Comparative indexation of potentially toxic elements for soil pollution monitoring using ICP-OES and FTIR spectroscopy in Central Morocco

The accumulation of potentially toxic elements (PTEs) in agricultural soils poses significant risks to food safety and ecosystem health, necessitating rapid and cost-effective monitoring approaches. While inductively coupled plasma optical emission spectroscopy (ICP-OES) provides accurate PTE quantification, its high cost, time requirements, and chemical reagent necessitate the search for green, fast, robust, and cost-effective alternatives. This study aims to evaluate the suitability of mid-infrared Fourier transform infrared (MIR-FTIR) spectroscopy combined with partial least squares regression (PLSR) as an alternative rapid method for predicting PTE concentrations and calculating pollution indices in semi-arid agricultural soils of central Morocco. A total of 67 surface soil samples (0–20 cm) were collected from three distinct soil types: Lithic Calciustolls (n=23), Typic Haplusterts (n=23), and Typic Calciustolls (n=21). Ten PTEs (As, Ba, Cd, Cu, Mn, Pb, Se, Sr, Ti, and Zn) were measured by ICP-OES and predicted using MIR-FTIR (4000–400 cm −1 ) coupled with PLSR. Mean PTE concentrations varied substantially across soil types, with Cd ranging from 0.95 to 3.91 mg·kg −1 , Sr from 56.25 to 535.14 mg·kg −1 , and Zn from 38.23 to 59.63 mg·kg −1 . PTE Pollution Index (PI) was calculated using both datasets for comparative pollution assessment. Results demonstrated strong to excellent predictive performance (R² = 0.82-0.95) with the highest correlations for Ba, Zn, and Sr. PI calculations showed exceptional concordance between methods (mean PI: 1.54 for both), with all samples classified as low pollution. FTIR spectroscopy maintains the same geochemical relationships as ICP-OES (correlation differences <0.083), confirming method equivalence for soil pollution indexation. This approach offers significant advantages for large-scale monitoring programs while maintaining classification accuracy for environmental risk assessment.