Method, device, storage medium and product for detecting sodium cyclamate content in wheat flour

Abstract

The present invention discloses a method, device, storage medium and product for detecting the content of cyclamate in wheat flour, and relates to the field of terahertz spectrum detection technology. The method comprises: using terahertz time-domain spectroscopy technology to process a sample to be detected to obtain a terahertz time-domain signal of the sample to be detected; the sample to be detected is a mixture of cyclamate and wheat flour; obtaining a frequency domain waveform of the sample to be detected according to the terahertz time-domain signal of the sample to be detected; obtaining an absorption spectrum of the sample to be detected according to the frequency domain waveform of the sample to be detected; inputting the absorption spectrum of the sample to be detected into a quantitative analysis model to obtain the content of cyclamate in the sample to be detected. The present invention can accurately detect the content of cyclamate without complicated operations.

Description

Technical Field

[0001] The present invention relates to the field of terahertz spectroscopy detection technology, and in particular to a method, device, storage medium and product for detecting the content of sodium cyclamate in wheat flour. Background Art

[0002] As a commonly used sweetener in food production, the sweetness of sodium cyclamate is about 30 to 40 times that of sucrose, while its price is only about one-third of sucrose. Due to its low cost and high economic value, it has become an important sugar substitute product in the food processing industry and is welcomed by a large number of food production and processing companies in China.

[0003] As cyclamate is increasingly used in food production and processing, frequent consumption of foods containing cyclamate can easily lead to excessive consumption of cyclamate by consumers, which can cause serious harm to the liver and nervous system, especially to the elderly, children, pregnant women and other people with weak metabolic detoxification abilities. Therefore, it is stipulated that cyclamate can be used in limited quantities in 19 foods, including frozen drinks, canned foods, candied fruits, bread, cakes, beverages, jellies, etc., and is prohibited from being added to other foods. However, some unscrupulous vendors, driven by profit, illegally add cyclamate to wheat flour to make steamed buns for sale in order to increase the taste.

[0004] Therefore, the research on quantitative detection of cyclamate content in wheat flour has important practical significance. At present, there are many methods for detecting cyclamate in food, which are mainly divided into physical and chemical detection methods and chromatographic detection methods. However, these methods have the disadvantages of being unable to accurately detect the content and complicated operation methods. Therefore, it is of great significance to study a method that can accurately detect the cyclamate content without complicated operations to make up for the defects of old detection technology. Summary of the invention

[0005] The purpose of the present invention is to provide a method, device, storage medium and product for detecting the saccharin content in wheat flour, which can accurately detect the saccharin content without complicated operations.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for detecting the content of cyclamate in wheat flour comprises: using terahertz time-domain spectroscopy technology to process a sample to be detected to obtain a terahertz time-domain signal of the sample to be detected; the sample to be detected is a mixture of cyclamate and wheat flour.

[0008] A frequency domain waveform of the sample to be detected is obtained according to the terahertz time domain signal of the sample to be detected.

[0009] The absorption spectrum of the sample to be detected is obtained according to the frequency domain waveform of the sample to be detected.

[0010] The absorption spectrum of the sample to be tested is input into a quantitative analysis model to obtain the content of cyclamate in the sample to be tested.

[0011] Optionally, the process of determining the quantitative analysis model includes: preparing multiple mixed samples; the mass ratio of saccharin to wheat flour is different between each mixed sample.

[0012] Acquire the terahertz time domain signal of each mixed sample.

[0013] The frequency domain waveform of each mixed sample is obtained according to the terahertz time domain signal of each mixed sample.

[0014] The absorption spectrum of each mixed sample is obtained according to the frequency domain waveform of each mixed sample.

[0015] A partial least squares regression algorithm is adopted, with the absorption spectra of each mixed sample as the independent variable and the content of cyclamate in each mixed sample as the dependent variable, and a quantitative analysis model is constructed according to a sample set; the sample set includes the absorption spectra of each mixed sample.

