CN113049560B - Method for identifying honey and syrup - Google Patents
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- 235000012907 honey Nutrition 0.000 title claims abstract description 118
- 235000020357 syrup Nutrition 0.000 title claims abstract description 54
- 239000006188 syrup Substances 0.000 title claims abstract description 54
- 238000000034 method Methods 0.000 title claims abstract description 17
- 230000005284 excitation Effects 0.000 claims abstract description 37
- 238000001514 detection method Methods 0.000 claims abstract description 29
- 238000002189 fluorescence spectrum Methods 0.000 claims abstract description 22
- 238000002156 mixing Methods 0.000 claims abstract description 5
- 239000012153 distilled water Substances 0.000 claims abstract description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 4
- 238000012216 screening Methods 0.000 claims abstract description 3
- 238000005259 measurement Methods 0.000 claims 1
- 238000001506 fluorescence spectroscopy Methods 0.000 abstract description 4
- 230000007547 defect Effects 0.000 abstract description 3
- 230000008569 process Effects 0.000 abstract description 3
- 239000002699 waste material Substances 0.000 abstract description 2
- 239000000126 substance Substances 0.000 description 8
- 230000000052 comparative effect Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 240000007472 Leucaena leucocephala Species 0.000 description 4
- 235000010643 Leucaena leucocephala Nutrition 0.000 description 4
- 238000001228 spectrum Methods 0.000 description 4
- 235000016068 Berberis vulgaris Nutrition 0.000 description 3
- 241000335053 Beta vulgaris Species 0.000 description 3
- 240000007594 Oryza sativa Species 0.000 description 3
- 235000007164 Oryza sativa Nutrition 0.000 description 3
- 238000010521 absorption reaction Methods 0.000 description 3
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- 238000003860 storage Methods 0.000 description 3
- 238000005481 NMR spectroscopy Methods 0.000 description 2
- 240000002853 Nelumbo nucifera Species 0.000 description 2
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 2
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 2
- 240000008042 Zea mays Species 0.000 description 2
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 2
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 2
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- 238000010586 diagram Methods 0.000 description 2
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- 238000002290 gas chromatography-mass spectrometry Methods 0.000 description 2
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- 238000007619 statistical method Methods 0.000 description 2
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- MIDXCONKKJTLDX-UHFFFAOYSA-N 3,5-dimethylcyclopentane-1,2-dione Chemical compound CC1CC(C)C(=O)C1=O MIDXCONKKJTLDX-UHFFFAOYSA-N 0.000 description 1
- 206010003591 Ataxia Diseases 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 238000001237 Raman spectrum Methods 0.000 description 1
- 241001495449 Robinia pseudoacacia Species 0.000 description 1
- 238000000692 Student's t-test Methods 0.000 description 1
- 240000008866 Ziziphus nummularia Species 0.000 description 1
- 238000000540 analysis of variance Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000009341 apiculture Methods 0.000 description 1
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- 239000002562 thickening agent Substances 0.000 description 1
- 238000000870 ultraviolet spectroscopy Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6402—Atomic fluorescence; Laser induced fluorescence
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N2021/6417—Spectrofluorimetric devices
Abstract
The invention relates to a method for identifying honey and syrup, which comprises the following steps of: (1) Screening a sample to be detected, dissolving the sample in distilled water according to a certain proportion, and uniformly mixing by an oscillator for later use; (2) fluorescence density detection: recording the fluorescence emission spectrum with the emission wavelength of 300 to 550nm with the excitation wavelength of 280nm, and counting the maximum fluorescence density and the corresponding emission wavelength; (3) 3-D fluorescence spectrometry: the fluorescence spectrophotometer records the excitation wavelength and the emission wavelength and records the 3-D fluorescence spectrum; the final result of the 3-D fluorescence spectrum is shown as a set of numerical data in the form of a contour plot. The invention overcomes the defects of complex sample pretreatment, complicated process, high professional degree, inconvenient operation and time and labor waste in other detection methods, and establishes a simple, quick, effective, time-saving and labor-saving honey authenticity detection means.
Description
Technical Field
The invention relates to an identification method, in particular to a method for identifying honey and syrup by a fluorescence spectrum detection method.
