Analyzing the share of amorphous silica in mixtures with different soil minerals using fourier transform infrared spectroscopy and PLSR chemometrics

Amorphous silica (ASi) improves key soil functions and crop productivity but is difficult to quantify due to complex mineral mixtures and time-consuming chemical analyses. This study explored the possibility of using Fourier-transform infrared spectroscopy (FTIR) in combination with partial least-squares regression (PLSR) to estimate the ASi content in samples of mineral mixtures. For this purpose, mixtures of different pedogenic minerals (kaolin and montmorillonite) with known ASi content were produced and analysed using FTIR spectroscopy. Based on these data, a PLSR model was used to predict the ASi concentration based on the FTIR spectra. The results show that the model is capable of estimating ASi content in simple mineral mixtures with high accuracy. This suggests that FTIR, combined with PLSR, could be a promising method for the rapid and cost-effective determination of ASi in environmental samples. Future studies should investigate how the method performs with more complex mixtures and natural soil samples, and how factors such as mineral weathering and sample origin influence the accuracy of the prediction.