Real-time in-situ detection method and system for insect resistance level of plant

Abstract

The invention belongs to the field of plant insect-resistant characteristic analysis, and particularly discloses a real-time in-situ detection method and system for the insect-resistant level of a plant, and the method specifically comprises the following steps: after a to-be-detected plant is irradiated by ultraviolet light of different doses, a hyperspectral stimulated Raman scattering imaging subsystem is adopted to carry out stomata imaging and spectral signal acquisition on leaves of the to-be-detected plant; performing qualitative analysis on different metabolites in the leaves by adopting spectral signals of different wavebands, and performing quantitative detection on the metabolites in combination with characteristic peak areas and peak intensity characteristics; acquiring pore structure change based on pore imaging; and calculating the correlation between the pore structure and metabolite change of the plant caused by different irradiation and the insect resistance, thereby realizing in-situ detection of the insect resistance of the plant. According to the method provided by the invention, the complex process of plant disease and insect pest resistance can be comprehensively analyzed, and the non-invasiveness, high specificity and qualitative and quantitative capability can provide important theoretical basis and practical guidance for developing a green disease and insect pest control technology.

Description

Technical Field

[0001] The present application relates to the field of plant insect resistance characteristic analysis, and more specifically, to a real-time on-site detection method and system for plant insect resistance level. Background Art

[0002] Plants are continuously exposed to various environmental stresses throughout their growth process, including biotic stresses (such as pathogens and pests) and abiotic stresses (such as drought, salinity, high temperature, low temperature, and ultraviolet radiation). To adapt to these stresses, plants have evolved complex defense mechanisms involving changes at multiple levels, including physiological, biochemical, molecular, and structural. Understanding plant insect resistance is crucial for developing stress-resistant crop varieties and improving agricultural productivity. Ultraviolet radiation (UV), as an important component of solar radiation, has a dual effect on plants. Appropriate amounts of UV-B can promote plant growth and development and the synthesis of secondary metabolites, but excessive UV-B exposure can cause damage to the plant's photosynthetic system, DNA damage, and cell membrane disruption.

[0003] Traditional methods, such as histochemical staining, immunohistochemistry, gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), can provide detailed cellular and molecular information but are often destructive, time-consuming, and costly. In the study of plant stress defense mechanisms, these methods can only perform in vitro testing and are unable to achieve real-time dynamic monitoring of living plants. They also lack the ability to integrate spatiotemporal dynamics and multidimensionality. Furthermore, these methods can typically only analyze a limited number of molecules, making it difficult to provide a comprehensive understanding of complex plant insect resistance. Summary of the Invention

[0004] In response to the defects of the existing technology, the purpose of this application is to provide a real-time in-situ detection method and system for the insect resistance level of plants, aiming to solve the problem that traditional methods such as histochemical staining, immunohistochemistry, gas chromatography-mass spectrometry, and liquid chromatography-mass spectrometry can only analyze a limited number of molecules and are difficult to provide a comprehensive analysis of the insect resistance of complex plants.

[0005] To achieve the above objectives, in a first aspect, the present application provides a method for real-time in-situ detection of plant insect resistance levels, comprising the following steps: After irradiating the plants with different doses of ultraviolet light, a hyperspectral stimulated Raman scattering imaging subsystem was used to perform stomatal imaging and spectral signal acquisition on the leaves of the plants. Spectral signals of different wavelengths were used to qualitatively analyze different metabolites in leaves, while characteristic peak areas and peak intensity characteristics were combined to quantitatively detect metabolites. Stomatal structural changes were also acquired based on stomatal imaging. Calculate the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realize in situ detection of plant insect resistance.

[0006] Further preferably, based on the molecular vibration theory, 1550 ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

[0007] Further preferably, the correlation between plant stomatal structure and insect resistance for:

[0008] in, and are the sample means of X and Y respectively; and is the sample observation value; Y is insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation; ; .

