Traditional medicine has a complete theoretical system, embodies the broad wisdom of the Chinese people and the Chinese nation, and has made great contributions to the healthy reproduction and prosperity of the Chinese nation over thousands of years. In recent years, traditional Chinese medicine has attracted widespread attention from all over the world due to its rich research results in active ingredients and outstanding performance in the treatment and control of sudden infectious diseases [1-3]. At the same time, this also puts higher requirements on the quality of Chinese medicinal materials and Chinese medicine preparations. Precious Chinese medicinal materials are a typical and representative category of medicinal materials, and their quality evaluation and clinical application are particularly valued.
precious Chinese medicinal materials have accurate efficacy, are widely used, and are highly recognized by the public. However, due to harsh growth conditions, special medicines, and exquisite preparation, the yield is low and the price is expensive. At present, the quality of precious Chinese medicinal materials in my country's traditional Chinese medicine market is uneven, and there are phenomena such as fake products pretending to be genuine products or being faked, illegal dyeing, excessive sulfur fumigation, and re-circulation of extracted medicine residues [4]. From the results of the national market quality sampling from 2013 to 2018, it can be seen that although the overall pass rate of Chinese medicinal materials and decoctions has increased year by year, its overall pass rate in 2018 was only 88% [5].
precious Chinese medicinal materials and decoctions are inevitably the main targets of illegal merchants' counterfeiting and counterfeiting. For example, the common precious Chinese medicinal materials such as ginseng [6] and deer antler [7] have different degrees of counterfeit and inferior phenomena, which has caused serious concerns among the people about the quality of Chinese medicinal materials. Therefore, accelerating the modern quality testing of precious Chinese medicinal materials is the key to improving the overall quality level of Chinese medicinal materials and decoctions in my country.
Traditional Chinese medicine quality evaluation is mainly based on basic identification methods (base, traits, microscopy, physics and chemistry). With the development of quality research on traditional Chinese medicine, high performance liquid chromatography (HPLC), gas chromatography (GC), mass spectrometry (MS) and its combined technologies are widely used. However, most of these detection methods require expensive instruments and equipment or complex pre-processing processes, which also have high requirements for the professionalism of the operator, making it difficult to achieve large-scale inspection and universal application. It is urgent to find an analysis and testing method with low analysis cost, low operation difficulty and strong popularization.
Near-infrared (NIR) spectroscopy technology is characterized by simple operation, short analysis time and low cost. It has developed rapidly in recent years and has been widely used in the agriculture [8], food [9], petrochemical [10] and pharmaceutical [11] industries, and has achieved large-scale application results. NIR spectroscopy technology is widely used in the field traceability of food and agricultural products, nutritional content determination, grade classification and online detection [12]. Chinese medicinal materials are mostly derived from natural animals and plants, and NIR spectroscopy technology has great potential in the application of quality detection and quality control of traditional Chinese medicine. In the field of traditional Chinese medicine, NIR spectroscopy technology has been widely studied and applied in the authenticity identification, type identification, origin identification, quality evaluation of traditional Chinese medicine, especially precious Chinese herbal medicines [13]. This paper reviews the quality evaluation research of near-infrared spectroscopy technology in precious Chinese medicinal materials in recent years and looks forward to its future development direction (Figure 1).
1 NIR spectroscopy technology and features
1.1 Introduction to NIR spectroscopy
NIR is an electromagnetic wave between visible light and mid-infrared spectrum. American Materials and Testing Association (ASTM) stipulates that its wavelength range is 780-2526 nm (12 820-3959 cm−1) [14]. The NIR spectrum is mainly due to the non- resonance properties of the vibration of molecules, which can transition from the ground state to the high energy level. In NIR spectrum, it mainly comes from the absorption of frequency doubling and frequency combination of hydrogen-containing groups such as C-H, O-H, and N-H. Since the NIR spectrum generated by different groups differs in absorption wavelength and intensity, changes in sample composition will also lead to changes in spectrum characteristics, which lays the foundation for qualitative and quantitative analysis of near-infrared spectroscopy [15].