[0016] Optionally, a terahertz time domain signal of each mixed sample is obtained, specifically: a terahertz time domain spectroscopy system is used to detect each mixed sample to obtain a terahertz time domain signal of each mixed sample.

[0017] Optionally, the frequency domain waveform of each mixed sample is obtained according to the terahertz time domain signal of each mixed sample, specifically: the terahertz time domain signal of each mixed sample is processed by Fourier transform to obtain the frequency domain waveform of each mixed sample.

[0018] Optionally, the absorption spectrum of each mixed sample is obtained according to the frequency domain waveform of each mixed sample, specifically including: using an optical parameter extraction model to process the frequency domain waveform of each mixed sample to obtain the absorption spectrum of each mixed sample.

[0019] A computer device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for detecting the content of cyclamate in wheat flour.

[0020] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for detecting the content of cyclamate in wheat flour.

[0021] A computer program product includes a computer program, which implements the above-mentioned method for detecting the content of cyclamate in wheat flour when executed by a processor.

[0022] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention uses terahertz time-domain spectroscopy technology to process the sample to be detected to obtain the terahertz time-domain signal of the sample to be detected; obtains the frequency domain waveform according to the terahertz time-domain signal; obtains the absorption spectrum according to the frequency domain waveform; inputs the absorption spectrum into the quantitative analysis model to obtain the content of saccharin. The present invention uses terahertz spectroscopy detection technology to directly and effectively obtain the physical and chemical information inside the substance to be detected. Different substances show different characteristic absorption peaks in the terahertz frequency band, and the content of saccharin is obtained according to the absorption spectrum based on the quantitative analysis model. The saccharin content can be accurately detected without complicated operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 A flow chart of a method for detecting the content of cyclamate in wheat flour provided in an embodiment of the present invention.

[0025] Figure 2 The reference signal, terahertz time domain signal of cyclamate and wheat flour are measured when the method for detecting the cyclamate content in wheat flour provided by the present invention is adopted.

[0026] Figure 3 The refractive index spectra of pure cyclamate and pure wheat flour measured when the method for detecting the cyclamate content in wheat flour provided by the present invention is adopted.

[0027] Figure 4 The absorption spectra of pure cyclamate and pure wheat flour measured when the method for detecting cyclamate content in wheat flour provided by the present invention is adopted.

[0028] Figure 5 The present invention provides absorption spectra of mixtures of wheat flour and cyclamate in different mass proportions obtained by using the method for detecting cyclamate content in wheat flour provided by the present invention.

[0029] Figure 6 The present invention provides a scatter plot of a verification set and a prediction set of a quantitative analysis model of a partial least squares regression algorithm established when the method for detecting the content of cyclamate in wheat flour provided by the present invention is adopted.

[0030] Figure 7 This is a diagram of the internal structure of a computer device. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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 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.

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] like Figure 1 As shown, an embodiment of the present invention provides a method for detecting the content of cyclamate in wheat flour, specifically a method for detecting the content of cyclamate in wheat flour based on terahertz time-domain spectroscopy technology, the method comprising: step 101: using terahertz time-domain spectroscopy technology to process a sample to be detected to obtain a terahertz time-domain signal of the sample to be detected. The sample to be detected is a mixture of cyclamate and wheat flour.

[0034] Step 102: Obtaining a frequency domain waveform of the sample to be detected according to the terahertz time domain signal of the sample to be detected.

[0035] Step 103: Obtaining the absorption spectrum of the sample to be detected according to the frequency domain waveform of the sample to be detected.

[0036] Step 104: Input the absorption spectrum of the sample to be tested into a quantitative analysis model to obtain the content of cyclamate in the sample to be tested.

[0037] In practical applications, the process of determining the quantitative analysis model includes: preparing multiple mixed samples; the mass ratios of cyclamate and wheat flour are different between the mixed samples.

[0038] Acquire the terahertz time domain signal of each mixed sample.