[0009] Further preferably, the combined effect of metabolite changes on insect resistance is expressed as:

[0010] Correlation between metabolite changes and insect resistance for:

[0011] in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , and c are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

[0012] Further preferably, the hyperspectral stimulated Raman scattering imaging subsystem includes: A laser light source module is used to provide Stokes light and pump light. The pump light passes through a second half-wave plate and a second polarization beam splitter and is connected to a first dichroic mirror. The Stokes light passes through the first half-wave plate and the first polarization beam splitter and is then sinusoidally intensity modulated by an acousto-optic modulator. The modulated Stokes light passes through a time delay unit and is then combined with the pump light output by the second polarization beam splitter through the first dichroic mirror. The signal acquisition module includes an imaging unit and a detection unit; The imaging unit is used to introduce linear chirp, broadening the pulse in the time domain and making the frequency difference between the pump light and the Stokes light linearly distributed in time. The pulse is then connected to a microscope through a second dichroic mirror and focused on the plant leaf to be tested. The two-dimensional scanning galvanometer performs a planar scan of the plant leaf to be tested. After the scanning signal is collected by an oil-immersion condenser, the Stokes light is filtered and the pump light is received by a photodiode as the detection light. The detection unit is used to input the signal received by the photodiode into the lock-in amplifier to realize heterodyne detection.

[0013] In a second aspect, the present application provides a real-time in-situ detection system for plant insect resistance levels, comprising: A hyperspectral stimulated Raman scattering imaging subsystem is used to perform stomatal imaging and spectral signal acquisition on the leaves of plants to be tested; wherein the plants to be tested are plants irradiated with different doses of ultraviolet light; The data processing subsystem is used to conduct qualitative analysis of different metabolites in plant leaves using spectral signals of different bands, and to conduct quantitative detection based on characteristic peak area and peak intensity characteristics, and to obtain changes in stomatal structure based on stomatal imaging; it calculates the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realizes in situ detection of plant insect resistance.

[0014] Further preferably, the data processing subsystem adopts 1550 based on molecular vibration theory. ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

[0015] Further preferably, the correlation between plant stomatal structure and insect resistance in the data processing subsystem for:

[0016] in, and are the sample means of X and Y respectively; and is the sample observation value; Y is insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation; ; .

[0017] Further preferably, the combined effect of metabolite changes on insect resistance in the data processing subsystem is expressed as:

[0018] Correlation between metabolite changes and insect resistance for:

[0019] in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , and c are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

[0020] Further preferably, the hyperspectral stimulated Raman scattering imaging subsystem includes: A laser light source module is configured to provide Stokes light and pump light, and connect the pump light to the first dichroic mirror via a second half-wave plate and a second polarization beam splitter. The Stokes light passes through the first half-wave plate and the first polarization beam splitter, and then undergoes sinusoidal intensity modulation via an acousto-optic modulator. The modulated Stokes light passes through a time delay unit and is then combined with the pump light output from the second polarization beam splitter via the first dichroic mirror. The signal acquisition module includes an imaging unit and a detection unit; The imaging unit is used to introduce linear chirp, broadening the pulse in the time domain and making the frequency difference between the pump light and the Stokes light linearly distributed in time. The pulse is then connected to a microscope through a second dichroic mirror and focused on the plant leaf to be tested. The two-dimensional scanning galvanometer scans the plant leaf in a planar manner. After the scanning signal is collected by an oil-immersion condenser, the Stokes light is filtered and the pump light is received by a photodiode as the detection light. The detection unit is used to input the signal received by the photodiode into the lock-in amplifier to realize heterodyne detection.

[0021] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the existing technologies: The present application provides a real-time, in-situ detection method for the insect resistance level of plants. Stimulated Raman scattering (SRS) microscopy, which has the advantages of high sensitivity, label-free operation, and nanoscale resolution, can study the insect resistance mechanism at the molecular level. Hyperspectral stimulated Raman imaging combines the high sensitivity and fast imaging speed of SRS imaging with the high spectral resolution of hyperspectral imaging (HSI), and can simultaneously obtain spatial and spectral information of samples. It can detect the distribution of metabolites in plant cells at the subcellular level, characterize plant cells and tissues, including cell walls, cytoplasm, nuclei, chloroplasts, etc., reveal the spatial distribution of chemical molecules in cells caused by plant stress responses, and realize the simultaneous identification and qualitative and quantitative analysis of complex components and structures in plants. This method provides new tools and methods for plant physiological and pathological research, pest and disease detection, and agricultural product quality assessment. Through this method, the complex process of plant resistance to pests and diseases can be comprehensively analyzed. Its non-invasive, high specificity, and qualitative and quantitative capabilities can provide important theoretical basis and practical guidance for the development of green pest and disease control technologies. It can also play an irreplaceable role in the breeding of insect-resistant crops (such as screening high secondary metabolite lines) and the analysis of pest-plant interaction mechanisms. It has broad application space in plant pest resistance monitoring of crops such as tea gardens, research on rice resistance to brown planthoppers in the field, and real-time monitoring of insect resistance of grain crops such as rice and wheat. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a method for real-time in-situ detection of plant insect resistance levels provided in an embodiment of the present application; Figure 2 is a schematic diagram of the spectral focusing method provided in an embodiment of the present application; Figure 3 is a schematic diagram of a hyperspectral stimulated Raman microscopy system provided in an embodiment of the present application; Figure 4 This is a schematic diagram of the experimental data collection and processing steps provided in the embodiments of the present application; FIG5 (a) is a schematic diagram of quantitative analysis of flavonoids in plant leaves treated with different doses of ultraviolet light provided in the examples of the present application; FIG5( b ) is a schematic diagram of quantitative analysis of salicylic acid in plant leaves treated with different doses of ultraviolet light provided in an embodiment of the present application; FIG5( c ) is a schematic diagram of quantitative analysis of protein in plant leaves treated with different doses of UV light provided in the examples of the present application; Figure 6 Schematic diagram of stomatal opening characterization provided in the embodiment of the present application; Figure 7 Schematic diagram of the correlation analysis between insect resistance and related metabolites provided in the examples of the present application. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0024] The term "and / or" in this application describes an association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, or B exists alone. The symbol " / " in this document indicates that the associated objects are in an "or" relationship, for example, A / B means A or B.

