Method and device for detecting degree of salt stress of plants based on near infrared spectrum
By constructing a temperature-light coupled pure water vector and orthogonally eliminating moisture interference terms, extracting a pure ion residual vector, and combining it with the relative toxicity index to determine the degree of salt and alkali stress, the problem of accuracy and environmental disturbance in existing salt and alkali detection technologies has been solved, and the degree of salt and alkali stress has been quantitatively classified.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- INNER MONGOLIA HENGYUAN WATER CONSERVANCY ENG CO LTD
- Filing Date
- 2026-06-04
- Publication Date
- 2026-07-31
AI Technical Summary
Existing near-infrared spectroscopy methods for detecting plant salinity and alkali are difficult to accurately analyze the salinity and alkali damage status of plants without physical sampling. They are also easily affected by external environmental disturbances, leading to drastic changes in the assessment level and failing to objectively reveal the true state of salinity and alkali stress.
By constructing a temperature-light coupled pure water vector, the inner product projection of the original feature vector is calculated and a stimulated water interference term is generated. The stimulated water interference term is orthogonally removed, and the pure ion residual vector is extracted. The degree of salt-alkali stress is determined by combining the relative toxicity index and the agronomic safety threshold.
It accurately captures the signal crossover response caused by ion accumulation and water deficit in plants, improves the sensitivity of identifying early-stage salinity damage, effectively eliminates external environmental interference, and realizes the quantitative classification of the degree of salinity damage in the natural environment of the field.
Smart Images
Figure CN122306751B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of plant salt and alkali detection technology, specifically to a method and device for detecting the degree of plant salt and alkali stress based on near-infrared spectroscopy. Background Technology
[0002] With the development of modern agriculture and plant physiology, real-time and non-destructive assessment of plant salt and alkali stress is crucial for ensuring healthy crop growth and precise fertilization and irrigation. Traditional physicochemical analysis methods require the sampling of plant tissues, which is time-consuming, labor-intensive, and unable to meet the needs of large-scale simultaneous observation. In recent years, near-infrared spectroscopy has gradually become an important means of non-destructive detection of plant physiological states due to its advantages of non-destructive and rapid macroscopic perception. However, because the internal physiological mechanisms of plants are extremely complex, traditional absorbance analysis based on fixed wavelengths often lacks in-depth consideration of environmental parameters and is difficult to stably reflect the true evolution of stress when dealing with the changing climatic factors in the natural growth environment.
[0003] Existing near-infrared spectroscopy methods for plant detection typically collect spectral response data from plant leaves and perform smoothing filtering to eliminate high-frequency photoelectric crosstalk from the external environment. However, the shortcomings of these methods lie in their feature extraction process, which often overemphasizes the comparison of absolute absorbance values at discrete characteristic wavelengths. Furthermore, due to the singularity of the evaluation dimension, extensive physical destructive sampling in the field is frequently conducted to ensure that the derived physiological indicators match the actual situation. These spectral detection methods rely excessively on signal attenuation characteristics at specific nodes and on high-frequency physical tissue destruction tests for auxiliary verification. Consequently, they cannot accurately determine the true salinity and alkali damage status of plants purely based on non-destructive spectral signals without physical sampling.
[0004] In actual field saline-alkali environments, the physiological responses triggered by ion accumulation and water deficit in plants often lead to cross-over and aliasing of water molecule and inorganic ion signals in the spatial band of the spectral sequence. Simultaneously, due to the widespread presence of thermodynamic phase shifts and light scattering effects, drastic changes in external temperature fluctuations and light radiation intensity easily induce nonlinear drift in the spectral signal. Existing spectral signal processing techniques struggle to decouple the interference relationship between external environmental disturbances and internal water absorption from a physical mechanism perspective. This makes it highly susceptible to misinterpreting background changes caused by temperature and light fluctuations as substantial saline-alkali damage, resulting in drastic jumps in assessment levels and failing to objectively reveal the true toxic state of plants under saline-alkali stress.
[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0006] The purpose of this invention is to provide a method and apparatus for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy, so as to solve the problems mentioned in the background art.
[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy, comprising the following steps: Step 1: Within a preset time window, acquire a multi-frame spectral array of the target plant, ambient temperature, and photosynthetically active radiation intensity at a preset fixed frequency. Perform time-domain smoothing and mean processing on the multi-frame spectral array, and extract absorbance signals at water characteristic wavelengths and ion characteristic wavelengths to construct the original feature vector. Step 2: Construct a phase deflection term based on the ambient temperature and the preset thermodynamic phase shift constant, construct an amplitude correction term by combining the photosynthetically active radiation intensity and the preset light scattering attenuation constant, and perform nonlinear projection mapping on the preset pure water substrate using the phase deflection term and the amplitude correction term to obtain a temperature-light coupled pure water vector characterizing the current environmental characteristics. Step 3: Calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited water interference term, orthogonally remove the excited water interference term from the original feature vector, and extract the pure ion residual vector. Step 4: Obtain the spatial characteristic modulus of the pure ion residual vector, construct an optical osmotic pressure scalar based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, perform a nonlinear saturation mapping on the optical osmotic pressure scalar using a logarithmic function, and output a relative toxicity index characterizing the salt-alkali stress state. Step 5: Perform a difference mapping between the relative toxicity index and the preset agronomic safety threshold to obtain the disaster intensity base, and calculate the physical driving force in combination with the preset execution gain coefficient. Determine the degree of plant salt and alkali stress based on the preset level range to which the physical driving force belongs.
[0008] Furthermore, the specific steps for acquiring a multi-frame spectral array of the target plant at a preset fixed frequency within a preset time window include: The preset time window is a micro-transient window that traces back a preset time length from the current trigger detection time as the endpoint. The preset time length is a standard statistical period that covers multiple physical tremor cycles of the target plant leaves under natural wind fields. Continuous data acquisition is performed at a preset fixed frequency within the preset time window to generate data containing... A multi-frame spectral array of transient spectral data, wherein It is the product of the preset fixed frequency and the preset time length.
