Detection method for identifying fruit juice samples from different sources by using NMR (nuclear magnetic resonance)

Abstract

The invention relates to a detection method for identifying fruit juice samples from different sources by using NMR (nuclear magnetic resonance). The detection method for identifying fruit juice samples from different sources by using NMR comprises the following steps: step 1, obtaining a < 1 > H-NMR spectrogram of a fruit juice sample to be analyzed; step 2, performing hydrogen spectrum integral treatment on the obtained 1H-NMR spectrogram of the fruit juice sample, and identifying and removing residual water peaks in the 1H-NMR spectrogram to obtain a water-peak-removed 1H-NMR spectrogram; step 3, identifying each saccharide component in the water-peak-removed 1H-NMR spectrogram, determining the chemical shift range of each saccharide component, and recording each shift range to obtain a sugar-containing 1H-NMR spectrogram; and step 4, firstly removing a sugar peak interval in the sugar-containing 1H-NMR spectrogram, then carrying out data normalization and calibration, and carrying out multivariate analysis after calibration to obtain the real component difference between the fruit juice samples so as to judge whether the fruit juice is true or false. By eliminating the influence of residual signals and carbohydrate components in the < 1 > H-NMR spectrum of the fruit juice sample, the accuracy and reliability of detection and analysis data are improved.

Description

Technical Field

[0001] The invention relates to an improvement of a juice detection technology, belongs to the field of juice detection, and in particular to a detection method for identifying juice samples from different sources by using NMR. Background Art

[0002] The current quality inspection and analysis methods for juice include physical and chemical analysis and instrumental analysis. Among them, physical and chemical analysis includes juice sugar identification, organic acid identification, pectin identification, phenolic identification, inorganic element identification, amino acid identification and ketone identification. These methods only focus on the content and changes of one or several components, ignoring the existence of a large number of other adulterants, and cannot meet the needs of juice product quality control. Instrumental analysis includes instrument chromatography, stable isotope mass spectrometry and mass spectrometry, but the juice composition is complex and the source is wide. The existing technology has very limited detection capabilities for samples from different sources and unknown illegal additives. However, these methods usually only focus on the content and changes of one or several components, ignoring the existence of a large number of other adulterants, and therefore cannot meet the needs of juice product quality control. On the other hand, due to the complex composition and wide source of juice, the adulteration of samples from different sources and the addition of unknown illegal additives also affect the test results, and the interference of water peaks and sugars has the most obvious impact on the data, making the accuracy of the test and analysis data insufficient.

[0003] The Chinese patent application with application number CN202111395181.9 and application date November 23, 2021, discloses a method for detecting sugar adulteration in raw fruit juice rich in anthocyanins, which belongs to the field of food detection technology. A method for detecting sugar adulteration in raw fruit juice rich in anthocyanins, the method uses ultra-high performance liquid chromatography and mass spectrometry to detect the presence and content of the combination products of anthocyanins and sugar degradation products furfural compounds in fruit juice samples, and uses the concentration of the combination products in the test fruit juice sample of 2 mg / mL as the standard to judge whether there is sugar adulteration, but the above technology does not solve the problem of insufficient accuracy of detection and analysis of existing detection methods.

[0004] The information disclosed in this background technology section is only intended to increase the understanding of the overall background of this patent application, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to ordinary technicians in this field. Summary of the invention

[0005] The purpose of the present invention is to overcome the problem of insufficient accuracy of detection and analysis of existing detection methods in the prior art, and to provide a more accurate detection and analysis method for identifying juice samples from different sources using NMR.

[0006] To achieve the above objectives, the technical solution of the present invention is: a detection method for identifying juice samples from different sources using NMR, the detection method for identifying juice samples from different sources using NMR comprising the following steps:

[0007] Step 1, obtaining a 1H-NMR spectrum of the juice sample to be analyzed;

[0008] Step 2: Perform hydrogen spectrum integration processing on the 1H-NMR spectrum of the obtained juice sample, identify and remove the residual water peak in the 1H-NMR spectrum, and obtain a dehydrated 1H-NMR spectrum;

[0009] Step 3, identifying each sugar component in the dehydrated peak 1H-NMR spectrum, and determining the chemical shift range of each sugar component, and recording each shift range to obtain a sugar-containing 1H-NMR spectrum;

[0010] Step 4: First remove the sugar peak interval in the sugar-containing 1H-NMR spectrum, then perform data normalization and calibration, and perform multivariate analysis after calibration to obtain the true component differences between the juice samples, so as to determine the authenticity of the juice.