[0025] The terms "first" and "second" and the like in the description and claims of this application are used to distinguish different objects rather than to describe a specific order of the objects.

[0026] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0027] In the description of the embodiments of the present application, unless otherwise specified, “plurality” means two or more.

[0028] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application.

[0029] Hyperspectral stimulated Raman scattering (HSRS), an emerging nonlinear optical imaging technique, has recently demonstrated strong application potential in fields such as biomedicine and materials science. Compared to traditional spontaneous Raman scattering, SRS offers the advantages of high sensitivity, fast imaging speed, minimal photobleaching, labeling-free and non-invasive nature, and the absence of non-resonant background. Hyperspectral stimulated Raman imaging combines the high sensitivity and fast imaging speed of SRS with the high spectral resolution of HSI, enabling the simultaneous acquisition of spatial and spectral information from plant samples, enabling the simultaneous identification and quantitative analysis of multiple components in complex samples.

[0030] The following is an introduction to the hyperspectral stimulated Raman scattering imaging subsystem involved in this application. The hyperspectral stimulated Raman scattering imaging subsystem includes: The laser light source module outputs two laser beams, one of which has a wavelength fixed at 1045 nm and serves as Stokes light; the other has a wavelength set to 895 nm and serves as pump light. Both beams are Gaussian light. The Stokes light passes through a first half-wave plate and a first polarization beam splitter, and then undergoes sinusoidal intensity modulation at a frequency of 3.9 MHz via an acousto-optic modulator. The modulated Stokes light passes through a time delay unit and is then combined with the pump light via a first dichroic mirror. The pump light passes through a second half-wave plate and a second polarization beam splitter and is connected to the first dichroic mirror. The first dichroic mirror achieves spatial collinearity of the two laser beams, thereby achieving temporal and spatial combination of the two laser beams. The time delay unit, consisting of a motorized two-dimensional translation stage with a triangular reflecting prism at a 90° angle, is used to adjust the timing of the lasers. By moving the stage, the optical path of the Stokes light is changed to achieve temporal coupling of the two laser beams. A signal acquisition module, including an imaging unit and a detection unit; The imaging unit includes a glass rod, a second dichroic mirror, a microscope, a two-dimensional scanning galvanometer, an oil-immersion condenser, two bandpass filters, and a photodiode. The glass rod acts as a dispersive medium to introduce linear chirp into the femtosecond laser, broadening the pulse in the time domain. The overlapping portion of the two laser beams, due to the same linear chirp coefficient, produces a frequency difference that is linearly distributed on the time axis, thereby achieving hyperspectral stimulated Raman scattering imaging. The two collinear beams are connected to the microscope imaging system via a dichroic mirror and focused on the sample using a high-NA objective lens. The sample is scanned in a plane using a two-dimensional scanning galvanometer. After the signal is collected by the oil-immersion condenser, two bandpass filters are installed in front of the photodiode, in which Stokes light with a wavelength of 1045 nm is filtered out, and the pump light is received by the photodiode as detection light. The detection unit includes a phase-locked amplifier and a digital acquisition card; the signal received by the photodiode is input into the phase-locked amplifier to realize heterodyne detection, and the imaging signal of a specific frequency is amplified and output to the digital acquisition card for subsequent data analysis and processing.

