Method, system, medium and equipment for determining light energy capturing capability of crops based on spectral analysis under canopy

Abstract

The invention relates to the field of agricultural information, and discloses a crop light energy capturing capability determination method and system based on spectral analysis under canopy, a medium and equipment, and the method comprises the following steps: collecting a direct solar radiation spectrum and a transmission spectrum under the canopy of a crop in a space-time synchronization mode; preprocessing the collected spectral data, analyzing and determining the light energy capturing capability of the crop canopy, and performing accurate quantitative evaluation on the photosynthetic capability of the crop through the light energy capturing capability. According to the invention, the limitation of traditional single-point acquisition can be broken through, and non-destructive and real-time photosynthetic potential monitoring is realized.

Description

Technical Field

[0001] The present invention relates to the field of agricultural information technology, and in particular to a method, system, medium and equipment for measuring the light energy capture capacity of crops based on under-canopy spectral analysis. Background Art

[0002] The light energy capture ability of crops, as the core characterization parameter of photosynthesis, directly determines their material production efficiency and yield formation potential. Traditional crop light energy characteristic measurement technology is mainly achieved through single-point spectral collection above the canopy. This method is limited by natural environmental interference and the complexity of canopy structure, and it is difficult to accurately reflect the true light energy utilization status of crops. Specifically, the spatiotemporal heterogeneity of natural light (such as fluctuations in light intensity during the day and night, and transitions between cloudy and sunny weather) and atmospheric optical properties (dust scattering, water vapor absorption) will cause the light quality and intensity of the incident spectrum on the canopy surface to show significant dynamic changes; at the same time, the three-dimensional structural parameters of the canopy itself (leaf spatial distribution, leaf area index, and population density) further aggravate the multiple reflection and scattering effects of the spectral signal, making it impossible to separate environmental interference from the light energy capture characteristics of the crop itself in the spectral data above a single canopy, resulting in systematic deviations in the measurement results.

[0003] The transmission spectrum below the canopy is the comprehensive signal output after the crop group absorbs, reflects, and transmits incident light. Its spectral characteristics are directly related to the efficiency of light energy interception by the leaf photosynthetic organs and are less affected by external environmental fluctuations. It can more truly reflect the light energy utilization capacity of the crop group. However, current related research focuses on the inversion of single parameters of the spectrum above the canopy (such as vegetation index calculation) or local scene applications (such as chlorophyll content estimation), lacking the coordinated collection and comparative analysis of spectra inside and outside the canopy. In particular, in the field of quantitative measurement of light energy capture capacity, a systematic technical system covering "synchronous collection of spectral data - environmental interference correction - capacity index inversion" has not yet been established, resulting in the inability to accurately measure the crop light energy interception efficiency through quantitative comparison of the canopy transmission spectrum and the incident solar spectrum. Summary of the Invention

[0004] In response to the above problems, the purpose of the present invention is to provide a method, system, medium and equipment for measuring the light energy capture ability of crops based on subcanopy spectral analysis, which can break through the limitations of traditional single-point collection and realize non-destructive, real-time monitoring of photosynthetic potential.

[0005] To achieve the above objectives, in the first aspect, the technical solution adopted by the present invention is: a method for measuring the light energy capture capacity of crops based on spectral analysis under the canopy, which includes: collecting the direct sunlight spectrum and the transmission spectrum under the crop canopy in a time-space synchronous manner; after preprocessing the collected spectral data, analyzing and determining the light energy capture capacity of the crop canopy, and accurately quantitatively evaluating the photosynthetic capacity of the crop based on the light energy capture capacity.

[0006] Furthermore, the direct solar spectrum and the transmission spectrum under the crop canopy are collected in a spatiotemporal synchronous manner, including: The direct solar spectrum data is collected by sensors placed above the crop canopy; The transmission spectrum data under the crop canopy is collected by a collection module arranged under the crop canopy.

[0007] Furthermore, the direct solar spectrum data is collected by sensors placed above the crop canopy, including: The real-time collected direct solar spectrum covers the wavelength range of 230 to 850 nm, with a spectral resolution of 0.2 nm.

