Device for detecting mycorrhiza of crops and method for detecting mycorrhiza of crops

Abstract

The present application relates to the technical field of agricultural biological detection, and provides a crop mycorrhiza detection device and a crop mycorrhiza detection method. The crop mycorrhiza detection device comprises a linearly polarized laser, a half-transmission half-reflection mirror, a sample stage, a polarization unit, a detector and a processor. The linearly polarized laser is used to emit S-polarized light. The half-transmission half-reflection mirror is arranged opposite to the linearly polarized laser. The sample stage is arranged below the half-transmission half-reflection mirror. The polarization unit is arranged above the half-transmission half-reflection mirror and is used to filter out S-polarized light. The detector is used to receive P-polarized light and mixed light. The processor is electrically connected to the detector, and is used to obtain a false color image of mycelium and root fiber to distinguish the mycelium from the root fiber. The crop mycorrhiza detection device can distinguish mycelium light signals and root fiber light signals according to the different polarization light reflectivity characteristics of the mycelium and the root fiber, generate a false color image of mycorrhiza, and accurately distinguish the mycelium from the root fiber.

Description

Technical Field

[0001] This invention relates to the field of agricultural biological detection technology, and in particular to a crop mycorrhizal detection device and a crop mycorrhizal detection method. Background Technology

[0002] Mycorrhizae are symbiotic relationships between fungi and plant roots. Their microscopic characteristics (such as hyphal diameter, density, and activity state) directly affect the efficiency of crop absorption of nutrients such as nitrogen and phosphorus, as well as its stress resistance. Therefore, accurate and rapid detection of crop mycorrhizal microstructure is of great significance for optimizing fertilization, breeding stress-resistant varieties, and increasing crop yield.

[0003] However, cellulose, the main component of plant roots in mycorrhizae, and chitin, the fungal hyphae, are highly similar in spectral characteristics. Traditional polarization imaging techniques have difficulty quickly distinguishing between the two signals and usually rely on complex sample pretreatment or chemical analysis methods, resulting in low efficiency of mycorrhizal detection and difficulty in meeting the needs of practical applications. Summary of the Invention

[0004] This invention provides a crop mycorrhizal detection device and a crop mycorrhizal detection method to solve the problem of low efficiency in distinguishing mycelium from root fibers in the prior art.

[0005] This invention provides a crop mycorrhizal detection device, comprising: a linearly polarized laser for emitting S-polarized light; a semi-transparent mirror disposed opposite to the linearly polarized laser; a sample stage disposed below the semi-transparent mirror for placing mycorrhizae, the semi-transparent mirror reflecting the S-polarized light to the mycorrhizae, the mixed light reflected by the mycorrhizae being transmitted through the semi-transparent mirror, the mixed light including the S-polarized light and P-polarized light; a polarization unit disposed above the semi-transparent mirror, the polarization unit for filtering out the S-polarized light, or a portion of the polarization unit for filtering out the S-polarized light, the remaining portion of the polarization unit for beam splitting; and at least one detector, wherein if the polarization unit is only used for filtering, the detector is disposed above the polarization unit, and the polarization unit is used for both filtering and beam splitting. In this configuration, multiple detectors are respectively positioned above and to one side of the polarization unit. These detectors receive the P-polarized light and the mixed light. The mixed light, after removing the P-polarized light, becomes the root fiber light signal. A processor, electrically connected to the detectors, separates the mycelial light signal and the root fiber signal based on the different reflection efficiencies of the mycelium and root fibers towards the P-polarized light. It also establishes a linear correlation model of the mycelial diameter based on the phase delay of the P-polarized light and a mycelial sample database to obtain the mycelial diameter from the phase delay. Furthermore, the processor maps the mycelial color to the polarization degree of the P-polarized light to obtain a pseudo-color image of the mycelium. Finally, it maps the root fiber color to the intensity of the root fiber light signal to obtain a pseudo-color image of the root fiber, thus distinguishing the mycelium from the root fiber.

[0006] According to the present invention, a crop mycorrhizal detection device is provided, wherein the polarization unit is a polarizer, and the polarizer is movably disposed above the semi-transparent mirror; the number of detectors is one, and the detector is a first detector. When the polarizer and the semi-transparent mirror are disposed opposite to each other, the first detector is used to receive the P-polarized light; when the polarizer and the semi-transparent mirror are disposed offset, the first detector is used to receive the mixed light.

[0007] According to the present invention, a crop mycorrhizal detection device includes a polarization unit comprising: a beam splitter disposed above a semi-transparent mirror, the beam splitter being used to split the mixed light into a first mixed light and a second mixed light; a polarizer disposed above the beam splitter, the first mixed light becoming P-polarized light after passing through the polarizer; and a plurality of detectors, including: a second detector disposed above the polarizer, the second detector being used to receive the P-polarized light; and a third detector disposed on one side of the beam splitter, the third detector being used to receive the second mixed light.

[0008] According to the crop mycorrhizal detection device provided by the present invention, a driving mechanism is further included, which is used to drive the sample stage to move along the x-axis and y-axis directions.

[0009] According to the present invention, a crop mycorrhizal detection device further includes: a scanner disposed on the driving mechanism and electrically connected to the processor, the scanner being used to scan the spatial coordinates of each region; a rangefinder disposed on one side of the sample stage and electrically connected to the processor, the rangefinder being used to detect the displacement of the sample stage; the processor being used to bind and store the spatial coordinates of each region scanned by the scanner and the light signals of each region, and to obtain a full-domain pseudo-color image of the mycorrhizae using a stitching algorithm; the processor is also used to control the driving mechanism to move according to the displacement detected by the rangefinder, so that the sample stage moves along a preset path.

[0010] According to the present invention, a crop mycorrhizal detection device further includes: a guide rail disposed between the semi-transparent mirror and the first detector, wherein the polarizer is slidably connected to the guide rail; and a driver connected to the polarizer, wherein the driver is used to drive the polarizer to slide along the guide rail.

[0011] The present invention also provides a crop mycorrhizal detection method based on the crop mycorrhizal detection device described above, comprising: acquiring a first optical signal of P-polarized light and a second optical signal of mixed light, wherein the first optical signal represents a hyphal optical signal; obtaining a third optical signal based on the difference between the second optical signal and the first optical signal, wherein the third optical signal represents a root fiber optical signal; calculating the phase delay and polarization degree of the first optical signal; establishing a linear correlation model of hyphal diameter based on the phase delay and a hyphal sample database to obtain the hyphal diameter; mapping hyphal color based on the polarization degree to obtain a pseudo-color image of the hyphae; and mapping the color of root fibers based on the intensity of the third optical signal to obtain a pseudo-color image of the root fibers to distinguish the hyphae from the root fibers.

[0012] According to a crop mycorrhizal detection method provided by the present invention, the step of establishing a linear correlation model of hyphal diameter based on the phase delay and hyphal sample database includes: collecting mycorrhizal samples, calibrating hyphal diameter, and establishing a hyphal sample database; fitting the phase delay and hyphal diameter using the least squares method to obtain a linear correlation model of hyphal diameter.

[0013] According to the method for detecting crop mycorrhizae provided by the present invention, the method further includes: dividing the mycorrhizae into multiple regions; driving the sample stage to move along a preset path; acquiring the original image of the mycorrhizae in each region; and obtaining a full-domain pseudo-color image of the mycorrhizae by stitching together multiple original images.