Background
The honey adulteration phenomenon in the current market is serious, so that the rights and interests of consumers are seriously endangered, and the healthy development of the honey industry is destroyed. The adulteration phenomenon mainly comprises: (1) Pure syrup honey is mainly prepared by blending high fructose syrup, caramel pigment and essence; (2) Mixing part of syrup honey, adding rice syrup, fructose syrup, etc. into part of honey; (3) Honey source adulteration: low-priced honey (mainly rape honey) is added to high-priced honey to make more profit. The quality control of honey becomes an important issue of attention, and is one of the problems puzzling the global bee keeping industry, and the authenticity evaluation of honey is a problem to be solved urgently at present. The establishment of the simple, quick, effective, time-saving and labor-saving honey authenticity detection method has important significance for honey quality control.
Although there are many standards for honey detection at present, such as national standards for honey detection (GB 14963-2011), standards for the industry of supply and marketing cooperation (GHT 18796-2012) and imported and exported honey inspection regulations (SNT 0852-2012), these standards cannot fundamentally solve the problem of honey adulteration. Traditional honey detection methods such as (1) pollen identification are very time consuming, require experienced analysts and rely strongly on expert ability and judgment; (2) Sensory identification methods are susceptible to being affected during honey processing, storage and crystallization. With the use of pigments, syrups and thickeners, the organoleptic properties of honey change greatly. Meanwhile, sensory authentication is artificially participated, and has subjectivity; (3) Physical and chemical index identification is time-consuming and labor-consuming, and certain physical and chemical indexes can be changed in the honey processing and storage processes, so that the result is accidental. Modern detection methods such as (1) gas chromatography-mass spectrometry (GCMS), high performance liquid chromatography (HPLC-MS) and combined technology thereof require early treatment of honey samples, and are time-consuming, labor-consuming, high in professional requirements and expensive in instruments; (2) Nuclear Magnetic Resonance (NMR) techniques, stable isotope detection techniques, expensive instrumentation, and reliance on professionals; (3) The artificial intelligent detection technology such as an electronic nose and an electronic tongue is a comprehensive chemical sensor established based on a biological taste mode and a liquid analysis instrument for mode identification, has high sensitivity, but mainly aims at detecting volatile components in honey; (4) Gene detection techniques such as DNA detection techniques rely primarily on a detection method of proteins and major enzymes in honey, but are not very accurate; (5) The spectrum detection technology, such as Raman spectrum, infrared spectrum and fluorescence spectrum detection technology, is mainly based on the substance of honey, does not need complex treatment on a sample in the early stage, can realize rapid and nondestructive detection, has high sensitivity, and is a powerful tool for detecting the authenticity of the honey.
The invention provides an identification method for detecting the authenticity of honey based on a fluorescence spectrum technology.
Disclosure of Invention
The invention aims to provide a simple and rapid method for identifying honey and syrup aiming at the defects of the prior art.
A method for identifying honey and syrup by fluorescence spectrum detection, comprising the following steps:
(1) Screening a sample to be detected, dissolving the sample in distilled water according to a certain proportion, and uniformly mixing by an oscillator for later use;
(2) Fluorescence density detection: recording the fluorescence emission spectrum with the emission wavelength of 300-550 nm with the excitation wavelength of 280nm, and counting the maximum fluorescence density and the corresponding emission wavelength;
(3) 3-D fluorescence spectrometry: the fluorescence spectrophotometer records the excitation wavelength and the emission wavelength and records the 3-D fluorescence spectrum; the final result of the 3-D fluorescence spectrum is shown as a set of numerical data in the form of a contour plot.
In the preferred scheme, in the step (2), parameters are set as follows: increase by 1nm; slit: at excitation and emission, 1.5.
In the preferred scheme, in the step (3), parameters are set as follows: the excitation wavelength is from 200 to 450nm, with a step size of 10nm, the emission wavelength is from 260 to 560nm, with a step size of 10 nm.
The method preferably further comprises the step of (4) fluorescence lifetime detection: fluorescence lifetime of different samples was measured at a fixed excitation wavelength recorded with a fluorescence spectrometer, the fluorescence lifetime graph was fitted by Origin 8, and the fluorescence lifetime of different samples was calculated by the following formula
The invention has the advantages that:
(1) The invention overcomes the defects of complex sample pretreatment, complicated process, high professional degree, inconvenient operation and time and labor waste in other detection methods, and establishes a simple, quick, effective, time-saving and labor-saving honey authenticity detection method;
(2) The invention can further improve the identification accuracy through mutual verification of three different fluorescence spectrum detection means.