[0008] Furthermore, the transmission spectrum data under the crop canopy is collected by a collection module arranged under the crop canopy, including: The collection module is a sensor integrated into a self-propelled field collection vehicle. The field self-propelled field collection vehicle adjusts the height of the sensor to adapt to the canopy of different crops, and moves continuously under the canopy to collect the transmission spectrum under the crop canopy.

[0009] Furthermore, after pre-processing the collected spectral data, the light energy capture capacity of the crop canopy is determined by analysis, including: The pre-processed spectral data is matched with a standard spectral library containing different crop varieties and growth stages to accurately locate the position and intensity differences of absorption and reflection peaks, quantify the spectral response characteristics of crops to the key red, blue and green bands, and generate spectral characteristic curves; Combining the incident spectrum above the canopy and the transmitted spectrum data below, the absorption coefficient and reflection coefficient of the crop for light of wavelengths from 230 to 850 nm are calculated to intuitively reflect the crop's interception efficiency for different light qualities. The light energy capture capacity of the crop canopy is determined based on the interception efficiency and spectral characteristic curve.

[0010] Furthermore, the light energy capture capacity of the crop canopy includes the light energy capture amount, the maximum light energy capture functional period, and the high function duration.

[0011] Furthermore, the photosynthetic capacity of crops can be accurately and quantitatively evaluated through light energy capture capability, including: Light energy capture, the total amount of photosynthetically active radiation intercepted by the canopy per unit time, reflects the efficiency of light energy utilization of the colony; The maximum light energy capture period refers to the duration during which the light energy capture capacity reaches its peak during the crop's entire growth period, which characterizes the high light efficiency and sustained characteristics. High functional duration, the length of time that light energy capture remains above a set peak value, is used to assess the photosynthetic stability of the population.

[0012] In the second aspect, the technical solution adopted by the present invention is: a crop light energy capture ability measurement system based on subcanopy spectral analysis, which is used to implement the above-mentioned crop light energy capture ability measurement method based on subcanopy spectral analysis, which includes: a spectral acquisition module, including a sensor set above the crop canopy and a sensor integrated on a field self-propelled acquisition vehicle that collects data in a time-space synchronous manner; the sensor set above the crop canopy is located at a position directly above the crop without being blocked by external objects to collect direct sunlight spectrum, and the sensor integrated on the field self-propelled acquisition vehicle is located below the crop canopy to collect the transmission spectrum under the canopy; a data processing module, including a preprocessing unit, a spectral analysis unit, a storage unit and an evaluation module; the preprocessing unit is used to remove random spectral data. Noise and outliers are detected to improve the signal-to-noise ratio of spectral data; the spectral analysis unit automatically identifies the characteristics of absorption peaks and reflection peaks, calculates the absorption coefficient and reflection coefficient, and generates a spectral characteristic curve; the storage unit is used to establish a distributed database, classify and store original spectral data, preprocessing results, analysis parameters and historical evaluation records, and support multi-dimensional data retrieval and long-term retrospective analysis; the evaluation module includes an evaluation model unit, a result output unit and a growth status prediction unit; the evaluation model unit constructs a spectral capture capability evaluation model and outputs the crop spectral capture capability evaluation results; the result output unit displays and stores the evaluation results; the growth status prediction unit predicts the growth status of crops in the future based on the spectral capture capability evaluation results and the crop growth model.

[0013] In a third aspect, the technical solution adopted by the present invention is: a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device executes any one of the above methods.

[0014] In a fourth aspect, the technical solution adopted by the present invention is: a computing device, comprising: one or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the above methods.

[0015] The present invention has the following advantages due to the adoption of the above technical solution: 1. This invention can achieve multi-dimensional and precise evaluation: by synchronously collecting spectra above and below the canopy, combined with core parameters such as total light energy capture, maximum functional period, and high functional duration, it breaks through the limitations of traditional single-point measurement and achieves multi-dimensional and precise measurement of crop photosynthetic efficiency, providing scientific quantitative indicators for variety breeding.

[0016] 2. The present invention can realize growth stage identification: by utilizing the differences in spectral characteristics of different growth stages, a standardized discrimination model is constructed to realize non-contact intelligent identification of key growth stages such as seedling stage and jointing stage, providing data support for field management measures (such as irrigation and topdressing).