[0011] The obtaining of the 1H-NMR spectrum of the juice sample to be analyzed refers to:

[0012] The acquired samples were placed on a Bruker Avance III 600MHz spectrometer. For each sample, the 90° pulse width was set to about 10-12μs, the spectrum width was set to 20ppm, the sampling points were 64K, the FID was accumulated 64 times, and all one-dimensional 1H-NMR spectra were multiplied by an exponential window function with a broadening factor of 1.0Hz before Fourier transformation. The data transformation points were 128K, thereby obtaining the 1H-NMR spectrum of the juice sample.

[0013] The proton resonance frequency is 600.13 MHz and the experimental temperature is set to 298.0 K.

[0014] Before collecting the 1H-NMR spectra of the juice sample, each spectrum was manually phase and baseline corrected.

[0015] The identifying and removing the residual water peak in the 1H-NMR spectrum refers to removing the signal in the range of δ5.0-4.68, which is the water peak removal operation.

[0016] The chemical shift range of each sugar component is determined as follows: TSP is added to the sample as an internal standard, and the chemical shift of this peak is positioned at 0 ppm. In the calibrated spectrum, the signals of sugar components such as glucose, sucrose, and fructose are between δ5.46-3.20.

[0017] The chemical shift range of each sugar component is δ5.46-3.20.

[0018] The removing of the sugar peak interval in the sugar-containing 1H-NMR spectrum refers to removing the signal in the chemical shift interval of δ5.46-3.20 of the sugar component.

[0019] The data normalization and calibration refers to: integrating the δ9.0-0.5 range in the 1H-NMR spectrum of each sample in sections and performing normalization processing at the same time, that is, dividing the integrated area of ​​each section by the sum of all integrated areas, and each integrated interval is 0.004 ppm.

[0020] After the data were normalized, the least partial squares discriminant was used for automatic normalization and standardization, and the inter-group distinction of metabolites was further analyzed.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] 1. In a detection method for identifying juice samples from different sources using NMR, the present invention identifies and removes the residual water peak in the 1H-NMR spectrum, removes the sugar peak interval in the sugar-containing 1H-NMR spectrum, and then performs data normalization and calibration. After calibration, multivariate analysis is performed to obtain the true component differences between the juice samples, thereby judging the authenticity of the juice. When applied, this method eliminates the residual signal and the influence of sugar components in the 1H-NMR spectrum of the juice sample by spectrum processing, thereby removing these interfering factors, so that the PLA-DA analysis can more accurately reflect the true component differences between different juice samples, improve the accuracy and reliability of the detection and analysis data, improve the quality control of juice and adulteration detection, and provide a reliable analysis method for juice quality evaluation and variety identification. Therefore, the accuracy and reliability of the detection and analysis data of the present invention are higher, and the operation is simple.

[0023] 2. In the detection method of using NMR to identify juice samples from different sources, the high-resolution NMR technology is used to analyze and detect the chemical components of juice, and the composition change information of juices from different sources, different varieties and different brands can be obtained, and the law of changes in the components of juices from different sources can be analyzed to perform real-time and dynamic analysis and detection. Therefore, the detection of the present invention is convenient and can be detected and queried in real time.

[0024] 3. In the detection method of using NMR to identify juice samples from different sources, various types of juice samples can be analyzed and compared in the laboratory. The specific data processing method can be adjusted and optimized according to actual needs to adapt to the characteristics and analysis requirements of different juice samples, while eliminating the interference of water peaks and sugar components, so as to more accurately reflect the inherent differences of juice samples. Therefore, the present invention can adapt to the detection of different fruits, and the analysis method is more flexible. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the NMR spectrum of the present invention. DETAILED DESCRIPTION

[0026] The present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0027] See also Figure 1 A method for identifying juice samples from different sources using NMR, the method comprising the following steps:

[0028] Step 1, obtaining a 1H-NMR spectrum of the juice sample to be analyzed;

[0029] Step 2: Perform hydrogen spectrum integration processing on the 1H-NMR spectrum of the obtained juice sample, identify and remove the residual water peak in the 1H-NMR spectrum, and obtain a dehydrated 1H-NMR spectrum;

[0030] Step 3, identifying each sugar component in the dehydrated peak 1H-NMR spectrum, and determining the chemical shift range of each sugar component, and recording each shift range to obtain a sugar-containing 1H-NMR spectrum;

[0031] Step 4: First remove the sugar peak interval in the sugar-containing 1H-NMR spectrum, then perform data normalization and calibration, and perform multivariate analysis after calibration to obtain the true component differences between the juice samples, so as to determine the authenticity of the juice.

