A simple but effective evaluation criterion for parameters optimization of EPO and its application to moisture insensitive prediction of soil organic matter

Abstract

Field measurement using portable NIR spectrometer is becoming a popular way to provide in situ, rapid estimation of soil organic matter content. However, in situ NIR spectra is altered by external environmental factors, such as soil moisture. The external parameter orthogonalization (EPO) has been recognized as one of the most effective method to minimize effect of soil moisture on spectra. In general, the root mean squared error of cross validation (RMSECV) was mainly used as an evaluation criterion to optimize the parameters involved in EPO algorithm, which ensures that the wet soil spectra corrected by EPO could have a good quantitative performance, but ignores the spectral similarity between the dry soil spectra and the wet soil spectra corrected by EPO. In this study, we present a simple but effective evaluation criterion for optimization of EPO, which we refer to as the mean of spectral correlation coefficient (MSCC). Compared with the commonly used RMSECV criterion, the spectra corrected by EPO (MSCC) are more similar to the corresponding dry soil spectra, and MSCC is more robust to different spectral pretreatment methods. In addition, the quantitative results of MSCC are equivalent to those of RMSECV, and sometimes slightly better than those of RMSECV.