[0017] 3. The present invention can realize the inversion of physiological parameters: based on the red light / near-infrared spectrum ratio algorithm, it can invert the chlorophyll content and nitrogen nutrition status of leaves in real time, solve the problems of low efficiency and strong hysteresis of traditional manual detection, support variable fertilization decision-making, and improve resource utilization efficiency.

[0018] 4. The present invention can optimize the group structure: by analyzing the group light transmittance and leaf area index through canopy spectroscopy, the rationality of planting density can be quantitatively evaluated to avoid waste of light energy due to overcrowding or idle land resources due to oversparseness, thus helping to build a high-yield group structure.

[0019] 5. This invention can realize the screening of stress-resistant varieties: it analyzes the spectral response characteristics under adverse conditions such as high temperature and drought, quantitatively evaluates the stress resistance of crops, and provides phenotypic data support for the selection and breeding of stress-resistant varieties; at the same time, the spectral measurement results can directly calibrate the parameters of the crop growth model to improve the simulation prediction accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a flow chart of a method for determining crop light energy capture capacity based on under-canopy spectral analysis in an embodiment of the present invention; Figure 2 This is a table showing the proportion of red, green, and blue spectra in the spectrum under the corn canopy under different nitrogen fertilizer treatments in the embodiment of the present invention, showing that as the amount of nitrogen fertilizer increases, the proportion of red, green, and blue under the canopy decreases significantly, reflecting an improvement in light energy utilization efficiency; Figure 3 This is a table showing the proportions of red, green, and blue spectra in the spectrum under the corn canopy at different growth stages under different nitrogen fertilizer treatments in the embodiments of the present invention, revealing the dynamic changes in spectral characteristics from the tasseling stage to the full maturity stage, and providing a basis for growth stage identification. DETAILED DESCRIPTION

[0021] Traditional crop photosynthetic capacity assessment techniques rely on destructive sampling or single-band reflectance measurements, resulting in low accuracy and inability to dynamically monitor crops. Existing spectral techniques primarily focus on canopy reflectance spectra, ignoring the direct role of subcanopy transmission spectra in characterizing light energy utilization. Furthermore, there is a lack of quantitative models for crop light capture efficiency that incorporate the dynamic changes of the full solar spectrum. This invention proposes a method, system, medium, and device for measuring crop light capture capacity based on subcanopy spectral analysis. Using two spectral acquisition devices, the direct solar spectrum and subcanopy transmission spectra are synchronously collected in time and space. After preprocessing, parameters such as light capture amount, maximum capture period, and duration of high function are analyzed to achieve accurate quantitative assessment of crop photosynthetic capacity. The system comprises a sensor module and a self-propelled module. The sensors cover the 230-850nm wavelength range and possess high-resolution and high-frequency acquisition characteristics. This invention establishes a standardized and automated measurement system, providing technical support for crop breeding, cultivation management, and growth model optimization, and promoting the development of agricultural informatization.

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0023] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0024] In one embodiment of the present invention, a method for measuring the light energy capture capacity of crops based on spectral analysis under the canopy is provided, which relates to a technology for measuring the light energy capture capacity of crops. By collaboratively collecting and analyzing spectra inside and outside the canopy, an accurate quantitative assessment of the photosynthetic efficiency of crops is achieved, providing key technical support for smart agriculture. The multi-growing period, high-frequency, and high-precision method for measuring the light energy capture capacity of crops provided in this embodiment is as follows: Figure 1 Specifically, the method includes the following steps: 1) Collect the direct sunlight spectrum and the transmission spectrum under the crop canopy in a spatiotemporal synchronous manner; 2) After preprocessing the collected spectral data, the light energy capture capacity of the crop canopy is analyzed and determined, and the photosynthetic capacity of the crop is accurately quantified based on the light energy capture capacity.

[0025] When in use, the present invention constructs a measurement system that is not affected by environmental interference by designing a synchronous spectral collection device above and below the canopy, combining it with a spectral interception efficiency quantification algorithm, breaking through the limitations of traditional single-point collection and realizing non-destructive, real-time monitoring of photosynthetic potential.

[0026] In step 1) above, two sets of spectral acquisition devices are used to collect data synchronously in time and space during the entire crop growth period: an above-canopy sensor and a below-canopy acquisition module.

