Headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) combined with chemometrics was employed to track volatile aroma compounds during the nine-steaming and nine-drying process. A total of 84 volatile signals (including monomers, dimers, and polymers) were tentatively identified, of which 73 volatile compounds were semi-quantified. Principal component analysis (PCA) revealed a mixed clustering pattern across cycles, indicating that unsupervised methods alone could not adequately resolve the volatile changes. A partial least squares discriminant analysis (PLS-DA) model supported clear chemical discrimination among the three hypothesized stages—early (cycles 1–3), middle (4–6), and late (7–9). Based on VIP > 1 and ANOVA (q < 0.05), 29 key differential compounds were screened and categorized into three dynamic groups (decreasing, transient, and accumulating), revealing three proposed transformation windows: green-grassy odor dissipation (cycles 1–3), roasted/malty aroma generation (cycles 4–6), and aroma stabilization via end-product accumulation (cycles 7–9). Relative odor activity value (ROAV) analysis revealed a decoupling between abundance and sensory impact: high-abundance Maillard products like maltol showed negligible ROAV (<0.0003), whereas esters and aldehydes dominated the ROAV profiles, suggesting their potential as important contributors to the fruity, sweet, and malty notes. The maltol/α-cedrol ratio (M/C) increased by an order of magnitude after the seventh steaming, and color parameters E*ab correlated negatively with ester accumulation. This study provides chemical insights and quantitative indicators for aroma quality control and process determination in black ginseng production.

The volatile compounds (VOCs) evolution of wild ginseng (WG) across growth years is not a unidirectional process but a divergent remodeling of the chemical fingerprint. In this study, HS-GC-IMS combined with chemometrics was employed to characterize the dynamic changes in VOCs in WG at four growth stages (10, 15, 20, and 25 years). Samples were collected from three independent sites, with ≥5 roots pooled per site per age group to obtain population-representative composite samples. A total of 68 VOCs were tentatively identified and semi-quantified. Terpenes and pyrazines exhibited the most pronounced directional trends: terpenes such as camphene, (E,E)-α-farnesene, and β-ionone accumulated progressively (increases of 242%, 74.6%, and 93.4%, respectively), whereas pyrazines showed an overall decline through distinct trajectories—2,3,5-trimethylpyrazine declined monotonically (57.3%), 2-ethyl-6-methylpyrazine decreased moderately (27.7%), and 2,5-dimethylpyrazine exhibited a transient peak at 20 years before a sharp terminal decline (52.3%). In contrast, the majority of compounds (66%) displayed non-monotonic patterns, underscoring the complexity of this divergent evolution. Partial least squares-discriminant analysis (PLS-DA) effectively distinguished samples across growth years (R²Y = 0.997, Q² = 0.993), with a 200-times permutation test confirming no overfitting. 29 differential compounds (VIP > 1) were identified. The divergent accumulation patterns of terpenes and pyrazines, together with 29 VIP-identified differential compounds, provide chemical evidence that the VOCs fingerprint could serve as a supplementary tool for growth-year assessment. These findings provide chemical evidence that WG flavor quality evolves divergently over time, suggesting that VOCs fingerprint could serve as a supplementary tool for growth-year assessment, particularly for “high-quality but poor-shape” specimens that are undervalued by traditional morphology-based methods.

The chemical composition and perceived quality of wild ginseng (WG) are influenced by its geographical origin, yet clear chemical criteria for origin authentication remain lacking, and this problem is further complicated by the confounding effect of growth year. In this study, volatile and non-volatile fingerprints of 15- and 20-year-old WG from Huanren, Tonghua, and Ji’an (China) were characterized using HS-GC-IMS and HPLC. Partial least squares discriminant analysis (PLS-DA) models constructed separately for each growth-year group achieved complete origin separation of volatile fingerprints, with ten shared VIP markers identified. However, none maintained a consistent origin ranking across years, suggesting that the geographical signal may reside in the multivariate patterns. Ginsenoside profiling revealed a hierarchical candidate marker system: Rf, Rg1, Rc, Rb2 as robust candidate markers for Huanren, and Re as a 20-year-specific discriminator for Tonghua. The pervasive origin × growth year interaction observed across both volatile and non-volatile fractions indicates that growth-year-specific chemometric models are a necessity for reliable WG origin authentication. A practical two-step workflow—growth year determination followed by age-matched origin assignment—is proposed. These findings provide a scientific foundation for the geographical traceability and quality evaluation of WG.