Method, device and electronic equipment for evaluating the degree of drought stress of crops
By analyzing the Raman spectral data collected from crop leaf samples, the Raman spectral characteristic peak area of carotenoids and anthocyanins was obtained, and the drought stress index was calculated, which solved the problems of low recognition sensitivity and poor accuracy in the existing technology, and achieved high accuracy identification of the degree of early drought stress in crops.
Patent Information
- Application Number
- CN202411867087.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-18
- Publication Date
- 2025-04-25
- Estimated Expiration
- 2044-12-18
AI Technical Summary
In the prior art, the sensitivity and accuracy of early drought stress recognition of crops are low.
By collecting Raman spectral data of crop leaf samples at multiple points, the area of Raman spectral characteristic peaks of carotenoids and anthocyanins is obtained, and the Raman spectral index of drought stress is calculated to evaluate the degree of drought stress in crops.
It has achieved rapid and sensitive identification of the degree of early drought stress in crops, and improved the accuracy of identification.
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Figure CN119322051B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of crop detection, and in particular to a method, a device and an electronic device for evaluating the degree of drought stress of crops. Background Art
[0002] Drought, as the main abiotic stress factor for crops, has a significant impact on the growth of crops. Under drought stress, crop plants will adapt to the new environment through a series of physiological and morphological adjustments to ensure survival. However, these adaptive changes will delay plant growth, lead to a decrease in yield, and even affect product quality, posing severe challenges to farmers' harvests.
[0003] Therefore, evaluating the early drought stress level of crops is of great significance for taking timely anti-drought measures and ensuring yield. However, traditional manual observation methods consume a lot of manpower and have poor reliability, making it difficult to identify the degree of drought stress in crops. Nowadays, non-destructive testing methods based on phenotypic imaging technology are used in the field of plant stress detection. Although these methods have their own advantages in different application scenarios, their common limitation is that they focus on changes in plants at the morphological and physiological levels, and have low sensitivity and poor accuracy in identifying early drought stress in crops. Summary of the invention
[0004] The invention provides a method, a device and an electronic device for evaluating the degree of drought stress of crops, which are used to solve the problems of low sensitivity and poor accuracy in identifying early drought stress of crops in the prior art.
[0005] The present invention provides a method for evaluating the degree of drought stress of crops, comprising:
[0006] Collect Raman spectral data of crop leaf samples at multiple points;
[0007] According to the Raman spectrum data of each point, a plurality of Raman spectrum peaks of the crop leaf sample at each point are obtained; and from the plurality of Raman spectrum peaks, the Raman spectrum characteristic peaks corresponding to each drought stress marker are obtained; the drought stress markers include carotenoids and anthocyanins;
[0008] Obtaining the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins;
[0009] According to the drought stress Raman spectral indexes at various points, the drought stress degree evaluation result of the crop leaf sample is obtained.
[0010] According to the method for evaluating the degree of drought stress of crops provided by the present invention, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained by the following method:
[0011] Obtain the wavenumber range of the characteristic peak of the Raman spectrum corresponding to each drought stress marker;
[0012] According to the wave number range and the corresponding Raman scattering intensity, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained.
[0013] According to the method for evaluating the degree of drought stress of crops provided by the present invention, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained according to the area of the characteristic peak of the Raman spectrum of carotenoids and the area of the characteristic peak of the Raman spectrum of anthocyanins, including:
[0014] According to the ratio of the area of the characteristic peak of the Raman spectrum of the anthocyanin to the area of the characteristic peak of the Raman spectrum of the carotenoid, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained.
[0015] According to the method for evaluating the degree of drought stress of crops provided by the present invention, the method of obtaining multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point includes:
[0016] Acquire Raman spectrum data within a preset Raman shift range in the Raman spectrum data of each point;
[0017] Within a preset Raman shift range, multiple Raman spectrum peaks of the crop leaf sample at each point are obtained.