[0027] Specifically, the direct sunlight spectrum and the transmission spectrum under the crop canopy are collected in a spatiotemporal synchronous manner, including the following steps: 1.1) Collecting direct solar spectral data through sensors placed above the crop canopy; In this embodiment, the sensor above the canopy is deployed in a position directly above the crop without being blocked by external objects. The direct sunlight spectrum collected in real time covers a wavelength range of 230 to 850 nm, with a spectral resolution of 0.2 nm. Data is collected at least once per second to ensure that an interference-free environmental incident spectrum is obtained.

[0028] 1.2) The transmission spectrum data under the crop canopy is collected by a collection module set below the crop canopy.

[0029] In this embodiment, the transmission spectrum data under the crop canopy is collected by a collection module arranged below the crop canopy. Specifically, the collection module is a sensor integrated on a self-propelled field collection vehicle. The field self-propelled field collection vehicle adjusts the height of the sensor to adapt to the canopy of different crops, and continuously moves below the canopy to collect the transmission spectrum under the crop canopy.

[0030] Transmission spectra can be collected at sampling intervals of 1 to 5 seconds. For example, when collecting data under a corn canopy, a 1-second sampling interval and 5nm spectral resolution can be used to achieve high-resolution monitoring of the dynamic changes in light absorption and reflection at specific wavelengths.

[0031] During spectral data collection in step 1), at least 20 sets of data were collected from each measurement plot, distributed linearly and evenly to ensure coverage of canopy spatial heterogeneity. After collection, the spectral data were preprocessed using filtering algorithms to remove noise and outliers, laying a foundation for high-quality data for subsequent analysis.

[0032] In step 2) above, after pre-processing the collected spectral data, the light energy capture capacity of the crop canopy is analyzed and determined, including the following steps: 2.1.1) Match the preprocessed spectral data against a standard spectral library covering different crop varieties and growth stages (e.g., corn seedling, jointing, and tasseling). Accurately locate the positions and intensity differences of absorption and reflectance peaks, quantify the crop's spectral response characteristics to key red, blue, and green wavelengths, and generate spectral characteristic curves to assess growth at each growth stage and predict yield.

[0033] 2.1.2) Calculate crop absorption of wavelengths from 230 to 850 nm by combining incident light spectrum data from above the canopy with transmitted light spectrum data from below. This provides a visual reflection of crop interception efficiency for different light qualities. Determine the crop canopy's light energy capture capacity based on interception efficiency and spectral characteristic curves.

[0034] In this embodiment, the light energy capture capability of the crop canopy includes the light energy capture amount, the maximum light energy capture function period, and the high function duration.

[0035] In step 2) above, the photosynthetic capacity of crops is accurately and quantitatively evaluated by light energy capture capability, including the following steps: 2.2.1) Light energy capture (TEC), the total amount of photosynthetically active radiation intercepted by the canopy per unit time (control light intensity minus subcanopy light intensity), which reflects the efficiency of light energy utilization of the colony; 2.2.2) Maximum Photoperiod (MCP): The duration of time during which the photoperiod capacity of a crop reaches its peak during its entire growth period, characterizing the persistence of high photoperiod efficiency. 2.2.3) High Functional Duration (HFD) refers to the duration during which light energy capture remains above a set peak value, which is used to assess the photosynthetic stability of the population.

[0036] In one embodiment of the present invention, a system for measuring crop light energy capture capacity based on under-canopy spectral analysis is provided, which is used to implement the crop light energy capture capacity measurement method based on under-canopy spectral analysis described in the above embodiments. In this embodiment, the system includes: The spectrum acquisition module includes a sensor located above the crop canopy and a sensor integrated into a self-propelled field acquisition vehicle, which collect data in a spatiotemporal synchronous manner. The sensor located above the crop canopy is located directly above the crop without any obstruction to collect the direct sunlight spectrum, while the sensor integrated into the self-propelled field acquisition vehicle is located below the crop canopy to collect the subcanopy transmission spectrum. Data processing module, including pre-processing unit, spectrum analysis unit, storage unit and evaluation module; The preprocessing unit is used to remove random noise and outliers in the spectral data and improve the signal-to-noise ratio of the spectral data; The spectrum analysis unit automatically identifies the absorption peak and reflection peak characteristics, calculates the absorption coefficient and reflection coefficient, and generates a spectrum characteristic curve; The storage unit is used to establish a distributed database, classify and store raw spectral data, preprocessing results, analysis parameters and historical evaluation records, and support multi-dimensional data retrieval and long-term retrospective analysis; The evaluation module includes an evaluation model unit, a result output unit and a growth status prediction unit; the evaluation model unit constructs a spectral capture capability evaluation model and outputs the crop spectral capture capability evaluation results; the result output unit displays and stores the evaluation results; the growth status prediction unit predicts the crop's yield, probability of disease and pest occurrence and other growth conditions in the future based on the spectral capture capability evaluation results and combined with the crop growth model, providing a decision-making basis for agricultural production management.