[0031] First, as Figure 1 As shown, the present application provides a real-time in-situ detection method for plant insect resistance level, comprising the following steps: After irradiating the plants with different doses of ultraviolet light, a hyperspectral stimulated Raman scattering imaging subsystem was used to perform stomatal imaging and spectral signal acquisition on the leaves of the plants. Spectral signals of different bands were used to qualitatively analyze different metabolites in leaves, and characteristic peak areas and peak intensity characteristics were combined to quantitatively detect metabolites. Obtain stomatal structure changes based on stomatal imaging, where stomatal structure changes include changes in stomatal open rate and average stomatal open area; Calculate the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realize in situ detection of plant insect resistance.

[0032] Further preferably, based on the molecular vibration theory, 1550 ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

[0033] Further preferably, the correlation between plant stomatal structure and insect resistance for:

[0034] in, and are the sample means of X and Y respectively; and is the sample observation value; Y is the insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation.

[0035] Further preferably, the combined effect of metabolite changes on insect resistance is expressed as:

[0036] Correlation between metabolite changes and insect resistance for:

[0037] in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , and c are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

[0038] In a second aspect, the present application provides a real-time in-situ detection system for plant insect resistance levels, comprising: A hyperspectral stimulated Raman scattering imaging subsystem is used to perform stomatal imaging and spectral signal acquisition on the leaves of plants to be tested; wherein the plants to be tested are plants irradiated with different doses of ultraviolet light; The data processing subsystem is used to conduct qualitative analysis of different metabolites in plant leaves using spectral signals of different bands, and to conduct quantitative detection based on characteristic peak area and peak intensity characteristics, and to obtain changes in stomatal structure based on stomatal imaging; it calculates the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realizes in situ detection of plant insect resistance.

[0039] Further preferably, the data processing subsystem adopts 1550 based on molecular vibration theory. ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

[0040] Further preferably, the correlation between plant stomatal structure and insect resistance in the data processing subsystem for:

[0041] in, and are the sample means of X and Y respectively; and is the sample observation value; Y is insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation; ; .

[0042] Further preferably, the combined effect of metabolite changes on insect resistance in the data processing subsystem is expressed as:

[0043] Correlation between metabolite changes and insect resistance for:

[0044] in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , andc are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

[0045] Example 1 Plant pretreatment: In this embodiment, plants were treated with different doses of ultraviolet light (0.6 mJ, 1.2 mJ, and 1.8 mJ), and a control group was set up. Images and Raman spectra of plant leaves were collected. Signal acquisition: Use hyperspectral SRS microscopy system to image and collect spectra of plant leaves; imaging data acquisition 1600 Wave number image signal, analyze the changes in stomatal structure caused by UV-B. Spectral signal collection 1550~1800 2800~3050 band, used to analyze the changes in metabolites caused by UV-B; Signal preprocessing: average the collected signals, perform preprocessing operations such as noise reduction and baseline correction to remove noise interference; Metabolite detection: Based on molecular vibration theory, 1550~1800 The C=C stretching vibration, C=O stretching vibration and 2800~3050 Band asymmetry Perform qualitative analysis; perform quantitative detection based on characteristic peak area and peak intensity features.

[0046] Correlation analysis: According to Pearson correlation analysis method,

[0047] in, and are the sample means of X and Y respectively; and is the sample observation value; the correlation between the stomatal structure changes caused by UV-B supplementary irradiation and insect resistance was analyzed; Y is insect resistance; X is the change in plant stomatal structure caused by different doses of UV-B supplementary irradiation.

[0048] Introducing the correlation weight coefficient ( a , b , c ), calculate the combined effects of protein (P), salicylic acid (SA), flavonoid (F) and other metabolites (M) on insect resistance, and calculate the correlation coefficient;

[0049]