[0039] The frequency domain waveform of each mixed sample is obtained according to the terahertz time domain signal of each mixed sample.

[0040] The absorption spectrum of each mixed sample is obtained according to the frequency domain waveform of each mixed sample.

[0041] A partial least squares regression algorithm is adopted, with the absorption spectra of each mixed sample as the independent variable and the content of cyclamate in each mixed sample as the dependent variable, and a quantitative analysis model is constructed according to a sample set; the sample set includes the absorption spectra of each mixed sample.

[0042] In practical applications, the terahertz time domain signal of each mixed sample is obtained, specifically: a terahertz time domain spectroscopy system is used to detect each mixed sample to obtain the terahertz time domain signal of each mixed sample.

[0043] In practical applications, the frequency domain waveform of each mixed sample is obtained according to the terahertz time domain signal of each mixed sample, specifically: the terahertz time domain signal of each mixed sample is processed by Fourier transform to obtain the frequency domain waveform of each mixed sample.

[0044] In practical applications, the absorption spectrum of each mixed sample is obtained according to the frequency domain waveform of each mixed sample, specifically including: using an optical parameter extraction model to process the frequency domain waveform of each mixed sample to obtain the absorption spectrum of each mixed sample.

[0045] The present invention provides a more specific embodiment to introduce the above method in detail: it comprises the following steps: Step 1: prepare the sample.

[0046] Step 1.1: Use an electronic balance to weigh a certain amount of pure wheat flour and pure cyclamate powder, and put them into the powder tablet press for sample preparation. The tableting pressure is 4t and the time is 30s. The pure wheat flour and pure cyclamate tablets required for the test are obtained. The diameter is 13mm and the thickness is about 1.2mm. Qualified sample tablets should have a smooth surface and no cracks.

[0047] Step 1.2: Mix saccharin and wheat flour in different mass proportions and use a tablet press to prepare samples (the saccharin proportions are 0%, 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 100%, a total of 10 groups of different mass fractions), prepare 2 samples for each mass proportion, and prepare a total of 20 samples.

[0048] Step 2: Use the terahertz time-domain spectroscopy system to test and collect data on the sample obtained in step 1.1.

[0049] Step 2.1: At room temperature, reduce the humidity of the sample chamber of the transmission terahertz time-domain spectroscopy system to about 10%. When no sample is placed, measure the terahertz time-domain reference signal and save the reference signal data. Specifically, after the terahertz time-domain spectroscopy system is turned on, use an air compressor to fill the system with dried gas. After preheating for about half an hour, start collecting spectra when the air humidity in the system drops to about 10%. First, measure the reference signal without placing a sample to obtain the terahertz time-domain reference signal R(t).

[0050] Step 2.2: Place the pure wheat flour tablets and pure cyclamate tablets prepared in step 1.1 on the sample rack of the terahertz time-domain spectroscopy system in turn for testing, obtain the terahertz time-domain signals of pure wheat flour and pure cyclamate respectively, and save the data; specifically, place the sample on the rack for measurement after step 2.1 to obtain the terahertz time-domain signal S(t) of the sample. After each sample replacement, wait until the humidity in the system drops to about 10% before collecting the spectrum.

[0051] Step 3: Perform Fourier transform on the collected data to obtain the absorption spectrum.

[0052] Fourier transform is performed on the R(t) measured in step 2.1 and the time domain signal S(t) of pure wheat flour and pure cyclamate measured in step 2.2 to obtain the corresponding frequency domain waveforms S(ω) and R(ω), respectively. By inputting the frequency domain waveforms of pure wheat flour and pure cyclamate into the existing optical parameter extraction model, the absorption spectra (refractive index spectrum and absorption coefficient spectrum) of pure wheat flour and pure cyclamate can be obtained. By comparing the absorption spectra of the above two pure wheat flours and pure cyclamate, it can be found that cyclamate has two absorption peaks at 1.39THz and 1.69THz, while wheat flour has no obvious absorption peak, which can be used as the fingerprint information of cyclamate in the terahertz frequency band for qualitative identification of substances. Whether it is cyclamate or wheat flour, the information of the terahertz absorption spectrum is richer than that of the refractive index spectrum, so in the subsequent quantitative detection of mixtures, modeling and quantitative analysis can be performed based on the absorption spectrum.