1.2 Principles of NIR spectral analysis technology
NIR spectral analysis technology consists of spectrometer , stoichiometric software and calibration model. Spectrometers are used to collect sample spectra, stoichiometric software is used to construct correction models, and corrected model constructed based on spectral and calibration data of modeled samples is used for qualitative or quantitative detection of samples to be tested.
NIR spectral instruments can be divided into fixed wavelength filters, grating dispersion, acousto-optical adjustable filters and Fourier transforms from spectroscopic systems. NIR spectrometers have a variety of detection terminals, such as flow cells, transmission probes and integral spheres. The detection methods such as transmission (transmissive, diffuse transmission), reflection (diffuse reflection) and other detection methods can realize the determination of liquids and solid particles, powders, etc. [16-19].
correction model occupies a key position in the research of NIR spectroscopy technology. An ideal correction model has good robustness and excellent prediction capabilities, which can achieve good application within the predetermined parameter range. Building an ideal correction model often requires relatively strict preconditions, mainly including: (1) Accurate acquisition of the target values of the near-infrared spectra of the sample to be tested and its corresponding target physical and chemical properties; (2) Suitable spectral preprocessing methods and wavelength (band) selection methods; (3) Preferred fitting algorithms, such as using one or more algorithms of partial least squares (PLS), artificial neural network, support vector machine and other algorithms to achieve the construction of the optimal correction model. The process of correcting the construction and optimization of the model also requires comprehensive evaluation to screen. Commonly used evaluation parameters are mainly determination coefficient (R2), cross-validation root mean square error (RMSECV), prediction root mean square error (RMSEP), relative analysis error (RPD), etc.
stoichiometric software is a medium for model construction and application, and can quickly complete the construction and evaluation of correction models. Generally speaking, stoichiometric software can be divided into three categories. One is professional stoichiometric software provided by NIR spectrometer suppliers; one is professional processing software that focuses on modeling, such as Unscrambler, Matlab, etc.; and the other is special software developed by users themselves.
1.3 Technical characteristics of NIR spectrum
NIR spectrum analysis technology has the advantages of "more, fast, better and less" compared to traditional analysis methods, which is mainly reflected in: (1) Many analysis objects: different measurement methods are used to collect the spectrum, and can measure uniform and thorough liquids [16], solid particles and powders [17], viscous liquids such as petroleum [18], milk [19], etc. (2) Fast analysis speed and high efficiency: The measurement speed can reach seconds or milliseconds. (3) Environmentally friendly: Direct detection of samples can be achieved, and the sample is generally not required to be pretreated, which avoids the use of chemical reagent and does not cause pollution to the environment. (4) Low detection cost: NIR spectroscopy technology is a non-destructive detection technology, which avoids the use of reagents and the waste of samples. ; At the same time, NIR spectroscopy technology is simple to operate and has low demand for professionals. The spectral signal can be conducted through quartz or glass fiber, real-time online quality analysis, greatly reducing labor costs.
As an emerging analysis technology, NIR spectroscopy technology has developed rapidly in recent years, but it also has some weaknesses: (1) As an indirect detection technology, NIR spectroscopy technology needs to obtain original data based on standard methods to establish a model. The accuracy of the original data and the rationality of the model establishment directly affect its prediction results. (2) The NIR spectrum overlaps severely. The detection limit of is generally considered to be 0.1% to 0.01%. At present, there is still a certain difficulty in analyzing trace components. (3) The application of NIR spectroscopy is more suitable for the analysis of samples with large numbers of samples and daily needs, and is not suitable for the analysis of samples with small numbers of samples or dispersible ones. (4) The construction and application of correction models requires relatively more manpower and material resources, and this process requires in-depth intervention from professionals.