[0018] According to the method for evaluating the degree of drought stress of crops provided by the present invention, the Raman spectral data of the crop leaf samples at multiple points are collected by a Raman spectral system.
[0019] The present invention also provides a device for evaluating the degree of drought stress of crops, comprising:
[0020] A data acquisition module is used to collect Raman spectrum data of crop leaf samples at multiple points;
[0021] A data processing module is used to obtain multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point; and obtain Raman spectrum characteristic peaks corresponding to each drought stress marker from the multiple Raman spectrum peaks; the drought stress markers include carotenoids and anthocyanins;
[0022] An index acquisition module, used for obtaining the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins;
[0023] The result acquisition module is used to obtain the drought stress degree evaluation result of the crop leaf sample according to the drought stress Raman spectrum index at each point.
[0024] According to the crop drought stress evaluation device provided by the present invention, the area of the Raman spectrum characteristic peak corresponding to each drought stress marker is obtained by the following method:
[0025] Obtain the wavenumber range of the characteristic peak of the Raman spectrum corresponding to each drought stress marker;
[0026] According to the wave number range and the corresponding Raman scattering intensity, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained.
[0027] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for evaluating the degree of drought stress of crops as described above is implemented.
[0028] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for evaluating the degree of drought stress of crops as described in any one of the above is implemented.
[0029] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for evaluating the degree of drought stress of crops as described in any one of the above is implemented.
[0030] The method, device and electronic device for evaluating the degree of drought stress of crops provided by the present invention obtain the Raman spectrum characteristic peaks corresponding to each drought stress marker in the Raman spectrum data of the crop leaf sample, and obtain the drought stress Raman spectrum index through the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins to characterize the changes of carotenoids and anthocyanins in the crop leaf sample. When the crops are subjected to drought stress, the drought stress Raman spectrum index at each point can change quickly and sensitively, so that a more sensitive and accurate evaluation result of the degree of drought stress of the crops can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0032] Figure 1 It is a structural schematic diagram of the control device and the Raman spectroscopy system provided by the present invention.
[0033] Figure 2 It is a schematic diagram of the structure of the Raman spectroscopy system provided by the present invention.
[0034] Figure 3 It is a schematic diagram of the process of the method for evaluating the degree of drought stress of crops provided by the present invention.
[0035] Figure 4 It is a schematic diagram of the corresponding relationship between Raman scattering intensity and Raman shift provided by the present invention.
[0036] Figure 5 It is a structural schematic diagram of a device for evaluating the degree of drought stress of crops provided by the present invention.
[0037] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION
[0038] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0039] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the descriptions used in this way can be interchanged where appropriate, so that the embodiments can be implemented in a sequence other than that illustrated or described in the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of the steps that appear in the present application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved. The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between units can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical units, or may be distributed in multiple circuit units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present application.
[0040] An embodiment of the present invention provides a Raman spectroscopy system, such as Figure 1 As shown, the control device collects Raman spectroscopy data of crop leaf samples at multiple points by controlling the Raman spectroscopy system.
[0041] The control device in the embodiment of the present invention is used to execute the method for evaluating the degree of drought stress of crops, including but not limited to mobile phones, tablet computers, laptop computers, PDAs, vehicle-mounted electronic devices, wearable devices, ultra-mobile personal computers (UMPC), netbooks or personal digital assistants (PDA), etc.
[0042] The Raman spectroscopy system provided in the embodiments of the present invention is described below.
[0043] like Figure 2As shown, the Raman spectroscopy system includes a crop leaf sample 1, a sliding slot 2, a sample holder 3, a movable platform 4, an x-axis displacement mechanism 4-1, a y-axis displacement mechanism 4-2, a drive motor 5, an optical lens group 6, a dichroic mirror 6-1, a lens group 6-2, a laser 7, and a spectrometer 8. Among them, the control device 9 is used to control the Raman spectroscopy system.
