Regional differentiation based on volatile compounds via HS-SPME/GC-MS and chemical compositions comparison of hemp (Cannabis sativa L.) seeds.

Cannabis sativa L., has gained increasing attention due to its potential applications in various fields. However, the compositions of hemp seeds from different producing regions are quite different, significantly affects resource utilization. This work conducted the regional differentiation of hemp seeds from Dongbei, Guangxi, Inner Mongolia and Shanxi in China based on the headspace solid phase micro-extraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) and multivariate analysis. Moreover, the chemical composition, amino acid and fatty acid profiles of hemp seeds and antioxidant activities of hemp protein isolate were evaluated from above four producing regions. The results showed that hemp seeds had large amounts of fat (24.30-34.65%) and protein (21.87-23.40%) with ideal amino acid and fatty acid profiles and large amounts of volatiles. More than 300 volatile compounds were detected, and 35 key contributors to the unique aroma were finally identified out of 110 volatile compounds with odor activity values (OAVs), including 14 aldehydes, 2 ketones, 4 alcohols, 2 esters, 1 acid, 3 aromatics, 5 terpenes and 4 other compounds. The content of alcohols in all hemp seeds was highest and 16 unique volatiles only found in hemp seeds from Shanxi. Meanwhile, the VIP scores indicated that acetic acid, hexanal, hexan-1-ol and eucalyptol contributed the most to the difference among groups. According to the results of fuzzy comprehensive evaluation, the hemp seeds from Shanxi seemed to have the better quality. Therefore, multivariate analysis combined with HS-SPME/GC-MS could effectively distinguish hemp seeds from different producing regions, and thus decipher the geographical characteristics of raw materials.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2022. Published by Elsevier Ltd.)