Plant natural active component efficient detection method based on multi-channel anti-interference

Abstract

The invention discloses a multi-channel anti-interference based efficient detection method for natural active components of plants, which comprises the following steps: a multi-channel micro-fluidic chip is adopted to detect the natural active components of the plants, and the multi-channel micro-fluidic chip comprises a plurality of independent channels; a molecularly imprinted polymer with specific molecular recognition capability is preloaded in the independent channel, and natural active ingredients of the plant are captured by the molecularly imprinted polymer under the assistance of a pulsed electric field; the elution buffer solution flushes the independent channels, and the natural active ingredients of the plants enter a detection area; the natural active ingredients of the plants are detected by adopting ultraviolet and fluorescent dual modes; carrying out real-time denoising on a detection result by adopting an AI algorithm; and matching the de-noised detection result with a standard spectrum library, and outputting a component content and purity report. By adopting multi-channel synergistic separation and multi-channel synchronous treatment, the detection efficiency is improved, the single detection time is less than or equal to 30 minutes, the molecularly imprinted polymer filler is combined with the pulsed electric field, and the target component recovery rate is greater than or equal to 90%.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of chemical and biological detection technology, and particularly relates to a high-efficiency detection method for plant natural active ingredients based on multi-channel anti-interference. BACKGROUND

[0002] Plant active ingredient detection is to accurately identify, quantify and analyze chemical substances with specific biological activities (such as antioxidant, anti-inflammatory, antibacterial, anticancer, hypoglycemic, etc.) in plant materials.

[0003] The existing plant active ingredient detection method has the following problems: 1. Single-channel limitation: traditional chromatography or spectroscopy method usually uses a single detection channel, which cannot simultaneously analyze multiple components, and the efficiency is low (single detection time > 2 hours); 2. Serious matrix interference: impurities such as pigments and polysaccharides in plant extracts interfere with the detection of target components, which requires complex pretreatment (such as solid-phase extraction) and low recovery rate (≤70%); 3. Insufficient sensitivity: low content components (such as trace alkaloids) are easily covered by noise, and the detection limit is high (≥0.1 μg / mL); 4. Strong dependence on equipment: high-precision mass spectrometry or nuclear magnetic resonance instruments are expensive and difficult to popularize.

[0004] Based on the above reasons, a high-efficiency detection method for plant natural active ingredients based on multi-channel anti-interference is proposed, which realizes high-efficiency detection of multiple natural active ingredients (such as flavonoids, alkaloids, polyphenols, etc.) in plants, and is suitable for drug research and development, food quality control and plant resource development. SUMMARY

[0005] In view of the deficiencies of the prior art, the purpose of the present application is to provide a high-efficiency detection method for plant natural active ingredients based on multi-channel anti-interference, which realizes high-efficiency detection of multiple natural active ingredients (such as flavonoids, alkaloids, polyphenols, etc.) in plants, and is suitable for drug research and development, food quality control and plant resource development.

[0006] To achieve the above technical purpose, the technical scheme adopted by the present application is as follows: A high-efficiency detection method for plant natural active ingredients based on multi-channel anti-interference, comprising the following contents, (I) A multi-channel microfluidic chip is used to detect plant natural active ingredients in plant extracts, the multi-channel microfluidic chip comprises a plurality of independent channels, a molecularly imprinted polymer (MIP) with specific molecular recognition ability is preloaded in each independent channel, impurities in the plant extract are discharged by the waste liquid channel, and the plant natural active ingredients in the plant extract are captured by the molecularly imprinted polymer under the assistance of a pulse electric field; (II) The independent channels are washed with elution buffer, and the plant natural active ingredients enter the detection zone; (III) using ultraviolet and fluorescence dual mode to detect the plant natural active ingredients; (IV) using AI algorithm to denoise the detection results in real time; (V) matching the denoised detection results with the standard spectral library, and outputting the component content and purity report.

