Prediction of soil cation exchange capacity using visible and near infrared spectroscopy

dc.contributor.authorMouazen, Abdul M.
dc.contributor.buuauthorUlusoy, Yahya
dc.contributor.buuauthorTekin, Yücel
dc.contributor.buuauthorTümsavaş, Zeynal
dc.contributor.departmentUludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu.tr_TR
dc.contributor.departmentUludağ Üniversitesi/Ziraat Fakültesi.tr_TR
dc.contributor.researcheridJ-3560-2012tr_TR
dc.contributor.researcheridAAG-6056-2021tr_TR
dc.contributor.scopusid6508189419tr_TR
dc.contributor.scopusid15064756600tr_TR
dc.contributor.scopusid6507710594tr_TR
dc.date.accessioned2022-11-17T06:33:42Z
dc.date.available2022-11-17T06:33:42Z
dc.date.issued2016-12
dc.description.abstractThis 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.sponsorshipICT-AGRI (62-FARMFUSE) (The European Commission's ERA-NET scheme under the 7.Framework Programme)en_US
dc.description.sponsorshipDepartment for Environment, Food & Rural Affairs (DEFRA) - IF0208en_US
dc.identifier.citationUlusoy, 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.endpage93tr_TR
dc.identifier.issn1537-5110
dc.identifier.issn1537-5129
dc.identifier.issueSpecial Issueen_US
dc.identifier.scopus2-s2.0-84964262614tr_TR
dc.identifier.startpage79tr_TR
dc.identifier.urihttps://doi.org/10.1016/j.biosystemseng.2016.03.005
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S1537511015303573
dc.identifier.urihttp://hdl.handle.net/11452/29466
dc.identifier.volume152tr_TR
dc.identifier.wos000390624200008tr_TR
dc.indexed.scopusScopusen_US
dc.indexed.wosSCIEen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.collaborationYurt dışıtr_TR
dc.relation.journalBiosystems Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.relation.tubitak1120471tr_TR
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAgricultureen_US
dc.subjectCation exchange capacityen_US
dc.subjectOn-line soil sensoren_US
dc.subjectSoil mappingen_US
dc.subjectVis-NIR spectroscopyen_US
dc.subjectReflectance spectroscopyen_US
dc.subjectOnline measurementen_US
dc.subjectMoisture-contenten_US
dc.subjectOrganic-carbonen_US
dc.subjectSensoren_US
dc.subjectCalibrationen_US
dc.subjectAgreementen_US
dc.subjectAccuracyen_US
dc.subjectSpectraen_US
dc.subjectPhen_US
dc.subjectForecastingen_US
dc.subjectLaboratoriesen_US
dc.subjectLeast squares approximationsen_US
dc.subjectMean square erroren_US
dc.subjectNear infrared spectroscopyen_US
dc.subjectPositive ionsen_US
dc.subjectRegression analysisen_US
dc.subjectSoil surveysen_US
dc.subjectSoilsen_US
dc.subjectTexturesen_US
dc.subjectCation exchange capacitiesen_US
dc.subjectNIR spectroscopyen_US
dc.subjectPartial least-squares regressionen_US
dc.subjectRoot mean squared errorsen_US
dc.subjectSoil sensorsen_US
dc.subjectVisible and near infrareden_US
dc.subjectVisible and near-infrared spectroscopyen_US
dc.subjectInfrared devicesen_US
dc.subject.scopusSoil Color; Near-Infrared Spectroscopy; Hyperspectralen_US
dc.subject.wosAgricultural engineeringen_US
dc.subject.wosAgriculture, multidisciplinaryen_US
dc.titlePrediction of soil cation exchange capacity using visible and near infrared spectroscopyen_US
dc.typeArticle
dc.wos.quartileQ2 (Agricultural engineering)en_US
dc.wos.quartileQ1 (Agriculture, multidisciplinary)en_US

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