基于大样本检测数据的中药材二氧化硫残留风险分级与高风险品种识别

Risk Grading and High-Risk Variety Identification of Sulfur Dioxide Residues in Traditional Chinese Medicines Based on Large-Scale Sample Testing Data

中文关键词:中药材  二氧化硫残留量  CRITIC权重  风险分级  高风险品种识别

keywords:TraditionalChinesemedicines  Sulfurdioxideresidue  CRITICweighting  Riskgrading  High-riskvarietyidentification

中文摘要:摘要：目的 基于中药材大样本二氧化硫残留量检测数据，通过多维度风险评价分级，精准识别高风险品种，为中药材质量安全靶向监管提供数据支撑与技术依据。方法：以1089批次中药材及饮片二氧化硫残留量为研究对象，采用R4.4.2软件（readxl、ggplot2等包）完成数据处理与统计分析，进行整体描述性统计与膳食暴露评估；计算各品种超标率、平均暴露量、平均超标倍数、变异系数，采用CRITIC法客观确定指标权重，计算综合风险指数进行风险分级；结合层次聚类验证分级合理性。结果1089批次样品总体超标率14.69%，其中饮片超标率（18.2%）显著高于药材（3.8%）（χ2检验，p<0.001）；CRITIC权重分析显示，变异系数贡献最大（0.3915），其次为平均超标倍数（0.2059）；识别高风险品种为半夏、白芷、独活、党参、百合；暴露评估显示，所有品种平均HI＜0.08，无即时健康风险。结论?多维度风险评价模型可有效实现中药材二氧化硫残留量风险分级与高风险品种精准识别，建议将半夏、白芷等列为重点监控对象，强化监督检查与无硫加工技术推广。

Abstract:[Abstract]Objective?To establish a multi-dimensional risk grading system based on large-scale testing data of sulfur dioxide residues in traditional Chinese medicines (TCMs), and to accurately identify high-risk varieties, thereby providing data support and technical basis for targeted supervision of TCM quality safety.?Methods?A total of 1089 batches of TCMs and decoction pieces were analyzed for sulfur dioxide residues. Data processing and statistical analysis were performed using R 4.4.2 software (packages including readxl, ggplot2, etc.). Descriptive statistics and dietary exposure assessment were conducted. For each variety, the exceedance rate, average exposure level, average exceedance multiple, and coefficient of variation were calculated. The CRITIC method was used to objectively determine indicator weights, and a comprehensive risk index was calculated for risk grading. The SRI index (residue level × exceedance frequency × batch weight) was constructed to quantify risk burden, and hierarchical clustering was employed to validate the rationality of grading.?Results?The overall exceedance rate of the 1089 batches was 14.69%, with the rate for decoction pieces (18.2%) significantly higher than that for crude medicinal materials (3.8%) (χ2 test, p<0.001). CRITIC weighting analysis revealed that the coefficient of variation contributed the most (0.3915), followed by the average exceedance multiple (0.2059). The identified high-risk varieties were?Pinelliae Rhizoma,?Angelicae Dahuricae Radix,?Angelicae Pubescentis Radix,?Codonopsis Radix, and?Lilii Bulbus. Exposure assessment indicated that the average hazard index (HI) for all varieties was<0.08, suggesting no immediate health risk.?Conclusion?The multi-dimensional risk assessment model effectively enables the risk grading of sulfur dioxide residues in TCMs and accurately identifies high-risk varieties. It is recommended that varieties such as?Pinelliae Rhizoma?and?Angelicae Dahuricae Radix?be designated as priority monitoring targets, with strengthened supervision and promotion of sulfur-free processing technologies.