3.4.11 Soil S prediction
The results pertaining to the S showed that the calibration prediction accuracy was the highest with SVR (R2c=0.96; MBEc=-0.41; RMSEc=5.79; RPDc=3.21; rank=1.25) and it was followed by MARS (R2c=0.93; MBEc=-0.08; RMSEc=6.58; RPDc=2.82; rank=1.75). Among different models validated, PLSR had the highest but non-reliable predictions (R2p=0.76; MBEp=0.39; RMSEp=11.33; RPDp=1.27; rank=1.00). The best overall rank was obtained by using PLSR to predict the S (Figure 4k). Cozzolino et al. (2013) predicted soil total sulfur (TS) using the spectral reflectance data (350-1800 nm) with accuracy of R2=0.81 using PLSR analysis. Wijewardane et al.(2018) reported satisfactory prediction of TS with R2>0.95 and RPD>5.5 using PLSR and ANN models in the MIR region.