[0053] The optical parameter extraction model is:

[0054] By formula The amplitude ratio ρ(ω) of the sample and the reference signal and the phase difference φ(ω) of the sample and the reference signal can be calculated, and then according to the formula and formula The refractive index n(ω) and absorption coefficient of the sample can be calculated , where d represents the thickness of the sample, c represents the speed of light, ω represents the angular frequency, and j represents the imaginary unit.

[0055] Step 4: Use the terahertz time-domain spectroscopy system to test and collect data on the sample obtained in step 1.2.

[0056] Step 4.1: Use the terahertz time-domain spectroscopy system again to detect the sample obtained in step 1.2, and obtain the absorption spectrum through the optical parameter extraction model, with a total of 20 sets of data.

[0057] Step 4.2: Establish a quantitative analysis model. Since the absorption of terahertz waves by cyclamate is weaker than that of wheat flour, when the content of cyclamate in the mixture increases, the overall amplitude of the absorption coefficient of the mixture shows a gradual downward trend, indicating that the absorption spectrum of the mixture can reflect the change in the concentration of cyclamate in the mixture. Therefore, the absorption spectrum of the mixture can be used as an independent variable, and the cyclamate content in the mixture can be used as a dependent variable. The partial least squares regression algorithm is used to establish a quantitative analysis model for the content of cyclamate in the mixture. Specifically, the 20 groups of mixture absorption spectra measured above are randomly divided into a validation set and a prediction set in a ratio of 3:1, and 15 groups of data are obtained as validation sets for the partial least squares regression algorithm to establish a quantitative analysis model, and the remaining 5 groups of data are used as prediction sets to evaluate the quality of the model.

[0058] The formula of the quantitative analysis model is: , where Y represents the content of sodium cyclamate in the mixture, N is the number of variables in the absorption spectrum used for modeling, and i is the i-th variable in the absorption spectrum. is the absorption spectrum of the i-th variable in the absorption spectrum, represents the regression coefficient of the i-th variable in the absorption spectrum, and B is the intercept of the model.

[0059] Step 5: Select the absorption spectrum of the mixture sample to be tested (the mixture of saccharin and wheat flour that needs to be quantitatively analyzed) and input it into the quantitative analysis model established above. The output is the saccharin content of the mixture sample to be tested.

[0060] The present invention provides a means for quantitative detection of cyclamate content in wheat flour. Compared with traditional detection methods, the terahertz spectroscopy detection technology can directly and effectively obtain physical and chemical information inside the substance being tested. Different substances show different characteristic absorption peaks in the terahertz frequency band. Based on the quantitative analysis model of the partial least squares regression algorithm established above, the quantitative detection of cyclamate content in wheat flour can be realized simply, conveniently, quickly and accurately.

[0061] The present invention provides a more specific embodiment to verify the above method, which specifically includes:

[0062] Step A1: Instrument and sample.

[0063] Terahertz time-domain spectroscopy system, electronic scale, powder tablet press, agate grinding mortar, weighing dish; wheat flour powder sample, cyclamate crystalline powder sample.

[0064] Step A2: Sample preparation.

[0065] Step A2.1: Put wheat flour into a weighing dish, weigh an appropriate amount of wheat powder with an electronic scale, and use a powder tablet press to prepare pure wheat flour tablets for standby use; use an agate grinding mortar to fully grind the saccharin crystalline powder sample into powder, put the saccharin powder into a weighing dish, weigh an appropriate amount of saccharin with an electronic scale, and use a powder tablet press to prepare pure saccharin tablets for standby use.

