Black fungus quality analysis method based on infrared spectrum

Abstract

The invention discloses a black fungus quality analysis method based on infrared spectroscopy, and belongs to the field of black fungus quality analys.The method comprises the steps that infrared spectroscopy collection and data analysis are conducted on black fungus samples of different producing areas and different batches, and the corresponding relation between spectral characteristics and main components of black fungus is established; therefore, rapid, lossless and multi-dimensional detection and evaluation of components such as auricularia auricula polysaccharides, proteins, lipids, calcium oxalate crystals and the like are realized. Compared with a traditional method depending on sensory indexes, physicochemical indexes and single chemical analysis, the method has the advantages that the detection time is short, complex sample pretreatment is not needed, and more comprehensive and objective quality information can be provided.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of Auricularia auricula quality analysis, and particularly relates to a quality analysis method for Auricularia auricula based on infrared spectrum. BACKGROUND

[0002] Auricularia auricula is an important fungus for both food and medicine in China, which has a wide application in food and medicine fields due to its rich nutritional components and pharmacological effects. However, its quality is easily affected by factors such as production environment, cultivation method, harvesting time and processing technology, resulting in significant quality difference. The existing quality evaluation methods mainly rely on sensory indexes (such as appearance, color), physicochemical indexes (such as moisture, ash content) and chemical analysis methods (such as phenol-sulfuric acid method for determining polysaccharide content). These traditional methods generally have the disadvantages of long detection time, complex operation, destructiveness and single evaluation dimension, which are difficult to meet the needs of modern food industry for rapid, objective and multi-dimensional quality control. SUMMARY

[0003] To solve the above technical problems, the present application provides a quality analysis method for Auricularia auricula based on infrared spectrum, which comprises the following steps:

[0004] obtaining the infrared spectrum of an Auricularia auricula sample;

[0005] performing pretreatment on the original infrared spectrum to obtain a standardized spectrum;

[0006] extracting the peak position, peak shape and relative peak height information of at least four characteristic absorption peaks from the standardized spectrum, the four characteristic absorption peaks being 1075 cm -1 and 1040 cm -1 double strong peaks, 1650 cm -1 single strong peak, 1735 cm -1 weak shoulder peak, 1320 cm -1 small weak sharp peak;

[0007] generating an overall quality analysis result of Auricularia auricula according to the characteristic absorption peak information.

[0008] Optionally, the step of obtaining the infrared spectrum of an Auricularia auricula sample comprises:

[0009] preparing the Auricularia auricula sample into a solid sheet;

[0010] performing spectral scanning on the solid sheet using an infrared spectrometer to obtain original spectrum data;

[0011] The step of preparing the Auricularia auricula sample into a solid sheet comprises:

[0012] crushing and sieving the Auricularia auricula sample;

[0013] The sample powder is mixed with potassium bromide and pressed into a thin slice.

[0014] Optionally, the process of performing spectral scanning on the solid slice by the infrared spectrometer comprises:

[0015] The scanning range is set to 4000 cm -1 to 400 cm -1 , the resolution is 4 cm -1 , and the scanning times are 16 times.

[0016] A background spectrum is collected before each test, and the interference of carbon dioxide and water vapor is deducted.

[0017] Optionally, the process of extracting the peak position, peak shape, and relative peak height information of at least four characteristic absorption peaks from the normalized spectrum comprises:

[0018] Baseline correction, normalization, and smoothing processing are performed on the infrared spectrum to obtain a pretreated spectrum.

[0019] Characteristic absorption peaks in the pretreated spectrum are identified.

[0020] Optionally, the process of identifying characteristic absorption peaks comprises:

[0021] The relative peak height of each characteristic absorption peak is calculated.

[0022] The relative peak height is taken as the characteristic absorption peak information.

[0023] Optionally, the process of calculating the relative peak height of each characteristic absorption peak comprises:

[0024] The higher of the double strong peaks at 1075 cm -1 and 1040 cm -1 is taken as the reference, and the peak height values of other characteristic peaks are normalized.

[0025] Optionally, the process of generating the overall quality analysis result of Auricularia auricula-judae comprises:

[0026] The characteristic absorption peak information is compared with a preset quality grade standard.

[0027] According to the comparison result, the quality grade of Auricularia auricula-judae is determined.