[0009] Furthermore, the specific steps for constructing the original feature vector are as follows: The multi-frame spectral array The transient spectral data of each frame are summed at the same wavelength coordinates, and the summation result is divided by the total number of frames. A smooth reference spectrum curve was constructed; Locate the water characteristic wavelength corresponding to the absorption characteristics of water molecules and the ion characteristic wavelength corresponding to the salt and alkali distortion characteristics on the smooth reference spectral curve. Extract the first absorbance value at the water characteristic wavelength as the absorbance signal at the water characteristic wavelength, and extract the second absorbance value at the ion characteristic wavelength as the absorbance signal at the ion characteristic wavelength. Encapsulate the first absorbance value and the second absorbance value into a two-dimensional column matrix structure through matrix transpose operation to construct the original feature vector.
[0010] Furthermore, the specific steps for obtaining the temperature-light coupled pure water vector are as follows: The phase deflection term is constructed by multiplying the ambient temperature with a preset thermodynamic phase shift constant. The photosynthetically active radiation intensity is multiplied by a preset light scattering attenuation constant, and the negative of the product is used as the exponent. An exponential attenuation value with the natural constant as the base is extracted to construct an amplitude correction term. Calculate the cosine and sine values of the phase deflection term respectively, multiply the cosine value with the amplitude correction term, and label the result of the multiplication as the first product; multiply the sine value with the amplitude correction term, and label the result of the multiplication as the second product. The first product is mapped to the first orthogonal dimension of the preset pure water substrate, and the second product is mapped to the second orthogonal dimension of the preset pure water substrate to perform nonlinear projection mapping; The mapped first and second products are encapsulated into a two-dimensional column vector through matrix transpose to obtain the temperature-optical coupled pure water vector. The specific calculation formula is as follows: In the formula, To calculate the temperature-light coupling pure water vector, To preset the thermodynamic phase shift constant, For ambient temperature, To preset the light scattering attenuation constant, Photosynthetically active radiation intensity, superscript This is the matrix transpose operator.
[0011] Furthermore, the specific steps for extracting the pure ion residual vector are as follows: The original feature vector is transposed, and the transposed original feature vector is multiplied by the temperature-light coupled pure water vector. The result is multiplied by the temperature-light coupled pure water vector to obtain the inner product projection of the original feature vector onto the temperature-light coupled pure water vector. The ambient temperature is multiplied by a preset thermodynamic coupling constant, and the result of the multiplication is used as an exponent. An exponential gain value with the natural constant as the base is extracted to construct an exponential penalty term. The exponential penalty term is multiplied by the inner product projection to construct the stimulated moisture interference term. Then, in the vector space, based on the original feature vector, a subtraction operation is performed on the stimulated moisture interference term to perform orthogonal directional processing, obtaining the pure ion residual vector. The specific calculation formula is as follows: In the formula, For the calculated pure ion residual vector, The original feature vector, For ambient temperature, To presuppose thermodynamic coupling constants, For temperature-light coupled pure water vector, superscript This is the matrix transpose operator.
[0012] Furthermore, the specific steps for outputting the relative toxicity index are as follows: Perform a matrix transpose operation on the pure ion residual vector, and perform a dot product operation between the transposed pure ion residual vector and the original pure ion residual vector. Perform a square root operation on the result of the operation to obtain the spatial characteristic modulus and use the spatial characteristic modulus as the molecule. The absolute value of the inner product projection is summed with a preset minimum zero constant, and the summation result is used as the denominator. The numerator and denominator are then divided to construct the optical osmotic pressure scalar. The optical osmotic pressure scalar is summed with a numerical value, and the natural logarithm of the summation result is extracted to perform a nonlinear saturation mapping, outputting the relative toxicity index. The specific calculation formula is as follows: In the formula, This is the relative toxicity index. For pure ion residual vectors, The original feature vector, For temperature-light coupling pure water vector, For the preset minimum zero-prevention constant, superscript This is the matrix transpose operator.
[0013] Furthermore, the specific steps for calculating the physical driving quantity are as follows: The relative toxicity index is subtracted from the preset agronomic safety threshold to perform difference mapping. The calculation result of the difference mapping is compared with the value of zero and the maximum value of the two is extracted to obtain the disaster intensity base. The disaster intensity base number is multiplied and coupled with a preset execution gain coefficient. Through nonlinear amplification and dimensional transformation of the disaster signal, the physical driving quantity is calculated.
[0014] Furthermore, the specific steps for determining the degree of salt stress in plants based on the preset level range to which the physical driving force belongs are as follows: The physical driving quantity is compared with a preset level range, which includes a no-stress range, a mild-stress range, a moderate-stress range and a severe-stress range, and each range is defined by a value of zero, a first-level critical point and a second-level critical point, wherein the first-level critical point is a value greater than zero and less than the second-level critical point. When the physical driving force is equal to zero, it falls into the no-stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the no-stress level. When the physical driving force is greater than zero and less than or equal to the first level critical point, it falls into the mild stress range, and the plant salt and alkali stress level of the monitored plant is determined to be mild stress level. When the physical driving force is greater than the first level critical point and less than or equal to the second level critical point, it falls into the moderate stress range, and the plant salt and alkali stress level of the monitored plant is determined to be the moderate stress level. When the physical driving force exceeds the second-level critical point, it falls into the severe stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the severe stress level.
[0015] The present invention also provides a plant salt stress degree detection device based on near-infrared spectroscopy. This device is used to implement the aforementioned plant salt stress degree detection method based on near-infrared spectroscopy, comprising: The original feature construction module is used to acquire a multi-frame spectral array of the target plant, ambient temperature and photosynthetically active radiation intensity at a preset fixed frequency within a preset time window, perform time-domain smoothing mean processing on the multi-frame spectral array, and extract absorbance signals at water feature wavelength and ion feature wavelength respectively to construct the original feature vector. The temperature-light coupling mapping module is used to construct a phase deflection term based on the ambient temperature and a preset thermodynamic phase shift constant, construct an amplitude correction term by combining the photosynthetically active radiation intensity and a preset light scattering attenuation constant, and perform nonlinear projection mapping on a preset pure water substrate using the phase deflection term and the amplitude correction term to obtain a temperature-light coupling pure water vector characterizing the current environmental characteristics. The moisture interference removal module is used to calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited moisture interference term, orthogonally remove the excited moisture interference term from the original feature vector, and extract the pure ion residual vector. The relative toxicity output module is used to obtain the spatial characteristic modulus of the pure ion residual vector, construct an optical osmotic pressure scalar based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, perform a nonlinear saturation mapping on the optical osmotic pressure scalar using a logarithmic function, and output a relative toxicity index characterizing the salt-alkali stress state. The stress level determination module is used to perform difference mapping between the relative toxicity index and the preset agronomic safety threshold to obtain the disaster intensity base, and calculate the physical driving quantity in combination with the preset execution gain coefficient, and determine the degree of plant salt and alkali stress according to the preset level interval to which the physical driving quantity belongs.
