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中国精品科技期刊2020
刘伟, 赵杨, 苏东林, 李高阳, 单杨. 直接进样-质谱检测指纹图谱技术结合化学计量学研究干燥方法对黄花菜质量的影响[J]. 食品工业科技, 2018, 39(16): 220-225. DOI: 10.13386/j.issn1002-0306.2018.16.039
引用本文: 刘伟, 赵杨, 苏东林, 李高阳, 单杨. 直接进样-质谱检测指纹图谱技术结合化学计量学研究干燥方法对黄花菜质量的影响[J]. 食品工业科技, 2018, 39(16): 220-225. DOI: 10.13386/j.issn1002-0306.2018.16.039
LIU Wei, ZHAO Yang, SU Dong-lin, LI Gao-yang, SHAN Yang. Influence of Drying Processes on Characterisation of Daylily Flowers Using Flow Injection Mass Spectrometric Fingerprinting Method Combined with Chemometric Analysis[J]. Science and Technology of Food Industry, 2018, 39(16): 220-225. DOI: 10.13386/j.issn1002-0306.2018.16.039
Citation: LIU Wei, ZHAO Yang, SU Dong-lin, LI Gao-yang, SHAN Yang. Influence of Drying Processes on Characterisation of Daylily Flowers Using Flow Injection Mass Spectrometric Fingerprinting Method Combined with Chemometric Analysis[J]. Science and Technology of Food Industry, 2018, 39(16): 220-225. DOI: 10.13386/j.issn1002-0306.2018.16.039

直接进样-质谱检测指纹图谱技术结合化学计量学研究干燥方法对黄花菜质量的影响

Influence of Drying Processes on Characterisation of Daylily Flowers Using Flow Injection Mass Spectrometric Fingerprinting Method Combined with Chemometric Analysis

  • 摘要: 采用直接进样-质谱检测指纹图谱技术(flow injection mass spectrometric fingerprinting method,FIMS)结合化学计量学方法研究不同干燥方法处理黄花菜质量的影响。自然干燥、热风干燥、真空冷冻干燥3种处理后的30个黄花菜样品经简单提取后,不经色谱柱分离,直接进入质谱仪进行分析,FIMS分析1个样品仅需2 min,采集m/z 100~1000的离子响应强度信息,经预处理后由分析软件Simca-P进行主成分分析(PCA)和偏最小二乘法判别分析(PLS-DA)。结果表明负离子模式下m/z 191.06、259.09、341.11、503.16、421.15、609.15、665.21、711.22、827.27及989.32等离子出现高的响应强度。经PCA和PLS-DA分析得到的分布图将不同干燥处理的黄花菜聚为3类,反应了其化学成分的差异性;采用PCA处理后3个主成分的贡献率是91.2%,采用PLS-DA的分类模型预测能力达到97.3%。通过载荷图则可发现在分类过程中起决定作用的化学标记物。该方法作为一种极具特点的指纹图谱分析技术,可以用于不同加工方式的农产品质量快速判别研究。

     

    Abstract: A flow-injection mass spectrometric metabolic fingerprinting method in combination with chemometrics was used to study the characterisation of daylily flowers from different drying processes. 30 daylily flower samples with three different drying treatments(vacuum freeze drying,solar drying and hot-air drying treatments)were extracted in a simple way and were directly injected into the mass spectrometer for the analyses with no column used. FIMS fingerprinting method required 2 min of analysis time per sample. Based on the intensities of the ions at m/z 100~1 000,principal components analysis and partial least square discrimination analysis were utilized to analyze by Simca-P software. The results showed that prominent ions at m/z 191.06,259.09,341.11,503.16,421.15,609.15,665.21,711.22,827.27 and 989.32.Daylily flower samples from different drying treatment were classified into three clusters in scores plot by PCA and PLS-DA analysis. The cumulative contribution rate was 91.2% in the PCA model,and the prediction accuracies of validation set were 91.2% in the PLS-DA model. The biomarkers which played the most important roles in classification were screened out. FIMS as a novel and characteristic fingerprinting method could be widely and efficiently used in characterisation research of agricultural products from different processes.

     

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