[0032] The obtaining of the 1H-NMR spectrum of the juice sample to be analyzed refers to:

[0033] The acquired samples were placed on a Bruker Avance III 600MHz spectrometer. For each sample, the 90° pulse width was set to about 10-12μs, the spectrum width was set to 20ppm, the sampling points were 64K, the FID was accumulated 64 times, and all one-dimensional 1H-NMR spectra were multiplied by an exponential window function with a broadening factor of 1.0Hz before Fourier transformation. The data transformation points were 128K, thereby obtaining the 1H-NMR spectrum of the juice sample.

[0034] The proton resonance frequency is 600.13 MHz and the experimental temperature is set to 298.0 K.

[0035] Before collecting the 1H-NMR spectra of the juice sample, each spectrum was manually phase and baseline corrected.

[0036] The identifying and removing the residual water peak in the 1H-NMR spectrum refers to removing the signal in the range of δ5.0-4.68, which is the water peak removal operation.

[0037] The chemical shift range of each sugar component is determined as follows: TSP is added to the sample as an internal standard, and the chemical shift of this peak is positioned at 0 ppm. In the calibrated spectrum, the signals of sugar components such as glucose, sucrose, and fructose are between δ5.46-3.20.

[0038] The chemical shift range of each sugar component is δ5.46-3.20.

[0039] The removing of the sugar peak interval in the sugar-containing 1H-NMR spectrum refers to removing the signal in the chemical shift interval of δ5.46-3.20 of the sugar component.

[0040] The data normalization and calibration refers to: integrating the δ9.0-0.5 range in the 1H-NMR spectrum of each sample in sections and performing normalization processing at the same time, that is, dividing the integrated area of ​​each section by the sum of all integrated areas, and each integrated interval is 0.004 ppm.

[0041] After the data were normalized, the least partial squares discriminant was used for automatic normalization and standardization, and the inter-group distinction of metabolites was further analyzed.

[0042] The principle of the present invention is described as follows:

[0043] By using high-resolution NMR technology to analyze and detect the chemical components of fruit juice, we can obtain information on changes in the composition of fruit juice from different sources, varieties and brands. We can also analyze the patterns of changes in the ingredients of fruit juice from different sources to conduct real-time and dynamic analysis and detection.

[0044] Embodiment 1:

[0045] A detection method for identifying juice samples from different sources using NMR, the detection method for identifying juice samples from different sources using NMR comprising the following steps:

[0046] Step 1, obtaining a 1H-NMR spectrum of the juice sample to be analyzed;

[0047] Step 2: Perform hydrogen spectrum integration processing on the 1H-NMR spectrum of the obtained juice sample, identify and remove the residual water peak in the 1H-NMR spectrum, and obtain a dehydrated 1H-NMR spectrum;

[0048] Step 3, identifying each sugar component in the dehydrated peak 1H-NMR spectrum, and determining the chemical shift range of each sugar component, and recording each shift range to obtain a sugar-containing 1H-NMR spectrum;

[0049] Step 4: First remove the sugar peak interval in the sugar-containing 1H-NMR spectrum, then perform data normalization and calibration, and perform multivariate analysis after calibration to obtain the true component differences between the juice samples, so as to determine the authenticity of the juice.

[0050] Embodiment 2:

[0051] Embodiment 2 is substantially the same as Embodiment 1, except that:

[0052] The obtaining of the 1H-NMR spectrum of the juice sample to be analyzed refers to:

[0053] A detection method for identifying juice samples from different sources using NMR, wherein the obtained samples are placed on a Bruker Avance III 600 MHz spectrometer, and the 90° pulse width of each sample is set to about 10 μs, and the spectrum width is set to 20 ppm. The width of 20 ppm is set because the juice sample solution signal is distributed within 0 to 10 ppm, and the signal outside this range is a baseline signal. Selecting a 20 ppm sampling range is conducive to determining the baseline and facilitating data baseline correction. The number of sampling points is 64K, and the FID is accumulated 64 times to ensure that the spectrum processed from the collected data has a higher resolution. All one-dimensional 1H-NMR spectra are processed by multiplying the FID by an exponential window function with a broadening factor of 1.0 Hz before Fourier transformation. The number of data transformation points is 128K. In NMR experiments, when processing hydrogen spectra, the number of transformation points is usually twice that of the sampling points. When collecting NMR experimental data, the relaxation time of different substances varies. It may not be completely attenuated within one sampling time, and a truncation effect will occur when the spectrum is transformed (similar jagged lines appear on both sides of the bottom of the single peak). Doubling the number of processing points can effectively reduce this effect, making the spectrum peak smoother and more symmetrical, that is, improving the spectrum quality, thereby obtaining a 1H-NMR spectrum of the juice sample; the proton resonance frequency is 600.13 MHz, and the experimental temperature is set to 298.0 K; before collecting the 1H-NMR spectrum of the juice sample, each spectrum is manually phase and baseline corrected. Due to the differences in the physicochemical properties of each sample, the spectrum generated by the Fourier transform of the collected raw data will have phase differences, resulting in an uneven baseline, so the baseline needs to be adjusted. When adjusting the baseline, first set 0 ppm as the 0th order phase, and then adjust the 1st order phase to make the entire NMR spectrum baseline straight.

[0054] Embodiment 3:

[0055] Embodiment 3 is substantially the same as Embodiment 1, except that:

[0056] A detection method for identifying juice samples from different sources using NMR, wherein the obtained samples are placed on a Bruker Avance III 600 MHz spectrometer, the 90° pulse width of each sample is set to about 12 μs, the spectrum width is set to 20 ppm, the sampling points are 64K, the FID is accumulated 64 times, all one-dimensional 1H-NMR spectra are multiplied by an exponential window function with a broadening factor of 1.0 Hz before Fourier transformation, the data transformation points are 128K, so as to obtain the 1H-NMR spectrum of the juice sample; the proton resonance frequency is 600.13 MHz, and the experimental temperature is set to 298.0 K; before collecting the 1H-NMR spectrum of the juice sample, each spectrum is manually phase and baseline corrected.

[0057] Embodiment 4:

[0058] Embodiment 4 is substantially the same as Embodiment 1, except that:

[0059] A detection method for identifying juice samples from different sources using NMR, wherein the identification and removal of residual water peaks in 1H-NMR spectra refers to: removing signals in the range of δ5.0-4.68, i.e., removing water peaks. When processing NMR data of juice, water peaks are not analyzed as variables, so water signals must be removed, otherwise the data analysis will not be able to reflect the true differences between different juice samples; the determination of the chemical shift range of each sugar component is specifically: adding TSP as an internal standard to the sample, and positioning the chemical shift of this peak at 0ppm, and in the calibrated spectrum In the 1H-NMR spectrum, the signals of sugar components such as glucose, sucrose, and fructose are between δ5.46-3.20; the chemical shift range of each sugar component is δ5.46-3.20; the removal of the sugar peak interval in the sugar-containing 1H-NMR spectrum refers to: removing the signal in the chemical shift interval of the sugar component δ5.46-3.20. Since the proportion of sugar is quite high regardless of the source of the juice, the proportion of the sugar signal peak is quite large, which affects the signal peaks of other material components of the juice. By removing the chemical shift of sugar, juices from different sources can be easily distinguished;

[0060] The data normalization and calibration refers to: performing segmented integration of the δ9.0–0.5 range in the 1H-NMR spectrum of each sample, and performing normalization processing at the same time, that is, dividing the integrated area of ​​each segment by the sum of all integrated areas, and each integrated interval is 0.004ppm. Each integrated interval obtained is a variable factor reflecting the chemical components and their contents in the juice. In the spectrum collected on a 600MHz spectrometer, 0.004ppm is converted to 2.4Hz, which is exactly the same as the peak width. Using this width as the segmentation standard is conducive to fully extracting the spectrum information. Too large a segmentation will result in too low data resolution and cannot reflect subtle differences, while too small a segmentation will increase the difficulty of data analysis. Further analysis of the distinction between metabolites and groups, and finding the difference characteristics of juices from different sources from small molecule chemicals other than sugar components;

[0061] The normalized NMR data set was subjected to multivariate analysis using SIMCA-P+ software (version 11.0, Umetrics). In principal component analysis (PCA), mean-centered (Ctr) was used to standardize the data, and the results were presented in a Scores plot and a Coefficient Plot annotated with correlation coefficients. In order to determine the predictive quality of the model, i.e., the validity of the model, a permutation test was used to test the credibility of the model, with n=200 random permutations.

[0062] The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiment. Any equivalent modifications or changes made by ordinary technicians in this field based on the contents disclosed by the present invention should be included in the protection scope recorded in the claims.

Claims

1. A method for identifying juice samples from different sources using NMR, characterized in that: The detection method for identifying juice samples from different sources using NMR comprises the following steps: Step 1, obtaining a 1H-NMR spectrum of the juice sample to be analyzed; Step 2: Perform hydrogen spectrum integration processing on the 1H-NMR spectrum of the obtained juice sample, identify and remove the residual water peak in the 1H-NMR spectrum, and obtain a dehydrated 1H-NMR spectrum; Step 3, identifying each sugar component in the dehydrated peak 1H-NMR spectrum, and determining the chemical shift range of each sugar component, and recording each shift range to obtain a sugar-containing 1H-NMR spectrum; Step 4: First remove the sugar peak interval in the sugar-containing 1H-NMR spectrum, then perform data normalization and calibration, and perform multivariate analysis after calibration to obtain the true component differences between the juice samples, so as to determine the authenticity of the juice.

2. The method for identifying juice samples from different sources using NMR according to claim 1, characterized in that: The obtaining of the 1H-NMR spectrum of the juice sample to be analyzed refers to: The acquired samples were placed on a Bruker Avance III 600MHz spectrometer. For each sample, the 90° pulse width was set to about 10-12μs, the spectrum width was set to 20ppm, the sampling points were 64K, the FID was accumulated 64 times, and all one-dimensional 1H-NMR spectra were multiplied by an exponential window function with a broadening factor of 1.0Hz before Fourier transformation. The data transformation points were 128K, thereby obtaining the 1H-NMR spectrum of the juice sample.

3. The method for identifying juice samples from different sources using NMR according to claim 2, characterized in that: The proton resonance frequency is 600.13 MHz and the experimental temperature is set to 298.0 K.

4. The method for identifying juice samples from different sources using NMR according to claim 3, characterized in that: Before collecting the 1H-NMR spectra of the juice sample, each spectrum was manually phase and baseline corrected.

5. The method for identifying juice samples from different sources using NMR according to claim 1, characterized in that: The identifying and removing the residual water peak in the 1H-NMR spectrum refers to removing the signal in the range of δ5.0-4.68, which is the water peak removal operation.

6. The method for identifying juice samples from different sources using NMR according to claim 1, characterized in that: The chemical shift range of each sugar component is determined as follows: TSP is added to the sample as an internal standard, and the chemical shift of this peak is positioned at 0 ppm. In the calibrated spectrum, the signals of sugar components such as glucose, sucrose, and fructose are between δ5.46-3.

20.

7. The method for identifying juice samples from different sources using NMR according to claim 6, characterized in that: The chemical shift range of each sugar component is δ5.46-3.

20.

8. The method for identifying juice samples from different sources using NMR according to claim 7, characterized in that: The removing of the sugar peak interval in the sugar-containing 1H-NMR spectrum refers to removing the signal in the chemical shift interval of δ5.46-3.20 of the sugar component.

9. The method for identifying juice samples from different sources using NMR according to claim 1, characterized in that: The data normalization and calibration refers to: integrating the δ9.0-0.5 range in the 1H-NMR spectrum of each sample in sections and performing normalization processing at the same time, that is, dividing the integrated area of ​​each section by the sum of all integrated areas, and each integrated interval is 0.004 ppm.

10. The method for identifying juice samples from different sources using NMR according to claim 9, characterized in that: After the data were normalized, the least partial squares discriminant was used for automatic normalization and standardization, and the inter-group distinction of metabolites was further analyzed.

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