Drawings
FIG. 1 is a graph of fluorescence density at 280nm excitation for different samples; a, b, collecting a fluorescent spectrum chart of the locust honey in Taian and Zibo areas in 2019; c, d, collecting a fluorescent spectrum diagram of the locust honey in Taian and Zibo areas in 2020; e, a fluorescent spectrum chart of locust honey purchased randomly by a supermarket; f, fluorescence spectrum of syrup. SS, randomly purchased supermarket honey; TJ, syrup;
FIG. 2 is a 3-D fluorescence contour plot of different samples; a-D, four different regions of acacia honey 3-D fluorescence contour map in 2019 (lotus, taan, catalbo, jujube); e-h, four different regions of acacia honey 3-D fluorescence contour map in 2020 (Yiyi, taian, zibo, zaozhuang); i, a honey 3-D fluorescence contour map purchased randomly by a supermarket; j-l, 3-D fluorescence contour map of three syrups (TJ 01 rice syrup; TJ04 invert sugar; TJ05 beet syrup)
FIG. 3 is a graph of a 2019 honey fluorescence lifetime fit; a, a fluorescent lifetime fitting chart of locust honey in the Jinan area in 2019; b, a fluorescent lifetime fitting chart of locust honey and syrup in the south-ataxia area in 2019.
FIG. 4 is a graph showing a fluorescent lifetime fit of locust honey in 2020; a, a fluorescent life fitting chart of locust honey in a Zibo region in 2020; b, a fluorescent lifetime fitting chart of locust honey and syrup in the Zibo region in 2020.
FIG. 5 is a plot of fluorescence lifetime fit for supermarket randomly purchased honey and syrup; a, a black locust honey fluorescence lifetime fitting map purchased randomly by a supermarket; b, fluorescent lifetime fitting graph of locust honey and syrup purchased randomly by supermarket.
Detailed Description
The present invention will be specifically described below by way of examples. It is noted herein that the following examples are given solely for the purpose of illustration and are not to be construed as limiting the scope of the invention, as many insubstantial modifications and variations of the invention will become apparent to those skilled in the art in light of the above disclosure.
Example 1
(1) Collection and storage of honey samples:
collecting acacia honey (lotus, taian, linyi, zaozhuang, jinan, zibo, weifang, jining) in Shandong region 2019;
(2) Treatment of the honey sample:
20 μl of the sample was dissolved in 1mL distilled water and mixed well with a shaker for use. 1cm quartz cuvette.
(3) Detecting the index:
(1) fluorescence density detection: the excitation wavelength was 280nm and the fluorescence emission spectra were recorded at emission wavelengths of 300 to 550nm (1 nm increase; slit: 1.5 at both excitation and emission).
(2) 3-D fluorescence spectrometry: the fluorescence spectrophotometer records the excitation wavelength (from 200 to 450nm in steps of 10 nm) and the emission wavelength (from 260-560nm in steps of 10 nm) and the 3-D fluorescence spectrum. The final result of the 3-D fluorescence spectrum is shown as a set of numerical data in the form of a contour plot.
(3) Fluorescence lifetime detection
When a substance is excited by a beam of laser, the molecules of the substance absorb energy and then transition from a ground state to an excited state, and then fluoresce in a radiation transition mode to return to the ground state. When excitation light is removed, the time required for the fluorescence intensity of the molecule to drop to 1/e of the maximum intensity I0 of fluorescence upon excitation is called fluorescence lifetime and is commonly denoted by τ. Fluorescence lifetimes of different honey samples at fixed excitation wavelengths were recorded with a fluorescence spectrometer. The fluorescence lifetime plots were fitted by Origin 8 and the fluorescence lifetimes of the different samples were calculated by the following formula.
(4) Statistical analysis
All experiments were independently repeated at least 3 times. Data are expressed as mean ± SD. Statistical analysis involved paired Student t-test and ANOVA using SPSS version 18.0. P-values < 0.05 are considered to indicate statistically significant differences.
Example 2
Unlike example 1, the samples were selected from honey (Jining, taian, lin, zaozhuang, jinan, zibo, weifang, chat) in the mountain eastern region of 2020; the other steps are unchanged.
Example 3
Unlike example 1, the samples were chosen for 6 types of locust honey purchased randomly at the supermarket; the other steps are unchanged.
Comparative example 1
Unlike example 1, 5 syrups (corn syrup 1, corn syrup 2, rice syrup, invert sugar, beet syrup) were selected for the samples; the other steps are unchanged.
Results:
1. fluorescence density detection result
And measuring the maximum absorption wavelength of the locust honey by adopting an ultraviolet-visible spectrophotometer, and taking the maximum absorption wavelength as the excitation wavelength of the locust honey. Whereas the maximum absorption wavelength of most honey samples is around 280nm, we selected 280nm as the excitation wavelength for all samples. The maximum fluorescence intensities measured at 280nm excitation wavelength were significantly different for the different samples (Table 1).
TABLE 1 maximum fluorescence intensities for different samples at an excitation wavelength of 280nm
Example 1 a honey sample (n=80) taken from 2019; example 2a 2020 honey sample was taken (n=80); example 3 commercial honey (n=6); comparative example 1 syrup (n=5). Data are shown as mean plus or minus standard deviation (mean ± SD). The different letters (a, b, c) in each column represent significant differences calculated using Turkey.
The maximum fluorescence intensity of the honey sample of example 2 was higher than that of the honey of example 1, and the maximum fluorescence intensity of the honey sample purchased in example 3 was lower than that of the raw honey sample, but higher than that of the syrup sample. The fluorescence intensity of the five different syrups was much lower than that of the honey sample. Corresponding to the emission wavelength of the maximum fluorescence. The honey samples of example 1 and example 2 have no obvious difference in intensity; about 338nm and 337nm, respectively (fig. 1).
In addition, the emission wavelength corresponding to the maximum fluorescence intensity of different syrups is more than 370 nm. The same phenomenon was also found in some of the processed locust honey samples, which indicated that the maximum fluorescence intensity of the mixed syrup or concentrated honey corresponds to a significant red shift in the emission wavelength.
From the above results, it can be seen that although the content of fluorescent substance in the honey sample was decreased with the lapse of time, there was no significant difference in emission wavelength corresponding to the maximum fluorescence intensity in the honey sample.
In combination with the maximum fluorescence intensity and its corresponding emission wavelength, the adulterated honey can be easily distinguished.
2. Three-dimensional fluorescence spectrometry of different honey samples and syrups
The fluorescence spectra of different samples were further tested using three-dimensional fluorescence spectra with excitation wavelength ranges from 200 to 440nm and emission wavelength ranges from 260 to 560 nm. In addition, two major peaks appear in most honey samples, one with excitation wavelengths around 240nm and one with excitation wavelengths around 280 nm. The peak for 280nm excitation is higher than the peak for 240nm excitation (FIGS. 2 a-h). The difference between the maximum peaks of the samples of example 1 honey, example 2 honey, example 3 and comparative example 1 was not significant at excitation wavelengths around 240nm, and the distinction was not significant; the maximum peak difference between different samples is significant at excitation wavelengths around 280nm, with the order of peak from high to low: example 2 locust honey, example 1 locust honey, example 3 honey, which shows that the content of fluorescent substances in the honey sample decreases with time, which is consistent with the previous fluorescent density results. In the locust honey samples of examples 1 and 2, the excitation wavelength and emission wavelength corresponding to the maximum peak were 280nm and 350nm, respectively (fig. 2). At the 280nm excitation wavelength, the peak of the syrup was much lower than that of the honey sample (table 2).
TABLE 2 maximum peak values for different samples at different excitation wavelengths
Example 1 a honey sample (n=80) taken from 2019; example 2a 2020 honey sample was taken (n=80); example 3 commercial honey sample (n=6); comparative example 1 syrup (n=5). Data are shown as mean plus or minus standard deviation (mean ± SD). The different letters (a, b, c) in each column represent significant differences calculated using Turkey.
The three-dimensional fluorescence contour map of 5 syrups is significantly different from that of the locust honey sample, and the fluorescence contour map of beet syrup is completely different from that of other samples. The highest peaks of the other four syrups also correspond to excitation wavelengths different from the locust honey samples (fig. 2 i-l).
Under 280nm excitation, the acacia honey can be distinguished from the concentrated honey and syrup by a three-dimensional contour diagram and a corresponding highest peak value.