2 Identification of authenticity of Chinese medicinal materials based on NIR spectroscopy technology
traits and microscopic identification based on morphology characteristics are simple and fast means to identify Chinese medicinal materials, but the appraiser must have high professional ability and rich practical experience. Thin-layer chromatography (TLC) can identify traditional Chinese medicines in a short time, but their specificity is poor, making it difficult to distinguish Chinese herbal materials with similar seed sources [20]. Therefore, it is of great significance to choose fast and effective near-infrared spectroscopy technology to identify the authenticity of precious Chinese medicinal materials.
2.1 Authentic and fake products identification
Fritillaria was first published in " Shennong Bencao Jing ", and subsequent herbal works have been recorded in previous dynasties. The 2020 edition of the Chinese Pharmacopoeia contains kenalli , gema , gema , flat fritilli gema , and Hubei Fritilli , a total of 5 lemonaceae plant fritilli vegetative varieties. Among them, Fritillaria kebayashi is the most commonly used, and has a high medicinal value. The market price is very different from other varieties of Fritillaria. It is very common in the market to mix Fritillaria skeletalis, Fritillaria skeletalis, Fritillaria skeletalis, etc. The 2020 edition of the Chinese Pharmacopoeia uses fritillarin B as a TLC identification reference for fritillaria kebayashi and fritillaria kebayashi [21]. The identification method lacks specificity and it is difficult to effectively identify fritillaria kebayashi and other fritillaria.
Zhou Ting et al. [22] used K value clustering method and combined with PLS method to cluster the NIR spectrum of Fritillaria kebayashi and Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi, and Fritillaria kebayashi, respectively, and the value range of Fritillaria kebayashi is 5.06~5.96. While achieving effective distinction between Fritillaria kebayashi and other fritillaria, this study also achieved a preliminary distinction between 6 varieties of , Sichuan fritillaria , including 6 varieties, including Dark Purple Fritillaria, Wab Fritillaria, Fritillaria kebayashi, Fritillaria kebayashi, Fritillaria kebayashi and Fritillaria kebayashi.
Huang Bisheng et al. [23] used cluster analysis method to establish a NIR spectral qualitative model of dragon teeth medicinal materials, which can quickly identify the authenticity of dragon teeth medicinal materials with an identification rate of 82%. Qu Haibin et al. [24] collected the NIR spectrum of donkey-hide gelatin powder, performed multiple scattering correction and wavelet transform spectral pretreatment, and used similarity matching and Mahayana distance methods to establish discriminant models. The results show that the established NIR models can accurately identify genuine and fake donkey-hide gelatin. Wang Gangli et al. [25] collected 300 NIR diffuse reflection spectra of Chinese red ginseng and a variety of pseudo-maru red ginseng, and used discriminatory analysis (DA) method to establish their qualitative identification model. The results showed that the prediction results of the model verification were exactly the same as the actual situation, proving that the NIR spectrum can accurately identify red participating in its pseudo-maru.
2.2 Identification of authentic and counterfeit products
NIR spectroscopy technology can not only identify the authenticity of precious Chinese medicinal materials, but also identify the medicinal materials of doped part of the counterfeit products and detect the doping amount of their counterfeits.
Panax notoginseng is the dry root and rhizome of F. H. Chen [21], which has the effects of dispersing blood stasis and stopping bleeding, reducing swelling and relieving pain, and is widely used in traditional Chinese medicine orthopedics, surgery, gynecology, etc. Panax notoginseng powder and Sophora ginseng powder or corn flour have similar taste and appearance, and are low in adulteration cost, so it is easy to incorporate Sophora ginseng powder or corn flour. Nie et al. [26] used three wavelength ranges of visible light, short-wave near-infrared spectroscopy and long-wave near-infrared spectroscopy respectively. They established the quantitative model of Panax notoginscopy in adulterated Panax notoginscopy based on two correction methods: partial least squares regression (PLSR) and least squares support vector machine (LSSVM). They gave priority to the PLSR model based on long-wave near-infrared spectroscopy as the best model for quantitative determination of Panax notoginscopy, realizing rapid quantitative analysis of PLSR powder.