[0014] According to a crop mycorrhizal detection method provided by the present invention, the step of acquiring the original image of mycorrhizae in each region and obtaining a global pseudo-color image of mycorrhizae by stitching together multiple original images includes: acquiring a first light signal image and a second light signal image of each region to obtain the original image of each region; stitching multiple original images into a complete original image; and processing the complete original image to obtain the global pseudo-color image.

[0015] According to a crop mycorrhizal detection method provided by the present invention, the step of acquiring the original image of mycorrhizae in each region and obtaining a global pseudo-color image of mycorrhizae by stitching together multiple original images includes: processing the original image of each region to obtain a phase delay / polarization parameter matrix and a pseudo-color image of each region; and performing weighted fusion of multiple pseudo-color images of multiple regions based on the coordinate mapping relationship of the parameter matrix to obtain the global pseudo-color image.

[0016] The crop mycorrhizal detection device provided by this invention, by setting up a semi-transparent and semi-reflective mirror, a polarization unit, a detector and a processor, can distinguish the mycelial light signal and the root fiber light signal based on the different reflectivities of mycelium and root fibers to P-polarized and S-polarized light, and generate pseudo-color images of mycelium and root fibers, thereby accurately distinguishing mycelium and root fibers, so as to facilitate scientific cultivation based on the microstructure of mycelium. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is one of the structural schematic diagrams of the crop mycorrhizal detection device provided by the present invention.

[0019] Figure 2 This is the second schematic diagram of the structure of the crop mycorrhizal detection device provided by the present invention.

[0020] Figure 3 It is a false-color image of mycelium and root fibers.

[0021] Figure 4 It is one of the images of mycorrhizae in the existing technology.

[0022] Figure 5 This is a standard image of mycorrhizae.

[0023] Figure 6 This is a schematic diagram of multi-regional mycorrhizal collection.

[0024] Figure 7 It is a full-area pseudo-color image of hyphae and root fibers.

[0025] Figure 8 It is a full-area pseudo-color image of mycelium and root fibers that is manually spliced ​​together.

[0026] Figure label: 10. Linearly polarized laser; 11. Optical guide rail; 20. Semi-transparent mirror; 21. Support; 30. Sample stage; 41. Polarizer; 42. Beam splitter; 51. First detector; 52. Second detector; 53. Third detector; 60. Drive mechanism; 70. Rangefinder; 81. Guide rail; 82. Stepper motor. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0028] The following is combined with Figures 1-8 The present invention describes the crop mycorrhizal detection device and the crop mycorrhizal detection method.

[0029] like Figure 1 and Figure 2 As shown, in an embodiment of the present invention, the crop mycorrhizal detection device includes: a linearly polarized laser 10, a semi-transparent mirror 20, a sample stage 30, a polarization unit, a detector, and a processor. The linearly polarized laser 10 emits S-polarized light. The semi-transparent mirror 20 is positioned opposite the linearly polarized laser 10. After the S-polarized light enters the semi-transparent mirror 20, the light is reflected by the semi-transparent mirror 20 onto the sample stage 30. The sample stage 30 is located below the semi-transparent mirror 20 and is used to hold the mycorrhizae. After the S-polarized light is reflected to the mycorrhizae, the mixed light reflected by the mycorrhizae passes through the semi-transparent mirror 20 and enters the polarization unit. In this embodiment, the mixed light includes S-polarized light and P-polarized light.

[0030] A polarization unit is positioned above the semi-transparent mirror 20. In embodiments of the present invention, the polarization unit can be used solely to filter out S-polarized light from the mixed light, or it can perform beam splitting while filtering out S-polarized light. When the polarization unit is used solely for filtering, a detector is positioned above the polarization unit; when the polarization unit is used for both filtering and beam splitting, two detectors are used: one above the polarization unit and one to one side of the polarization unit. The detectors are used to receive P-polarized light and the mixed light.

[0031] Specifically, when the polarization unit is used only to filter out S-polarized light in the mixed light, the light received by the detector after the S-polarized light is filtered out by the polarization unit is pure P-polarized light. In this embodiment, the polarization unit is movable. Moving the polarization unit away allows the mixed light transmitted through the semi-transparent mirror 20 to directly enter the detector. At this time, the light received by the detector is the mixed light.

[0032] When the polarization unit is used not only to filter out S-polarized light in the mixed light, but also to split the light, after the mixed light is transmitted through the semi-transparent and semi-reflective mirror, the mixed light is first split by the polarization unit. After 50% of the S-polarized light in the mixed light is filtered out, the pure P-polarized light enters a detector, and the remaining 50% of the mixed light enters a detector, thus obtaining the mixed light.

[0033] In embodiments of the present invention, the P-polarized light signal represents the mycelial signal, and the S-polarized light signal represents the root fiber signal. The processor is electrically connected to the detector and is used to separate the P-polarized light signal and the S-polarized light signal. Specifically, by testing the polarization reflectance of chitin in the mycelia of four crops (wheat, corn, etc.) and cellulose in the root fibers, the following results were obtained: the reflectance of mycelial chitin to P-polarized light is 85%-90%, while the reflectance of cellulose in the root fibers to P-polarized light is 35%-40%, with the mycelial reflectance being 2.1-2.6 times that of the root fibers; the reflectance of mycelia to S-polarized light is 3%-5%, while the reflectance of root fibers to S-polarized light is 15%-18%, with the root fibers' reflectance being 3-6 times that of the mycelia.

[0034] In this embodiment, the mixed light signal = P-polarized light signal of hyphae + S-polarized light signal of hyphae + P-polarized light signal of root fibers + S-polarized light signal of root fibers. Since: hyphae have extremely low reflectivity to S-polarized light (3%-5%), their contribution to the total S-polarized light signal in the mixed light is ≤15% (negligible); root fibers have extremely low reflectivity to P-polarized light (35%-40%), their contribution to the total P-polarized light signal in the mixed light is ≤30%, which can be offset through correlation model calibration. Therefore: The mixed optical signal - P-polarized optical signal ≈ S-polarized optical signal of root fibers (accounting for ≥85%), meets the requirements for precise separation.

[0035] When the processor receives P-polarized light signals and mixed light signals, it performs signal preprocessing on the P-polarized light and mixed light. The Otsu adaptive threshold segmentation (threshold T=0.3±0.05) automatically filters out the S-polarized light noise that contributes weakly to the hyphae, ensuring that the purity of the final root fiber signal is ≥95%.

[0036] The following details the specific separation process of P-polarized light signals and S-polarized light signals.

[0037] Assuming the total light intensity irradiated onto the sample by the laser is 100 μW, and the reflectance of both hyphae and root fibers to the two polarized light types is taken as the median, that is, hyphae (chitin): 88% reflectance to P-polarized light (strong reflectivity), and 4% reflectance to S-polarized light (extremely weak reflectivity); root fibers (cellulose): 38% reflectance to P-polarized light (weak reflectivity), and 16% reflectance to S-polarized light (moderate reflectivity). Assuming that the detection area is 50% hyphae and 50% root fibers, with no soil background (simplified scenario; actual background will be filtered later).

