| Abstract:Objective: In this study, volatile composition, content, and odor of Zingiberis Rhizoma (ZR) from different regions and a content prediction model for key components were analyzed to provide methodological references in quality evaluation of ZR. Methods: Headspace-gas chromatography-mass spectrometry (HS-GC-MS) was used to analyze volatile components qualitatively and quantitatively of ZR from different regions and the ROAV values were used to select the key odor compounds. Fourier Transform-near infrared spectroscopy (FT-NIR) technique was employed to obtain the spectral information. Partial least squares regression (PLSR) was applied to establish a quantitative model to achieve content prediction of volatile components in ZR. Results: HS-GC-MS results showed that a total of 33 volatile components were identified, of which sesquiterpenes accounted for 52.69% and monoterpenes accounted for 37.21%. The most abundant compounds were zingiberene (29.25%), β-phellandrene (14.34%), and camphene (8.69%). Chemometric analyses showed that ZR from different regions could be accurately classified. A total of 10 key compounds were screened by variable importance projection (VIP), and the top three were 4-terpineol, (+)-cyclosativene, and (-)-α-copaene. The ROAV values showed that α-pinene, linalool, β-myrcene, 2-heptanol, and borneol exhibited high contribution to the ZR aroma. FT-NIR analyses showed that an accurate classification of different ZR regions could be achieved. The coefficients of determination for prediction (R2p) were 0.932, 0.902, 0.887, and the values of residual predictive deviation (RPD) were all greater than 2.0 in the PLSR models, indicating that the predicted values of NIR models and the measured values demonstrated a good linear relation, suggesting a great prediction ability of the models. Conclusion: This study demonstrated a comprehensive method that combined multiple analysis techniques to accurately realize the quality evaluation of ZR. This established strategy can also provide a new idea for quality assessment of other homology of medicine and food. |