Hao et al. [27] established a NIR discriminant model based on partial least squares discriminant analysis (PLS-DA), and distinguished pure Huoshan Dendrobium and doped with Henan Dendrobium . At the same time, the PLSR model was used to realize quantitative detection of Henan Dendrobium doping in Huoshan Dendrobium samples. The value of R2 of the PLS-DA model is 0.489 8, the mean square variance of the prediction set is 0.155 4, and the accuracy of the verification set reaches 100%; the R2 of the PLSR model is 0.994 6, and the mean square variance of the prediction set is 2.38. Hu Gangliang et al. [28] established a NIR detection method for the human amount of Fritillaria in Fritillaria in Fritillaria in Fritillaria in Fritillaria. The correlation coefficient of the predicted value and the true value is 0.999 7, the sample recovery rate is 97.96% to 100.90%, and the RSD is 0.81%, realizing rapid detection of the incorporation amount of Zhebei in Fritillaria in Fritillaria.
3 Types of Chinese medicinal materials based on NIR spectroscopy technology
Nutritious Chinese medicinal materials often have multiple sources of one medicine, and most of them are from plants of similar shapes within the same family. It is difficult for traditional methods to achieve rapid identification. Some precious Chinese medicinal materials are also affected by the place of origin or planting and cultivation methods, resulting in large differences in efficacy. NIR spectroscopy technology has been widely studied in the identification of authenticity, origin identification and content determination of precious Chinese medicinal materials, but there are relatively few researches on the classification and identification of medicinal materials of the same genus and between different cultivation and cultivation methods.
3.1 Identification of the types of Chinese medicines of the same genus
Rhodiola is derived from the dried roots and rhizomes of the plant of Sedumaceae family large flower Rhodiola Rhodiola crenulate (Hook. f. et Thoms.) H. Ohba's dry roots and rhizomes [21]. However, there are many species of Rhodiola, and there are 73 Rhodiola plants in my country; Li et al. [29] combined with stoichiometric analysis to achieve rapid and non-destructive discrimination analysis of four different varieties of Rhodiola, Rhodiola perimeter, Rhodiola narrow-leaf and Rhodiola short-handled.
Ganoderma lucidum is widely used, but there are many varieties, and the efficacy differences between different types of Ganoderma lucidum. Yang Ji et al. [30] collected NIR spectra of 540 samples of 9 Ganoderma lucidum, established a qualitative model of principal component analysis (PCA) based on multivariate scattering correction spectral pretreatment, and achieved a correct recognition rate of 100% for the classification and attribute of different varieties of Ganoderma lucidum, achieving rapid and non-destructive detection of Ganoderma lucidum species.
3.2 Different cultivation (planting) methods of the same Chinese medicine are identified by different methods of
bovine is a dry gallstone of the bovine animal Bos Taurus domesticusGmelin, which has the effects of clearing the heart, snuffing phlegm, opening orifices, cooling the liver, suffocating wind, and detoxifying. Beef huang is cultivated in vitro using the fresh bile of the beef as mother liquor, and add deoxycholic acid, cholic acid , compound bilirubin calcium, etc.; artificial beef huang is artificially prepared by referring to the known ingredients of natural beef huang. Although the three different cultivation methods are included in the pharmacopoeia , the price difference is very large. Nie Lixing et al. [31] used NIR spectroscopy and used , a Mahstanese distance discrimination method , and used , to distinguish and analyze in vitro beef, artificial beef and natural beef in vitro. The results show that the spatial distribution of the main components of the three beefs is obvious, and different beefs are accurately classified. The error judgment numbers of the correction set and verification set are both 0, and the model accuracy is 100%.
ginseng is a dry root and rhizome of the vegetative family ginseng Panax ginseng C. A. Mey. It has the effects of greatly replenishing vital energy, replenishing the pulse and strengthening the detachment, nourishing the spleen and lungs, producing fluid and nourishing blood, etc. Due to scarce resources, pure wild ginseng has been listed as a first-class protected plant in my country. The Chinese Pharmacopoeia no longer contains wild ginseng since the 2005 edition. The wild ginseng sold on the market mostly refer to under the forest ginseng after artificially sown in the mountains and forests and naturally grows naturally in the wild state for a certain period of time. Xing Lin et al. [32] used the FT-NIR instrument to collect NIR spectra of ginseng samples of 10,000 to 4,100 cm−1 in different cultivation methods, and combined with stoichiometric software to establish a qualitative clustering model of four types of ginseng, including pond bottom, wild ginseng transplantation, wild ginseng and garlic. The qualitative clustering model established for the four samples was 98%, 97%, 98%, and 97%, respectively, and the recognition rate of the verification collection of the four ginseng modeling samples reached 98%.
