AUTHOR=Yang Rui-Qi , Li Jia-Hui , Feng Hui-Shang , Yao Yue-Bao , Guo Xing-Yu , Yu Shu-Lin , Cui Yang , Zou Hui-Qin , Yan Yong-Hong TITLE=Identification of Nutmeg With Different Mildew Degree Based on HPLC Fingerprint, GC-MS, and E-Nose JOURNAL=Frontiers in Nutrition VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2022.914758 DOI=10.3389/fnut.2022.914758 ISSN=2296-861X ABSTRACT=

Nutmeg (Myristicae Semen), the so-called Rou-Dou-Kou in Chinese, is one kind of Chinese herbal medicines (CHMs) as well as a globally popular spice. Hence, its stable quality and safe application attract more attention. However, it is highly prone to mildew during storage due to its rich volatile components and fatty oil. Therefore, in this study, an electronic nose (E-nose) was introduced to attempt to reliably and rapidly identify nutmeg samples with different degrees of mildew. Meanwhile, the chemical composition and volatile oil were analyzed using HPLC fingerprint and GC-MS, respectively, which could support and validate the result of E-nose. The results showed that the cluster results of HPLC fingerprint and GC-MS were generally consistent with E-nose, and they all clustered into two categories. Additionally, a discriminant model was established, which divided the samples into three categories: mildew-free, mildew-slight, and mildew, and a high DPR was obtained, which indicates that the E-nose could be a novel and promising approach for the establishment of a quality evaluation system to identify CHMs with different degrees of mildew rapidly, especially to identify early mildew.