Tobacco raw material spectrogram data management method and system and storage medium

Abstract

The invention provides a tobacco leaf raw material spectrogram data management method and system and a storage medium. The tobacco leaf raw material spectrogram data management method comprises the steps of S1, obtaining initial spectrogram data of tobacco leaf raw materials; s2, classifying and managing the initial spectrogram data according to preset spectrogram data types to obtain target spectrogram data; and S3, performing data analysis processing on the target spectrogram data to generate an analysis result corresponding to the tobacco leaf raw material. The invention aims to provide core technical support for design and implementation of a tobacco scientific research big data management system. According to the method, spectrogram sources and formats are investigated, spectrogram data are classified, deep analysis mining is performed according to the classified spectrogram data in combination with multiple chemometrics algorithms, a foundation is laid for centralized storage, efficient retrieval, unified management and safe sharing of the spectrogram data and other scientific research data, the tobacco scientific research efficiency can be improved, and the tobacco scientific research efficiency can be improved. And powerful support is provided for industry scientific and technological innovation and decision making.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of tobacco raw material management analysis, and particularly relates to a tobacco raw material spectrum data management method, a tobacco raw material spectrum data management system and a storage medium. BACKGROUND

[0002] Tobacco scientific research data covers a wide range, has a complex structure, is closely related, and is distributed in multiple links such as agriculture (such as tobacco leaf harvesting, conditioning, and quality evaluation), industry (such as formula design, use of flavorings, spices and additives, and finished product testing), and commerce (such as brand development and authenticity identification). The data is derived from production practice, experimental research, observation records and statistical surveys, and also includes a large amount of unstructured data (such as images and instrument spectrum data), and with the application of new technologies such as the Internet of Things, the scale of unstructured data continues to expand. At present, tobacco scientific research big data still has the following outstanding problems in resource management:

[0003] (1) The standardization system is not perfect, and a unified data standard and specification have not been established, which restricts the standardized management and effective sharing of data;

[0004] (2) The degree of data fusion is low, the existing information systems are scattered, the data sources are diverse, the time span is large, the completeness is uneven, there is a lack of coordination and exchange mechanism between platforms, and there are obstacles to resource integration;

[0005] (3) The whole-process data management is missing, and part of the enterprises do not systematically collect and save the intermediate data in the research and development process, which is not conducive to comprehensive analysis and reuse;

[0006] (4) The management capability is uneven, only a few enterprises have built unified data centers and realized internal sharing, a large amount of data is still stored in a scattered form in project groups or individuals, intensive management has not been formed, and the value of data has not been fully tapped;

[0007] (5) The data analysis capability is limited, the existing system function is relatively simple, and basic query is mainly used, lacking depth mining and analysis capability, and it is difficult to form a strong support for actual production and operation.

[0008] Among them, the multi-source and massive spectrum data generated by precise instruments such as mass spectrometry, chromatography and spectroscopy, as a core category of scientific research data, faces significant bottlenecks in integrated management and sharing application. SUMMARY

[0009] Therefore, the application aims to provide a tobacco raw material spectrum data management method, a tobacco raw material spectrum data management system and a storage medium to solve the above problems.

[0010] To solve the above technical problems, the application adopts the following technical solutions:

[0011] In a first aspect, the present application provides a tobacco raw material spectrum data management method, which comprises:

[0012] Step S1: obtaining initial spectrum data of the tobacco raw material;

[0013] Step S2: classifying and managing the initial spectrum data according to a preset spectrum data type to obtain target spectrum data;

[0014] Step S3: performing data analysis and processing on the target spectrum data to generate an analysis result corresponding to the tobacco raw material.

[0015] Further, step S1 comprises: step S11: obtaining an initial spectrum association file of the tobacco raw material;

[0016] Step S12: performing data verification on the initial spectrum association file to obtain target spectrum association file;

[0017] Step S13: analyzing the target spectrum association file to obtain the initial spectrum data.

[0018] Further, step S12 comprises: step S121: performing integrity check on the initial spectrum association file;

[0019] Step S122: when it is determined that the integrity check result of the initial spectrum association file meets a preset result, performing accuracy check on the initial spectrum association file;

[0020] Step S123: determining whether the check result of the accuracy check of the initial spectrum association file meets a preset result: if yes, determining the initial spectrum association file as the target spectrum association file.

