not been quantified
yet. This study investigated these effects by using 180
well-characterized soil samples that were ground for
different times (0, 2 or 4 minutes) and then used for MIR
measurements. To study the impact of sample preparation,
soil spectra were subjected to principal component analyses
(PCA), multiple regression and partial least square (PLS)
analysis. The results indicate that the prediction accuracy
of MIR models for soil organic carbon (SOC) and pH and the
qualitative spectral information were better overall for
lightly ground (2 minutes) soil samples compared with
intensively (4 minutes) or unground soil samples. Whereas
the grinding procedure did not show any effect on spectra of
clay minerals, spectral information for quartz and for SOC
was modified. Even though it is difficult to recommend a
global standardized soil sample grinding procedure for MIR
measurements because of different mill types available
within laboratories, we highly recommend using an internally
standardized grinding procedure. Moreover, we show that
neither land use nor soil sampling depth influences the
prediction of the SOC content. However, sand and clay
content substantially affect the score vectors used by the
PLS algorithm to predict the SOC content. Thus, we recommend
using soil samples similar in texture for more precise SOC
calibration models for MIR spectroscopy.},
cin = {IBG-3},
ddc = {630},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {Terrestrische Umwelt},
pid = {G:(DE-Juel1)FUEK407},
shelfmark = {Soil Science},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000297206100007},
doi = {10.1111/j.1365-2389.2011.01401.x},
url = {https://juser.fz-juelich.de/record/17682},
}