This work aims to present a simple, cost-effective, and environmentally friendly digestion method with diluted HNO3 and H2O2 for simultaneous determination of As, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, P, Pb, Sr and Zn in medicinal herbs employed inductively coupled plasma optical emission spectrometry (ICP OES). A fractional factorial design uses a multivariate strategy to optimize the experimental parameters of the sample preparation. The application of a multi-response function established the best experimental conditions. After optimized digestion conditions with a final volume of 8.0 mL and 0.1 g of medical herb sample mass in the reaction flask system was of 4.0 mol L-1 HNO3 concentration, 6.0% (m m-1) H2O2 concentration, the temperature of 180°C and digestion time, 120 min, employing a closed block digester. The optimized procedure resulted in low residual carbon content and residual acid acidity concentration, showing good chemical analysis conditions introduced by ICP OES. Accuracy was confirmed through the certified reference materials analysis of tomato leaves (CRM-Agro C1003a), sugar cane leaves (CRM-Agro C1005a), and tea (NCS DC 73351), where agreement ranged from 83 (Sr) to 116% (As), for all analytes. Values obtained of the limit of detection (LOD) and limit of quantification (LOQ) ranged from 0.06 (Cd) to 1.9 (P) mg kg-1 and from 0.2 (Cd) to 6.3(P) mg kg-1, respectively. Finally, twenty-seven medicinal herbs samples were used to assess the applicability of the developed procedure. It was obtained from the markets of Salvador (State of Bahia) and Belém (State of Pará), both cities Brazilian. The analyte concentrations in the samples comprised a range of As (< 0.5–2.74 mg kg-1), Ca (0.44–2.96%), Cu (< 2.2–20.3 mg kg-1), Fe (103.7–976 mg kg-1), K (0.102-4.0%), Mg (0.029-0.80%), Mn (8.9–2020 mg kg-1), Na (< 2.0-3.4%), P (< 6.3–0.31%), Sr (19.5–692 mg kg-1), and Zn (3.19–75.7 mg kg-1). Cadmium, Cr, and Pb showed values of concentration below LOQ for the analytical method proposed. Principal component analysis (PCA) was applied to inorganic constituent concentrations data in an attempt to classify the medicinal herbs, being an excellent tool for classifying samples.
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