[0021] Further, step S12 further comprises: step S124: visually displaying and statistically analyzing the spectrum information of the target spectrum association file.

[0022] Further, the spectrum data type comprises chromatographic data, mass spectrometric data, spectral data and physicochemical data.

[0023] Further, step S3 comprises: step S31: performing correction processing on the target spectrum data;

[0024] Step S32: performing data analysis on the corrected target spectrum data based on a chemometric algorithm to generate an analysis result corresponding to the tobacco raw material.

[0025] In a second aspect, the present application provides a tobacco raw material spectrum data management system, which comprises: a data acquisition module, a data management module and a data analysis module,

[0026] The data acquisition module is configured to acquire initial spectrum data of the tobacco raw material;

[0027] The data management module is configured to classify and manage the initial spectrum data according to a preset spectrum data type to obtain target spectrum data.

[0028] The data analysis module is configured to perform data analysis on the target spectrum data to generate an analysis result corresponding to the tobacco raw material.

[0029] In a third aspect, the present application provides a computer system comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the tobacco raw material spectrum data management method.

[0030] In a fourth aspect, the present application provides a computer readable storage medium having a computer program / instruction stored thereon, wherein the computer program / instruction is executed by a processor to implement the steps of the tobacco raw material spectrum data management method.

[0031] In a fifth aspect, the present application provides a computer program product comprising a computer program / instruction, wherein the computer program / instruction is executed by a processor to implement the steps of the tobacco raw material spectrum data management method.

[0032] According to the above technical solution, the tobacco raw material spectrum data management method, the tobacco raw material spectrum data management system and the storage medium provided by the present application have the following advantages and positive effects:

[0033] The present application aims to provide core technical support for the design and implementation of a tobacco scientific research big data management system. By researching the sources and formats of spectra, classifying spectrum data, and performing deep analysis and mining on the classified spectrum data using various chemometrics algorithms, the present application realizes the centralized storage, efficient retrieval, unified management and safe sharing of spectrum data and other scientific research data, which helps to improve the efficiency of tobacco scientific research and provides strong support for industry scientific and technological innovation and decision-making. BRIEF DESCRIPTION OF DRAWINGS

[0034] The above content of the present application and the following detailed description will be better understood when read in conjunction with the accompanying drawings. It should be noted that the drawings are only examples of the claimed technical solutions.

[0035] Figure 1 is a flowchart of the tobacco raw material spectrum data management method of the present application;

[0036] Figure 2 is a data verification flowchart of the present application;

[0037] Figure 3 is a data upload success page of the present application;

[0038] Figure 4 is a data quality evaluation page of the present application;

[0039] Figure 5 is a data storage evaluation page of the present application;

[0040] Figure 6 is a chromatogram database page of the present application;

[0041] Figure 7 is a sample chromatogram list page of the present application;

[0042] Figure 8 is a data analysis home page of the present application;

[0043] Figure 9 is a data analysis spectrum selection page of the present application;

[0044] Figure 10 is a data analysis spectrum correction page of the present application;

[0045] Figure 11 is a data analysis statistical result page of the present application. DETAILED DESCRIPTION

[0046] The specific features and advantages of the present application will be described in detail in the detailed description of the present application, which is sufficient for any person skilled in the art to understand the technical content of the present application and to implement it, and the person skilled in the art can easily understand the related purposes and advantages of the present application according to the description, claims and drawings disclosed in the specification.

[0047] The present application will now be described with reference to the drawings, in which like reference numerals refer to like elements. Although specific structures and arrangements are discussed, it should be understood that this is done for illustrative purposes only. A person skilled in the art will recognize that other structures and arrangements can be used without departing from the spirit and scope of the present application. It will be apparent to those skilled in the art that the present application can also be used in a variety of other applications.

[0048] In the present specification and claims, a plurality of terms will be mentioned, unless otherwise indicated, these terms will be defined as having the following meanings:

[0049] The singular forms "a" and "the" include the corresponding plural forms. "At least one" means one or more, "a plurality of" means two or more. "At least one of the following" or the like means any combination of the items, including any combination of single items or multiple items. For example, at least one of a, b or c can mean a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, c can be single or multiple.