[0007] The plant natural active ingredients in the plant extract are detected by using the multi-channel microfluidic chip with independent channels. The independent channels of the multi-channel microfluidic chip are preloaded with molecularly imprinted polymers. According to different objects to be captured, the molecularly imprinted polymers preloaded in each independent channel are also different. The molecularly imprinted polymers are used for adsorbing corresponding components, such as flavonoids (such as rutin), alkaloids (such as caffeine), polyphenols (such as gallic acid), and terpenes (such as menthol). The synchronous separation of multiple types of components is realized to improve the detection efficiency. During adsorption, the multi-channel microfluidic chip applies a pulsed electric field to strengthen mass transfer and improve specificity, thereby assisting the combination of the plant natural active ingredients in the plant extract with the molecularly imprinted polymers, and finally improving the recovery rate of the target components. Under the combined action of the pulsed electric field and the molecularly imprinted polymers, the target components are captured, and the unnecessary impurities are discharged through the waste liquid channel. After the impurities are separated, the independent channels are washed by elution buffer to separate the plant natural active ingredients from the molecularly imprinted polymers and enter the detection area. The plant natural active ingredients are detected under ultraviolet and fluorescence dual mode. The dual mode is used to improve the range of detectable objects, improve the reliability of detection results, and avoid interference. Sometimes, some types of plant natural active ingredients cannot be detected by fluorescence detection, and some types of plant natural active ingredients cannot be detected by ultraviolet detection. The combination of the two methods can improve the range of detectable objects. For some objects that can be detected by fluorescence and ultraviolet, the combination of the two methods can improve the reliability of the detection results, reduce the interference of external factors on the results, and finally, the two detection methods can be used as backups for each other. When one detection method fails due to failure, the other method can still work, avoiding the impact on daily detection. After the preliminary detection is completed, the detection results are filtered by AI algorithm to remove distorted noise points and improve the signal-to-noise ratio. Finally, the detection results are matched with the standard spectral library, and the component content and purity report is output.

[0008] As a preferred technical solution of the present application, the plant extract is filtered before step (I) to obtain a filtrate.

[0009] In the present application, filtration can remove larger impurities, reduce impurity interference, reduce the difficulty of capturing target components, and improve the accuracy of detection results.

[0010] In some optional examples, the plant extract is filtered through a microfiltration membrane with a pore size of 0.22 microns.

[0011] As a preferred technical solution of the present application, the inner wall of the independent channel is coated with an anti-absorption coating to reduce impurity retention.

[0012] In the present application, the anti-absorption coating improves the passage of impurities and avoids the absorption and retention of impurities.

[0013] In some optional examples, the anti-absorption coating uses polyethylene glycol.

[0014] As a preferred technical solution of the present application, the parameters of the pulsed electric field are a voltage of 5V and a frequency of 10Hz.

[0015] As a preferred technical solution of the present application, the wavelength range used for ultraviolet and fluorescent dual-mode detection is 200-600nm.

[0016] As a preferred technical solution of the present application, a convolutional neural network algorithm is used as the AI algorithm for cleaning and filtering the detection results.

[0017] In the present application, the convolutional neural network algorithm not only effectively extracts features, but also has considerable superiority in computing efficiency and generalization ability.

[0018] Advantages of the present application 1. Multi-channel cooperative separation, multiple channels are processed synchronously, detection efficiency is improved, and single detection time is ≤30 minutes, 2. Specific anti-interference, molecularly imprinted polymer filler is combined with pulsed electric field, target component recovery rate is ≥90%, and impurity removal rate is >95%; 3. Intelligent denoising, AI algorithm dynamically eliminates baseline drift and noise, and detection limit is as low as 0.01 micrograms / mL; 4. Miniaturized design, system volume is only 1 / 5 of traditional high-performance liquid chromatograph, and cost is reduced by 60%. BRIEF DESCRIPTION OF DRAWINGS

[0019] The present application can be further illustrated by the non-limiting examples shown in the accompanying drawings; Figure 1 Flowchart of the embodiments of the present application DETAILED DESCRIPTION

[0020] The technical solutions of the present invention will be described in detail below with reference to specific embodiments and accompanying drawings. The embodiments described herein are specific implementations of the present invention, used to illustrate the concept of the present invention; these descriptions are explanatory and exemplary, and should not be construed as limiting the implementation methods or the scope of protection of the present invention. In addition to the embodiments described herein, those skilled in the art can employ other obvious technical solutions based on the content disclosed in the claims and specification of this application. These technical solutions include those that make any obvious substitutions and modifications to the embodiments described herein. Example

[0021] Sample preparation: Take 1g of tea powder and extract it with 70% ethanol by ultrasonic extraction, then centrifuge and collect the supernatant.

