Botanical supplements with broad traditional and medicinal uses represent an area of growing importance for American health management; 25% of U.S. adults use dietary supplements daily and collectively spent over $9. 5 billion in 2019 in herbal and botanical supplements alone. To understand how natural products benefit human health and determine potential safety concerns, careful in vitro, in vivo, and clinical studies are required. However, botanicals are innately complex systems, with complicated compositions that defy many standard analytical approaches and fluctuate based upon a plethora of factors, including genetics, growth conditions, and harvesting/processing procedures. Robust studies rely upon accurate identification of the plant material, and botanicals' increasing economic and health importance demand reproducible sourcing, as well as assessment of contamination or adulteration. These quality control needs for botanical products remain a significant problem plaguing researchers in academia as well as the supplement industry, thus posing a risk to consumers and possibly rendering clinical data irreproducible and/or irrelevant. Chemometric approaches that analyze the small molecule composition of materials provide a reliable and high-throughput avenue for botanical authentication. This review emphasizes the need for consistent material and provides insight into the roles of various modern chemometric analyses in evaluating and authenticating botanicals, focusing on advanced methodologies, including targeted and untargeted metabolite analysis, as well as the role of multivariate statistical modeling and machine learning in phytochemical characterization. Furthermore, we will discuss how chemometric approaches can be integrated with orthogonal techniques to provide a more robust approach to authentication, and provide directions for future research.
Introduction
Selection of marker compounds for targeted chemical analysis is complicated when considering varying instrumentation and closely related plant species. High‐resolution gas chromatography–mass spectrometry (GC–MS), via orbitrap detection, has yet to be evaluated for improved marker compound selection.
Objective
This study directly compares high‐ and low‐resolution GC–MS for botanical maker compound selection using Ocimum tenuiflorum L. (OT) and Ocimum gratissimum L. (OG) for botanical ingredient authentication.
Methods
The essential oils of OT and OG were collected via hydrodistillation before untargeted chemical analysis with gas chromatography coupled to single‐quadrupole (GC‐SQ) and orbitrap (GC‐Orbitrap) detectors. The Global Natural Products Social Molecular Networking (GNPS) software was used for compound annotation, and a manual search was used to find the 41 most common Ocimum essential oil metabolites.
Results
The GC‐Orbitrap resulted in 1.7‐fold more metabolite detection and increased dynamic range compared to the GC‐SQ. Spectral matching and manual searching were improved with GC‐Orbitrap data. Each instrument had differing known compound concentrations; however, there was an overlap of six compounds with higher abundance in OG than OT and three compounds with a higher abundance in OT than OG, suggesting consistent detection of the most variable compounds. An unsupervised principal component analysis (PCA) could not discern the two species with either dataset.
Conclusion
GC‐Orbitrap instrumentation improves compound detection, dynamic range, and feature annotation in essential oil analysis. However, considering both high‐ and low‐resolution data may improve reliable marker compound selection, as GC‐Orbitrap analysis alone did not improve unsupervised separation of two Ocimum species compared to GC‐SQ data.
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