Effect of the internal soil standard on the spectral assessment of clay content

Soil spectral libraries (SSLs) are being created worldwide due to their enormous potential to train machine learning algorithms that may benefit environmental and agricultural activities. Accordingly, the extent to which the different SSLs maintain their accuracy for unknown samples is important. Recently, the internal soil standard (ISS) has garnered attention in the soil spectroscopy literature, due to its capacity to rectify systematic effects during spectral measurements. Moreover, a new initiative by the Institute of Electrical and Electronics Engineers Standards Association (IEEE SA) to create an agreed-upon measurement standard and protocol for soil spectral measurements has been launched. Application of the ISS to align one spectrum with another for merging different SSLs is highly needed. This led us to postulate the necessity of evaluating the performance of spectral-based models using different large SSLs that were created following different protocols. Using the random forest (RF) algorithm, we tested four different well-known large SSLs to predict clay content. From these SSLs, two of them were created using the ISS method (GEOCRADLE and Israel) and the other two without (LUCAS and ICRAF–ISRIC). Then, three groups of soils from different regions (Israel, Czech Republic, and Brazil) were used as external test samples to examine the SSLs' performance. The SSLs that were generated following the ISS protocol yielded the best performance in a group of samples that utilized the same method. It was concluded that using an agreed ISS such as the Lucky Bay (LB) soil sample enables a favorable way to merge SSLs.