[0038] The P-polarized light signal reflected by hyphae = total incident light intensity × hyphal P-reflectivity × hyphal area ratio = 100μW × 88% × 50% = 44μW; The S-polarized light signal reflected by hyphae = total incident light intensity × hyphal S-reflectivity × hyphal area ratio = 100μW × 4% × 50% = 2μW; Total hyphal signal = 44 μW (P light) + 2 μW (S light) = 46 μW; Key findings: The signal from the hyphae mainly came from P-polarized light (44 μW, accounting for 95.7%), while the S-polarized light signal was almost negligible (2 μW, accounting for 4.3%).

[0039] The P-polarized light signal reflected by the root fibers = total incident light intensity × root fiber P-light reflectivity × root fiber area ratio = 100μW × 38% × 50% = 19μW; The S-polarized light signal reflected by the root fibers = total incident light intensity × root fiber S-polarized reflectivity × root fiber area ratio = 100μW × 16% × 50% = 8μW; Total signal of root fibers = 19 μW (P light) + 8 μW (S light) = 27 μW; Key findings: The signal from root fibers mainly comes from S-polarized light (8μW, accounting for 29.6%), while P-polarized light accounts for a high proportion (19μW, accounting for 70.4%), but this will be differentiated later.

[0040] Mixed light signal = total mycelial signal + total root fiber signal = 46μW + 27μW = 73μW. The mixed light includes 44μW of mycelial P light + 2μW of mycelial S light + 19μW of root fiber P light + 8μW of root fiber S light.

[0041] Pure P light signal = mycelial P light signal + root fiber P light signal = 44μW + 19μW = 63μW.

[0042] The mixed light signal - pure P-polarized light signal = 73μW - 63μW = 10μW. This 10μW is actually the sum of the "mycelial S-polarized light signal + root fiber S-polarized light signal", which is the total signal of all S-polarized light. In this embodiment, the mycelial S-polarized light signal is 2μW, which is lower than the set threshold. The Otsu threshold segmentation algorithm in the processor will automatically filter out the mycelial S-polarized light signal. The remaining 8μW light signal after filtering is the S-polarized light signal of the root fiber.

[0043] Within the pure P-polarized light signal (63 μW), there is also 19 μW of polarized light reflected from the root fibers. This portion of polarized light can be subsequently calibrated using a correlation model to isolate the contribution of the root fibers to the P-polarized light; that is, the P-polarized light signal is simply the pure mycelial light signal. The mycelial signal and root fiber signal can be separated using the above method.

[0044] In this embodiment, the processor is also used to establish a linear correlation model of hyphal diameter based on the phase delay of P-polarized light and the hyphal sample database to obtain the hyphal diameter. The processor is also used to map hyphal color based on the polarization degree of P-polarized light to obtain a pseudo-color image of hyphae. The processor is also used to map the color of root fibers based on the intensity of root fiber light signals to obtain a pseudo-color image of root fibers to distinguish hyphae from root fibers.

[0045] Specifically, in this embodiment, the phase delay and degree of polarization of P-polarized light are calculated. Mycorrhizal samples are collected, hyphal diameter and hyphal activity are calibrated, and a hyphal sample database is established. The least squares method is used to fit the phase delay and hyphal diameter to obtain a linear correlation model of hyphal diameter, thus the hyphal diameter can be obtained from the phase delay of P-polarized light. In this embodiment, polarization degree is related to mycelial activity. Mycelial color is mapped according to polarization degree: polarization degree ≥ 0.75 is mapped to red, which has a strong visual impact, highlighting highly active hotspots, corresponding to vigorous mycelial metabolism, dense and regularly arranged chitinous structure, and a reflectivity of 85%-90% for P-polarized light; polarization degree between 0.4 and 0.75 is mapped to yellow, which is between red and gray, visually representing a transitional state of activity, corresponding to slow mycelial metabolism, intact but loosely arranged chitinous structure, and a reflectivity of 60%-85% for P-polarized light, indicating dynamic activity; polarization degree < 0.4 is mapped to gray, which has a soft visual appearance and forms a clear contrast with active areas, marking non-functional areas, corresponding to dormant mycelial metabolism ceasing (loose chitinous structure), damaged structure in slippery mycelia, and a reflectivity of ≤ 50% for P-polarized light, indicating no physiological function. This yields a pseudo-color image of the mycelium. The color of root fibers is mapped based on the intensity of their optical signals. In this mapping, the signal is extremely weak (0.0-0.2), mapped to black, corresponding to the soil background color; weak (0.2-0.4), mapped to light blue, corresponding to sparse root fibers; moderate (0.4-0.6), mapped to medium blue, corresponding to dense root fibers; strong (0.6-0.8), mapped to dark blue, corresponding to robust root fibers; and extremely strong (0.8-1.0), mapped to navy blue, corresponding to root fiber bundles. This generates a pseudo-color image of the root fibers, distinguishing them from mycelia. In this embodiment, the processor has a display screen that can display the pseudo-color image of the mycorrhizae.

[0046] Optionally, after collecting mycorrhizal samples, the diameter of the root fibers can be calibrated to establish a root fiber sample database. A linear correlation model of the root fiber diameter is obtained by fitting the phase delay of S-polarized light and the root fiber diameter using the least squares method. This allows the root fiber diameter to be determined from the phase delay of S-polarized light, and then combined with the intensity of S-polarized light to obtain a pseudo-color image of the root fibers. The advantage of this embodiment is that the boundaries of the root fibers are clearer, resulting in higher image recognition.

[0047] Optionally, the linearly polarized laser 10 is a 532nm linearly polarized laser, the wavelength of which is determined according to the characteristic response wavelength of mycelial chitin and root cellulose; the power of the linearly polarized laser 10 is 10-20mW, which can ensure that the mycelial survival rate is ≥97% after continuous irradiation for 30 minutes; the spectral linewidth is ≤1nm to ensure laser monochromaticity and reduce dispersion interference.

[0048] Optionally, an optical guide rail 11 can be provided below the linearly polarized laser 10. The linearly polarized laser 10 is disposed on the optical guide rail 11 and can slide along the optical guide rail 11 to adjust the distance between the linearly polarized laser 10 and the semi-transparent mirror 20.

[0049] Optionally, in an embodiment of the present invention, the semi-transparent mirror 20 can be a single mirror body with a reflective film coated on the side facing the linearly polarized laser 10. When S-polarized light passes through the semi-transparent mirror 20, 50% of the light is reflected onto the mycorrhizae, and 50% of the light is transmitted. Optionally, the semi-transparent mirror 20 can also be a combination of a reflector and a transmissive mirror, with the reflector facing the linearly polarized laser 10. In this embodiment, the semi-transparent mirror 20 has a transmittance and reflectivity of ≥90% for light with a wavelength of 532nm, achieving a closed-loop optical path of "vertical downward reflection of polarized light" and "vertical upward transmission of mixed light," avoiding module conflicts in the horizontal optical path and reducing the size of the device.

[0050] In an embodiment of the present invention, a semi-transparent mirror 20 is disposed on a support 21, and a sample stage 30 is disposed below the support 21. The sample stage 30 can be a fixed platform or a movable platform. When the sample stage 30 is a movable platform, the position of the mycorrhizae can be adjusted by moving the sample stage 30 so that the mycorrhizae are opposite to the semi-transparent mirror 20, thereby allowing reflected light to be incident on the mycorrhizae and reflected by the mycorrhizae back to the semi-transparent mirror 20.