[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention constructs a temperature- and light-coupled pure water vector and calculates the inner product projection of the original feature vector onto it to generate a stimulated water interference term. Then, it extracts the pure ion residual vector through orthogonal elimination and calculates the relative toxicity index by combining spatial feature modulus and logarithmic function saturation mapping. This invention overcomes the shortcomings of traditional spectral detection, which relies heavily on comparing the absolute values of discrete feature absorbance and is highly dependent on destructive sampling of physical tissues. It accurately captures and separates the signal cross-aliasing response caused by ion accumulation and water deficit in plants, significantly improving the sensitivity of identifying very early-stage weak salt and alkali damage to plants. This invention also calculates the baseline intensity of the disaster by mapping the difference between the relative toxicity index and the agronomic safety threshold, and calculates the physical driving force by combining it with the execution gain coefficient. Based on its preset interval, the degree of salt-alkali stress in plants is determined. This mechanism, through pre-correction of the thermodynamic phase shift constant and the light scattering attenuation constant, combined with the nonlinear convergence of the logarithmic function, effectively eliminates spectral drift interference caused by large fluctuations in external temperature or sudden changes in light radiation. This prevents the misjudgment of background variations caused by changes in field temperature and light as substantial salt-alkali damage, avoiding drastic jumps in the determination level. Thus, it achieves the quantitative classification of the degree of salt-alkali damage in plants under natural field conditions. Attached Figure Description
[0017] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a diagram showing the synchronous evolution of optical osmotic pressure scalar, relative toxicity index, and physical driving factors under salt-alkali stress. Figure 3 This is a schematic diagram of the overall device structure of the present invention. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.
[0019] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0020] Example: Please see Figures 1-2 The present invention provides a technical solution: A method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy, comprising the following steps: Step 1: Within a preset time window, acquire a multi-frame spectral array of the target plant, ambient temperature, and photosynthetically active radiation intensity at a preset fixed frequency. Perform time-domain smoothing and mean processing on the multi-frame spectral array, and extract the absorbance signals at the water characteristic wavelength and ion characteristic wavelength to construct the original feature vector.
[0021] In this embodiment, because the target plant is affected by wind in a natural outdoor environment, its leaves will experience physical tremors and disordered spatial orientation shifts. Therefore, this embodiment takes the current trigger detection time as the endpoint and traces back a preset time window, where the preset time window is a standard statistical period covering multiple physical tremor cycles of the target plant leaves under natural wind conditions. Within the preset time window, continuous data acquisition is performed at a preset fixed frequency to generate data containing… A multi-frame spectral array of transient spectral data, wherein This is the product of the preset fixed frequency and the preset time length. Since the dominant frequency of blade mechanical vibration caused by natural breezes is usually concentrated in the low-frequency band, this embodiment sets the preset time length to... The preset fixed frequency is set to This generates the total number of acquisition frames. The result is a continuous spectral matrix of 120. This operation avoids the random risk of capturing extremely distorted light spots in a single snapshot, transforming the spatial displacement difference of leaves caused by wind into a spectral sample set containing complete positive and negative deviation signals. Simultaneously, the instantaneous stomatal conductance, transpiration rate, and microscopic water distribution of plant leaves in the natural environment are strongly modulated by external meteorological conditions. To prevent interference from natural diurnal rhythm fluctuations on stress state determination, the ambient temperature and photosynthetically active radiation intensity of the current microenvironment are simultaneously read while acquiring the spectral array. This provides physical background boundary parameters for subsequent removal of temporary apparent water loss characteristics caused by high-temperature exposure or strong light transpiration.
[0022] After acquiring the multi-frame spectral array, a temporal smoothing and averaging process is performed. This process involves averaging the values contained within the multi-frame spectral array. The transient spectral data were subjected to sequential summation on a completely consistent wavelength coordinate axis, and the summation result was divided by the total number of acquired frames. This allows for the construction of a smooth baseline spectral curve. The total number of acquisition frames... Set to 120 frames per second, high-frequency random scattering noise caused by physical leaf vibration is filtered out using the statistical cancellation principle of samples. Since the essence of salt-alkali stress in plants is a dual physicochemical damage intertwined with osmotic stress (obstructed water acquisition) and ion toxicity (excessive accumulation of salt ions), based on this characteristic, water molecules are located and characterized on the smoothed baseline spectral curve. Water characteristic wavelength of bond doubling absorption ( ), and characteristic ion wavelengths that characterize the solvation distortion of specific salt ions ( The first absorbance value at the characteristic wavelength of water and the second absorbance value at the characteristic wavelength of ions are extracted respectively. This extraction operation reduces the dimensionality of the full-band continuous spectral data and maps it into two discrete numerical parameters characterizing the degree of cellular osmotic water loss and the degree of ion solvation distortion. Finally, the first and second absorbance values are transformed into a matrix transpose by converting the horizontal one-dimensional row vector formed by the first and second absorbance values into a vertical two-dimensional column matrix structure, thereby constructing the original feature vector.
[0023] Step 2: Construct a phase deflection term based on the ambient temperature and the preset thermodynamic phase shift constant, and construct an amplitude correction term by combining the photosynthetically active radiation intensity and the preset light scattering attenuation constant. Use the phase deflection term and the amplitude correction term to perform nonlinear projection mapping on the preset pure water substrate to obtain a temperature-light coupled pure water vector characterizing the current environmental characteristics.