[0050] All figures used to represent component amounts, properties (e.g., molecular weight), reaction conditions, etc., should be considered to be modified in all cases by the terms "within the unavoidable margin of error" or "about". Therefore, the numerical values ​​set forth herein are approximate and may vary depending on the desired properties sought to be obtained by the present invention. The principle of equivalents, which is applied to a minimum and not intended to limit the scope of the claims, should be applied, for example, each value should be interpreted at least according to the specified significant digits and by applying conventional rounding techniques.

[0051] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0052] In the description of this embodiment, it should be noted that the terms "upper", "lower", "inner", "bottom", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product is usually placed during use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0053] Unless otherwise indicated, the following abbreviations have the following meanings, and any other abbreviations used herein but not defined have their generally accepted standard meanings:

[0054] All other terms used herein that are specifically defined herein shall have the general meaning understood by one of ordinary skill in the art, in particular meaning that, upon reading the claims, specification and drawings of this patent, one can directly and without doubt determine how the technical solution of this patent can be implemented.

[0055] Even if there are incomplete descriptions, omissions, or ambiguities in the grammar, words, punctuation, graphics, symbols, etc. of the claims, specification, and drawings of this patent, a person skilled in the art can still arrive at the only correct understanding by reading the claims, specification, and drawings as a whole without extensive reasoning or experimentation, and effectively exclude various incorrect interpretations that are not aimed at achieving the purpose of this patent.

[0056] Those skilled in the art would first choose to read the claims, specification, and drawings of this patent to reasonably interpret the terms; secondly, they would choose to refer to the relevant definitions in other documents published by the applicant before the filing date to reasonably interpret the terms; thirdly, they would choose the references cited in this patent to reasonably interpret the terms; and finally, they would choose to combine the technical dictionaries, technical manuals, reference books, textbooks, national or industry technical standards, etc., commonly used by those skilled in the art to reasonably interpret the terms.

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0058] Please refer to Figure 1 This application provides a method for managing spectral data of tobacco raw materials. The specific steps of this method are as follows:

[0059] Step S1: Obtain the initial spectral data of tobacco raw materials.

[0060] Step S1 includes:

[0061] Step S11: Obtain the initial spectral association file of the tobacco raw material.

[0062] Step S12: Perform data verification on the initial spectrum association file to obtain the target spectrum association file.

[0063] Step S12 includes:

[0064] Step S121: Perform an integrity check on the initial spectrum association file.

[0065] Step S122: When the integrity check result of the initial spectrum association file is determined to be consistent with the preset result, the accuracy check of the initial spectrum association file is performed.

[0066] Step S123: Determine whether the accuracy check result of the initial spectrum association file meets the preset result:

[0067] If so, the initial spectrum association file will be determined as the target spectrum association file.

[0068] If not, the corresponding error message will be mapped according to the pre-set error code mapping table and a prompt will be displayed to remind the user to check.

[0069] Preferably, the initial spectrum association file can be checked for completeness first, and then the initial spectrum association file can be checked for accuracy.

[0070] When the integrity check results show an error, a prompt can be issued to the user to terminate the accuracy check of the initial spectrum association file, thereby improving the processing speed of data verification of the initial spectrum association file.

[0071] If both the integrity check and the accuracy check result are correct, then the initial spectrum association file is determined as the target spectrum association file.

[0072] Step S124: Visualize and statistically analyze the spectral information of the target spectrum associated file.

[0073] Specifically, please refer to Figure 2 Users can selectively upload one or more compressed (zip format) files by clicking the "Upload File" button and then click "OK" to complete the data upload.

[0074] The system performs an integrity check on the uploaded data file. If any data file is found to be missing, the upload will fail, and the system will prompt that the data file is missing, requiring the user to verify and re-upload it.

[0075] If no data files are missing, the upload is successful, and the next step, accuracy checking, will proceed. The uploaded data undergoes an accuracy check, which is displayed in the "File List," and the parsing accuracy is updated in real time. The "File List" section shows the quality assessment results of the accuracy verification.

[0076] Users can click "View Details" on the corresponding file, and the system will display the evaluation results of all samples under that file in a table. Additionally, users can click "View Report" on the corresponding file to view its quality evaluation report. Finally, the initial spectrum association files that pass the accuracy check are determined as the target spectrum association files and stored in the database.