[0051] It should be noted that the crop mycorrhizal detection device provided in this embodiment of the invention is applicable to a variety of crops such as wheat, corn, soybeans, and rice.

[0052] The crop mycorrhizal detection device provided in this invention, by setting up a semi-transparent mirror, a polarization unit, a detector, and a processor, can distinguish the mycelial light signal and the root fiber light signal based on the different reflectivities of mycelium and root fibers to P-polarized and S-polarized light, and generate pseudo-color images of mycelium and root fibers, thereby accurately distinguishing mycelium and root fibers, so as to facilitate scientific cultivation based on the microstructure of mycelium.

[0053] like Figure 1As shown, in one embodiment of the present invention, the polarization unit is a polarizer 41, which is movably disposed above the semi-transparent mirror 20. There is one detector, designated as the first detector 51. During detection, the polarizer 41 is first positioned above the semi-transparent mirror 20. S-polarized light is reflected by the semi-transparent mirror 20 to the mycorrhizae. The light reflected by the mycorrhizae includes both S-polarized and P-polarized light, forming a mixed light. This mixed light is transmitted through the semi-transparent mirror 20 and then enters the polarizer 41. The polarizer 41 filters out the S-polarized light, while the P-polarized light can pass through the polarizer 41 and enter the first detector 51. The first detector 51 then receives pure P-polarized light.

[0054] Next, the polarizer 41 is removed, and the mixed light reflected by the mycorrhizae is transmitted through the semi-transparent mirror 20 and directly enters the first detector 51. At this time, the light received by the first detector 51 is the mixed light. The first detector 51 sends both the received P-polarized light signal and the mixed light signal to the processor, and the processor obtains a pseudo-color image of the hyphae and root fibers.

[0055] Optionally, the polarizer 41 can be moved manually or automatically. Figure 1 As shown, the crop mycorrhizal detection device also includes a guide rail 81 and a driver. The guide rail 81 is disposed between the semi-transparent mirror 20 and the first detector 51. The polarizer 41 is slidably connected to the guide rail 81, and the driver is connected to the polarizer 41. The driver can drive the polarizer 41 to slide along the guide rail 81, so that the polarizer 41 switches positions back and forth. Optionally, the driver is a stepper motor 82.

[0056] Optionally, the polarizer 41 is a Glan-Taylor prism with a polarization direction of 90° (orthogonal to S-polarized light), an extinction ratio ≥1000:1, a light-transmitting aperture ≥20mm, and is mounted on the guide rail 81 (positioning accuracy ≤0.5μm), with a switching time ≤50ms.

[0057] like Figure 2 As shown, in an embodiment of the present invention, the polarization unit includes a polarizer 41 and a beam splitter 42. The beam splitter 42 is disposed above the semi-transparent mirror 20 and is used to split the mixed light into a first mixed light and a second mixed light. The polarizer 41 is disposed above the beam splitter 42, and the first mixed light becomes P-polarized light after passing through the polarizer 41. In this embodiment, there are multiple detectors, including a second detector 52 and a third detector 53. The second detector 52 is disposed above the polarizer 41 and is used to receive P-polarized light. The third detector 53 is disposed on one side of the beam splitter 42 and is used to receive the second mixed light.

[0058] Specifically, the mixed light is transmitted through the semi-transparent mirror 20 and then enters the beam splitter 42. The beam splitter 42 splits the mixed light into a first mixed light and a second mixed light. The first mixed light is incident on the polarizer 41, which filters out the S-polarized light in the first mixed light. The P-polarized light in the first mixed light is then incident on the second detector 52. The second detector 52 receives pure P-polarized light. The second mixed light is then incident on the third detector 53, which receives the mixed light. Both the second detector 52 and the third detector 53 send the received light signals to the processor, which then obtains a pseudo-color image of the hyphae and root fibers.

[0059] In this embodiment, the beam splitter 42 is a polarization-independent 1:1 beam splitter prism with a working wavelength of 532nm and a light-transmitting aperture ≥20mm. The beam splitter 42 splits the mixed light into two beams of the same origin, with a light intensity loss ≤10% and a parallelism deviation between the two optical axes ≤0.1°.

[0060] In the embodiments of the present invention, the first detector 51, the second detector 52, and the third detector 53 have the same performance parameters. Their detection performance deviation is ≤2%, sampling frequency is ≥100Hz, response time is ≤1μs, pixels are ≥300,000, they support synchronous acquisition (time synchronization error ≤1ms), and the single-area acquisition coverage is ≥5mm×5mm.

[0061] like Figure 1 and Figure 2 As shown, in an embodiment of the present invention, the crop mycorrhizal detection device further includes a drive mechanism 60, which drives the sample stage 30 to move along the x-axis and y-axis directions. Specifically, in this embodiment, the sample stage 30 includes a platform, an x-axis linear module, and a y-axis linear module. The platform is disposed on the x-axis linear module, and the x-axis linear module is disposed on the y-axis linear module. The platform is used to place mycorrhizae. The x-axis linear module and the y-axis linear module are connected to the drive mechanism 60. Under the action of the drive mechanism 60, the x-axis linear module and the y-axis linear module move. When the x-axis linear module moves, it drives the platform along the x-axis direction. When the y-axis linear module moves, it drives the x-axis linear module and the platform to move together along the y-axis direction to adjust the position of the mycorrhizae. Optionally, the drive mechanism 60 can be multiple stepper motors, and the linear module can be a screw and nut structure; the drive mechanism 60 can also be a cylinder or hydraulic cylinder, and the linear module can also be a slide rail or slider structure. In this embodiment, the specific structures of the drive mechanism 60 and the sample stage 30 can be referenced from the relevant structures in the prior art. In this embodiment, the sample stage 30 has a stroke of 50 mm along the x-axis and y-axis, a displacement accuracy of ≤0.5 μm, and a moving speed of 0.1-5 mm / s.

[0062] like Figure 1 and Figure 2As shown, in an embodiment of the present invention, the crop mycorrhizal detection device further includes a scanner and a rangefinder 70. The scanner is disposed on the drive mechanism 60, and the scanner, drive mechanism 60, and rangefinder 70 are all electrically connected to the processor. The scanner is used to scan the mycorrhizae, and the rangefinder 70 is disposed on one side of the sample stage 30 and is used to detect the displacement of the sample stage 30. In this embodiment, when the drive mechanism 60 moves the sample stage 30 along the x-axis, S-polarized light can be irradiated to different positions of the mycorrhizae, thereby obtaining pseudo-color images of mycelia and root fibers at different positions of the mycorrhizae.

[0063] Specifically, the mycorrhizae can be pre-divided into multiple regions, and the movement path of the sample stage 30 can be set. Each time the sample stage 30 moves a certain distance, the scanner scans the spatial coordinates of that region. The scanner sends the spatial coordinate numbers of each region to the processor. The detector acquires the P-polarized light signal and mixed light signal of the mycorrhizae in each region and sends them to the processor to obtain pseudo-color images of the hyphae and root fibers in each region. After gradual movement, multiple pseudo-color images of multiple regions can be obtained. The processor stitches together these multiple pseudo-color images to obtain a global pseudo-color image of the mycorrhizae, which is then displayed on the screen.

