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Objective To analyze Cyperus esculentus by near infrared spectroscopy, and trace geographical origin of Cyperus esculentus by the identification model in chemometrics. Methods A total of 408 samples of Cyperus esculentus samples from Hebei, Hunan, Shandong, Xinjiang, and Yunnan were analyzed for provenance tracing using near-infrared spectroscopy and chemometric software, 3 kinds of spectral preprocessing methods including multiplicative scatter correction, standard normal variate transformation and standard normal variate transformation & detrending, were used respectively, and 5 kinds of recognition modes such as support vector machine (SVM), soft independent modeling of class analogy (SIMCA), orthogonal partial least squares discriminant analysis (OPLS-DA), partial least squares discriminant analysis (PLS-DA), and K-nearest neighbor algorithm (KNN) were used to identify the geographical origin. Results The modeling recognition rates of the 5 kinds of modes including SVM, SIMCA, OPLS-DA, PLS-DA, and KNN were 91.89%, 94.47%, 62.37%, 65.32%, and 100.00% respectively. The KNN was selected as the origin identification model, and the impact of different preprocessing methods, data preprocessing and sample distance on the stability of the model prediction results were analyzed in order to select the optimal model parameters. The prediction set recognition rate could reach 100.00% by using multiplicative scatter correction spectral preprocessing method, one of data preprocessing methods including UV, Pareto, automatic, or centering, and block distance as the sample distance. Conclusion The technology of near infrared spectroscopy combined with KNN mode has the advantages of fast analysis speed, simple operation, easy sample pretreatment, non-destructive, on-line qualitative and quantitative analysis, etc., and has a certain application prospect.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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