[0028] Optionally, the preset quality grade standard comprises:

[0029] According to the relative peak heights of the double strong peaks at 1075 cm -1 and 1040 cm -1 , the polysaccharide content grade is divided.

[0030] According to the relative peak height of the double strong peak at 1650 cm -1 , the protein content grade is divided.The relative peak height of a single strong peak is used to classify the content level of protein substances;

[0031] Based on 1735cm -1 The relative peak height of a weak shoulder peak is used to classify lipid content levels;

[0032] Based on 1320cm -1 The relative peak height of small, weak peaks is used to classify the calcium oxalate crystal content level.

[0033] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0034] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0035] Compared with the prior art, the present invention has the following advantages and technical effects:

[0036] The proposed infrared spectral quality evaluation method for black fungus significantly improves detection efficiency, reducing single-sample detection time from several hours to just minutes compared to traditional methods. This method requires no complex pretreatment or chemical reagents, consumes minimal sample, and can even directly detect intact dried fungus pieces, avoiding the damage caused by traditional methods. By extracting and analyzing characteristic peaks in the infrared spectrum, information on multiple components such as polysaccharides, proteins, lipids, and calcium oxalate crystals can be simultaneously obtained, enabling multi-dimensional comprehensive quality evaluation and overcoming the limitations of traditional methods that rely on single evaluation indicators. A grading model based on the intensity and relative height of spectral characteristic peaks allows for scientific classification, improving the objectivity and consistency of grading. Furthermore, by utilizing the differences in spectral characteristics of black fungus from different origins, origin traceability can be achieved, meeting the needs of quality traceability and standardized management. In summary, this invention has significant advantages in detection speed, non-destructive testing, information dimensionality, scientific grading, and traceability capabilities, providing reliable technical support for the black fungus industry. Attached Figure Description

[0037] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0038] Figure 1 This is a schematic diagram of the superimposed state of infrared spectra of 15 batches of black fungus samples according to an embodiment of the present invention;

[0039] Figure 2These are split images of the infrared spectra of 15 batches of black fungus samples from an embodiment of the present invention.

[0040] Figure 3 Embodiment 1 of the present invention # Normalized infrared spectrum of the sample;

[0041] Figure 4 3. This is an embodiment of the present invention. # Normalized infrared spectrum of the sample;

[0042] Figure 5 Example 4 of the present invention # Normalized infrared spectrum of the sample;

[0043] Figure 6 Example 5 of the present invention # Normalized infrared spectrum of the sample;

[0044] Figure 7 6 of the present invention # Normalized infrared spectrum of the sample;

[0045] Figure 8 7 of the present invention # Normalized infrared spectrum of the sample;

[0046] Figure 9 8 of the present invention # Normalized infrared spectrum of the sample;

[0047] Figure 10 Example 9 of the present invention # Normalized infrared spectrum of the sample;

[0048] Figure 11 This is embodiment 11 of the present invention. # Normalized infrared spectrum of the sample;

[0049] Figure 12 This is embodiment 12 of the present invention. # Normalized infrared spectrum of the sample;

[0050] Figure 13 This is embodiment 13 of the present invention. # Normalized infrared spectrum of the sample;

[0051] Figure 14 Example 14 of the present invention # Normalized infrared spectrum of the sample;

[0052] Figure 15 Example 15 of the present invention # Normalized infrared spectrum of the sample. Detailed Implementation

[0053] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0054] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0055] Example 1

[0056] This embodiment provides a method for quality analysis of black fungus based on infrared spectroscopy, including:

[0057] Obtain the infrared spectrum of the black fungus sample;

[0058] The original infrared spectrum was preprocessed to obtain a standardized spectrum;

[0059] The peak position, peak shape, and relative peak height information of at least four characteristic absorption peaks are extracted from the normalized spectrum. The four characteristic absorption peaks are 1075 cm⁻¹. -1 and 1040cm -1 Double peaks, 1650cm -1 Single strong peak, 1735cm -1 Weak acromion, 1320cm -1 Small, weak peaks;

[0060] Based on the characteristic absorption peak information, the overall quality analysis results of black fungus are generated.

