Volatile Fingerprinting and Regional Differentiation of Safflower (Carthamus tinctorius L.) Using GC–IMS Combined with OPLS-DA
This study aimed to systematically characterize the volatile organic compound (VOC) profiles of safflower (<i>Carthamus tinctorius</i> L.) from eight major production regions, providing a scientific basis for quality evaluation and geographical traceability. VOC profiling was conducted using gas chromatography-ion mobility spectrometry (GC-IMS), and regional differences were assessed through multivariate statistical analyses, including Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), Euclidean distance, and hierarchical clustering. Key differential compounds were identified by variable importance in projection (VIP) and relative odor activity value (ROAV) analyses, with aldehydes and esters emerging as the primary contributors to the discrimination of samples across regions. VOC fingerprints of safflower were further established, and a combined VIP-ROAV strategy was proposed for the screening of characteristic compounds. These findings provide a reliable reference for safflower quality control and offer practical guidance for its geographical authentication in the food industry.
Authors
- Wenjie Yan (ORCID: https://orcid.org/0000-0002-7009-8360)
- Jiao Liu (ORCID: https://orcid.org/0000-0002-9810-2325)
- Hao Duan
- Li Wang (ORCID: https://orcid.org/0000-0001-7692-5067)
- Jiaqi Liu (ORCID: https://orcid.org/0000-0003-4983-7816)
- Hong Liu (ORCID: https://orcid.org/0000-0002-7256-5751)
- Rui Qin (ORCID: https://orcid.org/0000-0003-4093-7044)
- Shuyuan Bao
Institutions
- Beijing Union University (CN)
- Central South University (CN)
- Minzu University of China (CN)
- National Medical Products Administration (CN)
Publication Details
- Journal
- Foods
- Published
- 2025-09-29
- DOI
- https://doi.org/10.3390/foods14193381
- Citations
- 1
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.67