[0024] In this embodiment, the spectral response of water molecules within the mesophyll tissue is highly susceptible to dynamic modulation by external meteorological factors. Changes in ambient temperature directly affect the thermal kinetic energy of water molecules, leading to a microscopic central wavelength shift in the characteristic absorption band of water molecules. The intensity of photosynthetically active radiation not only determines the path loss of diffuse reflection and internal scattering on the leaf surface but also alters the attenuation of local photon energy by inducing transient transpiration in the plant. Therefore, this embodiment multiplies the ambient temperature with a preset thermodynamic phase shift constant to construct a phase deflection term, linearly mapping the microscopic temperature dissipation effect into an angular rotation in algebraic space. Since the characteristic absorption band of water molecules undergoes a fixed physical shift at different temperatures, this embodiment calculates the preset thermodynamic phase shift constant by reading the wavelength difference of the target plant's water characteristic absorption peak under two conventional control conditions: room temperature and heating, and dividing by the corresponding temperature difference. This embodiment sets the preset thermodynamic phase shift constant as... This is used to establish the computational scale for transforming the temperature independent variable into polar coordinates by rotation angle, eliminating spectral spurious distortions caused by external environmental temperature disturbances. The photosynthetically active radiation intensity is multiplied by a preset light scattering attenuation constant, and the negative of this product is used as the exponent. An exponential attenuation value with a natural constant as the base is extracted to construct an amplitude correction term. Utilizing the nonlinear asymptotic convergence characteristic of the negative exponential function, the marginal benefit of light scattering energy accumulation during the penetration of high-intensity light radiation into the porous medium of the leaf is simulated. Since photons experience energy loss due to internal multiple scattering when penetrating the leaf, this embodiment obtains the preset light scattering attenuation constant by reading the energy amplitude difference of the target plant's absorbance under two conventional control lighting conditions (strong light and weak light) and performing conventional logarithmic division with the corresponding difference in photosynthetically active radiation intensity. In this embodiment, the preset light scattering attenuation constant is set as... This is used to establish the computational scale for converting external radiation intensity into amplitude suppression weights, preventing false baseline drift caused by midday sun exposure. The cosine and sine values of the phase deflection term are calculated separately. The cosine value is multiplied by the amplitude correction term, and the result is labeled as the first product. The sine value is multiplied by the amplitude correction term, and the result is labeled as the second product. The first product is mapped to the first orthogonal dimension of the preset pure water substrate, and the second product is mapped to the second orthogonal dimension of the preset pure water substrate to perform nonlinear projection mapping. The preset pure water substrate is the static scalar absorption coordinates of pure water components at the characteristic wavelengths of water and ions, completely unaffected by temperature and light fluctuations and salt and alkali stress. An absolutely static physical optical reference origin is established for the multidimensional spatial reconstruction within the feature space, thereby preventing severe masking of weak ion toxicity signals caused by the strong water absorption characteristics within plants at the source. This embodiment measures the purity of high-purity distilled water in a constant-temperature, radiation-free indoor environment. and The initial background absorbance at a given location is used as the preset pure water substrate. Finally, the mapped first and second products are transposed to convert the horizontal one-dimensional row matrix into a vertical structure and encapsulate it into a two-dimensional column vector, obtaining the temperature-light coupled pure water vector. The specific calculation formula is as follows: In the formula, To calculate the temperature-light coupling pure water vector, For phase deflection term, To preset the thermodynamic phase shift constant, For ambient temperature, For amplitude correction, To preset the light scattering attenuation constant, Photosynthetically active radiation intensity, superscript This is the matrix transpose operator.
[0025] The temperature-light coupled pure water vector represents the baseline trajectory of pure water components unaffected by salt and alkali under specific conditions in a two-dimensional orthogonal characteristic space. When its phase angle deflection is extremely large, it indicates that extreme high temperatures cause a drastic change in the hydrogen bond association state of water molecules, leading to a severe thermodynamic frequency shift in the spectral absorption peak. When its geometric modulus is extremely small, it indicates that intense sunlight induced a large amount of stray light interference in the porous medium of the leaf. The ambient temperature, combined with a preset thermodynamic phase shift constant, serves as a sine and cosine operator, driving the vector to rotate within the orthogonal plane to quantify the center wavelength drift caused by heat fluctuations. The photosynthetically active radiation intensity, combined with a preset light scattering attenuation constant, controls negative exponential attenuation, monotonically scaling the absolute amplitude of the orthogonal waveform. This calculation formula constructs an orthogonal triangular projection based on negative exponential attenuation modulation, forcibly increasing the dimensionality of the temperature scalar using the orthogonal properties of trigonometric functions, avoiding signal distortion caused by simple linear addition and subtraction, and further restoring the objective physical limit of diminishing marginal returns in photon scattering loss with increasing radiation using negative exponential operations with a natural constant as the base.
[0026] Step 3: Calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited water interference term, orthogonally remove the excited water interference term from the original feature vector, and extract the pure ion residual vector.
[0027] In this embodiment, the high concentration of water molecules within the plant leaf tissue exhibits extremely strong resonant absorption characteristics for photons in a specific wavelength band, while the distortion signal of inorganic salt ion concentration induced by salt-alkali stress is extremely weak and easily ignored. Furthermore, the water activity within the plant increases non-linearly with the injection of external heat. Therefore, in this embodiment, the original feature vector is transposed, and the transposed original feature vector is multiplied by the temperature-light coupled pure water vector. The result is then multiplied by the temperature-light coupled pure water vector to obtain the inner product projection of the original feature vector onto the temperature-light coupled pure water vector. This projection is used to construct a spatial component whose direction is consistent with the height of the pure water substrate and whose length accurately represents the initial contribution of water in the current mixed spectrum. The specific calculation formula is as follows: In the formula, For inner product projection, The original feature vector, For temperature-light coupled pure water vector, superscript This is the matrix transpose operator.
[0028] The inner product projection characterizes the axial orientation and initial amplitude of the energy contributed purely by the water component within the mixed spectrum. When the inner product projection value is extremely large, it indicates that the plant tissue is in a state of high water content, with water absorption dominating the mixed spectrum; when its value is extremely small, it indicates that the plant is experiencing severe physiological dehydration, with internal water deficit causing significant energy decay in the characteristic absorption band. The transposed original feature vector is multiplied by the temperature-light coupled pure water vector to accurately calculate the projection length of the mixed signal on the pure water axis. This projection is then multiplied by the temperature-light coupled pure water vector to completely reconstruct the baseline component of apparent water. Utilizing the vector inner product projection operator in multidimensional space eliminates the nonlinear signal distortion caused by traditional scalar addition and subtraction.
