Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

The increasing demand for natural medicine has increased the significance of Silybum marianum as a valuable medicinal plant. It is used to restore liver cells; reduce blood cholesterol; prevent prostate, skin, and breast cancer; and protect cervical cells and kidneys. To identify ecological factors affecting the distribution and amount of silymarin in S. marianum three machine learning algorithms including boosted regression trees (BRT), random forest (RF), and support vector machines (SVM) have been applied in Fars Province, Iran. Fourteen factors affecting S. marianum growth and development were determined and subsequently converted into raster maps for the modeling phase using a Geographic Information System (GIS). Subsequently, the Receiver Operating Characteristic (ROC) curve and random forest algorithm were used to evaluate the models and the significance of the factors, respectively. Results showed that The RF (ROC: 0.99), BRT (ROC: 0.98), and SVM (ROC: 0.96) models were highly accurate in predicting the habitat suitability of S. marianum. The results of the RF algorithm also revealed that factors such as distance from roads, elevation, and mean annual rainfall had the most significant influence on the habitat suitability of S. marianum. In addition, the mean annual rainfall, mean annual temperature, and elevation had the highest effects on silymarin accumulation. In general, the northern and northwestern regions of the Fars Province offer optimal environmental conditions for the growth of S. marianum. The southern and southwestern regions of Fars Province, characterized by higher temperatures and lower precipitation, are suitable for the enhanced biosynthesis of silymarin and expansion of its cultivation and production. This study provides a robust framework for understanding the ecological preferences of S. marianum and optimizing its cultivation and management for pharmaceutical applications. By identifying the most influential environmental variables, this research has the potential for the sustainable utilization of this species, enhancing both its conservation and use as a medicinal resource.