[0022] like Figure 1 As shown, this embodiment provides a high-efficiency detection method for plant natural active ingredients based on multi-channel anti-interference, including the following: (I) The supernatant was filtered through a microfiltration membrane to obtain the filtrate, the pore size of which was 0.22 μm; (II) A 4-channel microfluidic chip was used to detect the natural active ingredients of plants in the filtrate. The 4-channel microfluidic chip contains 4 independent channels. The interior of each of the 4 independent channels is coated with an anti-adsorption coating made of polyethylene glycol. Each independent channel is preloaded with a molecularly imprinted polymer with specific molecular recognition capabilities. The molecularly imprinted polymers in the independent channels are different. Impurities in the filtrate are discharged through the waste liquid channel. The natural active ingredients of plants in the filtrate are captured by the molecularly imprinted polymer under the assistance of a pulsed electric field. The parameters of the pulsed electric field are voltage 5V and frequency 10Hz. (III) Using acetic acid at pH 3.0 as the elution buffer, the independent channels are rinsed with the elution buffer, allowing the natural active ingredients of the plant to enter the detection area; (IV) The natural active ingredients of plants are detected using a dual-mode method of ultraviolet and fluorescence. The principle of ultraviolet detection is based on measuring the absorption of ultraviolet light by molecules, while the principle of fluorescence is based on measuring the long-wavelength light emitted by molecules after they are excited. (V) A convolutional neural network algorithm is used to denoise the detection results in real time; (VI) The denoised detection results are matched with the standard spectral library, and a report on the content and purity of the components is output.

[0023] In the embodiment, the results of ultraviolet detection are denoised by convolutional neural network algorithm, and it is found that there is absorption at 280 nm wavelength, which matches the standard spectrum library, and the component is polyphenol. The results of fluorescence are denoised by convolutional neural network algorithm, and it is found that there is reaction at Ex 360 nm / Em 460 nm, which matches the standard spectrum library, and the component is flavone. In the embodiment, multi-channel collaborative separation is realized by 4-channel synchronous processing, the detection efficiency is improved by 4 times, and the single detection time is less than or equal to 30 minutes; specific anti-interference: the molecularly imprinted polymer filler is combined with the pulsed electric field, the recovery rate of the target component is greater than or equal to 90%, and the removal rate of impurities is greater than 95%; intelligent denoising: the convolutional neural network algorithm dynamically eliminates the baseline drift and noise, and the detection limit is as low as 0.01 μg / mL; miniaturization design: the system volume is only 1 / 5 of the traditional detection method such as high performance liquid chromatograph (HPLC), the cost is reduced by 60%, and the later maintenance cost is reduced by 50%.

[0024] The above embodiments only exemplarily illustrate the principles and effects of the present application, and are not used to limit the present application. Any person skilled in the art can modify or change the above embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical thought disclosed by the present application should be covered by the claims of the present application.

Claims

1. A method for efficient detection of plant natural active ingredients based on multi-channel anti-interference, characterized in that: The application relates to a method for detecting plant natural active ingredients in plant extract liquid. The plant natural active ingredients in the plant extract liquid are captured by the molecularly imprinted polymers under the assistance of a pulse electric field. The elution buffer is used to flush the independent channels, and the plant natural active ingredients enter a detection area. The plant natural active ingredients are detected by using ultraviolet and fluorescence double modes. The detection results are denoised in real time by using an AI algorithm. The denoised detection results are matched with a standard spectrum library, and a component content and purity report is output.

2. The method according to claim 1, wherein the method is based on multi-channel anti-interference. Before the step (I) is implemented, the plant extract liquid is filtered to obtain a filtrate.

3. The method according to claim 2, wherein the method is based on multi-channel anti-interference. The plant extract liquid is filtered through a microfiltration membrane.

4. The method according to claim 1, wherein the method is characterized by: In the step (I), the molecularly imprinted polymers preloaded in each independent channel are different.

5. The method according to claim 4, wherein the method is based on multi-channel anti-interference. In the step (I), the inner walls of the independent channels are coated with an anti-adsorption coating layer for reducing impurity retention.

6. The method according to claim 1, wherein the method is based on multi-channel anti-interference. In the step (I), the parameters of the pulse electric field are 5V of voltage and 10Hz of frequency.

7. The method according to claim 1, wherein the method is based on multi-channel anti-interference. The wavelength range used in the ultraviolet and fluorescence double mode detection is 200-600nm.

8. The method according to claim 1, wherein the method is based on multi-channel anti-interference. In the step (IV), the AI algorithm used is a convolutional neural network algorithm.

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