[0029] The ambient temperature is multiplied by a preset thermodynamic coupling constant, and the result is used as an exponent. An exponential gain value with a base of the natural constant is extracted to construct an exponential penalty term. Since the water absorption intensity in plant tissues exhibits a nonlinear catalytic characteristic with increasing temperature, this embodiment, in a conventional soil environment without salinity or alkalinity interference, steps are taken to change the ambient temperature while simultaneously and continuously reading the water absorption spectrum of healthy plant leaves. The preset thermodynamic coupling constant is obtained by measuring the exponential increase slope of the absorbance in the water overtone band with temperature and performing a two-point comparative derivative calculation. In this embodiment, the preset thermodynamic coupling constant is set as... This is used to establish the underlying mathematical scale for the transformation of thermodynamic fluctuations into optical gain weights.
[0030] The exponential penalty term is multiplied by the inner product projection to construct the stimulated moisture interference term. The inner product projection is then nonlinearly amplified using the exponential penalty term to obtain the total apparent moisture absorption energy amplified by thermodynamic excitation under the current specific meteorological environment. Subsequently, in the vector space, based on the original feature vector, the stimulated moisture interference term is subtracted to perform orthogonal decoupling processing, obtaining the pure ion residual vector. Since the high-frequency spike noise of moisture absorption far exceeds the weak ion solvation signal in amplitude, the dynamic moisture background modulated by temperature and light is completely stripped and erased through asymmetric orthogonal space complement decomposition, thoroughly clearing the non-specific spectral overlap caused by environmental temperature and light fluctuations. The specific calculation formula is as follows: In the formula, For the calculated pure ion residual vector, The original feature vector, For the exponential penalty term, For ambient temperature, To presuppose thermodynamic coupling constants, For inner product projection, For temperature-light coupled pure water vector, superscript This is the matrix transpose operator.
[0031] The pure ion residual vector represents the degree of spectral solvation energy level distortion caused solely by the accumulation of inorganic salt ions in the cell sap after stripping away the background of temperature and light disturbances and water absorption. A very large modulus indicates severely excessive intracellular salt content, placing the plant on the verge of severe ion toxicity; a very small modulus indicates no substantial physicochemical damage from salt. The original eigenvector determines the spatial boundary of absorption intensity and is positively correlated with the dependent variable. The ambient temperature, combined with a preset thermodynamic coupling constant, acts on the exponential end of the natural constant to form an exponential penalty term, which, along with the inner product projection of the transposed original eigenvector and the temperature-light coupled pure water vector, determines the deduction fraction. Higher temperatures cause the exponential penalty term to expand rapidly, forcibly amplifying the negatively deducted stimulated water energy from the original eigenvector. Through asymmetric orthogonal space subtraction, the physical law that rising temperatures exacerbate the apparent artifacts of transpiration water, requiring amplification to eliminate the weights, is restored.
[0032] Step 4: Obtain the spatial characteristic modulus of the pure ion residual vector, construct an optical osmotic pressure scalar based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, perform a nonlinear saturation mapping on the optical osmotic pressure scalar using a logarithmic function, and output a relative toxicity index characterizing the salt-alkali stress state.
[0033] In this embodiment, to transform spatial deviation losslessly into a single quantifiable and gradable criterion, a matrix transpose operation is performed on the pure ion residual vector. The transposed pure ion residual vector is then multiplied by the original vector, and the result is square-rooted to obtain the spatial feature modulus. By obtaining the Euclidean distance of the residual vector in orthogonal space, the aggregation and dedirectionization purification of multidimensional features are achieved.
[0034] When plants suffer from saline-alkali damage, the physiological tolerance and damage behavior within cells are highly dependent on the relative ratio between the salt ion concentration and the available free water background in the cytoplasm. Therefore, in this embodiment, the spatial characteristic modulus is used as the numerator, the absolute value of the inner product projection is summed with a preset minimum zero constant, and the summation result is used as the denominator. The numerator and denominator are then divided to construct the optical osmotic pressure scalar. The specific calculation formula is as follows: In the formula, It is a scalar of optical osmotic pressure. For pure ion residual vectors, The original feature vector, For temperature-light coupling pure water vector, For the preset minimum zero-prevention constant, superscript This is the matrix transpose operator.
[0035] The optical osmotic pressure scalar represents the relative ratio between the total energy of salt ion toxicity in plant cell sap and the available free water background. When its value is extremely high, it indicates that the plant is in a severe state of extreme water scarcity and excessive ion levels, facing irreversible damage to its physiological structure; when its value is extremely low, it indicates that sufficient water is available to dilute trace amounts of salt, and no substantial osmotic pressure stress has occurred. The spatial characteristic modulus, as the numerator, directly determines the absolute basis of toxic energy and is positively correlated with the optical osmotic pressure scalar. The absolute value of the inner product projection, as the denominator, shows a negative correlation as the higher the baseline water content, the more the dependent variable is diluted and lowered. This reflects the plant characteristic that more abundant water dilutes ion toxicity, while less abundant water amplifies ion toxicity. The minimum zero-prevention constant is set by obtaining a value less than or equal to one-tenth of the standard deviation of the inherent background noise of the photoelectric sensor. In this embodiment, the preset minimum zero-prevention constant is set to... This avoids computational crashes caused by the denominator being zero when the absolute value of the inner product projection monotonically approaches zero due to extreme drought and dehydration of plants.
