Chen Pei, Luthria Devanand, Harrington Peter de B, Harnly James M
U.S. Department of Agriculture, Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, MD 20705, USA.
J AOAC Int. 2011 Sep-Oct;94(5):1411-21. doi: 10.5740/jaoacint.10-291.
Spectral fingerprints of samples of three Panax species (P. quinquefolius L., P. ginseng, and P. notoginseng) were acquired using UV, near-infrared (NIR), and MS. With principal component analysis, all three methods allowed visual discrimination among the three species. All three methods were able to discriminate between white and red ginseng, and showed distinctive subgroupings of red ginseng related to root quality (age/size). Analysis of variance was used to evaluate the relative variance arising from the species, run, and analytical uncertainty, and was used to identify the most information-rich portions of the spectrum for NIR and UV. Accurate classification of the three species was obtained by using partial least squares-discriminant analysis and a fuzzy rule-building expert system. Relatively poor accuracy was obtained using soft independent modeling of class analogy when a single component was used.
使用紫外光、近红外(NIR)和质谱技术获取了三种人参属植物(西洋参、人参和三七)样本的光谱指纹图谱。通过主成分分析,这三种方法都能够实现对这三种植物的视觉区分。这三种方法均能区分白参和红参,并且显示出与根质量(年龄/大小)相关的红参独特亚组。方差分析用于评估由物种、运行和分析不确定性引起的相对方差,并用于识别近红外和紫外光谱中信息最丰富的部分。通过使用偏最小二乘判别分析和模糊规则构建专家系统,实现了对这三种植物的准确分类。当使用单个成分时,采用类类比软独立建模得到的准确率相对较低。