[0064] Specifically, the scanner has a built-in position sensor module that can detect the displacement of the sample stage 30 in real time, assign a unique spatial coordinate number to each region, and send the spatial coordinate number to the processor in real time. After receiving the spatial coordinate number, the processor controls the detector to start, collect the P-polarized light signal and mixed light signal of that region, and binds and stores the collected light signal with the spatial coordinate number. After all regions have been collected, the processor calls the stitching algorithm, using the spatial coordinate number as a reference, to establish a global coordinate mapping matrix. Based on this matrix, the processor arranges, registers, and weights the pseudo-color image of each region according to its original coordinate position, and finally forms a full-domain pseudo-color image without misalignment or stitching gaps.

[0065] In this embodiment, every time the sample stage 30 moves a certain distance, the rangefinder 70 collects the displacement of the sample stage 30 along the x-axis and y-axis and sends it to the processor. The processor controls the drive mechanism 60 to move according to the received data so that the moving path of the sample stage 30 is consistent with the preset path.

[0066] In embodiments of the present invention, the scanner supports three scanning modes: rectangular, polyline, and contour matching. The acquisition interval (0.1-1mm) and overlap rate (10%-20%) can be customized to achieve synchronous control of translational movement and signal acquisition (synchronization error ≤1ms).

[0067] Furthermore, in an embodiment of the present invention, the crop mycorrhizal detection device also includes a power supply unit, which supplies power to the linearly polarized laser 10, sample stage 30, detector, drive mechanism 60, rangefinder 70, and processor. The power supply unit uses a 12V DC mobile power supply (output current ≥2A, capacity ≥10000mAh), supports continuous operation for ≥8 hours, and has overvoltage / overcurrent protection; an independent power supply branch is added for the drive mechanism 60 to ensure scanning stability.

[0068] This invention also provides a method for detecting crop mycorrhizae, specifically including the following steps: Step 100: Acquire the first optical signal of the P-polarized light and the second optical signal of the mixed light.

[0069] Specifically, after the processor receives the first and second optical signals, it performs noise reduction processing on the first and second optical signals. In response to the light intensity fluctuations and soil particle scattering interference in the field environment, Gaussian filtering (5×5 cores) is used to smooth the signal, preserving polarization characteristics while reducing noise (signal-to-noise ratio improvement ≥15dB).

[0070] Step 101: Obtain a third optical signal based on the difference between the second optical signal and the first optical signal. The third optical signal represents the root fiber optical signal.

[0071] Specifically, in the mixed light, removing the P-polarized light leaves only the S-polarized light. Therefore, the difference between the second and first light signals is the third light signal, which is the S-polarized light signal. The previous text explained the rationale for P-polarized light representing mycelial signals and S-polarized light representing root fiber signals, and how to separate the mycelial and root fiber signals; therefore, it will not be repeated here. Here, the first light signal represents the mycelial signal, and the third light signal represents the root fiber signal. After denoising, the first and third light signals are normalized. Due to the differences in reflected light intensity of different crop mycorrhizae (wheat mycorrhizae reflectance 15%-25%, rice mycorrhizae reflectance 10%-20%), maximum-minimum normalization is used to eliminate dimensional differences and ensure the consistency of parameter calculations.

[0072] Step 102: Calculate the phase delay and polarization degree of the first optical signal.

[0073] Specifically, phase retardation reflects the difference in refractive index between hyphal chitin and root cellulose fibers. The formula for calculating phase retardation is as follows: δ=arctan[(I pmax -I pmin ) / (I s+pmax -I s+pmin )]×π / 2, where δ is the phase delay, I pmax I is the maximum value of the first optical signal.pmin I is the minimum value of the first optical signal. s+pmax I is the maximum value of the second optical signal. s+pmin The minimum value of the second optical signal is given, with a calculation accuracy of ≤0.01π rad.

[0074] The degree of polarization can be used to reflect mycelial activity; the higher the mycelial activity, the higher the degree of polarization. The formula for calculating the degree of polarization is: P=(I max -I min ) / (I max +I min ), where P is the degree of polarization, I max I represents the maximum polarized light intensity of the first optical signal at the same detection point. min The minimum polarization intensity of the first optical signal is given, with a calculation accuracy of ≤0.01.

[0075] Step 103: Establish a linear correlation model of hyphal diameter based on phase delay and hyphal sample database to obtain hyphal diameter, and map hyphal color based on polarization degree to obtain pseudo-color image of hyphal.

[0076] Specifically, mycorrhizal samples are collected, hyphal diameters are calibrated, and hyphal activity levels are determined using staining methods to establish a hyphal sample database. A linear correlation model between phase delay and hyphal diameter is obtained by fitting the least squares method. Based on this linear correlation model, different hyphal diameters can be obtained for different phase delays. Polarization degree is used to map hyphal color; different polarization degrees correspond to different colors: polarization degree ≥ 0.75 maps to red, polarization degree between 0.4 and 0.75 maps to yellow, and polarization degree < 0.4 maps to gray. This allows for the determination of hyphal diameter and color under the same light signal, generating a pseudo-color image of the hyphae. Furthermore, statistical analysis is used to determine the correlation standard between polarization degree and activity level to ensure that the accuracy of activity determination is ≥ 90%.

[0077] Step 104: Map the color of the root fibers based on the intensity of the third light signal to obtain a pseudo-color image of the root fibers, so as to distinguish the hyphae from the root fibers.

[0078] Specifically, different intensities of the third light signal correspond to different colors, allowing us to obtain the color of root fibers under the same light signal and generate a pseudo-color image of the root fibers, thus distinguishing mycelia from root fibers. In this embodiment, after normalization, the intensity of the third light signal is 0-1. Between 0.0-0.2, the signal is extremely weak, mapped to black, corresponding to the soil background color; between 0.2-0.4, the signal is very weak, mapped to light blue, corresponding to sparse root fibers; between 0.4-0.6, the signal is moderate, mapped to medium blue, corresponding to dense root fibers; between 0.6-0.8, the signal is relatively strong, mapped to dark blue, corresponding to robust root fibers; and between 0.8-1.0, the signal is extremely strong, mapped to dark blue, corresponding to root fiber bundles. This allows us to obtain a pseudo-color image of the root fibers. In this embodiment, the pseudo-color image of the mycorrhiza has a pixel size of 2048×2048, with each pixel corresponding to an actual size ≤2μm, ensuring clear and discernible microstructure.

[0079] The crop mycorrhizal detection method provided in this invention can separate the first light signal and the third light signal, and then obtain a pseudo-color image of the hyphae based on the first light signal and a pseudo-color image of the root fibers based on the third light signal, thereby accurately distinguishing the hyphae from the root fibers, so as to facilitate scientific cultivation based on the microstructure of the hyphae.

[0080] In an embodiment of the present invention, the steps of establishing a linear correlation model of hyphal diameter based on phase delay and hyphal sample database include: collecting mycorrhizal samples, calibrating hyphal diameter, and establishing hyphal sample database; and fitting phase delay and hyphal diameter using the least squares method to obtain a linear correlation model of hyphal diameter.

