Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/29466
Title: Prediction of soil cation exchange capacity using visible and near infrared spectroscopy
Authors: Mouazen, Abdul M.
Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu.
Uludağ Üniversitesi/Ziraat Fakültesi.
Ulusoy, Yahya
Tekin, Yücel
Tümsavaş, Zeynal
J-3560-2012
AAG-6056-2021
6508189419
15064756600
6507710594
Keywords: Agriculture
Cation exchange capacity
On-line soil sensor
Soil mapping
Vis-NIR spectroscopy
Reflectance spectroscopy
Online measurement
Moisture-content
Organic-carbon
Sensor
Calibration
Agreement
Accuracy
Spectra
Ph
Forecasting
Laboratories
Least squares approximations
Mean square error
Near infrared spectroscopy
Positive ions
Regression analysis
Soil surveys
Soils
Textures
Cation exchange capacities
NIR spectroscopy
Partial least-squares regression
Root mean squared errors
Soil sensors
Visible and near infrared
Visible and near-infrared spectroscopy
Infrared devices
Issue Date: Dec-2016
Publisher: Elsevier
Citation: Ulusoy, Y. vd. (2016). "Prediction of soil cation exchange capacity using visible and near infrared spectroscopy". Biosystems Engineering, 152(Special Issue), 79-93.
Abstract: This study was undertaken to investigate the application of visible and near infrared (vis -NIR) spectroscopy for determining soil cation exchange capacity (CEC) under laboratory and on-line field conditions. Measurements were conducted in two fields with clay texture in field 1 (F1) and clay-loam texture in field 2 (F2) both in Turkey. Partial least squares (PLS) regression analyses with full cross-validation were carried out to establish CEC models using three datasets of F1, F2 and F1 + F2. Analytically-measured, laboratory vis-NIR and on-line vis-NIR predicted maps were produced and compared statistically by kappa coefficient. Results of the CEC prediction using laboratory vis-NIR data gave good prediction results, with averaged r(2) values of 0.92 and 0.72, root mean squared errors of prediction (RMSEP) of 1.89 and 1.54 cmol kg(-1) and residual prediction deviations (RPD) of 3.69 and 1.89 for F1 and F2, respectively. Less successful predictions were obtained for the on-line measurement with r(2) of 0.75 and 0.7, RMSEP of 4.79 and 1.76 cmol kg(-1) and RPD of 1.45 and 1.56 for F1 and F2, respectively. Comparisons using kappa statistics test indicated a significant agreement (kappa = 0.69) between analytically-measured and laboratory vis-NIR predicted CEC maps of F1, while poorer agreement was found for F2 (kappa = 0.43). A moderate spatial similarity was also found between analytically-measured and on-line vis-NIR predicted CEC maps in F1 (kappa = 0.50) and F2 (kappa = 0.49). This study suggests that soil CEC can be satisfactorily analysed using vis-NIR spectroscopy under laboratory conditions and with somewhat less precision under on-line scanning conditions.
URI: https://doi.org/10.1016/j.biosystemseng.2016.03.005
https://www.sciencedirect.com/science/article/pii/S1537511015303573
http://hdl.handle.net/11452/29466
ISSN: 1537-5110
1537-5129
Appears in Collections:Scopus
Web of Science

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