[0036] Plants exhibit a natural diminishing marginal return in their optical response to external abiotic stresses. This embodiment sums the optical osmotic pressure scalar with a numerical value, extracts the natural logarithm of the summation result, and performs a nonlinear saturation mapping to output a relative toxicity index. When saline-alkali damage is in its early or mild stages, the logarithmic function exhibits a very high slope in its low-value range, providing highly sensitive amplification of the weak osmotic pressure scalar. However, when the stress level exceeds the destructive threshold and enters the severe stage, widespread cell tissue damage occurs. The asymptotically smooth characteristic of the logarithmic function performs nonlinear compression on the extremely high-amplification osmotic pressure scalar, forcibly preventing the output value from diverging abruptly. Summing with a numerical value ensures that when the abiotic damage is zero, the output index is strictly aligned to the mathematical zero point. The specific calculation formula for the relative toxicity index is as follows: In the formula, This is the relative toxicity index. It is a scalar of optical osmotic pressure. For pure ion residual vectors, The original feature vector, For temperature-light coupling pure water vector, For the preset minimum zero-prevention constant, superscript This is the matrix transpose operator.
[0037] The relative toxicity index characterizes the absolute damage level caused by saline-alkali infestation to the physiological structure of plants after weather disturbances. A very high value indicates widespread damage to cell tissues, signifying that the plant has crossed the destructive threshold and entered a severely toxic stage. A very low value, approaching zero, indicates that the plant is in a healthy, stress-free state. The optical osmotic pressure scalar, acting as the damage driver, exhibits a non-linear positive correlation with the relative toxicity index; that is, as the optical osmotic pressure scalar increases, the relative toxicity index rises accordingly, but the rate of increase gradually flattens under the constraint of the natural logarithm operator. The summation with the numerical value serves as the absolute origin anchor term, ensuring that the output aligns with the mathematical zero point when there is no damage. Under mild stress, the logarithmic function exhibits a very high slope in its low interval, producing a highly sensitive amplification gain to the weak optical osmotic pressure scalar. When entering the severely destructive stage and the spectral absorption approaches the physical limit, the asymptotically flattened characteristic of the logarithmic function performs non-linear compression on the high-amplification scalar, forcibly preventing characteristic step divergence.
[0038] Step 5: Perform a difference mapping between the relative toxicity index and the preset agronomic safety threshold to obtain the disaster intensity base, and calculate the physical driving force in combination with the preset execution gain coefficient. Determine the degree of plant salt and alkali stress based on the preset level range to which the physical driving force belongs.
[0039] In this embodiment, various plants naturally possess a certain physiological buffering and tolerance capacity to slightly saline-alkali habitats due to their own vacuolar membrane compartmentalization and ion pump mechanisms. To accurately filter harmless optical fluctuations, this embodiment subtracts a preset agronomical safety threshold from the relative toxicity index to perform difference mapping. The calculation result of the difference mapping is compared with the value of zero, and the maximum value is extracted to obtain the disaster intensity baseline. The preset agronomical safety threshold represents the maximum spectral distortion tolerance of the target plant without substantial yield loss. In this embodiment, the field controlled variable method is used to compare the correlation curves between yield and relative toxicity index over the years, and the index value corresponding to the yield reduction inflection point is extracted as the preset agronomical safety threshold. In this embodiment, the preset agronomical safety threshold is set to 0.15. By extracting the maximum value, harmless spectral differences below the preset agronomical safety threshold are directly cleared to zero, reducing the risk of false alarms caused by benign environmental background fluctuations.
[0040] This embodiment performs a multiplicative coupling operation between the disaster intensity baseline and a preset execution gain coefficient. Through nonlinear amplification and dimensional transformation of the disaster signal, the physical driving quantity is calculated. Specifically, to perform nonlinear amplification and dimensional transformation of the disaster signal, this embodiment obtains the preset execution gain coefficient by dividing the full-load safe driving extreme value of the physical instrument by the ratio of the maximum disaster intensity baseline measured for the plant under local historical extreme stress conditions. This embodiment sets the value of the preset execution gain coefficient to 5.0 to achieve proportional amplification of the optical damage rating.
[0041] Because applying a single intervention to crops with varying degrees of damage can easily lead to a waste of water and fertilizer resources, this embodiment compares the physical driving force with preset level intervals. The preset level intervals include progressively increasing intervals of no stress, mild stress, moderate stress, and severe stress, each interval being defined by a value of zero, a first-level critical point, and a second-level critical point, where the first-level critical point is a value greater than zero and less than the second-level critical point. This embodiment obtains the first-level and second-level critical points by combining historical plant observation records and extracting the historical statistical averages of the physical driving forces corresponding to two apparent nodes: the initial slight chlorosis and yellowing of leaves, and large-scale irreversible wilting and shedding. In this embodiment, the first-level critical point is set to 3.0, and the second-level critical point is set to 7.0. The specific determination logic is as follows: When the physical driving force is equal to zero, it falls into the no-stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the no-stress level. When the physical driving force is greater than zero and less than or equal to the first level critical point, it falls into the mild stress range, and the plant salt and alkali stress level of the monitored plant is determined to be mild stress level. When the physical driving force is greater than the first level critical point and less than or equal to the second level critical point, it falls into the moderate stress range, and the plant salt and alkali stress level of the monitored plant is determined to be the moderate stress level. When the physical driving force exceeds the second-level critical point, it falls into the severe stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the severe stress level.
[0042] Table 1 is an example table of comprehensive data on the cross-level evolution of optical toxicity index distortion and physical driving force of the plant under test at 25 sampling times.