[0044] It should be noted that the Raman spectroscopy system provided in the embodiment of the present invention is used to collect Raman spectroscopy data of crop leaf samples at multiple points, which is not a limitation on the method of obtaining Raman spectroscopy data of crop leaf samples. Raman spectroscopy data can also be obtained through other equipment or mechanical devices.
[0045] Figure 3 A method for evaluating the degree of drought stress of crops provided in an embodiment of the present invention comprises:
[0046] Step S301, collecting Raman spectrum data of crop leaf samples at multiple points.
[0047] In an embodiment of the present invention, taking the crop corn as an example, the Zhengdan 958 corn variety widely used in production and research is selected for cultivation, and crop leaf samples of the corn are collected after normal growth to the three-leaf and one-heart stage. Raman spectral data of the crop leaf samples at multiple points are obtained through Raman spectral data acquisition equipment.
[0048] In a possible implementation, Raman spectral data of crop leaf samples at multiple points are collected by a Raman spectroscopy system.
[0049] Next, combine Figure 2 , the process of collecting Raman spectrum data of crop leaf samples at multiple points in an embodiment of the present invention is specifically described.
[0050] Before collecting spectral data, first adjust the sample holder 3 in the sliding groove 2 to a suitable position according to the leaf size and shape of the crop leaf sample, flatten the crop leaf sample 1 and fix it with the sample holder 3, and then adjust the movable platform 4 to the initial position according to the laser focus position and the sampling point position. The collection device composed of an optical lens group 6, a laser 7, and a spectrometer 8 is used for data collection. The control device 9 controls the driving motor 5 according to the set program to drag the movable platform 4 to move in an "S-shaped path" to cooperate with the collection device in the Raman spectroscopy system to collect the Raman spectral data of the crop leaf sample 1.
[0051] The driving motor 5 is controlled by the control device 9, and the driving motor 5 drags the movable platform 4, so that the crop leaf sample 1 can move in the x-axis and y-axis directions, and move m and n points in the two directions respectively, to collect Raman spectrum data of m×n points.
[0052] When collecting spectra, a collection device is composed of a laser 7, an optical lens group 6, and a spectrometer 8. The excitation light generated by the laser 7 is focused on the crop leaf sample 1 through the optical lens group 6, and the molecules of the crop leaf sample 1 undergo Raman scattering and are collected in the spectrometer 8 through the optical lens group 6. The control device 9 controls the various parts to cooperate with each other, and obtains a p-dimensional Raman spectrum every time it moves to a sampling point, and obtains a total of m×n×p three-dimensional Raman spectrum data. The control device 9 then obtains the data output by the spectrometer and performs subsequent processing steps.
[0053] The following describes the parameters of the Raman spectroscopy system during the acquisition process in the embodiment of the present invention.
[0054] The wavelength of the excitation light was selected to be 532 nm, the laser power was 3.6 mW, the integration time of each sampling point was 1 s, and the number of integrations was 2. For the sampling point array, m=37 and n=61 points were taken in the x-axis and y-axis directions with a fixed step size of 100 μm and 80 μm, respectively, and a total of 2257 points of Raman spectral data were collected in an area of 3.6 mm×4.8 mm.
[0055] Step S302, obtaining multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point; and obtaining the Raman spectrum characteristic peaks corresponding to each drought stress marker from the multiple Raman spectrum peaks; the drought stress markers include carotenoids and anthocyanins.
[0056] Specifically, when crops face drought stress, they will undergo rapid stress responses at the molecular level. Raman spectroscopy can be used to quickly detect drought stress marker molecules in plant tissues. As the degree of drought stress in crops increases, the intensity of the Raman spectrum characteristic peaks of carotenoids in the Raman spectrum of crop leaf samples tends to decrease, while the intensity of the Raman spectrum characteristic peaks of anthocyanins tends to increase. Therefore, using carotenoids and anthocyanins as drought stress markers can quickly and sensitively reflect changes in crop drought stress.
