1. 吉林农业大学中药材学院,吉林,长春,130118
2. 农业部参茸产品质量监督检测中心,吉林长春,130118
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邢琳, 汪树理, 任谓明, 等. 傅里叶变换近红外光谱结合化学计量学对不同类别人参的快速无损鉴别研究[J]. 上海中医药杂志, 2019,53(7):75-82.
XING Lin, WANG Shuli, REN Weiming, et al. Study on Fourier-transform near infrared spectroscopy combined with chemometrics for rapid and nondestructive identification of different kinds of ginseng [J]. Shanghai Journal of Traditional Chinese Medicine, 2019,53(7):75-82.
邢琳, 汪树理, 任谓明, 等. 傅里叶变换近红外光谱结合化学计量学对不同类别人参的快速无损鉴别研究[J]. 上海中医药杂志, 2019,53(7):75-82. DOI: 10.16305/j.1007-1334.2019.07.019.
XING Lin, WANG Shuli, REN Weiming, et al. Study on Fourier-transform near infrared spectroscopy combined with chemometrics for rapid and nondestructive identification of different kinds of ginseng [J]. Shanghai Journal of Traditional Chinese Medicine, 2019,53(7):75-82. DOI: 10.16305/j.1007-1334.2019.07.019.
目的:建立近红外快速无损定性聚类模型,以从分子水平上快速无损鉴别外观相似但类别不同的池底(Chidi ginseng)、野山参(wild ginseng)、野山参移栽(transplantation of wild ginseng)和趴货(Pahuo ginseng)。 方法:利用傅里叶变换近红外光谱仪在无损条件下采集样品,近红外谱图扫描的波数范围为10 000 cm-1~4 100 cm-1,结合化学计量学软件建立4种样品的快速无损定性聚类模型。 结果:建立的定性聚类模型对4种样品的识别率分别为98%、98%、97%、97%,4种样品的验证合集谱图的识别率为98%。池底样品、野山参样品、野山参移栽样品和趴货样品在第一主成分(first principal component,PC1)上的得分分别为0.089 724~0.125 83,0.098 37~0.127 75,0.045 894~0.186 13,0.084 432~0.131 41;在第二主成分(secondly principal component,PC2)上的得分分别为-0.290 4~0.168 99,-0.310 65~0.211 6,-0.165 8~0.117 87,-0.200 84~0.160 3;在第三主成分(thirdly principal component,PC3)上的得分分别为-0.190 41~0.322 63,-0.255~0.201 1,-0.359 39~0.227 26,-0.211 3~0.286 93。 结论:所建立的近红外快速无损定性聚类模型达到了对4种不同类别人参定性检测的目的,具有一定的应用价值。
Objective:To establish the near infrared rapid nondestructive qualitative clustering model for rapid and nondestructive identification of Chidi ginseng, wild ginseng, transplantation of wild ginseng and Pahuo ginseng at the molecular level. MethodsNondestructive collection of samples was performed using a Fourier-transform near infrared spectrometer, with wavenumbers in the range of 10 000 cm-1~4 100 cm-1, and then the rapid and nondestructive qualitative clustering model of four samples was established with a chemometrics software. Results:The identification rate of the established qualitative clustering model for the four types of samples was 98%, 98%, 97% and 97% respectively, and the overall identification rate of the verification spectra of the four types of samples was up to 98%. The scores of Chidi ginseng sample, wild ginseng sample, transplantation-of-wild-ginseng sample and Pahuo ginseng sample on the first principal component (PC1) were 0.089 724~0.125 83,0.098 37~0.127 75,0.045 894~0.186 13 and 0.084 432~0.131 41, respectively. On the secondly principal component (PC2), the scores were -0.290 4~0.168 99, -0.310 65~0.211 6, -0.165 8~0.117 87 and -0.200 84~0.160 3, respectively and the scores on the thirdly principal component (PC3) were -0.190 41~0.322 63, -0.255~0.201 1, -0.359 39~0.227 26 and -0.211 3~0.286 93, respectively. Conclusion:The established near-infrared rapid and nondestructive qualitative clustering model is capable for qualitative detection of the 4 different kinds of ginseng and has certain application value.
无损检测傅里叶变换近红外化学计量学不同类别人参
nondestructive detectionFourier-transform near infrared spectroscopychemometricsdifferent kinds of ginseng
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