[0043] Table 1: Comprehensive Data Table on the Trans-level Evolution of Optical Toxicity Indicators Distortion and Physical Driving Quantities Table 1 shows the data demonstrating the accuracy of this method in quantifying and delineating the physical intervention boundaries of plant areas under varying degrees of salt-alkali stress under natural weather fluctuations. While the optical osmotic pressure scalars of samples 1-3 and 5 exhibited slight fluctuations with the natural environment (maintaining between 0.108 and 0.162), the relative toxicity index was extremely low due to the lack of a true toxicity accumulation signal. Furthermore, under the filtering of the agronomic safety threshold, the calculated physical driving force was strictly clamped to a minimum value. This reflects the conventional spectral reflectance characteristics of living plants in an undamaged state or under weak natural weather transpiration fluctuations, lacking substantial osmotic pressure imbalances in the physicochemical structure within cells. The optical osmotic pressure scalars of samples 6-18 showed a significant overall increase with localized micro-fluctuations (reaching a maximum of 2.105), while the relative toxicity index smoothly crossed the preset agronomic safety threshold of 0.15 and showed a logarithmic growth trend, with the physical driving force increasing proportionally. This indicates that plasmolysis has begun to occur within plant cells. Although there are slight disturbances from the natural environment (such as local numerical declines at samples 8 and 9), the numerical evolution still shows a smooth progression due to the nonlinear saturation constraint of the natural logarithmic operator. At the severe stress stage, samples 22 to 25 show a nonlinear surge in optical osmotic pressure scalars. Meanwhile, the relative toxicity index does not diverge infinitely under the convergence of the logarithmic function, but stabilizes in a high range, and the final output physical driving quantity is forcibly truncated after reaching the full-load extreme value. The maximum cutoff value is the upper limit of the maximum analog control voltage allowed by the physical instrument; in this embodiment, the maximum cutoff value is 10. This table shows that traditional monitoring methods based on single-spectral absorbance are prone to confusing natural plant water fluctuations with actual salt and alkali toxicity. This scheme filters out meteorological disturbances and pseudo-interference from plant background elasticity through a composite algebraic mapping mechanism.
[0044] Please see Figure 3 The present invention also provides a plant salt stress degree detection device based on near-infrared spectroscopy. This device is used to implement the aforementioned plant salt stress degree detection method based on near-infrared spectroscopy, comprising: The original feature construction module is used to acquire a multi-frame spectral array of the target plant, ambient temperature and photosynthetically active radiation intensity at a preset fixed frequency within a preset time window, perform time-domain smoothing mean processing on the multi-frame spectral array, and extract absorbance signals at water feature wavelength and ion feature wavelength respectively to construct the original feature vector. The temperature-light coupling mapping module is used to construct a phase deflection term based on the ambient temperature and a preset thermodynamic phase shift constant, construct an amplitude correction term by combining the photosynthetically active radiation intensity and a preset light scattering attenuation constant, and perform nonlinear projection mapping on a preset pure water substrate using the phase deflection term and the amplitude correction term to obtain a temperature-light coupling pure water vector characterizing the current environmental characteristics. The moisture interference removal module is used to calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited moisture interference term, orthogonally remove the excited moisture interference term from the original feature vector, and extract the pure ion residual vector. The relative toxicity output module is used to obtain the spatial characteristic modulus of the pure ion residual vector, construct an optical osmotic pressure scalar based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, perform a nonlinear saturation mapping on the optical osmotic pressure scalar using a logarithmic function, and output a relative toxicity index characterizing the salt-alkali stress state. The stress level determination module is used to perform difference mapping between the relative toxicity index and the preset agronomic safety threshold to obtain the disaster intensity base, and calculate the physical driving quantity in combination with the preset execution gain coefficient, and determine the degree of plant salt and alkali stress according to the preset level interval to which the physical driving quantity belongs.
[0045] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.
[0046] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.
[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.
[0048] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.
Claims
1. A method for detecting the degree of salt stress of plants based on near infrared spectroscopy, characterized by, The specific steps include: Within a preset time window, a multi-frame spectral array of the target plant, ambient temperature, and photosynthetically active radiation intensity are acquired at a preset fixed frequency. The multi-frame spectral array is then subjected to time-domain smoothing and mean processing. Absorbance signals at water characteristic wavelengths and ion characteristic wavelengths are extracted to construct the original feature vector. A phase deflection term is constructed based on the ambient temperature and a preset thermodynamic phase shift constant. An amplitude correction term is constructed by combining the photosynthetically active radiation intensity and a preset light scattering attenuation constant. The phase deflection term and the amplitude correction term are used to perform a nonlinear projection mapping on a preset pure water substrate to obtain a temperature-light coupled pure water vector characterizing the current environmental properties. The specific steps for obtaining the temperature-light coupled pure water vector are as follows: The phase deflection term is constructed by multiplying the ambient temperature with a preset thermodynamic phase shift constant. The photosynthetically active radiation intensity is multiplied by a preset light scattering attenuation constant, and the negative of the product is used as the exponent. An exponential attenuation value with the natural constant as the base is extracted to construct an amplitude correction term. Calculate the cosine and sine values of the phase deflection term respectively, multiply the cosine value with the amplitude correction term, and label the result of the multiplication as the first product; multiply the sine value with the amplitude correction term, and label the result of the multiplication as the second product. The first product is mapped to the first orthogonal dimension of the preset pure water substrate, and the second product is mapped to the second orthogonal dimension of the preset pure water substrate to perform nonlinear projection mapping; The mapped first and second products are encapsulated into a two-dimensional column vector through matrix transpose to obtain the temperature-optical coupled pure water vector. The specific calculation formula is as follows: In the formula, is a calculated temperature-light coupling pure water vector, is a preset thermodynamic phase shift constant, is an ambient temperature, is a preset light scattering attenuation constant, is a photosynthetically active radiation intensity, and the superscript is a matrix transpose operator; Calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited water interference term, orthogonally remove the excited water interference term from the original feature vector, and extract the pure ion residual vector. The spatial characteristic modulus of the pure ion residual vector is obtained. Based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, an optical osmotic pressure scalar is constructed. A nonlinear saturated mapping is performed on the optical osmotic pressure scalar using a logarithmic function to output a relative toxicity index characterizing the salt-alkali stress state. The relative toxicity index is mapped to a preset agronomic safety threshold to obtain the disaster intensity base, and the physical driving force is calculated in combination with the preset execution gain coefficient. The degree of plant salt and alkali stress is determined according to the preset level range to which the physical driving force belongs.
2. The method for detecting the degree of salt stress of plants based on near-infrared spectroscopy according to claim 1, characterized in that: The specific steps for acquiring a multi-frame spectral array of the target plant at a preset fixed frequency within a preset time window include: The preset time window is a micro-transient window that traces back a preset time length from the current trigger detection time as the endpoint. The preset time length is a standard statistical period that covers multiple physical tremor cycles of the target plant leaves under natural wind fields. Continuous data acquisition is performed at a preset fixed frequency within the preset time window to generate data containing... A multi-frame spectral array of transient spectral data, wherein It is the product of the preset fixed frequency and the preset time length.
