Objective To establish a multi-index weighted optimization strategy for wine-processed Xiangfu (Cyperi Rhizoma) by integrating CRITIC weighting, Box-Behnken design-response surface methodology (BBD-RSM), and an artificial neural network (ANN), and define a robust operating space based on model prediction, thereby providing a reference for process parameter fixation and quality consistency control. Methods The contents of cyperotundone, α-cyperone, total flavonoids, and total volatile oil were used as comprehensive evaluation indices. Objective weights were assigned using the CRITIC method, and an overall desirability (OD) value was calculated. Based on single-factor experiments, a four-factor, three-level Box-Behnken design (BBD) was conducted with processing temperature, processing time, moistening time, and dosage as independent variables, and a regression model was established. An ANN prediction model was then developed, and the Garson algorithm was applied to interpret the relative contributions of factors. In addition, the Pareto non-dominated solution set was used to screen the process-parameter space to obtain a robust operating interval (model-predicted). Results The CRITIC-derived weights for cyperotundone, α-cyperone, total volatile oil, and total flavonoids were 0.274 9, 0.255 4, 0.253 4, and 0.216 3, respectively. The optimal processing conditions were determined as follows: processing temperature 140 ℃, processing time 19 min, moistening time 6.9 h, and dosage 32 g/L. The OD obtained from validation experiments was 0.655 1, RSD was 2.97%, which was close to the predicted value (0.653 3). The robust parameter interval defined based on ANN prediction and the Pareto non-dominated solution set was as follows: processing temperature 140—150 ℃, processing time 18—22 min, moistening time 6.5—7.5 h, and dosage 30—35 g/L. The model suggested that OD could remain relatively stable under ± 5% parameter fluctuations within this interval. Conclusion The constructed BBD-ANN-Pareto coupling model demonstrated good predictive ability and stability, which may provide a reference for optimizing the processing technology and ensuring the quality consistency of wine-processed Cyperi Rhizoma.

wine-processed Cyperi Rhizoma  /  processing technology  /  Box-Behnken design  /  CRITIC weight assignment method  /  artificial neural network  /  Pareto non-dominated solution set  /  cyperotundone  /  α-cyperone  /  total flavonoids  /  total volatile oil  /  robust operation interval