[0081] Specifically, 300 mycorrhizal samples from four crops—wheat, corn, soybean, and rice—were collected. The hyphal diameter (1-10 μm) was determined using electron microscopy, and the activity level was assessed using staining. A sample database was established. The phase delay and hyphal diameter were fitted using the least squares method to obtain a linear correlation model δ = 0.08d + 0.12 (R²). 2 =0.96), fitting error ≤0.02π rad; the correlation standard between polarization degree and mycelial activity was determined by statistical analysis (based on 95% confidence interval) to ensure that the accuracy of activity determination is ≥90%.

[0082] Table 1 shows the processing accuracy of test data for 20 sets of mycelial-root fiber samples with known parameters, as shown in the table below: Table 1: Validation metrics Test Results δ calculation error ≤0.015π rad P calculation error ≤0.02 Accuracy of separating mycorrhizae from root fibers ≥96% Activity level determination accuracy ≥93% Pseudo-color image matching degree with the gold standard ≥95% As shown in Table 1, the crop mycorrhizal detection method provided in this embodiment of the invention has high testing accuracy and can accurately distinguish between mycelia and root fibers.

[0083] In an embodiment of the present invention, the crop mycorrhizal detection method further includes: dividing the mycorrhizae into multiple regions, driving the sample stage 30 to move along a preset path, acquiring the original image of the mycorrhizae in each region, and obtaining a full-domain pseudo-color image of the mycorrhizae by stitching together multiple original images.

[0084] Specifically, since mycorrhizae have a certain length, when the mycorrhizae are placed on the sample stage 30 and left stationary, only a local pseudo-color image of the mycorrhizae can be obtained. If a pseudo-color image of the entire length of the mycorrhizae is to be obtained, the mycorrhizae can be divided into multiple regions, and the sample stage 30 can be moved along a preset path so that each region is in turn opposite to the semi-transparent and semi-reflective mirror 20, thereby obtaining a pseudo-color image of each region. By stitching together the pseudo-color images of multiple regions, a full-area pseudo-color image of the mycorrhizae can be obtained, which can better distinguish between hyphae and root fibers.

[0085] Optionally, in one embodiment of the present invention, the step of acquiring the original image of mycorrhizae in each region and obtaining a global pseudo-color image of mycorrhizae by stitching together multiple original images includes: acquiring a first light signal image and a second light signal image of each region; stitching multiple original images into a complete original image; and processing the complete original image to obtain a global pseudo-color image.

[0086] Specifically, in this embodiment, as the sample stage 30 moves along a preset path, the detector obtains first and second optical signal images of multiple regions, stores them in TIFF format, and stitches the multiple region images into a complete original image through SIFT feature point extraction (≥500 feature points per region), RANSAC robust matching (matching accuracy ≥98%), and geometric correction (correction error ≤1μm). The stitched complete original image is then batch-processed according to the processing methods for mycelial pseudo-color images and root fiber pseudo-color images described above, outputting a full-domain pseudo-color image.

[0087] In another embodiment of the present invention, the step of obtaining the original image of mycorrhizae in each region and obtaining a global pseudo-color image of mycorrhizae by stitching together multiple original images includes: processing the original image of each region to obtain the phase delay / polarization parameter matrix and pseudo-color image of each region; and performing weighted fusion of multiple pseudo-color images of multiple regions based on the coordinate mapping relationship of the parameter matrix to obtain a global pseudo-color image.

[0088] Specifically, in this embodiment, the phase delay / polarization parameter matrix, pseudo-color images of hyphae, and pseudo-color images of root fibers for each region's mycorrhizae are obtained using the method described above. The parameter matrices of adjacent regions are verified; if the phase delay deviation is >0.05πrad or the P deviation is >0.03, data for that region is reacquired (to avoid splicing misalignment). Based on the coordinate mapping relationship of the parameter matrices, the pseudo-color images of each region are weighted and fused (overlapping regions are weighted according to distance) to eliminate splicing gaps and output a global pseudo-color image.

[0089] Of the two methods described above for generating full-domain pseudo-color images, the first method simplifies the stitching and processing workflow, reducing the total time consumption by 40% compared to the second method's stitching mode, making it suitable for rapid batch detection in the field. The second method avoids the cumulative errors of stitching the original images, achieving parameter consistency ≥99%, making it suitable for high-precision detection at the research level.

[0090] Table 2 shows the test data of a 50mm×50mm corn root sample (including 20 collection areas).

[0091] Table 2: splicing mode Scanning time splicing time splicing error Global parameter consistency Post-processing of original images 2.1 minutes 280ms ±1.8% ≥97% Post-processed parametric image stitching 2.1 minutes 450ms ±1.5% ≥99% As shown in Table 2, regardless of the method used to obtain the global pseudo-color image, the consistency of the global parameters is very good.

[0092] Figure 3 The image shown is a full-area pseudo-color image obtained using the crop mycorrhizal detection method provided in this embodiment of the invention, wherein red represents the root fiber image, blue represents the highly active mycelium image, and gray represents the soil background. Figure 4 The mycorrhizal images obtained by existing technology can only distinguish mycorrhizae from the soil background, but cannot distinguish hyphae from root fibers. Figure 5 The mycorrhizal images obtained by staining microscopy are used as the gold standard to verify the accuracy of the crop mycorrhizal detection method provided in this embodiment of the invention in distinguishing between hyphae and root fibers.

[0093] Figure 6 This is a schematic diagram of multi-regional sampling of maize root systems, with a total of 20 sampling areas marked. Figure 7 The full-domain pseudo-color image obtained using the crop mycorrhizal detection method provided in this embodiment of the invention has no stitching gaps or misalignment of activity distribution. Figure 8 The image is a full-area pseudo-color image obtained by manual stitching, which has obvious stitching gaps and misalignment of active material distribution.

[0094] The following are the results of mycorrhizal testing on various crops.

[0095] Example 1: Mycorrhizal detection of maize (variety: Zhengdan 958, large root system) Sample characteristics: Roots at the jointing stage, 8cm in length (cut into 5cm×3cm test areas), mycelial diameter 1-3μm, fragile and easily broken, with well-developed root fibers.

[0096] Detection parameters: laser power 12mW, detection time 3 seconds / area, detector sampling frequency 150Hz; scanning mode: rectangular path, scanning range 50mm×30mm, step size 0.3mm, overlap rate 15%.

[0097] Results: The accuracy rate of distinguishing mycelia from root fibers was 93%, the measurement error of mycelial diameter was ≤ ±0.2 μm, the activity identification accuracy rate was 91%, the survival rate after 30 minutes of irradiation was 97%, and there were no breaks; the splicing error of large-scale spliced ​​atlases was ±1.7%, which clearly showed that the mycorrhizal activity was the highest in the middle section of the root system (P=0.75-0.85), and slightly lower at both ends (P=0.6-0.75).

[0098] Application scenario: Evaluation of mycorrhizal activity distribution in the entire root system during crop breeding.

[0099] Example 2: Detection of soybean mycorrhizal flora (variety: Zhonghuang 13, large sample with root nodules) Sample characteristics: Roots during flowering period, size 6cm×4cm, mycorrhizae and root nodules in symbiosis, strong background interference, thick and coarse root fibers.

