The Voronezh region has traditionally been the most significant area for crop production and agriculture. However, the development of mineral resources, the implementation of chemical fertilisers in agriculture, and the consequences of the Chernobyl accident have highlighted the necessity to ensure the food industry has access to safe and effective plant raw materials. The use of low-quality plant raw materials and products derived from them represents a significant source of exposure to various ecotoxicants, including radionuclides, which can enter the human body. Objective: to examine the accumulation of the most significant artificial and natural radionuclides in the roots of a large burdock plant, harvested in different territories of the Voronezh region, with a view to determining the extent of the anthropogenic impact. Materials and methods. Under experimental conditions, the specific activity of the main long-lived artificial radioisotopes (cesium-137, strontium-90) and naturally occurring radionuclides (thorium-232, potassium-40, radium-226) on a spectrometer (RADEK MKGB-01 radiometer) was determined in samples of the upper layers of soils and roots of large burdock. Results. All of the studied samples of large burdock roots, which had been prepared in natural and artificial phytocenoses in the Voronezh region, met the existing radiation safety requirements (first group). With an increase in the specific activity of strontium-90, cesium-137, thorium-232, potassium-40, radium-226 in the soil, there was an accompanying increase in the specific activity of these radionuclides in the roots of a large burdock. Correlation analysis of the specific activity of artificial and natural radionuclides in the soil and roots of large burdock revealed a highly significant relationship between these numerical indicators, thereby confirming the predominant transposed pollution. Conclusion. The accumulation patterns in roots of large burdock, naturally occurring and anthropogenic radionuclides are described by mathematical dependencies, with an accuracy of approximation that is as high as possible.