摘要
[目的]建立一种快速无损的铁棍山药真伪鉴别方法。[方法]在常温常压环境下,运用大气压化学电离质谱技术对不同产地的铁棍山药(TG)和非铁棍山药(FTG)化学成分进行检测,每种铁棍山药样品和非铁棍山药样品各采集200组数据,共获得3600个质谱数据点,利用主成分分析(PCA)和随机森林(RF)算法对获得的一级质谱数据进行模式识别分析,建立铁棍山药与非铁棍山药真伪鉴别模型。[结果]通过HS-APCI-MS获得的铁棍山药样品与非铁棍山药样品的一级质谱图差异明显,根据主成分累计方差贡献图,前7个主成分的累计方差贡献率为85.63%(≥85%);当决策树数量为25时,训练集、检测集准确率均达到100%,所建立的铁棍山药原位质谱分析结合RF算法对铁棍山药的鉴别效果显著,RF的分类效果优于PCA。[结论]应用原位质谱分析技术结合RF算法可以快速无损鉴别铁棍山药真伪。
[Objective]To establish a fast and nondestructive analysis method for identifying iron rod yam.[Methods]Atmospheric pressure chemical ionization mass spectrometry(APCI-MS)was employed to detect the chemical constituents of iron rod yam(TG)and noniron rod yam(FTG)from different origins under ambient temperature and pressure,With 200 sets of data collected from each type of TG and FTG,and a total of 3600 mass spectrometry data points were obtained.Subsequently,the initial level of the mass spectrometry data obtained was analyzed using Principal Component Analysis(PCA)and the random forest(RF)algorithm.Pattern recognition analysis established a model to differentiate between TG and FTG based on their chemical compositions.[Results]The difference between the firstlevel mass spectra obtained by HS-APCI-MS was obvious between TG samples and FTG samples.The cumulative variance contribution plot of the principal components showed that the first seven principal components accounted for 85.63%(≥85%)of the variance.The accuracy of the training set and detection set reached 100%when the number of decision trees was 25.HS-APCI-MS combined with RF algorithm had a significant identification effect on TG,and the classification effect of RF was superior to that of PCA.[Conclusion]Atmospheric pressure chemical ionization mass spectrometry,combined with the RF algorithm,can rapidly and non-destructively identify TG and FTG,providing a new technical method for authenticating TG.
作者
钟恒艳
陈春
欧阳永中
周林
郭伟清
ZHONG Hengyan;CHEN Chun;OUYANG Yongzhong;ZHOU Lin;GUO Weiqing(School of Foshan University,Foshan,Guangdong 528000,China;Foshan Polytechnic,Foshan,Guangdong 528137,China;Pharmacy Department,Guangdong Yifang Pharmaceutical Co.,Ltd.,Foshan,Guangdong 528244,China;GRINM(Guangdong)Institute for Advanced Materials and Technology,Foshan,Guangdong 528000,China)
出处
《食品与机械》
CSCD
北大核心
2024年第11期47-53,共7页
Food and Machinery
基金
中药复杂体系原位质谱分析方法研究(项目批号2021ZDZX2060)
佛山市南海区重点领域科技攻关专项。
关键词
铁棍山药
大气压化学电离源
主成分分析
随机森林算法
鉴别
iron rod yam
atmospheric chemical ionization source
principal component analysis
random forest algorithm
identification
