In this study, the process of steam distillation to collect volatile oils from Forsythia suspensa (F. suspensa) and Lonicera japonica (L. japonica) was optimized according to the concept of quality by design. First, the liquid/material ratio, distillation time, and collection temperature were identified as critical process parameters by a review of the literature and single-factor experiments. Then, a Box‒Behnken design was used to study the quantitative relationship between the three process parameters, two raw material properties, and the yield of volatile oil. A mathematical model was established with an R2 value exceeding 0.90. Furthermore, the design space of the volatile oil yield was calculated by a probability-based method. The results of a verification experiment showed that the model was accurate and the design space was reliable. A total of 16 chemical constituents were identified in the volatile oil from mixtures of F. suspensa and L. japonica. The content of β-pinene was the highest (54.75%), and the composition was similar to that of the volatile oil of F. suspensa. The results showed that when F. suspensa and L. japonica were distilled together, the main contribution to the volatile oil was from F. suspensa. The volatile oil yield from the combination of F. suspensa and L. japonica was not higher than that from L. japonica.

In this study, the electronic nose and GC/MS were used to analyze the chemical components of essential oils from different germplasm resources of Artemisia argyi Folium (A. argyi), in order to quickly identify essential oils of A. argyi from different germplasm resources and clarify the differences among different A. argyi samples. The essential oils of A. argyi were extracted by steam distillation. This article describes for the first time that electronic nose combined with chemometrics can distinguish the essential oils of A. argyi from different germplasm, which proves the reliability and potential of this technology. GC/MS was used to identify 134 volatile components from the essential oil of A. argyi. The main bioactive components were cineole, thujarone, artemisia ketone, βcaryophyllene, (À )-4-terpinol, 3,3,6-trimethyl-1,5-heptadien-4-ol, (À )-α-thujone, camphor, borneol. In addition, the results of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that there were significant differences in the essential oils of A. argyi from different germplasm resources, terpenes, alcohols and ketones played an important role in identifying the essential oils of A. argyi from different germplasm resources. This indicates that electronic nose and GC/MS combined with chemometrics can be used as reliable techniques to identify different germplasm resources of A. argyi, and provide certain reference value for quality evaluation, selection of high-quality varieties and rational development of resources of A. argyi.