[0066] Step A2.2: Use an electronic scale to weigh an appropriate amount of wheat flour, and then weigh an appropriate amount of sodium cyclamate powder, and prepare samples according to the proportion of sodium cyclamate in the mixture, which is 0%, 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 100%, a total of 10 groups of different mass fractions. Stir and mix the two in a weighing dish, and use a powder tablet press to prepare a mixture tablet. Prepare 2 samples for each mass fraction, a total of 20 samples, and set aside. When using a powder tablet press to make tablets, the pressure is 4t, the time is 30s, and finally a circular sample with a diameter of 13mm and a thickness of about 1.2mm is obtained.

[0067] Step A3: Use a terahertz time-domain spectroscopy system to perform terahertz spectroscopy detection on all samples.

[0068] Step A3.1: After the terahertz time-domain spectroscopy system is turned on, the system is filled with dried gas using an air compressor. After preheating for about half an hour, the spectrum is collected when the air humidity in the system drops to about 10%. First, the reference signal is measured without placing the sample prepared in step A2 to obtain the terahertz time-domain reference signal R(t). Then, the samples prepared in step A2 are placed one by one for measurement to obtain the terahertz time-domain signal S(t) of the sample. After each sample is replaced, it is necessary to wait until the humidity in the system drops to about 10% before collecting the spectrum. The results are as follows: Figure 2 shown.

[0069] Step A3.2: Perform Fourier transform on the measured signal R(t) and the terahertz time domain signal S(t) of each sample to obtain the corresponding frequency domain waveforms, R(ω) and S(ω), respectively.

[0070] Step A3.3: Then obtain the refractive index n(ω) and absorption coefficient , the refractive index spectrum and absorption spectrum of pure cyclamate and pure wheat flour are as follows Figure 3 and Figure 4 As shown, Figure 3 Part (a) is the refractive index spectrum of pure cyclamate. Figure 3 Part (b) is the refractive index spectrum of pure wheat flour. Figure 4 Part (a) is the absorption spectrum of pure cyclamate. Figure 4 Part (b) is the absorption spectrum of pure wheat flour.

[0071] Step A3.4: Use the terahertz time-domain spectroscopy system to detect the mixture sample obtained in step A2.2, and then use Fourier transform to calculate the absorption spectrum of the mixture sample. The result is as follows: Figure 5 shown.

[0072] Step A3.5: Quantitative analysis of the content of cyclamate in the mixture is performed using partial least squares regression (PLS). In this embodiment, a mixture of cyclamate and wheat flour is prepared according to 10 different mass ratios, and 2 samples are prepared for each mass ratio, making a total of 20 samples. The terahertz time-domain spectroscopy system is used to collect absorption spectra of these 20 samples to obtain the terahertz time-domain signal of each sample. The corresponding absorption spectra are calculated based on the terahertz time-domain signal of each sample, totaling 20 groups of data. According to the ratio of 3:1, these data are randomly divided into a validation set and a prediction set, and 15 groups of data are obtained as validation sets for the PLS algorithm to establish a quantitative analysis model, and the remaining 5 groups of data are used as prediction sets to evaluate the quality of the model. The results of the correlation coefficient and root mean square error of the quantitative analysis model are shown in Table 1.

[0073] Table 1 Correlation coefficient and root mean square error results of PLS ​​quantitative analysis model

[0074]

[0075] It can be seen from Table 1 that the correlation coefficient and root mean square error of the validation set reached 0.997691 and 0.016585 respectively, indicating that the model obtained through training has a good effect. The correlation coefficient and root mean square error of the prediction set are 0.995904 and 0.018264 respectively, proving that the model has good generalization ability. The correlation coefficients of both the validation set and the prediction set are very close to 1, indicating that the linear correlation between the predicted value and the true value is high. At the same time, the root mean square errors of the validation set and the prediction set are small, indicating that the difference between the predicted value and the true value is also small, proving that the model can accurately predict the content of cyclamate in the mixture.

