Hyperspectral spectrograph for geo-authentic crude drug identification and application

Abstract

The invention discloses a hyperspectral spectrograph for geo-authentic crude drug identification and application. The disclosed hyperspectral spectrograph for geo-authentic crude drug identification comprises an imaging module, a dispersion module and a detection module in sequence from bottom to top, wherein the imaging module comprises an imaging lens and a slit, the dispersion module comprises a collimating lens and a light splitting element, and the detection module comprises a tube lens and a detector. According to an imaging scene, the imaging module can replace a front lens to adjust the field of view and the resolution. The imaging scene comprises a photographing scene, a telescopic scene and a microscopic scene. The hyperspectral spectrograph can be used for identifying geo-authentic crude drugs, the hyperspectral spectrograph is used for collecting a large amount of high-resolution spectrum and image information of the medicinal materials, meanwhile, the spectrum and image information serve as training parameters to be input into a machine learning classifier, corresponding spectrograph databases of the different medicinal materials are established according to the different medicinal materials, and the features in the database are used as a reference basis for geo-authentic crude drug production place identification and quality analysis. The hyperspectral spectrograph has the advantages of no damage, rapidness, high efficiency, multiple dimensions and the like.

Description

technical field [0001] The invention relates to the field of hyperspectral spectrum detection and machine learning classification, in particular to a hyperspectral spectrometer for authentic medicinal material identification and its application. Background technique [0002] Authentic medicinal materials often refer to high-quality Chinese medicinal materials produced in a specific natural condition and ecological environment area, which are selected after long-term clinical application of traditional Chinese medicine. Compared with the same kind of Chinese medicinal materials produced in other regions, their quality and curative effect are better. And the quality is stable and has a high reputation. The production of authentic medicinal materials has a unique dependence on specific production areas, and has high requirements for production technology and processing technology; in comparison, non-authentic medicinal materials are not equal in terms of origin, efficacy, produ...

AI Technical Summary

Problems solved by technology

Chromatography is mostly used in contact detection, among which high-performance liquid chromatography is typical, that is, liquid is used as the mobile phase, and a high-pressure infusion system is used to mix mobile phases such as single solvents with different polarities or mixed solvents and buffers in different proportions. Pump into the chromatographic column equipped with stationary phase. After the components in the column are separated, they enter the detector for detection, so as to realize the analysis of the sample; this method can effectively obtain the fingerprint of the sample to be tested, and realize the accurate chemical composition. Quantitative measurement, but the application of contact measurement method is limited due to the cumbersome experimental operation process and the irreversible damage to the sample during the sample preparation process

Spectroscopic analysis is commonly used in non-contact detection, using a commercial spectrometer as a carrier, using Raman spectroscopy or near-infrared spectroscopy that can characterize the molecular fingerprint characteristics of the sample to be tested as a typical example, observing the characteristic peaks of a specific chemical substance, and then determining its component content ; but its single-point measurement is often inefficient, and with the gradual increase in the type and quantity of samples to be tested, the traditional spectral analysis method can no longer meet the needs of complex application scenarios

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