[0050] Analyze the correlation between metabolite changes and insect resistance, and determine the joint role of metabolites in the assessment of plant physiological status; like Figure 2 As shown, specifically 1550~1800 Band material analysis; the spectrum of the sample was collected by a hyperspectral SRS microscopy system, the pump light was tuned to 895 nm, and the collected spectrum was pre-processed by noise reduction, baseline correction and other operations; based on molecular vibration theory, this band is the characteristic band of the C=C stretching vibration of the benzene ring, and the benzene ring is the core structure of flavonoids and is widely distributed in plants; at the same time, the C=O stretching vibration in salicylic acid is also in this band, and it is qualitatively attributed to flavonoids and salicylic acid; in the quantitative analysis link, the ratio of the characteristic peak area to the total peak area is used to calculate the molecular content of flavonoids and salicylic acid; at 2800~3050 In the spectrum analysis of the band, the protein composed of amino acids contains a lot of asymmetric Structure, thus, 2930 The characteristic peaks were qualitatively attributed to proteins. In order to accurately obtain the changes in protein content, the spectral curve was adjusted at 2840 A method for normalization is used, and relative quantitative analysis is performed based on the normalized peak intensity, thereby achieving effective detection of the protein content in the sample.

[0051] Analysis method of leaf stomatal structure The effect of UV-B supplementary irradiation on leaf structure was studied, and a systematic analysis and statistics were conducted on the stomatal structure of leaves. In terms of the determination of stomatal structural parameters, the following method was used: the leaf stomata were imaged using a hyperspectral SRS microscopy system, and the stomatal open rate was calculated by dividing the number of open stomata by the total number of stomata; the area of ​​open stomata was measured using image analysis software, and the average stomatal open area was calculated. Through the above precise measurement and analysis of the stomatal structural parameters of leaves, the effect of UV-B supplementary irradiation on the stomatal structure of leaves can be effectively evaluated.

[0052] Example 2 Figure 3 This is a diagram of a hyperspectral stimulated Raman scattering imaging device for exploring plant stress and insect resistance mechanisms, provided in an embodiment of the present application. The device includes an excitation light source module, a time delay module, a laser scanning module, and a signal acquisition module. More specifically, the device includes: a laser light source, a half-wave plate, a polarization beam splitter, a time delay device, an acousto-optic modulator, a dichroic mirror, a scanning module, a scanning lens, a tube lens, an oil-immersion condenser, a bandpass filter, a photodiode, a lock-in amplifier, and a data acquisition card. Figures 4 to 7 The experimental data collection and processing steps are provided; quantitative analysis of flavonoids, salicylic acid, and protein in plant leaves treated with different doses of UV light; characterization of stomatal opening; and correlation analysis. Figures 5(a), 5(b), and 5(c) show the quantitative analysis of differential metabolites. The results show that the levels of total flavonoids and salicylic acid increased relative to the control group under low-dose UV light irradiation, but decreased at high doses. Total protein decreased relative to the control group under low-dose UV light irradiation, but increased at the highest dose in this experiment. Figure 6 The study provides correlation analysis results between insect resistance and stomatal structure. Plant insect resistance induced by different doses of UV-B irradiation also shows a high correlation with changes in stomatal structure. This indicates that stomata are the main site of gas exchange in plants. VOCs are released into the external environment through stomata during gas exchange, and structural changes can affect the release of VOCs. Figure 7 Because insect resistance and related metabolites show a very high correlation, the joint contribution level of plant insect resistance metabolites was correlated and analyzed. The results showed that protein and salicylic acid had a synergistic effect. At the same time, changes in the content of flavonoids were positively correlated with plant insect resistance. These data indicate that supplementing UVB radiation can effectively increase plant insect resistance, thereby providing new methods and new ideas for plant pest control.

[0053] It should be understood that the above-mentioned system is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the system are similar to those described in the above-mentioned method. The working process of the system can refer to the corresponding process in the above-mentioned method and will not be repeated here.

[0054] It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A real-time on-site detection method for plant insect resistance level, characterized in that: The following steps are involved: After irradiating the plants with different doses of ultraviolet light, a hyperspectral stimulated Raman scattering imaging subsystem was used to perform stomatal imaging and spectral signal acquisition on the leaves of the plants. Spectral signals of different wavelengths were used to qualitatively analyze different metabolites in leaves, while characteristic peak areas and peak intensity features were combined for quantitative detection. Stomatal structural changes were also acquired based on stomatal imaging. Calculate the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realize in situ detection of plant insect resistance.

2. The real-time on-site detection method according to claim 1, characterized in that: Based on molecular vibration theory, 1550 ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

3. The real-time on-site detection method according to claim 1 or 2, characterized in that: Correlation between plant stomatal structure and insect resistance for: in, and are the sample means of X and Y respectively; and is the sample observation value; Y is insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation; ; .