[0077] Please refer to Figure 3 Click the "View Sample Details" button for the corresponding file to navigate to the sample details page in that folder. The sample details page displays the evaluation results for all samples in the current file in a list format, with quick search functionality at the top of the list. Click the "View Report" button for the corresponding file to navigate to the sample report page in that folder.

[0078] Please refer to Figure 4 and Figure 5The quality evaluation page displays a visual statistical analysis of the chromatographic, mass spectrometric, spectral, and routine physicochemical data entered into the database. It supports quick retrieval of the entered data, and users can customize searches based on upload date, test item, and data source. The search list displays the corresponding sample code, test item, uploader, upload time, and quality evaluation results. The operation area allows users to view the original records, assessment details, and download the corresponding quality assessment report.

[0079] The data quality evaluation page displays the evaluation results for all user-uploaded data. Users can quickly search by testing item, data source, task origin, etc. The spectral library system's quality evaluation is based on rules generated according to data quality standards to check the quality of uploaded data, providing a quality evaluation report that assesses and evaluates quality indicators such as data completeness and accuracy.

[0080] Step S13: Parse the target spectrum association file to obtain the initial spectrum data.

[0081] Step S2: Classify and manage the initial spectral data according to the preset spectral data types to obtain the target spectral data.

[0082] The types of spectral data include chromatographic data, mass spectrometry data, spectral data, and physicochemical data.

[0083] Please refer to Figure 6 Taking chromatographic data as an example, the initial page of the chromatographic database under spectral management is shown below. The data displayed in the list on the left side of the initial page is the most recently added chromatographic data by default. Quick search is supported above the list. Users can quickly search by selecting the detection item, detection date, and task source in the search area. The upper right part of the page displays a thumbnail of the selected sample's chromatogram, and the lower right part displays the qualitative and quantitative results of the selected sample, as well as the molecular structure formula, Chinese and English names, and CAS number of the corresponding compound.

[0084] Clicking the "+" to the left of each sample code will display a drop-down list of all spectra for the selected sample. The upper right corner of the page defaults to the spectrum of the first selected sample. The page looks like this. Figure 7 As shown.

[0085] Step S3: Perform data analysis and processing on the target spectral data to generate analysis results corresponding to the tobacco raw materials.

[0086] Step S3 includes:

[0087] Step S31: Correct the target spectral data.

[0088] Step S32: Perform data analysis on the corrected target spectral data based on chemometric algorithms to generate analysis results corresponding to tobacco raw materials.

[0089] For details, please refer to Figures 8-11 .

[0090] Data analysis can be divided into four processes: spectrum selection → spectrum grouping → spectrum correction → data analysis.

[0091] Taking chromatographic data analysis as an example, users can select the corresponding sample according to the purpose of analysis, create the group, and then proceed to the spectral calibration step.

[0092] The selected samples will automatically undergo retention time adjustments, and the system supports preprocessing of spectra such as cropping, SG smoothing, and baseline correction. The system provides various chemometric algorithms, including principal component analysis, cluster heatmaps, partial least squares, and similarity analysis, for qualitative and quantitative analysis of tobacco data. It supports data manipulation to obtain better model analysis results and allows downloading of visualizations and analysis reports.

[0093] The system maintenance section includes document management, online help, and log recording. The document management page displays blank templates for testing projects, quality assessment forms, and other documents. Users can quickly search and download selected files on this page. The online help function provides real-time assistance tools for users (including system administrators, maintenance personnel, and general operators), aiming to resolve operational questions, troubleshooting, and process standardization issues encountered during system use. Its core objective is to improve maintenance efficiency and reduce operational risks.

[0094] Based on the same inventive concept, this application also provides a tobacco raw material spectrum data management system, which includes: a data acquisition module, a data management module, and a data analysis module.

[0095] The data acquisition module is used to obtain the initial spectral data of tobacco raw materials.

[0096] The data management module is used to classify and manage the initial spectral data according to the preset spectral data types to obtain the target spectral data.

[0097] The data analysis module is used to perform data analysis and processing on the target spectral data and generate analysis results corresponding to the tobacco raw materials.

[0098] Furthermore, the data acquisition module is also used to obtain the initial spectral association file of the tobacco raw material; to perform format verification on the initial spectral association file to obtain the target spectral association file; and to parse the target spectral association file to obtain the initial spectral data.