NIR spectroscopy technology has achieved rapid classification of medicinal materials through the establishment of models, which is conducive to the improvement of the phenomenon of fish-like mixed beads such as planted products in the market as wild products, artificial synthetic products as natural products, and promoting the precise use of traditional Chinese medicine in the clinical practice.
3.3 Identification of the origin of traditional Chinese medicinal materials
Different sources of traditional Chinese medicine will also have different quality. Authentic medicinal materials often have better quality and efficacy due to their excellent variety, suitable environment and excellent processing [33]. Identification of the origin of traditional Chinese medicinal materials is conducive to ensuring the efficacy and safety of traditional Chinese medicine.Chen et al. [34] collected near-infrared spectra of Ganoderma lucidum samples from 6 different origins from 3 different provinces and used PLS-DA, PCA and DA for modeling and classification. The results show that for the identification of samples from 3 different provinces, the PLS-DA model achieves 100% correct classification, and for samples from 6 different origins, the DA model achieves 96.6% correct classification. In addition, NIR spectroscopy technology is used in the identification of origin of different types of precious Chinese medicinal materials such as animals, plants, and fungi, see Table 1.
4 Determination of the content of traditional Chinese medicinal materials based on near-infrared spectroscopy
The composition of traditional Chinese medicinal materials is complex, and the efficacy and effects are affected by many aspects. The accurate determination of indicator components, active ingredients and risk substances of traditional Chinese medicinal materials is a necessary means to scientifically interpret and ensure their effectiveness and safety. The content measurement of the major components of Chinese medicinal materials is still mainly based on ultraviolet spectrophotometry, while the content measurement of monomer components is mostly used for HPLC, GC, MS and its combined technology. However, these methods are mostly complicated to process, have a long analysis time and are cumbersome to operate, so the accuracy of the analysis results is easily affected by the operation during the analysis process. The NIR map is simple to obtain. Scan a spectrum and can obtain a variety of information about the sample, which can quickly and without loss to determine the content of the intrinsic ingredients of precious Chinese medicinal materials.
4.1 Determination of content of effective parts (major components)
NIR spectroscopy technology is used to determine content of effective parts (major components) in precious Chinese medicinal materials. Lu Yongjun et al. [43] used NIR for rapid quantitative detection of total ginseng sugar, which proved the feasibility and superiority of NIR spectroscopy technology in the quantitative determination of total ginseng sugar content. [27] used attenuated total reflectance near infrared spectroscopy (ATR-NIR) technology combined with standard normal transformation combined with first-order derivative spectroscopy and PLS method to achieve rapid determination of the content of total polysaccharides and main monosaccharides mannose and glucose huoshanense C. Z. Tang et S. J. Cheng. Chen et al. [44] used the NIR spectral combination interval partial least squares-genetic algorithm (interval partial least squares-genetic algorithm, IPLS-GA) to determine the content of total flavonoid in snow lotus . The model prediction set RMSEC was 0.834 7%, the correction model correlation coefficient (RC) = 0.944 4, the verification set RMSEP was 1.076 6%, and the correlation coefficient RP = 0.900 6.