[0061] First, use an infrared spectrometer, specifically a Fourier transform infrared spectrometer or a dispersive infrared spectrophotometer. The instrument accuracy and resolution should be determined according to the methods described in GB / T21186 or General Chapter 0402 of the Pharmacopoeia of the People's Republic of China (2020 edition), and should meet the following requirements:

[0062] Accuracy: Polystyrene film calibration, Fourier transform infrared spectrometer at 3000 cm⁻¹ -1 The wavenumber error in the vicinity is no greater than ±5cm -1 , at 1000cm -1 The wavenumber error in the vicinity is no greater than ±2cm -1 .

[0063] Resolution: The optimal resolution of the instrument is no less than 4cm. -1 .

[0064] Meanwhile, infrared spectroscopy software should have basic functions such as coordinate axis unit transformation, baseline correction, normalization, smoothing, differentiation, peak position and peak intensity calculation, spectral library retrieval, and ATR correction.

[0065] The sampling method shall be in accordance with the relevant provisions of General Chapter 0211 of the Pharmacopoeia of the People's Republic of China (2020 Edition). Other sampling methods shall comply with relevant regulations or refer to the sampling methods for medicinal materials and processed medicinal slices. Generally, each solid sample shall be no less than 100g, each powdered solid sample no less than 25g, and each liquid sample no less than 25mL. The sampling amount may be appropriately reduced for precious or other special samples.

[0066] The sample preparation method shall be in accordance with the relevant provisions of General Chapter 0212 of the Pharmacopoeia of the People's Republic of China (2020 Edition). Other sample preparation methods shall comply with relevant regulations or refer to the sample preparation methods for medicinal materials and processed medicinal slices. Solid samples should be pulverized before testing, and the sample powder used for testing should pass through a stainless steel sieve with a mesh size of not less than 100. Liquid samples should be mixed before testing, and solutions with low solute concentrations should be concentrated or dried before testing.

[0067] This embodiment uses the traditional "tablet compression method", which is suitable for testing dry solid samples or liquid samples that do not contain dissolved solid diluents.

[0068] The following points should be noted:

[0069] The tableting method generally uses spectroscopically pure potassium bromide as a solid diluent. Potassium bromide is stored in a sealed container in a dry environment.

[0070] Nitrate impurity test in potassium bromide: The sample chamber is empty. The background spectrum is tested, then a potassium bromide film without the sample is placed in the chamber, and the sample spectrum is tested. The spectrum at 1384 cm⁻¹ is observed. -1 Are there absorption peaks nearby?

[0071] The powdered sample was mixed with potassium bromide at a mass ratio of approximately 1:100, ground evenly, and then pressed into transparent or translucent sheets using a tableting device.

[0072] To test liquid samples that do not dissolve potassium bromide, first prepare a thin sheet of potassium bromide, and then drop an appropriate amount of sample onto the potassium bromide sheet.

[0073] A potassium bromide sheet without the sample is placed in the sample chamber, and the background spectrum is tested. Then, the potassium bromide sheet without the sample is removed, and a potassium bromide sheet containing the sample is placed in it, and the sample spectrum is tested.

[0074] The transmittance of the strongest absorption peak in the infrared spectrum of the tablet compression method should be 10% to 30%, the transmittance of the baseline without obvious absorption peak should be 80% to 100%, and the difference between the transmittance of the strongest absorption peak and the baseline should not be less than 50%. If the transmittance of the sample spectrum does not meet the above requirements, the ratio of the sample to potassium bromide should be adjusted, and the tablet should be prepared and tested again.

[0075] Each sample should be tested at least twice, and a new sample should be taken and prepared for testing each time.

[0076] Spectral preprocessing can perform coordinate axis unit transformation, baseline correction, normalization, smoothing, differentiation, ATR correction, and other preprocessing on the original spectrum of the sample. The following points should be noted: a) Unnecessary preprocessing steps should not be added while ensuring the requirements of subsequent spectral analysis are met; b) The preprocessing measures applied to the original spectrum of the sample, along with relevant information such as the operating software and processing parameters, should be recorded in detail.

[0077] The process of chemical substance structure analysis includes: the infrared absorption peaks of chemical substances are related to their molecular structure. Based on the correspondence between infrared absorption peaks and functional groups of compounds, the structural characteristics of the chemical components corresponding to the infrared absorption peaks of a sample can be analyzed, thus identifying the types of compounds contained in the sample. It should be noted that complex samples are usually mixtures, and their infrared absorption peaks may be a superposition of infrared absorption signals from multiple chemical components with similar functional groups.

