The quality and safety of agricultural products are threatened by heavy metal ions in soil, which can be absorbed by the crops, and then accumulated in the human body through the food chain. In this paper, we report a low-cost and easy-to-use screen-printed electrode (SPE) for cadmium ion (Cd(II)) detection based on differential pulse voltammetry (DPV), which decorated with ionic liquid (IL), magnetite nanoparticle (Fe₃O₄), and deposited a bismuth film (Bi). The characteristics of Bi/Fe₃O₄/ILSPE were investigated using scanning electron microscopy, cyclic voltammetry, impedance spectroscopy, and linear sweep voltammetry. We found that the sensitivity of SPE was improved dramatically after functionalized with Bi/Fe₃O₄/IL. Under optimized conditions, the concentrations of Cd(II) are linear with current responses in a range from 0.5 to 40 µg/L with the lowest detection limit of 0.05 µg/L (S/N = 3). Additionally, the internal standard normalization (ISN) was used to process the response signals of Bi/Fe₃O₄/ILSPE and established a new linear equation. For detecting three different Cd(II) concentrations, the root-mean-square error using ISN (0.25) is lower than linear method (0.36). Finally, the proposed electrode was applied to trace Cd(II) in soil samples with the recovery in the range from 91.77 to 107.83%.

An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results.

The botanical origin of honey significantly impacts its nutritional composition, quality, and price.