Objective To address the potential uneven distribution of active ingredients indicated by uneven color within batches of soft material fine powder during the production process of Guizhi Fuling Capsules (GFC, 桂枝茯苓胶囊), a “cascade fault-tolerant model” was constructed based on color difference characteristics to explore a new low-cost approach for intermediate quality control. Methods A total of 177 samples of soft material fine powder from five batches were collected. The paeoniflorin content, determined by HPLC, was divided into low, medium, and high grades at a ratio of 2:6:2. Based on a traditional three-class model, a cascade fault-tolerant quality control model was constructed by comparing 126 algorithm combinations, which involved a primary algorithm for early warning and a secondary physical direction for correction. External validation was introduced to assess the generalization ability, and quality control experiments were conducted based on the model results. Finally, near-infrared spectroscopy (NIRS) technology was used for benchmarking against the upper limit of efficacy. Results Correlation analysis established paeoniflorin as the core grading indicator, with its content showing a significant positive correlation with red-green chroma a^* (r = 0.64, P < 0.001). The analysis indicated that the accuracy of the benchmark model was only 70.34% (RSD was 12.70%), which was difficult to meet quality control requirements. However, the cascade fault-tolerant model achieved an overall industrial accuracy of 78.62%, with significantly enhanced robustness (RSD was 6.79%), and its external validation accuracy was 80.56%. Quality control experiments showed that the RSD of paeoniflorin content in mixed samples decreased from 7.74% in random mixing to 2.34%, indicating a significant increase in material uniformity, and a simultaneous reduction in total mixing process time and load. Benchmarking results with NIRS (accuracy of 90.68%, RSD was 6.22%) indicated that the colorimeter had a high cost-performance ratio and could be used for batch screening; NIRS was more accurate and suitable for high-precision grading. Conclusion The cascade fault-tolerant model constructed in this study achieved the synergistic empowerment of algorithm early warning and physical correction, effectively enhancing the discriminative robustness of low-cost optical sensors. This provides a new strategy for quality control of active ingredients in batches of intermediates during the production process of traditional Chinese medicine in the future.

Guizhi Fuling Capsules  /  soft material fine powder  /  color difference feature  /  cascaded fault tolerance  /  intermediate product quality control  /  near-infrared spectroscopy  /  performance benchmarking  /  industrial application