[0099] Furthermore, the data acquisition module is also used to perform an integrity check on the initial spectrum association file; when it is determined that the integrity check result of the initial spectrum association file meets the preset result, an accuracy check is performed on the initial spectrum association file; it is then determined whether the accuracy check result of the initial spectrum association file meets the preset result: if so, the initial spectrum association file is determined as the target spectrum association file.

[0100] Furthermore, the data acquisition module is also used to visualize and statistically analyze the spectral information of the target spectrum-associated file.

[0101] Furthermore, the data analysis module is also used to correct the target spectral data; based on chemometric algorithms, it performs data analysis on the corrected target spectral data to generate analysis results corresponding to the tobacco raw materials.

[0102] It is understood that the tobacco raw material spectrum data management system provided in this application corresponds to the tobacco raw material spectrum data management method provided in this application. In order to keep the specification concise, the same or similar parts can be referred to the content of the tobacco raw material spectrum data management method section, and will not be repeated here.

[0103] The various modules in the aforementioned tobacco raw material spectrum data management system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the server's processor in hardware form, or stored in the server's memory in software form, so that the processor can call and execute the corresponding operations of each module. The processor can be a central processing unit (CPU), a microprocessor, a microcontroller, etc.

[0104] The aforementioned method and / or management system for tobacco raw material spectrum data can be implemented as a computer-readable instruction that can run on a computer system.

[0105] This application also provides a computer system including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described method for managing tobacco raw material spectrum data.

[0106] The computer system can be a server. The computer system includes a processor, a non-volatile storage medium, internal memory, an input device, a display screen, and a network interface connected via a system bus. The non-volatile storage medium of the computer system can store an operating system and computer-readable instructions. When these computer-readable instructions are executed, they can cause the processor to execute a tobacco raw material spectrum data management method according to various embodiments of this application. The specific implementation process of this method can be found in [reference needed]. Figure 1 The specific details will not be elaborated here.

[0107] The processor of this computer system provides computing and control capabilities, supporting the operation of the entire system. The internal memory stores computer-readable instructions, which, when executed by the processor, enable the processor to perform a method for managing tobacco raw material spectral data. The computer system's input devices are used for inputting various parameters, its display screen is used for display, and its network interface is used for network communication.

[0108] Based on the same inventive concept, this application provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps in the above-described tobacco raw material spectrum data management method.

[0109] The memory in the embodiments of this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0110] The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache.

[0111] By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0112] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs.

[0113] When computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions according to the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0114] Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means.

[0115] Computer-readable storage media can be any available medium that a computer can access, or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0116] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0117] 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 in electronic hardware or a combination of computer software and electronic hardware.

[0118] Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0119] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0120] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0121] Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0122] 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; that is, 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 according to actual needs.

[0123] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0124] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application.

[0125] The aforementioned storage media include: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0126] In this specification, references to "an embodiment" or "a specific implementation" mean that a particular feature, structure, or characteristic described in connection with that embodiment / specific implementation is included in at least one embodiment / specific implementation of the invention. Therefore, the phrase "in one embodiment / specific implementation" appearing in various places in this specification does not necessarily refer to the same embodiment / setting, but rather to potentially different embodiments. Furthermore, specific features, structures, or characteristics may be combined in one or more embodiments / settings in any suitable manner, as will be apparent to those skilled in the art from this disclosure.

[0127] Similarly, it should be understood that in the above description of exemplary embodiments / specific implementations of the invention, various features of the invention are sometimes combined in a single embodiment / specific implementation or its figures and description, with the aim of simplifying the disclosure and aiding in the understanding of one or more of the various aspects of the invention. However, the method of description in this patent should not be construed as reflecting an intention that the claimed features of the invention are more than those expressly stated in each claim, except where explicitly stated otherwise or in obvious technical contradiction or exclusion. Rather, the inventive aspect reflected in the claims lies in not all the features of a single foregoing disclosed embodiment / specific implementation. Therefore, the claims following the detailed description are expressly incorporated herein by reference, each claim existing independently as a separate embodiment / specific implementation of the invention.

[0128] Furthermore, while some embodiments / specific implementations described herein include, but are not limited to, other features included in other embodiments / specific implementations, combinations of features from different embodiments / specific implementations are intended to be within the scope of the invention and form different embodiments / specific implementations, as will be understood by those skilled in the art. For example, in the following claims, embodiments / specific implementations of any claim can be used in any combination.