[0076] Figure 6 Part (a) is the scatter plot of the validation set. Figure 6 Part (b) is a prediction scatter plot, where the horizontal axis represents the predicted value of cyclamate content and the vertical axis represents the true value of cyclamate content. Figure 6 The solid line in the figure represents the reference line, which can intuitively show the closeness between the predicted value and the true value. When the predicted value is closer to the true value, Figure 6 The closer the predicted point is to the reference line. When the error between the predicted value and the true value is greater, the predicted point will be farther from the reference line. The preparation process of the present invention is simple, and the content of sodium cyclamate can be quantitatively analyzed quickly and accurately without complicated operations.

[0077] In one embodiment, a computer device is provided. The computer device may be a database, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data processing method is implemented.

[0078] In one embodiment, a computer device is also provided, including a memory and a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0079] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0080] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0081] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards.

[0082] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0083] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for detecting the content of sodium cyclamate in wheat flour, characterized in that: include: Using terahertz time-domain spectroscopy technology to process the sample to be detected to obtain a terahertz time-domain signal of the sample to be detected; The sample to be tested is a mixture of sodium cyclamate and wheat flour; Obtaining a frequency domain waveform of the sample to be detected according to the terahertz time domain signal of the sample to be detected; Obtaining an absorption spectrum of the sample to be detected according to the frequency domain waveform of the sample to be detected; the absorption spectrum includes a refractive index spectrum and an absorption coefficient spectrum; The absorption spectrum of the sample to be tested is input into the quantitative analysis model to obtain the content of sodium cyclamate in the sample to be tested; the quantitative analysis model is Where, Y represents the content of sodium cyclamate in the sample to be tested, N is the number of variables in the absorption spectrum of the sample to be tested, and β i is the absorption spectrum of the i-th variable in the absorption spectrum of the sample to be tested, λ i represents the regression coefficient of the i-th variable in the absorption spectrum of the sample to be tested, and B is the intercept; The determination process of the quantitative analysis model includes: Preparing a plurality of mixed samples; wherein the mass ratio of sodium cyclamate to wheat flour is different between the mixed samples; Acquiring the terahertz time domain signal of each mixed sample, specifically comprising: using a terahertz time domain spectroscopy system to detect each mixed sample to obtain the terahertz time domain signal of each mixed sample; wherein, when the air humidity in the terahertz time domain spectroscopy system drops to about 10%, spectrum collection begins; Obtaining a frequency domain waveform of each mixed sample according to the terahertz time domain signal of each mixed sample; Obtaining the absorption spectrum of each mixed sample according to the frequency domain waveform of each mixed sample; A partial least squares regression algorithm is adopted, with the absorption spectra of each mixed sample as the independent variable and the content of cyclamate in each mixed sample as the dependent variable, and a quantitative analysis model is constructed according to a sample set; the sample set includes the absorption spectra of each mixed sample.

2. The method for detecting the content of sodium cyclamate in wheat flour according to claim 1, characterized in that: The frequency domain waveform of each mixed sample is obtained according to the terahertz time domain signal of each mixed sample, specifically: The terahertz time domain signal of each mixed sample is processed by Fourier transform to obtain the frequency domain waveform of each mixed sample.

3. The method for detecting the content of sodium cyclamate in wheat flour according to claim 1, characterized in that: The absorption spectrum of each mixed sample is obtained according to the frequency domain waveform of each mixed sample, specifically including: The frequency domain waveform of each mixed sample is processed using an optical parameter extraction model to obtain the absorption spectrum of each mixed sample.

4. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for detecting the saccharin content in wheat flour as described in any one of claims 1 to 3.

5. A 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 detecting the content of cyclamate in wheat flour as described in any one of claims 1 to 3 is implemented.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting the content of cyclamate in wheat flour as described in any one of claims 1 to 3 is implemented.

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