[0037] In the aforementioned embodiment, the spectrum acquisition module utilizes a high-sensitivity spectrum analyzer, and the spectrum analysis equipment utilizes a UV spectrum analyzer. This analyzer integrates measurement functions for spectrum, illuminance, color temperature, color rendering index, effective radiance (PAR), PPFD, YPFD, chlorophyll A, chlorophyll B, UV irradiance, UVA, UVB, UVC, R9, wavelength, irradiance, color coordinates, and color tolerance. The spectrum measurement range is (230-850) nm, with a wavelength accuracy of ±0.5 nm, an integration time of 0.1 ms to 10 s, and a stray light tolerance of <0.3%. The illuminance measurement range is 5-200,000 lx, the color temperature measurement range is 1000-100,000 K, and the PPFD measurement range is 0.1 μmol / m² / s to 6000 μmol / m² / s (without flicker). The device utilizes CCD technology with automatic zero calibration and temperature compensation to ensure accurate incident spectrum acquisition. Regarding data transmission components, the device is equipped with a USB port for data transfer between the host and host computer, as well as an SD card data output port. Powered by a lithium battery, the device can operate continuously for over 12 hours. It also has 8GB or more of built-in memory for data storage. Measuring 138×81×23mm, it is easy to carry and operate, and can efficiently transmit collected data for subsequent data processing.

[0038] In the above embodiment, the preprocessing unit preprocesses the spectral data using algorithms such as wavelet denoising and sliding average filtering.

[0039] In the above embodiment, the spectrum analysis unit automatically identifies the absorption peak and reflection peak characteristics based on the standard spectrum library matching algorithm, calculates key parameters such as the absorption coefficient and reflection coefficient, and generates a spectrum characteristic curve (such as Figure 2 The proportion of red, green and blue spectra in the spectrum under the corn canopy under different nitrogen fertilizer treatments is shown).

[0040] In the above embodiment, the direct sunlight spectrum and the transmission spectrum under the crop canopy are collected in a spatiotemporal synchronization manner, including: The direct solar spectrum data is collected by sensors placed above the crop canopy; The transmission spectrum data under the crop canopy is collected by a collection module arranged under the crop canopy.

[0041] In the above embodiment, the direct solar spectrum data is collected by a sensor disposed above the crop canopy, including: The real-time collected direct solar spectrum covers the wavelength range of 230 to 850 nm, with a spectral resolution of 0.2 nm.

[0042] In the above embodiment, the transmission spectrum data under the crop canopy is collected by a collection module disposed under the crop canopy, including: The collection module is a sensor integrated into a self-propelled field collection vehicle. The field self-propelled field collection vehicle adjusts the height of the sensor to adapt to the canopy of different crops, and moves continuously under the canopy to collect the transmission spectrum under the crop canopy.

[0043] In this example, a field collection vehicle, equipped with a height-adjustable sensor bracket, supports a constant speed of 0.1 to 0.5 m / s, ensuring a uniform sampling trajectory below the canopy. Sensor parameters are consistent with those above the canopy, enabling the simultaneous collection of spectral data above and below in both time and space.

[0044] In the above embodiment, after pre-processing the collected spectral data, analyzing and determining the light energy capture capacity of the crop canopy includes: The pre-processed spectral data is matched with a standard spectral library containing different crop varieties and growth stages to accurately locate the position and intensity differences of absorption and reflection peaks, quantify the spectral response characteristics of crops to the key red, blue and green bands, and generate spectral characteristic curves; Combining the incident spectrum above the canopy and the transmitted spectrum data below, the absorption coefficient and reflection coefficient of the crop for light of wavelengths from 230 to 850 nm are calculated to intuitively reflect the crop's interception efficiency for different light qualities. The light energy capture capacity of the crop canopy is determined based on the interception efficiency and spectral characteristic curve.