3. The method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to claim 2, characterized in that: The specific steps for constructing the original feature vector are as follows: The multi-frame spectral array The transient spectral data of each frame are summed at the same wavelength coordinates, and the summation result is divided by the total number of frames. A smooth reference spectrum curve was constructed; Locate the water characteristic wavelength corresponding to the absorption characteristics of water molecules and the ion characteristic wavelength corresponding to the salt and alkali distortion characteristics on the smooth reference spectral curve. Extract the first absorbance value at the water characteristic wavelength as the absorbance signal at the water characteristic wavelength, and extract the second absorbance value at the ion characteristic wavelength as the absorbance signal at the ion characteristic wavelength. Encapsulate the first absorbance value and the second absorbance value into a two-dimensional column matrix structure through matrix transpose operation to construct the original feature vector.
4. The method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to claim 1, characterized in that: The specific steps for extracting the pure ion residual vector are as follows: The original feature vector is transposed, and the transposed original feature vector is multiplied by the temperature-light coupled pure water vector. The result is multiplied by the temperature-light coupled pure water vector to obtain the inner product projection of the original feature vector onto the temperature-light coupled pure water vector. The ambient temperature is multiplied by a preset thermodynamic coupling constant, and the result of the multiplication is used as an exponent. An exponential gain value with the natural constant as the base is extracted to construct an exponential penalty term. The exponential penalty term is multiplied by the inner product projection to construct the stimulated moisture interference term. Then, in the vector space, based on the original feature vector, a subtraction operation is performed on the stimulated moisture interference term to perform orthogonal directional processing, obtaining the pure ion residual vector. The specific calculation formula is as follows: In the formula, For the calculated pure ion residual vector, The original feature vector, For ambient temperature, To presuppose thermodynamic coupling constants, For temperature-light coupled pure water vector, superscript This is the matrix transpose operator.
5. The method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to claim 1, characterized in that: The specific steps for outputting the relative toxicity index are as follows: Perform a matrix transpose operation on the pure ion residual vector, and perform a dot product operation between the transposed pure ion residual vector and the original pure ion residual vector. Perform a square root operation on the result of the operation to obtain the spatial characteristic modulus and use the spatial characteristic modulus as the molecule. The absolute value of the inner product projection is summed with a preset minimum zero constant, and the summation result is used as the denominator. The numerator and denominator are then divided to construct the optical osmotic pressure scalar. The optical osmotic pressure scalar is summed with a numerical value, and the natural logarithm of the summation result is extracted to perform a nonlinear saturation mapping, outputting the relative toxicity index. The specific calculation formula is as follows: In the formula, This is the relative toxicity index. For pure ion residual vectors, The original feature vector, For temperature-light coupling pure water vector, For the preset minimum zero-prevention constant, superscript This is the matrix transpose operator.
6. The method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to claim 1, characterized in that: The specific steps for calculating the physical driving force are as follows: The relative toxicity index is subtracted from the preset agronomic safety threshold to perform difference mapping. The calculation result of the difference mapping is compared with the value of zero and the maximum value of the two is extracted to obtain the disaster intensity base. The disaster intensity base number is multiplied and coupled with a preset execution gain coefficient. The physical driving quantity is calculated by nonlinear amplification and dimensional transformation of the disaster signal.
7. The method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to claim 6, characterized in that: The specific steps for determining the degree of salt stress in plants based on the preset level range to which the physical driving force belongs are as follows: The physical driving quantity is compared with a preset level range, which includes a no-stress range, a mild-stress range, a moderate-stress range and a severe-stress range, and each range is defined by a value of zero, a first-level critical point and a second-level critical point, wherein the first-level critical point is a value greater than zero and less than the second-level critical point. When the physical driving force is equal to zero, it falls into the no-stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the no-stress level. When the physical driving force is greater than zero and less than or equal to the first level critical point, it falls into the mild stress range, and the plant salt and alkali stress level of the monitored plant is determined to be mild stress level. When the physical driving force is greater than the first level critical point and less than or equal to the second level critical point, it falls into the moderate stress range, and the plant salt and alkali stress level of the monitored plant is determined to be the moderate stress level. When the physical driving force exceeds the second-level critical point, it falls into the severe stress range, and the plant salt-alkali stress level of the monitored plant is determined to be the severe stress level.
8. A device for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy, used to perform the method for detecting the degree of salt and alkali stress in plants based on near-infrared spectroscopy according to any one of claims 1-7, characterized in that, include: The original feature construction module is used to acquire a multi-frame spectral array of the target plant, ambient temperature and photosynthetically active radiation intensity at a preset fixed frequency within a preset time window, perform time-domain smoothing mean processing on the multi-frame spectral array, and extract absorbance signals at water feature wavelength and ion feature wavelength respectively to construct the original feature vector. The temperature-light coupling mapping module is used to construct a phase deflection term based on the ambient temperature and a preset thermodynamic phase shift constant, construct an amplitude correction term by combining the photosynthetically active radiation intensity and a preset light scattering attenuation constant, and perform nonlinear projection mapping on a preset pure water substrate using the phase deflection term and the amplitude correction term to obtain a temperature-light coupling pure water vector characterizing the current environmental characteristics. The moisture interference removal module is used to calculate the inner product projection of the original feature vector onto the temperature-light coupled pure water vector, construct an exponential penalty term by combining the ambient temperature and the preset thermodynamic coupling constant, use the exponential penalty term to perform nonlinear gain on the inner product projection to generate an excited moisture interference term, orthogonally remove the excited moisture interference term from the original feature vector, and extract the pure ion residual vector. The relative toxicity output module is used to obtain the spatial characteristic modulus of the pure ion residual vector, construct an optical osmotic pressure scalar based on the relative magnitude relationship between the spatial characteristic modulus and the inner product projection, perform a nonlinear saturation mapping on the optical osmotic pressure scalar using a logarithmic function, and output a relative toxicity index characterizing the salt-alkali stress state. The stress level determination module is used to perform difference mapping between the relative toxicity index and the preset agronomic safety threshold to obtain the disaster intensity base, and calculate the physical driving quantity in combination with the preset execution gain coefficient, and determine the degree of plant salt and alkali stress according to the preset level interval to which the physical driving quantity belongs.