[0057] In a possible implementation, in step S302, multiple Raman spectral peaks of the crop leaf sample at each point are obtained based on the Raman spectral data at each point, including: obtaining Raman spectral data within a preset Raman shift range in the Raman spectral data at each point; obtaining multiple Raman spectral peaks of the crop leaf sample at each point within the preset Raman shift range.
[0058] Specifically, Raman spectral data within a preset Raman shift range that can characterize the composition information of the crop leaf sample is selected from the Raman spectral data. Preferably, the preset Raman shift range may be 400-1800 .
[0059] In the embodiment of the present invention, all 2257 collected Raman spectrum data are batch preprocessed, and 400-1800 Raman spectra with leaf component information are selected. The airPLS method was used for baseline correction. After optimization, the Lambda parameter used to control the smoothness of the generated baseline was set to 60. The Savitzky-Golay filter method was used to smooth the Raman spectral data to improve the signal-to-noise ratio. After optimization, the window points were set to 20 and the polynomial order was set to 5.
[0060] Take one of the representative Raman spectra as an example to show the baseline correction effect. Figure 4 The Raman shifts attributed to carotenoids include 1004, 1156, 1521 There are 3 positions in total, including 539, 630, 674, 731, 875, 1238, 1332, 1596, 1642 for anthocyanins There are 9 positions in total, with 1521 and 539 The Raman spectral characteristic peaks at 400 nm are used to characterize carotenoids and anthocyanins.
[0061] Step S303, obtaining the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins.
[0062] In the embodiment of the present invention, the changes of carotenoids and anthocyanins at each point of the crop leaf sample are characterized by calculating the areas of the characteristic peaks of the Raman spectrum of carotenoids and the characteristic peaks of anthocyanins.
[0063] In a possible implementation, in step S303, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained by:
[0064] The wave number range of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained; and the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained according to the wave number range and the corresponding Raman scattering intensity.
[0065] Specifically, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is determined by the following formula:
[0066]
[0067] is the area of the characteristic peak of Raman spectrum corresponding to each drought stress marker, and It is the wavenumber range of the characteristic peak of Raman spectrum corresponding to each drought stress marker. is the Raman shift The Raman scattering intensity at .
[0068] Through the above method, the area of the Raman spectral characteristic peak corresponding to each drought stress marker is determined, which realizes the quantitative analysis of the degree of drought stress and improves the accuracy of the assessment.
[0069] In a possible implementation manner, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is specifically determined by the following formula:
[0070]
[0071] in, is the area of the characteristic peak of Raman spectrum corresponding to each drought stress marker, is the number of data within the wave number range, The wave number range is The Raman shift of the data is The wave number range is The Raman shift of the data is is the Raman shift The Raman scattering intensity at is the Raman shift The Raman scattering intensity at .
[0072] Through the above method, by calculating the area of the Raman spectrum characteristic peak corresponding to each drought stress marker in an integral manner, the intensity distribution of the Raman spectrum characteristic peak can be more accurately reflected, thereby improving the accuracy of the assessment.
[0073] In a possible implementation, in step S303, the drought stress Raman spectral index of the crop leaf sample at each point is obtained according to the area of the Raman spectral characteristic peak of carotenoids and the area of the Raman spectral characteristic peak of anthocyanins, including: obtaining the drought stress Raman spectral index of the crop leaf sample at each point according to the ratio of the area of the Raman spectral characteristic peak of anthocyanins to the area of the Raman spectral characteristic peak of carotenoids.
[0074] Specifically, the drought stress Raman spectroscopy index at each point is determined by the following formula:
[0075]
[0076] is the Raman spectral index of drought stress at each point, is the area of the characteristic peak of Raman spectrum corresponding to anthocyanin, is the area of the characteristic peak of Raman spectrum corresponding to carotenoids.
[0077] By comparing the area ratios of the characteristic peaks of the Raman spectra of anthocyanins and carotenoids through the above method, the degree of drought stress of crops can be more comprehensively evaluated, avoiding the one-sidedness that may be caused by a single indicator. Ratio analysis can more sensitively capture the physiological changes caused by drought stress, which helps to detect drought stress problems early.