[0129] The terms and expressions used in this specification are for illustrative purposes and not for limitation. In using these terms and expressions, it is not intended to exclude any equivalents of the features or portions thereof shown and described, but rather to recognize that various modifications may be possible within the scope of the invention.

[0130] Therefore, it should be understood that although the invention has been specifically disclosed through preferred embodiments, exemplary embodiments and optional features, those skilled in the art may take variations or modifications of the concepts disclosed herein, and such variations and modifications are therefore considered to be within the scope of the invention as defined by the appended claims.

[0131] The specific embodiments given in this specification are examples of useful implementations of the present invention. It will be apparent to those skilled in the art that the present invention can be implemented using many variations of the devices, device components, and method steps disclosed in this specification.

[0132] The foregoing description of specific embodiments fully discloses the general features of the present invention, enabling others to easily modify and / or adapt such specific embodiments for various applications by applying knowledge within the scope of the art, without conducting excessive experimentation and without departing from the general concept of the present invention.

[0133] Therefore, based on the teachings and guidance provided herein, it is intended that such modifications and alterations be included within the meaning and scope of equivalents of the disclosed embodiments. It should be understood that the wording or terminology used herein is for descriptive purposes and is not intended to be limiting; thus, the wording or terminology in this specification will be interpreted by those skilled in the art based on the foregoing teachings and guidance.

[0134] Furthermore, the scope of the invention should not be limited to any of the exemplary embodiments described above, but only to the appended claims and their equivalents.

Claims

1. A tobacco raw material profile data management method characterized by comprising: The tobacco raw material spectrum data management method comprises: Step S1: obtaining initial spectrum data of tobacco raw material; Step S2: classifying and managing the initial spectrum data according to a preset spectrum data type, to obtain target spectrum data; Step S3: performing data analysis and processing on the target spectrum data to generate an analysis result corresponding to the tobacco raw material.

2. The tobacco material profile data management method according to claim 1, characterized by, The step S1 comprises: Step S11: obtaining an initial spectrum correlation file of the tobacco raw material; Step S12: performing data verification on the initial spectrum correlation file to obtain target spectrum correlation file; Step S13: analyzing the target spectrum correlation file to obtain the initial spectrum data.

3. The tobacco material profile data management method according to claim 2, characterized by, The step S12 comprises: Step S121: performing integrity check on the initial spectrum correlation file; Step S122: when it is determined that the integrity check result of the initial spectrum correlation file meets a preset result, performing accuracy check on the initial spectrum correlation file; Step S123: determining whether the check result of the accuracy check of the initial spectrum correlation file meets a preset result: If yes, the initial spectrum correlation file is determined as the target spectrum correlation file.

4. The tobacco material profile data management method according to claim 3, characterized by, The step S12 further comprises: Step S124: visually displaying and statistically analyzing the spectrum information of the target spectrum correlation file.

5. The tobacco material profile data management method according to claim 1, characterized by, The spectrum data type comprises chromatographic data, mass spectrometric data, spectral data and physicochemical data.

6. The tobacco material profile data management method according to claim 1, characterized by, The step S3 comprises: Step S31: performing correction processing on the target spectrum data; Step S32: performing data analysis on the corrected target spectrum data based on a chemometrics algorithm to generate an analysis result corresponding to the tobacco raw material.

7. A tobacco raw material profile data management system characterized by comprising: The tobacco raw material spectrum data management system comprises a data acquisition module, a data management module and a data analysis module, The data acquisition module is configured to obtain initial spectrum data of tobacco raw material; The data management module is configured to classify and manage the initial spectrum data according to a preset spectrum data type, to obtain target spectrum data; The data analysis module is configured to perform data analysis and processing on the target spectrum data to generate an analysis result corresponding to the tobacco raw material.

8. A computer system comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program comprises instructions that, when executed by the processor, cause the processor to perform the method of any one of claims 1 to 7. The processor executes the computer program to realize the steps of the tobacco raw material spectrum data management method according to any one of claims 1-6.

9. A computer readable storage medium having stored thereon computer programs / instructions, characterized in that, The computer program / instruction is executed by the processor to realize the steps of the tobacco raw material spectrum data management method according to any one of claims 1-6.

10. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instruction is executed by the processor to realize the steps of the tobacco raw material spectrum data management method according to any one of claims 1-6.

Images