4.2 Determination of the content of active ingredients or index components
Yang Nanlin et al. [45] established a mannitol content determination model in Cordyceps sinensis based on NIR spectroscopy combined with artificial neural network. The RMSECV is 0.475, the RMSEP is 0.608, and the correlation coefficient is 0.917 7, achieving rapid detection of the content of mannitol in Cordyceps sinensis. Since NIR contains a large amount of chemical and physical information of the sample, through the establishment of mathematical models, NIR spectroscopy can realize the simultaneous detection of multi-components of traditional Chinese medicinal materials. Liu Jie et al. [46] used PLS combined with second-order derivative pretreatment to establish a NIR content determination model for drosogen A and drosogen B in domestic blood dysfunction . Hu Xin et al. [47] used PLS method to establish a total saffron and saffron-II content determination model in saffron ; RC and RMSEP reached 0.9560 and 4.343% of total saffron and 0.952 8 and 4.077% of total saffron and 0.952 8 and 4.077% respectively.
4.3 Moisture Determination
Medicinal materials have a significant impact on their quality stability. Mou Qianqian [48] used NIR diffuse reflection spectrum analysis technology combined with PLS to predict the content of moisture and rhodiola in Rhodiola medicinal materials. The experimental method was fast, accurate and pollution-free. Lei Jingwei et al. [49] used the moisture content of , woody medicinal materials as determined by toluene method, and combined with PLS to establish a quantitative NIR model of the moisture content of woody mei, and there was no statistical difference between the predicted value of the verification set and the reference value of the toluene method, indicating that the NIR spectrum can be applied to the rapid detection of moisture of medicinal materials.
Although NIR spectroscopy technology has many applications in the moisture determination of precious Chinese medicinal materials, it is still stuck in the construction and research of exclusive model construction of specific medicinal materials. means that different NIR moisture determination models need to be constructed for different medicinal materials, which consumes a lot of manpower and material resources.Establishing a general moisture detection model for a variety of medicinal materials may be a future development trend.
4.4 Risk substance detection
Due to the natural properties of traditional Chinese medicine, Chinese medicinal materials may have heavy metals, pesticide residues, and mycotoxin and other harmful substances. Liu Yande et al. [50] established a heavy metal copper near-infrared quantitative model of lilac leaves based on NIR spectroscopy technology combined with PLS-DA. After smoothing, the model RC is 0.950, the RMSEC is 5.99, the external verification correlation coefficient RP is 0.923, and the RMSEP is 7.38. It proves that near-infrared spectroscopy technology is feasible for rapid detection of heavy metal content in traditional Chinese medicine. Similarly, based on the current application research reports of near-infrared in food and agricultural products, it is found that near-infrared also has great potential in the detection of pesticide residues and mycotoxins of traditional Chinese medicinal materials [51-52]. However, at present, there are relatively few reports on risk substance detection of near-infrared spectroscopy in traditional Chinese medicinal materials, and further research is needed.
5 Comprehensive evaluation of traditional Chinese medicinal materials based on near-infrared spectroscopy technology
Currently, the rapid evaluation and grade classification of precious traditional Chinese medicinal materials on the market are mainly judged by "distinguishing the quality", that is, by the "characteristics" of the external "characteristics" of the medicinal materials such as shape, color, gas, and taste [53]. However, as an empirical identification method, "distinguishing the quality" has inevitable disadvantages, such as the discriminator needs to have rich practical experience; is influenced by the subjective consciousness of the discriminator; and can only achieve the initial judgment and classification. However, chemical composition content determination and fingerprint analysis based on HPLC, GC and MS, it is difficult to achieve large-scale inspection due to the expensive instrument, complex pre-processing, and long detection time, and it is still impossible to replace the traditional identification method. Based on the concept of Chinese medicine quality marker (Q-Marker), NIR spectroscopy technology is used to correlate the spectrum with the content information of the drug effect ingredient, which can achieve a simple and reliable rapid evaluation of the quality of Chinese medicine [54].
5.1 Quality grading evaluation based on NIR spectroscopy technology
agarwood has the effects of calming, analgesic, and hypnosis. It is deeply favored by the public and has a large market demand. However, wild white wood fragrance is on the verge of extinction, and a large number of adulterated and inferior agarwoods have appeared in the market. Ding et al. [55] used the method of combining UPLC-Q/TOF MS with PCA to identify the quality markers of agarwood, and determined four highly oxidized 5,6,7,8-tetrahydro-2-(2-phenethyl)chromone as potential markers for identifying the authenticity of agarwood, and used the coordinated partial least squares method to establish their NIR quantitative model with the Monte Carlo algorithm. The quantitative results were analyzed in depth by using system clustering analysis and PLS-DA. The 50 agarwood samples were divided into four categories: high-quality, qualified, unqualified and fake.
