白酒从原料到产品的农药残留分布特征分析及风险评估

Distribution characteristics analysis and risk assessment of pesticide residue in Baijiu from raw materials to products

中文关键词:  农药残留  高分辨质谱  白酒  分布特征  风险评估

英文关键词:pesticide residues  ultra performance liquid chromatography-Orbitrap-high resolution mass spectrometry  Baijiu  distribution characteristics  risk assessment

中文摘要:

      目的 建立一种高效、精准的分析方法, 以追踪农药残留从酿酒原料到白酒产品中的迁移与分布规律, 并评估其潜在风险。方法 采集不同来源的酿酒原料(大米、糯米)及对应的白酒产品, 样品经乙腈提取净化后, 采用超高效液相色谱-静电场轨道阱高分辨质谱技术进行分析, 通过拟靶向筛查与数据库匹配进行定性, 并利用标准物质进行定量。结果 所建立的三唑磷、禾草灭、稻瘟灵、合杀威和克草敌等5种农药残留定量方法在1.0~50.0 ng/mL范围内线性良好, 相关系数(r)>0.998, 方法检出限为0.12~0.32 ng/mL, 定量限为0.48~1.05 ng/mL, 加标回收率为88.60%~95.60%(相对标准偏差<3%)。分布特征分析表明: 农药残留主要集中在农户散种的原料中, 三唑磷、禾草灭、稻瘟灵在样品中普遍检出, 而合杀威(大米、糯米)与克草敌(仅糯米)则特异性出现在10月30日后收购的样品中, 显示出明显的时空分布差异; 基地种植的原料及所有白酒产品中均未检出高风险农药残留。风险评估结果显示, 所有检出农药的残留水平均低于GB 2763—2021《食品安全国家标准 食品中农药最大残留限量》规定的最大残留限量, 整体风险可控。结论 本研究成功揭示了酿酒链条中农药残留的关键分布节点与特征, 明确了风险主要源于特定来源和收购批次的原料。该研究为白酒产业实施源头精准管控和全过程风险预警提供了关键的数据支持与科学依据。

英文摘要:

      Objective To establish an efficient and accurate analytical method to track the transfer and distribution patterns of pesticide residues from brewing raw materials to the final Baijiu products, and to assess their potential risks. Methods Raw materials (rice and glutinous rice) from different sources and their corresponding Baijiu products were collected. Samples were extracted and purified with acetonitrile, then analyzed using ultra performance liquid chromatography-Orbitrap-high resolution mass spectrometry. Compounds were identified through a pseudo-targeted screening approach with database matching and quantified using reference standards. Results The established quantitative analytical methods for 5 kinds of pesticide residues, including triazophos, alloxydim, isoprothiolane, bufencarb and pebulate, exhibited good linearity in the range of 1.0–50.0 ng/mL (correlation coefficient, r>0.998). The method limits of detection and limits of quantitation were 0.12–0.32 ng/mL and 0.48–1.05 ng/mL, respectively. The spiked recoveries ranged from 88.60% to 95.60% with relative standard deviations below 3%. Analysis of distribution characteristics revealed that pesticide residues were primarily concentrated in raw materials from scattered household farming. Triazophos, alloxydim and isoprothiolane were commonly detected in both rice and glutinous rice samples, whereas butacarb (detected in both rice and glutinous rice) and pebulate (detected only in glutinous rice) were specifically found in samples collected after October 30, indicating significant spatio-temporal distribution differences. No high-risk pesticide residues were detected in raw materials from base cultivation or in any Baijiu products. The risk assessment indicated that the levels of all detected pesticide residues were below the GB 2763—2021 National food safety standards-Maximum residue limits of pesticides in food, suggesting that the overall risk is controllable. Conclusion This study successfully reveals the key distribution nodes and characteristics of pesticide residues throughout the Baijiu production chain, identifying that the risk primarily originates from raw materials of specific sources and procurement batches. It provides crucial data support and a scientific basis for implementing targeted source control and whole-process risk early warning in the Baijiu industry.