Prediction of soil cation exchange capacity using visible and near infrared spectroscopy
dc.contributor.author | Mouazen, Abdul M. | |
dc.contributor.buuauthor | Ulusoy, Yahya | |
dc.contributor.buuauthor | Tekin, Yücel | |
dc.contributor.buuauthor | Tümsavaş, Zeynal | |
dc.contributor.department | Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu. | tr_TR |
dc.contributor.department | Uludağ Üniversitesi/Ziraat Fakültesi. | tr_TR |
dc.contributor.researcherid | J-3560-2012 | tr_TR |
dc.contributor.researcherid | AAG-6056-2021 | tr_TR |
dc.contributor.scopusid | 6508189419 | tr_TR |
dc.contributor.scopusid | 15064756600 | tr_TR |
dc.contributor.scopusid | 6507710594 | tr_TR |
dc.date.accessioned | 2022-11-17T06:33:42Z | |
dc.date.available | 2022-11-17T06:33:42Z | |
dc.date.issued | 2016-12 | |
dc.description.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. | en_US |
dc.description.sponsorship | ICT-AGRI (62-FARMFUSE) (The European Commission's ERA-NET scheme under the 7.Framework Programme) | en_US |
dc.description.sponsorship | Department for Environment, Food & Rural Affairs (DEFRA) - IF0208 | en_US |
dc.identifier.citation | Ulusoy, Y. vd. (2016). "Prediction of soil cation exchange capacity using visible and near infrared spectroscopy". Biosystems Engineering, 152(Special Issue), 79-93. | en_US |
dc.identifier.endpage | 93 | tr_TR |
dc.identifier.issn | 1537-5110 | |
dc.identifier.issn | 1537-5129 | |
dc.identifier.issue | Special Issue | en_US |
dc.identifier.scopus | 2-s2.0-84964262614 | tr_TR |
dc.identifier.startpage | 79 | tr_TR |
dc.identifier.uri | https://doi.org/10.1016/j.biosystemseng.2016.03.005 | |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S1537511015303573 | |
dc.identifier.uri | http://hdl.handle.net/11452/29466 | |
dc.identifier.volume | 152 | tr_TR |
dc.identifier.wos | 000390624200008 | tr_TR |
dc.indexed.scopus | Scopus | en_US |
dc.indexed.wos | SCIE | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.collaboration | Yurt dışı | tr_TR |
dc.relation.journal | Biosystems Engineering | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.relation.tubitak | 1120471 | tr_TR |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Agriculture | en_US |
dc.subject | Cation exchange capacity | en_US |
dc.subject | On-line soil sensor | en_US |
dc.subject | Soil mapping | en_US |
dc.subject | Vis-NIR spectroscopy | en_US |
dc.subject | Reflectance spectroscopy | en_US |
dc.subject | Online measurement | en_US |
dc.subject | Moisture-content | en_US |
dc.subject | Organic-carbon | en_US |
dc.subject | Sensor | en_US |
dc.subject | Calibration | en_US |
dc.subject | Agreement | en_US |
dc.subject | Accuracy | en_US |
dc.subject | Spectra | en_US |
dc.subject | Ph | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Laboratories | en_US |
dc.subject | Least squares approximations | en_US |
dc.subject | Mean square error | en_US |
dc.subject | Near infrared spectroscopy | en_US |
dc.subject | Positive ions | en_US |
dc.subject | Regression analysis | en_US |
dc.subject | Soil surveys | en_US |
dc.subject | Soils | en_US |
dc.subject | Textures | en_US |
dc.subject | Cation exchange capacities | en_US |
dc.subject | NIR spectroscopy | en_US |
dc.subject | Partial least-squares regression | en_US |
dc.subject | Root mean squared errors | en_US |
dc.subject | Soil sensors | en_US |
dc.subject | Visible and near infrared | en_US |
dc.subject | Visible and near-infrared spectroscopy | en_US |
dc.subject | Infrared devices | en_US |
dc.subject.scopus | Soil Color; Near-Infrared Spectroscopy; Hyperspectral | en_US |
dc.subject.wos | Agricultural engineering | en_US |
dc.subject.wos | Agriculture, multidisciplinary | en_US |
dc.title | Prediction of soil cation exchange capacity using visible and near infrared spectroscopy | en_US |
dc.type | Article | |
dc.wos.quartile | Q2 (Agricultural engineering) | en_US |
dc.wos.quartile | Q1 (Agriculture, multidisciplinary) | en_US |
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