Improving the clay, silt and sand of soil prediction by removing the influence of moisture on reflectance using EPO

Moisture is one of the most important factors that affects soil reflectance spectra. Time and spatial variability of soil moisture leads to reducing the capability of spectroscopy in soil properties estimation. Developing a method that could lessen the effect of moisture on soil properly prediction using spectrometry, is necessary. This paper utilises an external parameter orthogonalisation (EPO) algorithm to remove the effect of soil moisture from spectra for the estimation of texture element contents of soil. ?????The reflectance of 175 soil samples with nominal moisture contents approximately air dry, 6, 12, 18, 24, 30 and 36% were measured. Cross validation was adapted to determine the optimum number of components in the EPO matrix model-coupled. PLSR method has been used for estimation of soil propetrices. The result shows that the presence of moisture leads to reducing the acuraccy reduction of clay (from R2=0.70 to R2=0.38), silt (from R2=0.34 to R2=0.20), and sand (from R2=0.40 to R2=0.30) prediction. Reduction in the accuracy increases by increasing the moisture levels. Removing the effects of moisture from the soil reflectance by EPO algorithm lead to improving 0.23, 0.12 and 0.16 in R2 of clay, silt and sand prediction by PLSR model, respectively. Therefore, using the EPO-PLS method, in any moisture level, VNIR spectroscopy is a viable tool for estimation of soil texture elements.