气相色谱-质谱法构建燕窝单糖指纹图谱及其掺伪鉴别

Construction of monosaccharides fingerprint and adulteration identification of edible bird’s nest by gas chromatography-mass spectrometry

中文关键词:  食用燕窝  气相色谱-质谱联用技术  单糖组成  指纹图谱  掺伪鉴别

英文关键词:edible bird’s nest  gas chromatography-mass spectrometry  monosaccharide composition  fingerprint  adulteration identification

中文摘要:

      目的 基于气相色谱-质谱法(gas chromatography-mass spectrometry, GC-MS)构建食用燕窝单糖标准指纹图谱, 并对食用燕窝进行掺伪鉴别。方法 以食用燕窝为研究对象, 采集34批次不同供应商的食用燕窝作为样本, 对其单糖进行GC-MS分析, 通过“中药色谱指纹图谱相似度评价系统”建立食用燕窝单糖标准指纹图谱, 并以掺伪量分别为1%、5%、10%、20%、30%、40%、50%的银耳多糖、黄明胶、果胶、结冷胶、卡拉胶和琼脂建立相应掺伪模型。结果 食用燕窝中含有岩藻糖、甘露糖、半乳糖、乙酰氨基葡萄糖和乙酰氨基半乳糖5种单糖成分, 平均相对质量比为1:1.5:8.4:6.6:4.1, 总糖含量在18.75~23.92 g/100 g, 通过相似度评价34批次食用燕窝的相似度均大于99.5%, 符合指纹图谱相似度评价要求。以相似度为99.8%作为食用燕窝鉴别标准, 在掺伪量在1%~50%时, 利用指纹图谱掺伪模型, 可有效预测掺伪量, 实现掺伪鉴别。结论 本研究通过分析食用燕窝单糖组成并建立GC-MS单糖标准指纹图谱及掺伪模型, 可有效对常见掺伪物进行鉴别和掺伪量预测, 为市场监管提供了一定的数据及技术支撑。

英文摘要:

      Objective To construct a standard fingerprint of monosaccharides in edible bird’s nest by gas chromatography-mass spectrometry (GC-MS), and identify the adulteration of edible bird’s nest. Methods Taking edible bird’s nest as the research object, 34 batches of monosaccharides in edible bird’s nest from different suppliers were analyzed by GC-MS. And a standard fingerprint of monosaccharides in edible bird’s nest was established using the “similarity evaluation system of traditional Chinese medicine chromatographic fingerprint”. The fingerprint was used to identify adulteration models of tremella fuciformis polysaccharide, yellow gelatin, pectin, gellan gum, carrageenan and agar with adulteration amounts of 1%, 5%, 10%, 20%, 30%, 40% and 50%, respectively. Results Edible bird’s nest contains 5 kinds of monosaccharide components: fucose, mannose, galactose, acetylglucosamine and acetylgalactosamine, with an average relative mass ratio of 1:1.5:8.4:6.6:4.1, and the total sugar content ranging from 18.75 g/100 g to 23.92 g/100 g, through similarity evaluation, the similarity of 34 batches of edible bird’s nests was more than 99.5%, meeting the requirements of fingerprint similarity evaluation. Taking a similarity of 99.8% as the identification standard for edible bird’s nests, when the adulteration level ranges from 1% to 50%, the fingerprint adulteration model could effectively predict the adulteration level and achieve adulteration identification. Conclusion This study analyzes the monosaccharide composition of edible bird’s nest and established a GC-MS-based standard monosaccharide fingerprint and adulteration model. This approach enables effective identification of common adulterants and quantification of adulteration ratios, offering data and technical support for market supervision.