Browsing by Author "Mouazen, Abdul Mounem"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Effect of moisture content on prediction of organic carbon and pH using visible and near-infrared spectroscopy
    (Wiley, 2012-01) Mouazen, Abdul Mounem; Tekin, Yücel; Tümsavaş, Zeynal; Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu.; Uludağ Üniversitesi/Ziraat Fakültesi.; J-3560-2012; 15064756600; 6507710594
    This study was undertaken to investigate the effect of moisture content (MC) on the prediction accuracy of soil organic C (SOC) and pH of soils collected from Turkey and the United Kingdom using a fiber-type visible and near infrared (Vis-NIR) spectrophotometer. The diffuse reflectance spectra of 270 soil samples were measured under six gravimetric MC levels of 0, 5, 10, 15, 20, and 25%. Partial least squares (PLS) regression analyses with full cross-validation were performed to establish models for SOC and pH. Before PLS analysis, the entire spectra were randomly split three times into calibration (80%) and validation (20%) sets. Results showed that the prediction performance of SOC in the validation set was successful, with root mean square errors of prediction (RMSEPs) of 1.26 to 1.55% and residual prediction deviations (RPDs) of 2.29 to 2.83, and rather poor for pH, with RMSEPs of 0.65 to 0.85 and RPDs of 1.29 to 1.65. The best accuracy achieved for SOC was for dry soil samples (RMSEP = 1.26%, RPD = 2.83), whereas the worst accuracy was for wet soil samples with 5% MC (RMSEP = 1.55%, RPD = 2.29). The best result for pH was obtained for dry samples (RMSEP = 0.70%, RPD = 1.65), although this accuracy was comparable to that of the 10% MC soil samples (RMSEP = 0.65%, RPD = 1.60). The ANOVA supported the conclusion that there was a significant effect of MC on prediction accuracy, although this effect was larger for SOC (P < 0.0000) than pH (P < 0.05).
  • No Thumbnail Available
    Item
    Effect of moisture content on the prediction of cation exchange capacity using visible and near infrared spectroscopy
    (WFL Publication, 2013) Mouazen, Abdul Mounem; Tümsavaş, Zeynal; Tekìn, Yücel; Uludağ Üniversitesi/Ziraat Fakültesi/Toprak Bilimi ve Bitki Besleme Bölümü.; Uludağ Üniversitesi/Teknik Bilimler Meslek Yüksekokulu/Makine Ve Metal Teknolojileri.; J-3560-2012; 6507710594; 15064756600
    his study was undertaken to investigate the effect of moisture content (MC) on the prediction accuracy of the cation exchange capacity (CEC) of soils collected from Turkey using a fibre-type Vis-NIR spectrophotometer. The diffuse reflectance spectra of 150 soil samples were measured under 6 gravimetric MC levels of 0, 5, 10, 15, 20 and 25%. The results showed that the effect of MC on the prediction accuracy of CEC was nonlinear. Due to the direct spectral response in the NIR range, the prediction of CEC in the independent validation set was successful with a root mean square error of prediction (RMSEP) ranging from 5.82 to 8.14% and a ratio of prediction deviation (RPD) ranging from 1.59 to 2.14. The highest accuracy achieved for CEC was with the 10 and 15% MC soil samples (RMSEP 5.82%; RPD 2.14 and 2.12, respectively), and the lowest accuracy was found for wet soil samples with a 20% MC (RMSEP 8.14%; RPD 1.59). These results suggested that there was a clear effect of MC on the prediction of CEC. Because the differences between the models at different levels of MC were significant for CEC.