[0078] The three essential elements of infrared spectroscopy are: the peak position, the intensity of the absorption peaks (bands), and the peak shape, which correspond to the various chemical components of the sample. These three elements constitute the three essential elements of infrared spectroscopy. Black fungus contains multiple chemical components. When infrared light irradiates black fungus, the superposition of absorption peaks (bands) of multiple components at different wavelengths yields the infrared spectrum of the sample. Identification is performed based on the position, intensity, and shape of the absorption peaks in the infrared spectrum.

[0079] The process for identifying the infrared spectra of black fungus includes: the infrared spectrum of the black fungus sample should contain the following 7 characteristic peaks (peak position, peak intensity, peak shape). The following are the main absorption information of the infrared spectrum of black fungus:

[0080] 3400cm -1 -3100cm -1 The broad and strong absorption peaks are attributed to the stretching vibrations of OH (hydroxyl) and NH (amino) in black fungus. Black fungus mainly originates from hydrogen bonds binding water molecules and amino acid residues in polysaccharides and proteins.

[0081] 2925cm -1 and 2850cm -1 The weaker peaks correspond to the CH stretching vibrations (-CH2 and -CH3) in black fungus, mainly originating from the methyl and methylene groups in lipid and carbohydrate molecules.

[0082] 1734cm -1 The weak absorption peak originates from the C=O stretching vibration in the esters or carboxylic acids of black fungus, indicating the presence of a small amount of lipid compounds.

[0083] 1642cm -1 The strong absorption peak is mainly attributed to the amide I band (C=O stretching vibration) of black fungus protein.

[0084] 1420cm -1 and 1378cm -1 : Derived from the CH bending vibration of black fungus or the COH deformation vibration of polysaccharides.

[0085] 1320cm -1 Small, weak spike: A characteristic absorption from calcium oxalate crystals in black fungus.

[0086] 1074cm -1 and 1039cm -1 : CO vibration from β-glycosidic bonds (such as β-glucan) in black fungus.

[0087] The infrared (FTIR) absorption characteristics of black fungus are mainly reflected in the vibrations of characteristic functional groups in its molecular structure, reflecting the composition and relative content of its main chemical components (such as proteins, polysaccharides, and lipids).

[0088] In addition, infrared spectroscopy technology, due to its holistic, rapid, and non-destructive characteristics, has important application value in the quality control and authenticity identification of edible fungi.

[0089] 9. Conclusions of Overall Infrared Spectroscopic Analysis of Black Fungus

[0090] The infrared spectral characteristics of black fungus mainly reflect its polysaccharide, protein, and lipid composition. Meanwhile, the absorption of calcium oxalate crystals also has certain characteristic features and biological significance. Therefore, the following four characteristic absorptions are mainly retained, and their relative heights are calculated. Among them:

[0091] 1075cm -1 and 1040cm -1 "Double strong peaks" can be used to assess the relative content of polysaccharides;

[0092] 1650cm -1 "Single strong absorption peak" can be used to assess the relative content of protein (amino acid) substances;

[0093] 1735cm -1 "Weak shoulder absorption peaks" can be used to assess the relative content of small amounts of lipids;

[0094] 1320cm -1"Small, weak peaks" can be used to assess the relative content of small amounts of calcium oxalate crystals.

[0095] The relative heights of the four main related absorption peaks are shown in Table 1.

[0096] Table 1

[0097]

[0098]

[0099] The data comes from the results of "absorbance-baseline correction-normalization-relative peak height calculation" of the infrared spectra of each sample.

[0100] The process of obtaining infrared spectral information from 10 different batches of samples included: a certain amount of sample was placed in an agate mortar and ground and mixed thoroughly. An appropriate amount was then weighed and placed in a special pressing mold, and pressed under 8 MPa pressure for 30 seconds to obtain a uniform, translucent sheet. To ensure the sample was not exposed to moisture, the sheet was dried under an infrared lamp.

