CN111413332B

CN111413332B - A method for distinguishing carbohydrates based on natural pigment anthocyanin

Info

Publication number: CN111413332B
Application number: CN202010272744.4A
Authority: CN
Inventors: 张凌; 闫姝君; 黄卉; 李永新; 李娇
Original assignee: Jilin University
Current assignee: Jilin University
Priority date: 2020-04-09
Filing date: 2020-04-09
Publication date: 2021-07-23
Anticipated expiration: 2040-04-09
Also published as: CN111413332A

Abstract

The invention discloses a method for distinguishing saccharides based on natural extract anthocyanin, belonging to the technical field of detection. The invention constructs a colorimetric array sensor detection system based on the color change of anthocyanin, which provides a method for distinguishing and distinguishing different saccharides. new method. Intermolecular interactions between different analytes and different active centers result in colorimetric changes that generate unique complex responses. The detection target forms a unique fingerprint, and through the visual digital imaging method, the overall process of the reaction is quantified to realize the differential analysis process of the sample. The colorimetric array sensor constructed based on anthocyanin in the present invention uses safe and harmless anthocyanins instead of chemically responsive dyes for the first time to complete the discrimination and identification of natural sugars. On the basis of division, each sugar can be clustered individually without any overlap and misjudgment.

Description

Saccharide distinguishing method based on natural pigment anthocyanin

Technical Field

The invention belongs to the technical field of detection, and particularly relates to a saccharide distinguishing method based on natural extract anthocyanin.

Background

Saccharides, a major biological material, are the largest class of compounds, vary in molecular weight from monosaccharides to polysaccharides, and play a fundamental role in various biological phenomena. In recent years, global soft drink consumption has increased dramatically. High sugar content in soft drinks is associated with certain cardiovascular diseases, obesity, dental caries and diabetes. In view of food safety and health care which people are pursuing increasingly, it is very effective to determine the kind and content of the added saccharides in soft drinks as important indexes for identifying the excellent quality of soft drinks. In addition, in other fields of food engineering, such as food fermentation, quality control is also closely related to carbohydrate analysis. Therefore, there is an increasing interest in analytical detection studies of carbohydrates. Since most sugars have only one functional group, the "hydroxyl", and many isomeric compounds, branched structures, and chromophore-lacking structures are present in the sugar molecule. We can only start with the analysis of both spatial conformation of a certain hydroxyl group and the number of different hydroxyl groups, and the analytical classification identification of carbohydrates is a challenging task. To date, most carbohydrate sensors are based on enzymatic reactions. The interaction of specific enzyme and sugar is usually required to form a traditional substrate-enzyme 'lock-key model', the selectivity is good, but the use of enzyme has important defects such as low durability and reproducibility, and the detection process is expensive and time-consuming, thereby increasing the difficulty of distinguishing each specific sensing unit in a complex mixture. Therefore, there is an urgent need for a practical method to detect and differentiate saccharides to assist in daily, real-time food quality control in the field.

Colorimetric sensor arrays effectively overcome the limitations of conventional enzyme reaction-based array sensors. Consisting of a multi-element sensor, where the sensing material making up the array is typically a chemically responsive dye (porphyrin derivative, pH indicator dye, etc.), structurally similar target analytes can be distinguished by overall cross-response of the corresponding color changes in the sensor elements of the array. However, the conventional chemical dyes have the problems of toxic, teratogenic, carcinogenic and the like, and are not suitable for application in the food industry. The anthocyanin is used as a natural colorant, has wide source and abundant resources, is convenient to extract, and is an effective substitute for a synthetic colorant which has toxic action on human bodies.

Disclosure of Invention

In order to solve the defects of the array sensor in the identification of the carbohydrate, the invention provides a novel method for distinguishing and identifying the carbohydrate, which is low in cost, safe and harmless. A colorimetric array sensor detection system taking natural extract anthocyanin as a sensing element is constructed. The colorimetric array sensor technology is a multidimensional sensing technology, and the molecular interaction between different analytes and different active centers causes the colorimetric change to generate unique composite response. The detection target object forms a unique fingerprint, and the whole reaction process is quantified by a visual digital imaging method to realize the process of differential analysis of the sample.

In order to achieve the above purpose, the invention adopts the following technical scheme:

a saccharide distinguishing method based on natural extract anthocyanin comprises the following specific steps:

(1) and preparing an array sensor: mixing anthocyanins extracted from five different anthocyanidin extraction sources in different proportions to serve as each sensing unit of the colorimetric array sensor, and preparing the colorimetric sensor array with multiple sensing units;

(2) and differential detection of different saccharides: respectively adding the prepared 3-nitrophenylboronic acid solution into 11 sugar solutions, wherein the response time is 1-5 minutes, respectively adding the sugar solutions into the colorimetric sensor array with multiple sensing units in the step (1), placing the reaction solution into 1ml of centrifuge tubes, and placing the centrifuge tubes of experiments in the same group on the same plane of a photographic box; placing the smart phone in front of a dark box, and collecting an array image; obtaining pre-reaction image information (blank analyte solution) as initial image information; photoshop CC is used for reading change conditions of red, green and blue (RGB) values in an image to serve as characteristic signals representing chemical property changes before and after reaction, obtained data are introduced into SPSS software to be subjected to linear discriminant analysis, feature vectors of the first two linear discriminant functions obtained through analysis are respectively used as a first factor and a second factor, the first factor is used as a horizontal coordinate, the second factor is used as a vertical coordinate, and a score map of 11 kinds of sugar is obtained. In the LDA score map, 11 sugars of different species are well separated;

