The field of traditional herbal product research is gaining global significance due to its widespread use across various cultures as food, medicine, and health supplements. These products are derived from a diverse range of biological organisms, including plants, animals, fungi, and others. Despite their popularity, there are critical challenges in ensuring the safety and efficacy of these products because of discrepancies between labeled and actual species composition. This problem is exacerbated by the complexity of finished products and the limitations of current quality control methods, such as morphological identification and chemical profiling, which often fall short in addressing species authentication. As traditional medicinal products undergo several processing steps, diagnostic biomarkers may degrade, complicating efforts to authenticate ingredients and maintain consumer trust.

This Research Topic aims to tackle these challenges by introducing innovative and integrative methodologies to accurately identify species composition in traditional herbal products. The primary focus will be on detecting adulterants or counterfeit ingredients through advanced techniques like DNA barcoding coupled with high-throughput sequencing, multi-omics technologies, chemical fingerprinting, and machine learning-driven approaches. Additionally, this topic invites research on establishing rigorous analytical frameworks and standardized protocols to guide the analysis of commercial products. Collaboration between researchers in both the scientific and economic domains is also encouraged to explore the root causes of ingredient adulteration and foster interdisciplinary dialogue.

To gather further insights into these efforts, we welcome articles addressing, but not limited to, the following themes:

DNA barcoding combined with high-throughput sequencing techniques for traditional medicinal product authentication.

Development of robust analytical frameworks integrating multi-omics and advanced data analysis tools.

Application of AI algorithms for the detection of adulterants in traditional herbal products.

Evaluation of emerging real-time detection techniques such as portable sequencing devices and hyperspectral imaging.

Establishment of standardized protocols that bridge the gap between raw material testing and product verification.

Exploration of regulatory advancements to enhance labeling transparency and traceability of raw materials.

Interdisciplinary discussions on economic and technological issues driving adulteration in traditional herbal products.

By focusing on these areas, the Research Topic aims to enhance the detection and prevention of adulteration in traditional herbal products, ensuring safety and efficacy for consumers. Original research articles and reviews are welcome to enrich this discussion.

Please note:

Studies need to comply with the best practice guidelines of the leading journals for pharmacological studies on plant extract / natural products, including the Four Pillars of Best Practice in Ethnopharmacology, and follow the standards established in the ConPhyMP statement Front. Pharmacol. 13:953205. A detailed description of the material studied, its extraction, and processing is essential, and manuscripts that lack such a description will be desk-rejected. You can freely download the full version here (https://ga-online.org/best-practice). Please self-assess your MS using the ConPhyMP tool.
Purely in silico studies are outside of the scope of this journal (e.g., network studies)

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Innovative approaches to authenticate multi-species traditional herbal products