[0078] Step S304, obtaining the drought stress degree evaluation result of the crop leaf sample according to the drought stress Raman spectrum index at each point.
[0079] In an embodiment of the present invention, the drought stress evaluation result of the crop leaf sample can be obtained by calculating the average value of the drought stress Raman spectrum index at each point.
[0080] Specifically, the samples of crop leaves are taken × Point The average value of drought stress was used as the evaluation result , which is used to reflect the different degrees of drought stress of crops. The calculation formula is:
[0081]
[0082] in , are the numbers of the sampling points taken in the x-axis direction and the y-axis direction respectively, For the Line The sampling points of the column value.
[0083] By adopting the above method, the present invention can achieve the following beneficial effects: by obtaining the Raman spectrum characteristic peaks corresponding to each drought stress marker in the Raman spectrum data of the crop leaf sample, and by the area of the Raman spectrum characteristic peak of the carotenoid and the area of the Raman spectrum characteristic peak of the anthocyanin, the drought stress Raman spectrum index is obtained to characterize the changes of carotenoids and anthocyanins in the crop leaf sample. When the crops are subjected to drought stress, the drought stress Raman spectrum index at each point can change quickly and sensitively, thereby obtaining a more sensitive and accurate evaluation result of the drought stress degree of the crops.
[0084] The following is a description of the crop drought stress degree evaluation device provided by the present invention. The crop drought stress degree evaluation device described below and the crop drought stress degree evaluation method described above can be referred to each other.
[0085] Figure 5 A schematic diagram of a device for evaluating the degree of drought stress of crops provided by the present invention includes the following parts:
[0086] The data collection module 510 is used to collect Raman spectrum data of crop leaf samples at multiple points.
[0087] The data processing module 520 is used to obtain multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point; and obtain the Raman spectrum characteristic peaks corresponding to each drought stress marker from the multiple Raman spectrum peaks; the drought stress markers include carotenoids and anthocyanins.
[0088] The index acquisition module 530 is used to obtain the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins.
[0089] The result acquisition module 540 is used to obtain the drought stress degree evaluation result of the crop leaf sample according to the drought stress Raman spectrum index at each point.
[0090] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6 As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communications interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute a method for evaluating the degree of drought stress of crops, including the following steps:
[0091] Collect Raman spectral data of crop leaf samples at multiple points;
[0092] According to the Raman spectrum data of each point, multiple Raman spectrum peaks of the crop leaf sample at each point are obtained; and from the multiple Raman spectrum peaks, the Raman spectrum characteristic peaks corresponding to each drought stress marker are obtained; the drought stress markers include carotenoids and anthocyanins;
[0093] According to the area of the characteristic peak of the Raman spectrum of carotenoids and the area of the characteristic peak of the Raman spectrum of anthocyanins, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained;
[0094] According to the Raman spectral indicators of drought stress at various points, the evaluation results of the drought stress degree of crop leaf samples were obtained.
[0095] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.
[0096] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute a method for evaluating the degree of drought stress of crops provided by the above methods, comprising the following steps:
[0097] Collect Raman spectral data of crop leaf samples at multiple points;
[0098] According to the Raman spectrum data of each point, multiple Raman spectrum peaks of the crop leaf sample at each point are obtained; and from the multiple Raman spectrum peaks, the Raman spectrum characteristic peaks corresponding to each drought stress marker are obtained; the drought stress markers include carotenoids and anthocyanins;
[0099] According to the area of the characteristic peak of the Raman spectrum of carotenoids and the area of the characteristic peak of the Raman spectrum of anthocyanins, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained;
[0100] According to the Raman spectral indicators of drought stress at various points, the evaluation results of the drought stress degree of crop leaf samples were obtained.