[0100] Detection parameters: laser power 15mW, detection time 4 seconds / area, detector sampling frequency 200Hz; scanning mode: contour fitting path, scanning range 60mm×40mm (segmented detection of the part exceeding the travel), step size 0.4mm, overlap rate 18%.

[0101] Results: The accuracy rate of distinguishing mycorrhizae from root fibers was 94%, the diameter measurement error was ≤ ±0.18μm, the activity identification accuracy rate was 93%, and the mycorrhizae and root nodules were clearly distinguished without interference; the large-scale spliced ​​atlas completely showed the high activity distribution of mycorrhizae around the root nodules (P=0.8-0.9).

[0102] Application scenario: Research on the symbiotic relationship between soil microorganisms and crops.

[0103] Example 3: Detection of rice mycorrhizal flora (variety: Nanjing 9108, large sample with water) Sample characteristics: Tillering stage root system, water content 30%, size 7cm×3cm, prone to polarization signal scattering, root fibers are thin and short.

[0104] Detection parameters: laser power 18mW (to compensate for moisture scattering loss), detection time 5 seconds / area, detector sampling frequency 150Hz; scanning mode: rectangular path, scanning range 50mm×30mm, step size 0.3mm, overlap rate 15%.

[0105] Results: The accuracy of distinguishing mycorrhizae from root fibers was 90%, the diameter measurement error was ≤ ±0.22 μm, the activity identification accuracy was 89%, there was no signal scattering in water-containing samples, and the detection stability was good; large-scale splicing maps showed that mycorrhizae were densely distributed at the root edge and had moderate activity (P=0.5-0.7).

[0106] Application scenario: Mycorrhizal detection in paddy field soil with high moisture content.

[0107] Example 4: Detection of barley mycorrhizae (Variety: Supi No. 3, large sample of microbial film) Sample characteristics: During the jointing stage, soil microbial film adhered to the roots, measuring 4cm×4cm, with hyphae diameter of 2-5μm, relatively thick cell walls, and uniformly distributed root fibers.

[0108] Detection parameters: laser power 15mW, detection time 3 seconds / area, detector sampling frequency 150Hz; scanning mode: rectangular path, scanning range 40mm×40mm, step size 0.2mm, overlap rate 12%.

[0109] Results: The accuracy rate of distinguishing mycorrhizae from root fibers was 92%, the diameter measurement error was ≤ ±0.21 μm, the activity identification accuracy rate was 90%, the mycorrhizal activity in the microbial film area was uniform (P=0.65-0.75), and the splicing error was ±1.5%.

[0110] Application scenario: Detection of microbial film activity in soil health assessment.

[0111] The performance of mycorrhizae detected using the crop mycorrhizal detection device provided in this embodiment of the invention was verified.

[0112] 1. Non-destructive testing Mycorrhizal samples from four crops—wheat, corn, soybean, and rice—were selected, with 10 replicates per group. Two different methods were used for continuous testing for 30 minutes, followed by staining to observe mycelial activity. Method 1 used a polarizer as the polarization unit, while Method 2 used both a polarizer and a spectrometer as the polarization unit.

[0113] Table 3 compares the survival rates of various technical solutions.

[0114] Table 3: Crop type Mycelial survival rate (%) of Option 1 Mycelial survival rate (%) of scheme 2 (Pre-existing technology) Survival rate (%) wheat 98 98 58 corn 97 97 55 soybeans 96 96 60 rice 95 95 52 The results demonstrate that both methods have significant non-destructive detection effects on mycorrhizae of multiple crops.

[0115] 2. Verification of the accuracy of distinguishing between mycorrhizae and root fibers Four crop mycelium-root fiber samples (mycelium diameter 1μm, 3μm, 5μm, 8μm, root fiber percentage 10%-40%) were selected and calibrated by electron microscopy, with 10 replicates in each group.

[0116] Table 4 compares the discrimination accuracy of various schemes.

[0117] Table 4: Crop type Accuracy rate of Option 1 (%) Accuracy rate of Option 2 (%) (Pre-existing technology) Discrimination accuracy (%) wheat 91 94 72 corn 90 93 70 soybeans 92 94 73 rice 89 90 68 As shown in Table 4, the discrimination accuracy of both schemes of the present invention is ≥89%, and the discrimination accuracy of the second scheme is 3%-4% higher than that of the first scheme, which is significantly better than the prior art.

[0118] 3. Verification of large-size sample scanning and stitching performance A 50mm×50mm standard calibration plate and a large corn root sample were used to test the scanning splicing performance.

[0119] Table 5 compares the splicing performance of the two schemes.

[0120] Table 5: Test object Scanning time (minutes / 50mm×50mm) splicing error (±%) Map overlap (%) Accuracy of activity distribution labeling (%) Standard calibration plate Option 1: 4.2; Option 2: 2.1 Option 1: 1.8; Option 2: 1.5 ≥99.0 / Corn root system Option 1: 5.1; Option 2: 2.5 Option 1: 2.0; Option 2: 1.7 ≥98.5 94 The results show that both schemes can efficiently complete the scanning and stitching of large samples, with scheme two being more efficient.

[0121] 4. Verification of detection efficiency Batch testing was conducted on 100 samples of mixed crop mycelium-root fiber (25 samples each of wheat, corn, soybean, and rice, including 50 large-format samples).

[0122] Table 6 shows a comparison of detection efficiency.

[0123] Table 6: Testing Plan Time taken for a single routine test (in seconds) Time taken for a single large-scale detection (in minutes) Total time (minutes) for 100 groups Efficiency improvement factor (vs. staining microscopy) Option 1 10 5.1 32.8 54 Option 2 3 2.5 16.5 180 Commercial polarization microscope 900 (15 minutes) (No splicing function) 250 3 Stain microscopy 2700 (45 minutes) (Unable to detect) 750 1 As can be seen from the table above, the crop mycorrhizal detection device provided in this embodiment of the invention has extremely high detection efficiency.

[0124] 5. Environmental adaptability verification Ten replicate tests were conducted on mycorrhizal-root fiber samples (including large-size samples) from four crops under field conditions (temperature 15-35℃, humidity 20%-40%). The detection accuracy of both schemes fluctuates within ≤2%, and the splicing error fluctuates within ±0.3%; the equipment can run continuously for 48 hours without failure; dust, slight vibration and other interference do not affect the detection results, and it is suitable for complex field environments.

[0125] 6. Verification of Spatial Matching Accuracy of Scheme Two Using a standard calibration plate and mycelial-root fiber samples, the spatial matching accuracy of the images in Scheme 2 was tested. Table 7 shows a comparison of the accuracy of spatial matchers.

[0126] Table 7: Test object Spatial matching error (μm) Image overlap (%) Impact on discrimination accuracy (%) Standard calibration plate ≤2.5 ≥99.2 No negative impact Wheat mycelium-root samples ≤2.8 ≥99.0 Accuracy fluctuation ≤ 0.5% Corn mycelium-root samples ≤3.0 ≥98.8 Accuracy fluctuation ≤ 0.8% The results demonstrate that the spatial matching calibration algorithm effectively ensures the accurate alignment of dual-optical-path images with minimal impact on the discrimination accuracy.