4. The real-time on-site detection method according to claim 1 or 2, characterized in that: The combined effect of metabolite changes on insect resistance is expressed as: Correlation between metabolite changes and insect resistance for: in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , and c are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

5. The real-time on-site detection method according to claim 1 or 2, characterized in that: Hyperspectral stimulated Raman scattering imaging subsystem, including: A laser light source module is configured to provide Stokes light and pump light. The pump light is connected to the first dichroic mirror via a second half-wave plate and a second polarization beam splitter. The Stokes light passes through the first half-wave plate and the first polarization beam splitter and is then sinusoidally intensity modulated by an acousto-optic modulator. The modulated Stokes light passes through a time delay unit and is then combined with the pump light output from the second polarization beam splitter via the first dichroic mirror. The signal acquisition module includes an imaging unit and a detection unit; The imaging unit is used to introduce linear chirp, broadening the pulse in the time domain and making the frequency difference between the pump light and the Stokes light linearly distributed in time. The pulse is then connected to a microscope through a second dichroic mirror and focused on the plant leaf to be tested. The two-dimensional scanning galvanometer scans the plant leaf in a planar manner. After the scanning signal is collected by an oil-immersion condenser, the Stokes light is filtered and the pump light is received by a photodiode as the detection light. The detection unit is used to input the signal received by the photodiode into the lock-in amplifier to realize heterodyne detection.

6. A real-time on-site detection system for plant insect resistance level, characterized in that: include: A hyperspectral stimulated Raman scattering imaging subsystem is used to perform stomatal imaging and spectral signal acquisition on the leaves of plants to be tested; wherein the plants to be tested are plants irradiated with different doses of ultraviolet light; The data processing subsystem is used to conduct qualitative analysis of different metabolites in plant leaves using spectral signals of different bands, and to conduct quantitative detection based on characteristic peak area and peak intensity characteristics, and to obtain changes in stomatal structure based on stomatal imaging; it calculates the correlation between changes in plant stomatal structure and metabolites caused by different irradiation and insect resistance, and realizes in situ detection of plant insect resistance.

7. The real-time on-site detection system according to claim 6, characterized in that: The data processing subsystem is based on the molecular vibration theory and adopts 1550 ~1800 The spectral signals of the band were used to qualitatively analyze the C=C chemical bond stretching vibration and C=O chemical bond stretching vibration of the benzene ring. ~ 3050 The spectral signal of the band is asymmetric Conduct qualitative analysis; among them, the benzene ring is the core structure of flavonoids; C=O stretching vibration is the core structure of salicylic acid; asymmetric The structure is the core structure of the protein.

8. The real-time on-site detection system according to claim 6 or 7, characterized in that: Correlation between plant stomatal structure and insect resistance in the data processing subsystem for: in, and are the sample means of X and Y respectively; and is the sample observation value; Y is insect resistance; X is the change in plant stomatal structure caused by ultraviolet light irradiation; ; .

9. The real-time on-site detection system according to claim 6 or 7, characterized in that: The combined effect of metabolite changes on insect resistance in the data processing subsystem is expressed as: Correlation between metabolite changes and insect resistance for: in, is the protein molecular content; is the salicylic acid molecular content; is the flavonoid molecule content; , and c are the correlation weight coefficients corresponding to protein, salicylic acid and flavonoids respectively; Y is insect resistance; is the Poisson function; M Represents metabolites.

10. The real-time on-site detection system according to claim 6, characterized in that: Hyperspectral stimulated Raman scattering imaging subsystem, including: A laser light source module is used to provide Stokes light and pump light, and connect the pump light to the first dichroic mirror via the second half-wave plate and the second polarization beam splitter; the Stokes light passes through the first half-wave plate and the first polarization beam splitter, and then is sinusoidally intensity modulated by the acousto-optic modulator. After the modulated Stokes light passes through the time delay unit, it is combined with the pump light output by the second polarization beam splitter through the first dichroic mirror; The signal acquisition module includes an imaging unit and a detection unit; The imaging unit is used to introduce linear chirp, broadening the pulse in the time domain and making the frequency difference between the pump light and the Stokes light linearly distributed in time. The pulse is then connected to a microscope through a second dichroic mirror and focused on the plant leaf to be tested. The two-dimensional scanning galvanometer scans the plant leaf in a planar manner. After the scanning signal is collected by an oil-immersion condenser, the Stokes light is filtered and the pump light is received by a photodiode as the detection light. The detection unit is used to input the signal received by the photodiode into the lock-in amplifier to realize heterodyne detection.

Images