[0101] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, a method for evaluating the degree of drought stress of crops provided by the above methods is implemented, comprising the following steps:
[0102] Collect Raman spectral data of crop leaf samples at multiple points;
[0103] According to the Raman spectrum data of each point, multiple Raman spectrum peaks of the crop leaf sample at each point are obtained; and from the multiple Raman spectrum peaks, the Raman spectrum characteristic peaks corresponding to each drought stress marker are obtained; the drought stress markers include carotenoids and anthocyanins;
[0104] According to the area of the characteristic peak of the Raman spectrum of carotenoids and the area of the characteristic peak of the Raman spectrum of anthocyanins, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained;
[0105] According to the Raman spectral indicators of drought stress at various points, the evaluation results of the drought stress degree of crop leaf samples were obtained.
[0106] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.
[0107] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0108] 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 embodiments of the present invention.
Claims
1. A method for evaluating the degree of drought stress of crops, characterized in that: include: Collect Raman spectral data of crop leaf samples at multiple points; According to the Raman spectrum data of each point, a plurality of Raman spectrum peaks of the crop leaf sample at each point are obtained; and from the plurality of Raman spectrum peaks, the Raman spectrum characteristic peaks corresponding to each drought stress marker are obtained; the drought stress markers include carotenoids and anthocyanins; Obtaining the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins; Obtaining a drought stress degree evaluation result of the crop leaf sample according to the drought stress Raman spectral index at each point; The area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained by the following method: Obtain the wavenumber range of the characteristic peak of the Raman spectrum corresponding to each drought stress marker; According to the wave number range and the corresponding Raman scattering intensity, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained; The drought stress Raman spectrum index of the crop leaf sample at each point is obtained according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins, including: According to the ratio of the area of the characteristic peak of the Raman spectrum of the anthocyanin to the area of the characteristic peak of the Raman spectrum of the carotenoid, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained.
2. The method for evaluating the degree of drought stress of crops according to claim 1, characterized in that: The method of obtaining multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point includes: Acquire Raman spectrum data within a preset Raman shift range in the Raman spectrum data of each point; Within a preset Raman shift range, multiple Raman spectrum peaks of the crop leaf sample at each point are obtained.
3. The method for evaluating the degree of drought stress of crops according to any one of claims 1 to 2, characterized in that: The Raman spectral data of the crop leaf samples at multiple points are collected by a Raman spectroscopy system.
4. A device for evaluating the degree of drought stress of crops, characterized in that: include: A data acquisition module is used to collect Raman spectrum data of crop leaf samples at multiple points; A data processing module is used to obtain multiple Raman spectrum peaks of the crop leaf sample at each point according to the Raman spectrum data of each point; and obtain Raman spectrum characteristic peaks corresponding to each drought stress marker from the multiple Raman spectrum peaks; the drought stress markers include carotenoids and anthocyanins; An index acquisition module, used for obtaining the drought stress Raman spectrum index of the crop leaf sample at each point according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins; A result acquisition module, used to obtain the drought stress degree evaluation result of the crop leaf sample according to the drought stress Raman spectrum index at each point; The area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained by the following method: Obtain the wavenumber range of the characteristic peak of the Raman spectrum corresponding to each drought stress marker; According to the wave number range and the corresponding Raman scattering intensity, the area of the characteristic peak of the Raman spectrum corresponding to each drought stress marker is obtained; The drought stress Raman spectrum index of the crop leaf sample at each point is obtained according to the area of the Raman spectrum characteristic peak of carotenoids and the area of the Raman spectrum characteristic peak of anthocyanins, including: According to the ratio of the area of the characteristic peak of the Raman spectrum of the anthocyanin to the area of the characteristic peak of the Raman spectrum of the carotenoid, the drought stress Raman spectrum index of the crop leaf sample at each point is obtained.
5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for evaluating the degree of drought stress of crops according to any one of claims 1 to 3 is implemented.
6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for evaluating the degree of drought stress of crops according to any one of claims 1 to 3 is implemented.
7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for evaluating the degree of drought stress of crops according to any one of claims 1 to 3 is implemented.