[0127] The crop mycorrhizal detection device and method provided in this invention enable continuous detection of mycorrhizal structures in multiple crops for 30 days. With a survival rate of ≥95% within minutes, it solves the problem of high-power damage to samples; it achieves precise separation of hyphae and root fibers with an accuracy rate of ≥92%, far exceeding traditional technologies (≤75%); it integrates two-dimensional motorized scanning and image stitching functions, with a coverage area of ​​≥50mm×50mm, enabling full-area detection of entire crop root systems and large-area soil microbial films, with a stitching error of ≤±2%, overcoming the limitations of local detection in traditional devices; it establishes a unified quantitative correlation model, outputting quantifiable indicators (hyphae diameter, activity level), and the stitched images support visual annotation of activity distribution, avoiding human interpretation errors, and the results are repeatable and comparable; the vertical coaxial layout avoids conflicts, the device weighs ≤4kg, and its volume is ≤25cm×20cm×15cm, which is 40% smaller than traditional horizontal optical path devices, making it suitable for field use; the pseudo-color image intuitively distinguishes different active hyphae, root fibers, and background, and the large-scale stitched images can be magnified locally and parameter annotations can be superimposed to enhance the reliability of the results; no core parameters need to be adjusted, and it is suitable for various crops such as wheat, corn, soybeans, and rice, with a detection accuracy rate of ≥89%.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A crop mycorrhizal detection device, characterized in that, include: Linearly polarized lasers are used to emit S-polarized light; A semi-transparent, semi-reflective mirror is positioned opposite to the linearly polarized laser. A sample stage is disposed below the semi-transparent mirror. The sample stage is used to place mycorrhizae. The semi-transparent mirror is used to reflect the S-polarized light to the mycorrhizae. The mixed light reflected by the mycorrhizae is transmitted through the semi-transparent mirror. The mixed light includes the S-polarized light and the P-polarized light. A polarization unit is disposed above the semi-transparent mirror. The polarization unit is used to filter out the S-polarized light, or a portion of the polarization unit is used to filter out the S-polarized light, and the remaining portion of the polarization unit is used for beam splitting. At least one detector is disposed above the polarization unit when the polarization unit is used only for filtering. When the polarization unit is used for filtering and splitting, multiple detectors are disposed above and to one side of the polarization unit respectively. The detector is used to receive the P-polarized light and the mixed light. The mixed light, after removing the P-polarized light, becomes the root fiber light signal. The processor, electrically connected to the detector, is used to separate the mycelial light signal and the root fiber signal based on the different reflection efficiencies of mycelia and root fibers to P-polarized light. It also establishes a linear correlation model of mycelial diameter based on the phase delay of P-polarized light and a mycelial sample database to obtain the mycelial diameter from the phase delay. Furthermore, the processor maps mycelial color to the polarization degree of P-polarized light to obtain a pseudo-color image of the mycelia. Additionally, it maps root fiber color to the intensity of the root fiber light signal to obtain a pseudo-color image of the root fibers, thus distinguishing the mycelia from the root fibers.

2. The crop mycorrhizal detection device according to claim 1, characterized in that, The polarization unit is a polarizer, which is movably disposed above the semi-transparent and semi-reflective mirror; The detector is a single detector, which is the first detector. When the polarizer and the semi-transparent mirror are arranged opposite each other, the first detector is used to receive the P-polarized light. When the polarizer and the semi-transparent mirror are arranged offset, the first detector is used to receive the mixed light.

3. The crop mycorrhizal detection device according to claim 1, characterized in that, The polarization unit includes: A beam splitter is disposed above the semi-transparent mirror, and the beam splitter is used to split the mixed light into a first mixed light and a second mixed light; A polarizer is disposed above the beam splitter, and the first mixed light becomes P-polarized light after passing through the polarizer; The number of detectors is multiple, and the multiple detectors include: A second detector is disposed above the polarizer, and the second detector is used to receive the P-polarized light; A third detector is disposed on one side of the beam splitter, and the third detector is used to receive the second mixed light.

4. The crop mycorrhizal detection device according to claim 1, characterized in that, It also includes a drive mechanism for driving the sample stage to move along the x-axis and y-axis.

5. The crop mycorrhizal detection device according to claim 4, characterized in that, Also includes: A scanner is disposed on the drive mechanism and electrically connected to the processor. The scanner is used to scan the spatial coordinates of each region. A rangefinder is disposed on one side of the sample stage and electrically connected to the processor. The rangefinder is used to detect the displacement of the sample stage. The processor is used to bind and store the spatial coordinates of each region scanned by the scanner and the light signals of each region, and to use a stitching algorithm to obtain a full-domain pseudo-color image of the mycorrhiza. The processor is also configured to control the drive mechanism to move according to the displacement detected by the rangefinder, so that the sample stage moves along a preset path.

6. The crop mycorrhizal detection device according to claim 2, characterized in that, Also includes: A guide rail is disposed between the semi-transparent mirror and the first detector, and the polarizer is slidably connected to the guide rail; A driver, connected to the polarizer, is used to drive the polarizer to slide along the guide rail.

7. A method for detecting crop mycorrhizae based on the crop mycorrhizae detection device according to any one of claims 1-6, characterized in that, include: Acquire a first optical signal of P-polarized light and a second optical signal of mixed light, wherein the first optical signal represents the mycelial light signal; A third optical signal is obtained based on the difference between the second optical signal and the first optical signal, and the third optical signal represents the root fiber optical signal; Calculate the phase delay and polarization degree of the first optical signal; A linear correlation model for hyphal diameter is established based on the phase delay and hyphal sample database to obtain the hyphal diameter. The hyphal color is mapped based on the polarization degree to obtain a pseudo-color image of the hyphae. The color of the root fibers is mapped based on the intensity of the third light signal to obtain a pseudo-color image of the root fibers, so as to distinguish the hyphae from the root fibers.

8. The method for detecting crop mycorrhizae according to claim 7, characterized in that, The steps for establishing a linear correlation model of hyphal diameter based on the phase delay and hyphal sample database include: Collect mycorrhizal samples, determine hyphal diameter, and establish a hyphal sample database; The phase delay and hyphal diameter were fitted using the least squares method to obtain a linear correlation model for the hyphal diameter.

9. The method for detecting crop mycorrhizae according to claim 7, characterized in that, Also includes: The mycorrhizae are divided into multiple regions; Drive the sample stage to move along a preset path; Obtain the original image of the mycorrhizae in each region, and obtain a global pseudo-color image of the mycorrhizae by stitching together multiple original images.

10. The method for detecting crop mycorrhizae according to claim 9, characterized in that, The step of obtaining the original image of the mycorrhizae in each region and obtaining a global pseudo-color image of the mycorrhizae by stitching together multiple original images includes: Acquire the first and second optical signal images of each region to obtain the original image of each region; Stitch together multiple original images into a complete original image; The full-domain pseudo-color image is obtained by processing the original image.

11. The method for detecting crop mycorrhizae according to claim 9, characterized in that, The step of obtaining the original image of the mycorrhizae in each region and obtaining a global pseudo-color image of the mycorrhizae by stitching together multiple original images includes: The original image of each region is processed to obtain the phase delay / polarization degree parameter matrix and pseudo-color image of each region; Based on the coordinate mapping relationship of the parameter matrix, multiple pseudo-color images from multiple regions are weighted and fused to obtain the global pseudo-color image.

Images