The current production of Chinese herbal decoction pieces faces several issues including strong subjectivity,unstable quality,low production efficiency,and a lack of intelligent systems.In order to expedite the intelligent transformation and upgrading of Chinese medicine processing,this paper delves deeply into the problems and challenges encountered in establishing a digital and intel-ligent production model for Chinese herbal pieces.Addressing the slow progress in fundamental research on traditional Chinese medi-cine processing mechanisms,the absence of online digital quality characterization techniques,the low level of production equipment in-telligence,and the lack of evaluation standards for high-quality decoction pieces,this paper proposes a"New Quality Productive Forces"formation approach driven by technological innovation.Through interdisciplinary integration methods,the paper explores the mechanisms of Chinese medicine processing in depth,clarifies the correlation between the processing procedures and the"medicinal properties-quality"relationship,and employs bionic sensing and artificial intelligence to achieve a holistic quality characterization of decoction pieces.Additionally,the use of cloud-edge collaborative big data systems is proposed to enhance intelligent upgrades of the production lines.The paper also aims to establish a high-quality decoction piece evaluation system integrating"physical-chemical-bio-logical"multimodal data fusion.This approach aims to steer the Chinese medicine processing towards becoming more efficient,precise,and sustainable,thereby promoting high-quality sustainable development of the Chinese herbal decoction industry and providing both theoretical and practical support for the modernization of traditional Chinese medicine.

OBJECTIVE To optimize the processing technology of Epimedium koreanum roasted with suet oil and analyze its characteristic chromatogram before and after processing. METHODS The optimal processing technology was optimized by orthogonal experiments with frying power， frying time and medicinal temperature as factors using the comprehensive score of appearance traits （color+odor）， alcohol-soluble extract， the contents of icariin and baohuoside Ⅰ as evaluation index， then proceed with verification. The E. koreanum roasted with suet oil was prepared with the optimal technology. The characteristic chromatograms of 15 batches of E. koreanum were established with the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 edition）， and then similarity analysis was also conducted. Clustering analysis， principal component analysis， and orthogonal partial least squares discriminant analysis were used to evaluate the differences in E. koreanum before and after processing. RESULTS The optimal processing technique for E. koreanum roasted with suet oil was as follows： first， heat 4 g of suet oil at a power of 600 W until it melts； next， when the temperature at the bottom of the pan reaches 140 ℃， add 20 g of E. koreanum silk and stir-fry for 6 minutes； finally， remove it and let it cool. Comprehensive score of 3 validation tests was 98.94 points　（RSD＜3%）. The established characteristic chromatogram of E. koreanum and E. koreanum roasted with suet oil were calibrated with 16 and 15 common peaks， respectively. Chromatographic peak 2 was determined to be chlorogenic acid， peak 5 to be chaohuoding A， peak 6 to be chaohuoding B， peak 7 to be chaohuoding C， peak 8 to be icariin， and peak 14 to be baohuoside Ⅰ. The similarities were all greater than 0.9. Results of cluster analysis and principal component analysis showed that E. koreanum and E. koreanum roasted with suet oil were clustered into distinct groups. The results of orthogonal partial least squares discriminant analysis showed that the variable importance projection values for peak 13， peak 15， peak 9， peak 1， peak 8， peak 12， peak 7， and peak 10 were all greater than 1. CONCLUSIONS The study successfully optimized the processing technology of suet oil-roasted E. koreanum. There are significant differences in the characteristic chromatograms of E. koreanum before and after processing. Among them， the chemical components corresponding to peak 13， peak 15， peak 9， peak 1， peak 8， peak 12， peak 7， and peak 10 may be the differential components of E. koreanum before and after processing.

ObjectiveIn order to find a fast odor-based method for the identification of sulfur fumigated Gastrodiae Rhizoma， an ultra-fast gas phase electronic nose technology was used to identify the odors of different degrees of sulfur fumigated Gastrodiae Rhizoma decoction pieces. MethodHeracles NEO ultra-fast gas phase electronic nose was employed to collect gas chromatograms of unsulfured and sulfured with different degrees of Gastrodiae Rhizoma decoction pieces， gas chromatograms were performed under programmed temperature （initial temperature of 40 ℃， 0.2 ℃·s^-1 to 60 ℃， and then 4 ℃·s^-1 to 250 ℃）， the sample volume was 5 mL， the incubation temperature was 65 ℃ and incubation time was 35 min. Kovats retention index and the AroChemBase database were used for qualitative analysis， and stoichiometric analysis was performed on this basis. Principal component analysis （PCA）， discriminant factor analysis （DFA） and partial least squares-discriminant analysis （PLS-DA） models were established to identify the Gastrodiae Rhizoma decoction pieces with different degrees of sulfur fumigation. ResultAccording to the comparative analysis of AroChemBase database， there were significant differences in the odor characteristics of sulfur fumigated and non-sulfur fumigated Gastrodiae Rhizoma， cyclopentane， acetone and heptane might be the odor components to distinguish the degree of sulfur fumigation in Gastrodiae Rhizoma decoction pieces. The identification index of PCA model was 81， the accumulative discriminant index of the discriminating factors was 92.09% in DFA model， the supervisory model interpretation rate of PLS-DA model was 0.963 and the predictive ability parameter was 0.956， indicating that PCA， DFA and PLS-DA models could well distinguish Gastrodiae Rhizoma decoction pieces with different sulfur fumigation degrees. ConclusionHeracles NEO ultra-fast gas phase electronic nose can be used as a rapid method to identify and distinguish Gastrodiae Rhizoma decoction pieces with different levels of sulfur fumigation. Meanwhile， it can provide a rapid， simple and green method and technology for identification of traditional Chinese medicine decoction pieces by sulfur fumigation.