5.2 The new method for NIR spectroscopy technology evaluation based on Q-Marker
Liu Changxiao Chinese medicine Q-Marker theory proposed by Academician [56-57] provides new ideas for the quality research of traditional Chinese medicine. Q-Marker refers to chemical components that are related to the effectiveness and safety of traditional Chinese medicine and can be detected. It is the key to establishing a quality control system of with therapeutic efficacy as the core. Baigang and others proposed a near-infrared intelligent evaluation system for the quality of traditional Chinese medicinal materials based on the traditional Chinese medicine Q-Marker [58], and established an intelligent evaluation system for the anti-inflammatory effects of Angelica sinensis [59], vasodilation effects [60], and honeysuckle anti-inflammatory [57] respectively. Since the current correlation between the quality evaluation methods of traditional Chinese medicinal materials and the efficacy of medicinal materials is unclear, and the technical standards for judging the efficacy of medicinal materials through Q-Marker have not yet been established, Baigang et al. [61] further proposed a new concept of comprehensive quality evaluation index. Taking Angelica medicinal materials as an example, through the integrated analysis of multiple testing indicators, a new method for comprehensive evaluation and grade identification of medicinal materials has been established.
6 Outlook
NIR spectroscopy technology has been widely studied in the evaluation of precious Chinese medicinal materials, but judging from its development trend, it is still in its infancy. Therefore, more research is needed in the future, especially in terms of model robustness, portability of spectrometers, networking of detection technology, construction and evaluation of general models. With the deepening of research, the application of NIR spectroscopy technology in the field of traditional Chinese medicine will gradually shift from simple qualitative and quantitative research to the evaluation of traditional Chinese medicine efficacy based on a variety of drug-active ingredients and a comprehensive evaluation of traditional Chinese medicine quality combined with a variety of traditional analytical methods.In view of this, the near-infrared rapid evaluation of traditional Chinese medicine quality based on quality markers is expected to become the main trend in the future rapid inspection of traditional Chinese medicine quality.
In addition, as the market circulation of precious Chinese medicinal materials gradually expands, traditional analysis methods have no longer met the needs of rapid development. Therefore, establishing a rapid quality identification system for precious Chinese medicinal materials will be an important trend in future development. The system can be composed of three parts: simple and portable near-infrared spectrometer , intelligent equipment with spectral transmission and data reception functions, and precious Chinese medicinal materials quality evaluation cloud service platform. Customers use simple and portable NIR spectrometer to collect spectra on samples, upload the map to the cloud platform through intelligent devices and corresponding software. The cloud platform quickly selects corresponding models based on customer needs to quickly evaluate the sample quality and feedback the results to the customer.
The construction and use of the rapid identification system for quality identification of precious Chinese medicinal materials can effectively combat the "counterfeiting and shoddy" phenomenon in the Chinese medicinal materials market and promote the production and circulation of high-quality medicinal materials. However, the system has a long way to go, and the following problems must be gradually overcome: ① The stability, reproducibility, portability and simplification of the operation of the NIR spectrometer. ②The robustness, versatility and accuracy of the NIR model. ③The robustness of cloud systems, rapid computing and accurate computing.
Conflict of interest All authors declare that there is no conflict of interest
References (omitted)
Source: Huang Zhiwei, Guo Tuo, Huang Wenjing, Li Bing, Xu Haoran, Ye Chuxuan, Yan Shikai, Xiao Xue, Luo Guoan. Research progress of near-infrared spectroscopy technology in the evaluation of quality of precious Chinese medicinal materials [J]. Chinese Herbal Medicine, 2022, 53(20): 6328-6336.
