Advancing the quality assessment of natural products with dried spot microsampling: A novel analytical approach

Efficient analytical workflows are needed for the quality assessment of natural products, including foods, supplements and phytotherapeutics, to promote consumer health. However, the sampling and sample preparation stages remain bottlenecks, demanding resources, time and labor. Dried spot microsampling, predominantly used for dried blood spots (DBS), features minute sample size, easy remote sampling, convenient storage, and transportation via post [ 1 ]. The dried spot format also allows for automated setups and is compatible with multiple analytical systems, including LC-MS [ 2 ] [ 3 ]. Such approaches could provide appealing solutions to the above challenges, yet they remain unjustifiably underexplored in this field. This work aimed to introduce dried spot methodologies in natural product characterization through proof-of-concept targeted and untargeted applications, using cannabis products and wine, respectively. Robust workflows were developed for chemical profiling of wine and cannabinoid determination in cannabis products (plant material, CBD oils, etc.) through sensitive LC-HRMS/MS analysis, encompassing volumetric sampling on paper cards, designed for field use by non-trained personnel or integration in regulated environments. Important parameters were optimized for throughput, sensitivity and extraction capacity, based on an automated card extraction platform. Through comparative experiments, the proposed methodologies showed similar results to common conventional techniques, while offering convenience, reproducibility, and minimal sample size and handling requirements. Overall, this study presents a novel framework in natural products analysis by unlocking the potential of the dried spot format to foster reliable and resource-efficient quality assessment, amid high-capacity workflows with reduced logistical burdens. Acknowledgments This work was supported by “GreenCosmIn” project (HORIZON-MSCA-2022-SE-01, Project code: 101131346). Publication History Article published online: 05 March 2026 © 2026. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany