Elemental Analysis for the Optimization of Plant Secondary Metabolites Using Cannabis sativa as a Model Organism

When cultivating medicinally valuable plants, it is often beneficial to assess production of secondary metabolites as these can act as markers for desired traits. Cannabis is one such medicinally valuable plant that has gained much attention recently due to its growing availability. Chemometric methods can be applied to understand the relationships governing the production of these compounds and optimize cultivation toward certain ends. In the current study, thirteen elements were quantitatively measured in the leaves of cannabis plants using inductively coupled plasma mass spectroscopy and an Elementar vario macro cube. Correlation analysis, principal components analysis, and K-means clustering were utilized to describe and elucidate trends in the dataset. Moderately positive, monotonic correlations were found between magnesium, boron, and calcium, along with nitrogen, sulfur, and copper. PCA was used to corroborate these relationships. Clustering analysis was able to identify three distinct groups to which strains could be mapped with a relatively high degree of resolution when compared to cultivator identifiers. These findings suggest similar methods of introduction and elemental incorporation into the strains of these distinct groups. The methods utilized in the current study serve as the basis for the future development of methods that may be utilized in the optimization of secondary metabolite production.