3. Fluorescence lifetime determination of different honey samples and syrups
Examples 1 and 2 the fluorescence lifetime of the honey samples, the supermarkets randomly purchased locust honey and syrup were different. As shown in table 3, there was no significant difference in fluorescence lifetime between the honey samples of example 1 and example 2. However, the fluorescence lifetime of the syrup is significantly higher than that of the honey sample. The fluorescent lifetime of the randomly purchased samples of locust honey in example 3 was higher than that of the locust honey but lower than that of the syrup. And the honey, the locust honey purchased randomly in supermarkets and the syrup can be obviously distinguished through the fitted fluorescence lifetime graph. The fluorescent lifetime plots of the locust honey of example 1 and example 2 almost completely overlap, as distinguished from the random purchases of locust honey and syrup by supermarkets (fig. 3-4). In addition, it is difficult to distinguish between the random purchases of locust honey and syrup by supermarkets through fitted fluorescence lifetime maps. (FIG. 5). In summary, honey, locust honey purchased randomly in supermarkets and syrup can be easily distinguished by fluorescence lifetime and fitted fluorescence pattern.
TABLE 3 fluorescence lifetime of different samples
Example 1 a honey sample (n=80) taken from 2019; example 2a 2020 honey sample was taken (n=80); example 3 commercial honey sample (n=6); comparative example 1 syrup (n=5). Data are shown as mean plus or minus standard deviation (mean ± SD). The different letters (a, b, c) in each column represent significant differences calculated using Turkey.
Claims (2)
1. A method for identifying honey and syrup, which is characterized in that the honey is locust honey, and the method is identified by a fluorescence spectrum detection method and comprises the following steps:
(1) Screening a sample to be detected, dissolving the sample in distilled water according to a certain proportion, and uniformly mixing by an oscillator for later use;
(2) Fluorescence intensity detection: recording fluorescence emission spectra with emission wavelengths of 300 to 550 and nm according to the excitation wavelength of 280nm, and counting the maximum fluorescence intensity and the corresponding emission wavelength; wherein the fluorescence intensity of the syrup is lower than that of the honey, the emission wavelength corresponding to the maximum fluorescence intensity of the syrup has obvious red shift phenomenon, and the honey and the syrup can be distinguished by combining the maximum fluorescence intensity and the emission wavelength corresponding to the maximum fluorescence intensity;
(3) Three-dimensional fluorescence spectrum measurement: measuring three-dimensional fluorescence spectra of the sample under different excitation wavelength ranges and emission wavelength ranges by adopting a fluorescence spectrophotometer; the final result of the three-dimensional fluorescence spectrum is displayed as a set of numerical data in the form of a contour plot; wherein the peak of the syrup is much lower than the peak of the honey under 280nm excitation; the honey and the syrup can be distinguished by a three-dimensional contour plot and a corresponding highest peak under 280nm excitation;
(4) Fluorescence lifetime detection: recording fluorescence lifetimes of different samples at a fixed excitation wavelength by adopting a fluorescence spectrometer, wherein the fixed excitation wavelength is 280 nm; the fluorescence lifetime map was fitted by Origin 8 and the fluorescence lifetimes of the different samples were calculated by the following formula:
；
wherein the fluorescence lifetime of the syrup is significantly higher than the fluorescence lifetime of the honey, and the honey and the syrup can be distinguished by the fluorescence lifetime and the fitted fluorescence lifetime map.
2. A method of identifying honey from syrup as claimed in claim 1 wherein in step (3) the parameters are set to: the excitation wavelength range is 200-440 nm, and the step length is 10 nm; the emission wavelength ranges from 260 to 560nm with a step size of 10 nm.
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| CN108375561A (en) * | 2018-03-05 | 2018-08-07 | 天津工业大学 | A method of quickly identification and quantitative analysis are carried out to adulterated honey based on three-dimensional fluorescence spectrum technology |
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| CN108375561A (en) * | 2018-03-05 | 2018-08-07 | 天津工业大学 | A method of quickly identification and quantitative analysis are carried out to adulterated honey based on three-dimensional fluorescence spectrum technology |
| CN108645829A (en) * | 2018-05-15 | 2018-10-12 | 中国农业科学院蜜蜂研究所 | A kind of method of quick identification honey types and adulterated honey |
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