Effects of Soil Properties on Pb, Cd, and Cu Contents in Tobacco Leaves of Longyan, China, and Their Prediction Models - Wei Xi; YuanYe Ping; HaiYang Cai; Qian Tan; Chaoyang Liu; Junru Shen; YaWen Zhang (International Journal of Analytical Chemistry)
Longyan City in Fujian Province is one of China’s top-quality tobacco-producing areas and plays an essential role in local economic development. To determine the correlation between heavy metal content in tobacco leaves and soil factors, soil physical and chemical properties and heavy metal contents of lead, cadmium, and copper in tobacco leaves were measured and analyzed by the correlation regression method. The content of lead, cadmium, and copper in soil was determined using hydrochloric acid extraction-AAS and graphite furnace atomic absorption spectrometry. Inductively coupled plasma-mass spectrometry was used to determine heavy metal in tobacco leaf. The findings revealed that the average concentrations of lead, cadmium, and copper in the soil were 12.1, 0.092, and 3.88 mg/kg, respectively. In contrast, the average levels of lead, cadmium, and copper in tobacco leaves were 2.33, 4.89, and 4.35 mg/kg, respectively. The cadmium enrichment coefficient of 54.3 was higher than lead and copper, indicating a greater health risk. Soil pH value was negatively correlated with lead content in tobacco leaf, while potassium and phosphorus nutrient levels were negatively correlated with copper content. In contrast, a positive correlation was established between the presence of organic matter with cadmium content in tobacco leaves. The prediction models of lead, cadmium, and copper in tobacco leaves can be expressed by the regression equation corresponding to each heavy metal as follows: YPb=2.33−0.005∗ XK+0.007∗XN −0.271∗XpH+0.065∗XPb (R2 = 0.787), YCd=1.55+0.012∗XOM−0.014∗XCu+34.6∗XCd (R2 = 0.891), and YCu=4.64−0.029∗XP−0.007∗XK+0.245∗XCu (R2 = 0.724), respectively. The prediction models above provide an effective predictive tool for assessing heavy metal risk in tobacco leaves using soil properties in the study area.