To develop a method for rapid detection of lead in dairy products by anodic stripping voltammetry.

The gold electrode and machine learning algorithm were used to optimize the deposition time, pulse height and sample pretreatment parameters. The linear range, limit of detection, recovery rate, relative standard deviation and other indicators of the method were determined.

Setting deposition time to 360 s,pulse height to 270 mV and the optimized parameters of sample pretreatment were as follows: 1:3 (V:V) for milk,1:2 (m:V) for milk powder and 1:4 (V:V) for yogurt, centrifugation 10 min (milk), 10 min (powder), 14 min (yogurt)were determined as the optimal parameters for rapid detection. The results showed that the method had good linearity in the range of 187.5–6000.0 ng/mL (r²>0.99), the limit of detections were 123.32–273.10 ng/mL, the recovery rates were 90%–110%, and the relative standard deviation was less than 5%.

This study establish a fast, simple and accurate method for detecting lead content in milk powder, yogurt and milk, providing standardized solutions for heavy metal prevention and control.