[0101] Parameter settings and indoor environment control: spectral scanning range 4000cm 1 -400cm 1 16 scans, 4cm resolution 1 To eliminate the influence of CO2 and H2O, the experimental environment temperature was controlled at 25℃ and the relative humidity was maintained at 25%-35%.

[0102] Results analysis: such as Figures 1-15 As shown, neither GB / T6192-2019 "Black Fungus" nor LYT1207-2021 "Black Fungus" includes "infrared characteristic absorption," lacking a practical means of "holistic, rapid, and non-destructive intuitive quality control." Therefore, this standard adds infrared spectra and (1075cm) measurements. -1 and 1040cm -1 "Double Strong Peaks", 1650cm -1 "Single strong absorption peak", 1735cm -1 "Weak shoulder absorption peak" and 1320cm -1 The absorption of the four typical characteristics of "small weak peaks" has a "fingerprint-like" quality (i.e., peak position, peak shape, and relative height). These four typical characteristics correspond to the relative content of four major categories of chemical substances (carbohydrates, proteins, fats, and calcium oxalate crystals), and are consistent with the national and industry standards for "total sugar (crude fiber), crude protein, and crude fat".

[0103] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0104] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0105] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An infrared spectroscopy-based method for analyzing the quality of black fungus, characterized in that, The application relates to a method for analyzing the quality of black fungus, and belongs to the field of quality analysis of black fungus. The method comprises the following steps: acquiring an infrared spectrum of a black fungus sample; extracting peak position, peak shape and relative peak height information of at least four characteristic absorption peaks, respectively 1075 cm -1 and 1040 cm -1 double strong peak, 1650 cm -1 single strong peak, 1735 cm -1 weak shoulder peak, 1320 cm -1 small weak sharp peak, from the standardised spectrum; performing pretreatment on the original infrared spectrum to obtain a standardized spectrum; 2. The method of claim 1, wherein, generating a black fungus overall quality analysis result according to the characteristic absorption peak information. The step of acquiring the infrared spectrum of the black fungus sample comprises the following steps: preparing the black fungus sample into a solid sheet; performing spectrum scanning on the solid sheet by using an infrared spectrometer to obtain original spectrum data; The step of preparing the black fungus sample into a solid sheet comprises the following steps: crushing and sieving the black fungus sample; 3. The method of claim 1, wherein, mixing the sample powder with potassium bromide and pressing into a sheet. The scanning range was set to 4000 cm -1 to 400 cm -1 , the resolution was 4 cm -1 , and the number of scans was 16. The step of performing spectrum scanning on the solid sheet by using an infrared spectrometer comprises the following steps:

4. The method of claim 1, wherein, acquiring a background spectrum before each test, and deducting the interference of carbon dioxide and water vapor. The process of extracting the peak position, peak shape and relative peak height information of at least four characteristic absorption peaks from the standardized spectrum comprises the following steps: performing baseline correction, normalization and smoothing processing on the infrared spectrum to obtain a pretreated spectrum; 5. The method of claim 1, wherein, identifying the characteristic absorption peaks in the pretreated spectrum. The step of identifying the characteristic absorption peaks comprises the following steps: calculating the relative peak height of each characteristic absorption peak; 6. The method of claim 5, wherein, taking the relative peak height as the characteristic absorption peak information. at 1075 cm -1 and 1040 cm -1 The higher of the two strong peaks was taken as a reference, and the peak height values of the other characteristic peaks were normalized.

7. The method of claim 1, wherein, The step of calculating the relative peak height of each characteristic absorption peak comprises the following steps: The process of generating the black fungus overall quality analysis result comprises the following steps: comparing the characteristic absorption peak information with a preset quality grade standard; 8. The method of claim 1, wherein, determining the quality grade of the black fungus according to the comparison result. According to 1075 cm -1 and 1040 cm -1 The relative peak height of the doublet divides the content level of polysaccharide substances. According to 1650 cm -1 The relative peak height of the single peak is used to divide the protein substance content level. According to 1735 cm -1 The relative peak height of the weak shoulder peak divides the lipid material content level. According to 1320 cm -1 The relative peak height of the small and weak peak divides the content level of calcium oxalate crystal.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that, The preset quality grade standard comprises the following steps:

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The processor performs the calculation program to realize the method in any one of claims 1-8. The computer program is executed by the processor to realize the method in any one of claims 1-8.

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