Objective To optimize the preparation process of Angelica sinensis volatile oil inclusion complex and the key parameters.

Methods Using the comprehensive score of encapsulation efficiency and inclusion complex yield as the evaluation indexes, the mass-volume ratio of β-cyclodextrin (β-CD) to volatile oil, the ratio of water to β-CD, and the grinding inclusion time were selected as the investigation factors. The process parameters were initially screened through orthogonal experiments. Furthermore, based on the orthogonal experimental data, a backpropagation (BP) neural network model was constructed to achieve global optimization of multi-factor nonlinear relationships. The inclusion complex was characterized by gas chromatography (GC) fingerprint similarity evaluation and differential scanning calorimetry.

Results The optimal inclusion process was as follows: the mass-to-volume ratio of β-CD to volatile oil was 10 ∶ 1, the ratio of water to β-CD was 3 ∶ 1, and the grinding and inclusion time was 20 min. The differential scanning calorimetry analysis and similarity evaluation of GC fingerprint indicated that the inclusion complex had been successfully formed and its main chemical components had not undergone significant changes.

Conclusion  The model established based on orthogonal experiment and BP neural network has the dual advantages of efficient screening and global optimization, significantly improving the accuracy and reliability of process optimization results. It can provide reference for the development of Angelica sinensis volatile oil inclusion process..

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