[0045] In the above embodiment, the light energy capture capability of the crop canopy includes the light energy capture amount, the maximum light energy capture function period, and the high function duration.

[0046] In the above embodiment, the photosynthetic capacity of crops is accurately and quantitatively evaluated by light energy capture capability, including: Light energy capture, the total amount of photosynthetically active radiation intercepted by the canopy per unit time, reflects the efficiency of light energy utilization of the colony; The maximum light energy capture period refers to the duration during which the light energy capture capacity reaches its peak during the crop's entire growth period, which characterizes the high light efficiency and sustained characteristics. High functional duration, the length of time that light energy capture remains above a set peak value, is used to assess the photosynthetic stability of the population.

[0047] The system provided in this embodiment is used to execute the above-mentioned method embodiments. Please refer to the above-mentioned embodiments for specific processes and detailed contents, which will not be repeated here.

[0048] The present invention is further illustrated using an experiment using nitrogen fertilizer in corn as an example. The corn variety used was Zhengdan 958. The experimental design included three replicates, four plots of 5-meter rows, 60-cm row spacing, and 25-cm plant spacing. Nitrogen fertilizer treatments included four nitrogen fertilizer gradients: 0 kg N / ha (no nitrogen), 120 kg N / ha (40% nitrogen reduction), 200 kg N / ha (normal nitrogen), and 280 kg N / ha (40% high nitrogen).

[0049] Data collection: The field collection vehicle moves at a speed of 0.1m / s, and it takes about 50s to pass through the row. The sensor collects data once per second, that is, 50 sets of data can be collected for each material each time. After excluding the 5 sets of data at the two ends, 40 sets of data are obtained.

[0050] Result analysis: (1) If Figure 2 As shown in the figure, the proportions of red, green and blue under the corn canopy were significantly different under different nitrogen fertilizer treatments, all lower than the direct sunlight spectrum (blank control 0.63), and decreased with the increase of nitrogen fertilizer amount, indicating that nitrogen fertilizer application promoted plant growth and improved light energy interception efficiency.

[0051] (2) If Figure 3 As shown, from the tasting stage to the full maturity stage, the proportion of red, green and blue in the no nitrogen treatment (000N) first decreased and then increased, reflecting the late aging process; the normal nitrogen treatment (200N) continued to decline, indicating that the high light efficiency lasted longer, which was consistent with the field yield performance.

[0052] In one embodiment of the present invention, a computing device is provided. The computing device may be a terminal and may include: a processor, a communications interface, a memory, a display screen, and an input device. The processor, communications interface, and memory communicate with each other via a communications bus. The processor is configured to provide computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. When executed by the processor, the computer program implements the methods described in the above embodiments. The internal memory provides an environment for the operating system and computer program in the non-volatile storage medium to run. The communications interface is configured to communicate with an external terminal via wired or wireless communication. The wireless communication may be achieved via Wi-Fi, a network management service provider, NFC (near field communication), or other technologies. The display screen may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen layer covering the display screen, or may be buttons, a trackball, or a touchpad provided on the computing device housing, or may be an external keyboard, touchpad, or mouse. The processor may invoke logic instructions stored in the memory.

[0053] In addition, the logical instructions in the above-mentioned memory can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0054] In one embodiment of the present invention, a computer program product is provided, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided by the above-mentioned method embodiments.

[0055] In one embodiment of the present invention, a non-transitory computer-readable storage medium is provided. The non-transitory computer-readable storage medium stores server instructions. The computer instructions enable a computer to execute the methods provided in the above embodiments.

[0056] The above embodiment provides a computer-readable storage medium, whose implementation principle and technical effects are similar to those of the above method embodiment, and will not be repeated here.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for determining crop light energy capture capacity based on under-canopy spectral analysis, characterized in that: include: The direct sunlight spectrum and the transmission spectrum under the crop canopy are collected in a spatiotemporal synchronous manner; After preprocessing the collected spectral data, the light energy capture capacity of the crop canopy is analyzed and determined, and the photosynthetic capacity of the crop is accurately quantitatively evaluated based on the light energy capture capacity.

2. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 1, wherein: The direct solar spectrum and the transmittance spectrum under the crop canopy are collected in a spatiotemporally synchronized manner, including: The direct solar spectrum data is collected by sensors placed above the crop canopy; The transmission spectrum data under the crop canopy is collected by a collection module arranged under the crop canopy.

3. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 2, wherein: The sensor is placed above the crop canopy to collect direct solar spectral data, including: The real-time collected direct solar spectrum covers the wavelength range of 230 to 850 nm, with a spectral resolution of 0.2 nm.

4. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 2, wherein: The transmission spectrum data under the crop canopy is collected by a collection module set under the crop canopy, including: The collection module is a sensor integrated into a self-propelled field collection vehicle. The field self-propelled field collection vehicle adjusts the height of the sensor to adapt to the canopy of different crops, and moves continuously under the canopy to collect the transmission spectrum under the crop canopy.

5. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 1, wherein: After pre-processing the collected spectral data, the light energy capture capacity of the crop canopy is determined by analysis, including: The pre-processed spectral data is matched with a standard spectral library containing different crop varieties and growth stages to accurately locate the position and intensity differences of absorption and reflection peaks, quantify the spectral response characteristics of crops to the key red, blue and green bands, and generate spectral characteristic curves; Combining the incident spectrum above the canopy and the transmitted spectrum data below, the absorption coefficient and reflection coefficient of the crop for light of wavelengths from 230 to 850 nm are calculated to intuitively reflect the crop's interception efficiency for different light qualities. The light energy capture capacity of the crop canopy is determined based on the interception efficiency and spectral characteristic curve.

6. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 5, characterized in that: The light energy capture capacity of crop canopies includes the amount of light energy captured, the maximum light energy capture functional period, and the duration of high function.

7. The method for determining crop light energy capture capacity based on under-canopy spectral analysis according to claim 6, wherein: Accurately quantify crop photosynthetic capacity through light energy capture capability, including: Light energy capture, the total amount of photosynthetically active radiation intercepted by the canopy per unit time, reflects the efficiency of light energy utilization of the colony; The maximum light energy capture period refers to the duration during which the light energy capture capacity reaches its peak during the crop's entire growth period, which characterizes the high light efficiency and sustained characteristics. High functional duration, the length of time that light energy capture remains above a set peak value, is used to assess the photosynthetic stability of the population.

8. A system for measuring crop light energy capture capacity based on under-canopy spectral analysis, for implementing the method for measuring crop light energy capture capacity based on under-canopy spectral analysis as claimed in any one of claims 1 to 7, characterized in that: include: Spectral acquisition module, including sensors set above the crop canopy and integrated on a self-propelled field acquisition vehicle that collect data in a spatiotemporal synchronous manner; The sensor installed above the crop canopy is located directly above the crop without any obstruction to collect the direct sunlight spectrum. The sensor integrated into the field self-propelled collection vehicle is located below the crop canopy to collect the transmission spectrum under the canopy. Data processing module, including pre-processing unit, spectrum analysis unit, storage unit and evaluation module; The preprocessing unit is used to remove random noise and outliers in the spectral data and improve the signal-to-noise ratio of the spectral data; The spectrum analysis unit automatically identifies the absorption peak and reflection peak characteristics, calculates the absorption coefficient and reflection coefficient, and generates a spectrum characteristic curve; The storage unit is used to establish a distributed database, classify and store raw spectral data, preprocessing results, analysis parameters and historical evaluation records, and support multi-dimensional data retrieval and long-term retrospective analysis; The evaluation module includes an evaluation model unit, a result output unit and a growth status prediction unit; the evaluation model unit constructs a spectral capture capability evaluation model and outputs the crop spectral capture capability evaluation results; the result output unit displays and stores the evaluation results; the growth status prediction unit predicts the growth status of crops in the future based on the spectral capture capability evaluation results and the crop growth model.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any one of the methods of claims 1 to 7 .

10. A computing device, characterized in that include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any one of the methods according to claims 1 to 7.

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