Inversion study of cadmium content in soil based on reflection spectroscopy and MSC-ELM model

Heavy metal pollution in saline-alkali land has a significant impact on the ecological environment and human health. Rapid and accurate inversion of cadmium (Cd) element content in the saline-alkali land is important for environmental protection, saline-alkali soil improvement and conversion of saline-alkali land to cultivated land. Using traditional chemical detection methods to detect the content of heavy metal elements requires a long testing time and has the drawback of high prices. In this paper, we select the saline-alkali land of Zhenlai County as the study area and combine visible-NIR spectroscopy with machine learning models to invert the Cd content in the saline-alkali land. We preprocess the original reflection spectra using fractional order derivatives (FOD), then construct six three-band spectral indices (TBIs) and obtain the corresponding optimal band combination parameters by the optimal band combination (OBC) algorithm. To address the shortcomings of two-hidden-layer extreme learning machine (TELM), this paper introduces new weight parameters among the nodes of the first hidden layer, further extends it to multiple layers on this basis, and proposes the MSC-ELM model. The improved model is compared with several models, such as random forest (RF), partial least squares (PLS) and extreme learning machine (ELM). And the model performance is analyzed and compared by introducing several performance indicators, such as root mean square error (RMSE) and the ratio of the performance to interquartile (RPIQ). The experimental results show that the FOD transformation can eliminate the baseline drift and reduce the spectral noise. The constructed TBIs can effectively enhance the correlation with Cd content relative to the original single band, reduce redundant information and enhance the spectral features. The MSC-ELM model achieves better performance metrics compared to the other models and obtains the optimal prediction performance. This study provides an accurate and rapid method for the detection of Cd content in saline soil, which is important for the improvement and ecological recovery of saline soil.