Spatial variability and climate response characteristics of chemical components of Tussilago farfara L.

Tussilago farfara L. is a typical habitat-dominated herbal medicine. In this work, for evaluating the effect of ecological environment on its quality, an integrated approach based on chemical composition and maximum entropy (MaxEnt) model was developed. 52 batches of T. farfara were collected by field survey from different origins in Gansu Province and their HPLC fingerprints were established. 19 common peaks were specified and subjected to principal component analysis and orthogonal partial least squares-discriminant analysis. The result indicated the quality varied with the origins and the common peaks 12, 6, 9, 14, 19, and 1 was the key to distinguish their quality. The MaxEnt model consisting of 205 occurrence records and 14 environmental variables was constructed and used to predict the potential distribution of T. farfara in Gansu Province. The prediction results showed that the current suitable habitat area of T. farfara was about 94,547.03 km2, accounting for 22.2% of the total area of Gansu Province, and showed a trend of increasing and then decreasing with time under future climate scenarios. Moreover, the dominant factors affecting its distribution were specified as min temperature of coldest month, precipitation of wettest month, precipitation seasonality, mean diurnal range and elevation. Eventually, the correlation model between chemical composition and environmental variables was established, based on which a quality zoning map of T. farfara was drawn. The obtained results would provide a scientific reference for the conservation and utilization of wild resources and the selection of planting site of T. farfara.

Automated summary

A comprehensive approach based on chemical composition and maximum entropy (MaxEnt) model was developed to evaluate the effect of ecological environment on the quality of Tussilago farfara L. The study found that the quality of T. farfara varied with different origins, and identified key peaks for quality distinction. The MaxEnt model, using occurrence records and environmental variables, predicted the potential distribution of T. farfara in Gansu Province and identified the dominant factors affecting its distribution. Finally, a correlation model between chemical composition and environmental variables was established, and a quality zoning map of T. farfara was drawn.