• EI
  • Scopus
  • 中国科技期刊卓越行动计划项目资助期刊
  • 北大核心期刊
  • DOAJ
  • EBSCO
  • 中国核心学术期刊RCCSE A+
  • 中国精品科技期刊
  • JST China
  • FSTA
  • 中国农林核心期刊
  • 中国科技核心期刊CSTPCD
  • CA
  • WJCI
  • 食品科学与工程领域高质量科技期刊分级目录第一方阵T1
中国精品科技期刊2020
杨赛男, 戴斌, 呙爱秀, 雷黎明. 真伪天麻的交叉响应特征谱研究[J]. 食品工业科技, 2017, (19): 227-230. DOI: 10.13386/j.issn1002-0306.2017.19.041
引用本文: 杨赛男, 戴斌, 呙爱秀, 雷黎明. 真伪天麻的交叉响应特征谱研究[J]. 食品工业科技, 2017, (19): 227-230. DOI: 10.13386/j.issn1002-0306.2017.19.041
YANG Sai-nan, DAI Bin, WO Ai-xiu, LEI Li-ming. Study on characteristic spectrum of Gastrodia elata based on cross response[J]. Science and Technology of Food Industry, 2017, (19): 227-230. DOI: 10.13386/j.issn1002-0306.2017.19.041
Citation: YANG Sai-nan, DAI Bin, WO Ai-xiu, LEI Li-ming. Study on characteristic spectrum of Gastrodia elata based on cross response[J]. Science and Technology of Food Industry, 2017, (19): 227-230. DOI: 10.13386/j.issn1002-0306.2017.19.041

真伪天麻的交叉响应特征谱研究

Study on characteristic spectrum of Gastrodia elata based on cross response

  • 摘要: 利用哺乳动物味觉系统的交叉响应原理,构建天麻特征谱,对真伪天麻进行鉴别,并对该检测系统进行精简。利用96孔板构建8传感单元的阵列传感器,使用酶标仪采集信号,组合8个传感单元信号即构成检测对象的特征谱。利用该传感器对天麻、新鲜天麻,以及天麻的4种常见伪品(芭蕉芋、马铃薯、羊角天麻、紫茉莉根)进行鉴别。结合主成分分析(PCA)、分层聚类分析(HCA)和判别分析(LDA)等模式识别方法进行数据处理。PCA结果显示,该传感器主要是基于极性与酸碱度实现对6种样本的识别;HCA结果表明,6类材料共24个样本均正确归类;LDA结果显示,该传感器对6类材料的识别准确率达100%。通过分析8个传感点的相关性,可对传感器进行精简,精简后的3单元传感器也可将6类材料聚类分开。该方法简单有效,且可批量操作,在真伪天麻的快速、通量鉴别中有潜在应用价值。 

     

    Abstract: A characteristic spectrum of Gastrodia elata was established based on the crossing response of gustatory system of mammals to identify true and false Gastrodia elata. This detection system was simplified. The array sensor with 8 sensing units was established by a piece of 96-well plate.Signal were collected by the ELIASA and combined with signals of 8 sensing units into the characteristic spectrum of detection objects. Gastrodia elata, fresh Gastrodia elata and four common categories of fake Gastrodia elata ( Canna edulis Ker, potato, Dobinea delavayi and Radix Mirabilis) were identified by this sensor.Data processing was carried out by combining principal component analysis ( PCA) , hierarchical clustering analysis ( HCA) and linear discriminant analysis ( LDA) . PCA results demonstrated that this sensor mainly identifies 6 samples based on polarity and p H value.According to HCA results, 24 samples of 6 categories were all classified accurately. LDA results showed that the identification accuracy of this sensor to six categories reached 100%. The established array sensor could be simplified into a sensor with 3 sensing units by analyzing correlation of 8 sensing units. The simplified sensor also can make accurate classification of 6 sample categories.The proposed method is simple and effective and can make mass-operations. It possesses promising potential application values in fast flux identification of Gastrodia elata.

     

/

返回文章
返回