differential detection of carbohydrates in real samples: selecting commercially available beverages with different sugar contents and sugar types, respectively adding 3-nitrophenylboronic acid/phosphate buffer solution with the pH of 7.4, reacting for 1-5 minutes, then adding into the colorimetric sensor array with multiple sensing units in the step (1), and fully mixing; placing the reaction solution into a 1ml centrifuge tube, and placing the centrifuge tubes in the same group of experiments on the same plane of a photographic box; placing the smart phone in front of a dark box, and collecting an array image; obtaining pre-reaction image information (blank analyte solution) as initial image information; reading the change condition of red, green and blue (RGB) values in the image by using Photoshop CC as a characteristic signal for representing the change of chemical properties before and after reaction; the obtained data are imported into SPSS software for linear discriminant analysis, feature vectors of the first two linear discriminant functions obtained through analysis are respectively used as a first factor and a second factor, the first factor is used as a horizontal coordinate, the second factor is used as a vertical coordinate, score maps of six kinds of commercially available beverages are obtained, and 11 kinds of sugars of different kinds are well distinguished in the LDA score maps;

further, the anthocyanin extracting solution in the step (1) is extracted from dried lycium ruthenicum, dried carnation flower tea, dried myosotis sylvatica flower tea, dried mulberry fruit or dried Chinese rose flower tea; the extraction method specifically comprises the steps of respectively crushing the raw materials, placing the obtained dry powder raw materials in a brown bottle to be stored in a dark place, selecting anhydrous ethanol with the mass fraction of 70% as an extracting agent, and mixing the extracting agent with the raw materials according to the material-liquid ratio of 1-2: mixing 20-30g/ml, leaching in a water bath at 50 ℃ for 3-5h, taking out, performing suction filtration by using a vacuum suction filtration device to obtain a pigment leaching solution, performing rotary evaporation and concentration at 50 ℃, and mixing the pigment leaching solution and the pigment leaching solution according to a material-liquid ratio of 2: 5 (wt%) and storing at low temperature in dark place.

Further, the anthocyanidin extracted from different anthocyanidin extraction sources in the step (1) is lycium ruthenicum anthocyanin, carnation anthocyanin, myosotis anthocyanin, mulberry anthocyanin and Chinese rose anthocyanin.

Further, the anthocyanin leaching liquor is added into a reaction system in an amount of 1.5% -2% (V/V) of lycium ruthenicum anthocyanin, 1.5% -2% (V/V) of carnation anthocyanin, 3% -4% (V/V) of myosotis anthocyanin, 1.5% -2% (V/V) of mulberry anthocyanin and 1.5% -2% (V/V) of China rose anthocyanin; the reaction system is a system formed by sugar solution and 3-nitrophenylboronic acid/phosphoric acid buffer solution.

Further, the anthocyanins in the step (1) are mixed according to different proportions, which are specifically as follows:

further, the eleven sugars in the step (2) are fructose, xylose, D-arabinose, mannitol, D-sorbitol, xylitol, galactose, D-ribose, sucrose, maltitol and D-anhydrous glucose; wherein fructose, xylose, D-arabinose, galactose, D-ribose, sucrose, maltitol and D-anhydrous glucose are saccharides, and mannitol, D-sorbitol, xylitol and maltitol are sugar alcohols.

Further, the sugar solution concentration in the step (2) is 25-100mM, the prepared 3-nitrophenylboronic acid solution is 50-200mM, the 3-nitrophenylboronic acid is dissolved in 1-10mM phosphate buffer, and the pH of the solution is adjusted to 7.4 by using 0.5M NaOH;

the 3-nitrophenylboronic acid/phosphate buffer solution with pH 7.4 of 150 mM and the 3-nitrophenylboronic acid with 200mM are dissolved in a phosphate buffer solution with 1-10mM, and the pH of the solution is adjusted to 7.4 with 0.5-1M NaOH.

The principle of the invention is as follows:

under physiological pH, boric acid is tightly combined with a diol-containing high-affinity compound through the formation of boric acid ester, so that the pH of the solution is changed, anthocyanins are different in color under different pH, the molecules of different anthocyanins are subjected to a co-color reaction, and the two color changes are synergistic and interacted, so that sugar can be distinguished only by visual observation.

Compared with the prior art, the invention has the following advantages:

the colorimetric array sensor is widely applied to a distinguishing and identifying method, but no report is found for constructing a sensor by using natural extract anthocyanin as a sensing element. The adoption of healthy and safe natural pigments to replace chemical dyes and the successful application of the natural pigments to the distinguishing and identifying of carbohydrate substances shows that the natural pigments can replace the chemical pigments to be applied to a simple array sensor to distinguish closely related analytes. The differential analysis work of the anthocyanin on the saccharides provides a new idea for the application of the anthocyanin in the field of food analysis and detection.

Drawings

FIG. 1 is a linear discriminant analysis (IDA) spectrum of the response of the colorimetric array sensor to the same concentration of sugar and different concentrations, with 5 parallel experiments;

FIG. 2 is a linear discriminant analysis spectrum of responses of a commercially available beverage and a colorimetric array sensor according to the present invention, wherein experiments are performed in parallel for 5 times.

Detailed Description

In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

(1) and preparing an array sensor: dissolving 50-200mM of 3-nitrophenylboronic acid in 1-10mM of phosphate buffer, and adjusting the pH to 7.4 with 0.5-1M of NaOH; mixing the extracted anthocyanin leaching liquor in 16 modes and different proportions.

The anthocyanidin is mixed according to different proportions, and is specifically shown in the following table:

TABLE 1 anthocyanins in various proportions

(2) And differential detection of different saccharides: respectively adding 11 sugar solutions into the 3-nitrophenylboronic acid/phosphate buffer solution in the step (1), wherein the response time is 1-5 minutes, reading the change of red, green or blue values of the colorimetric array sensor, namely delta R, delta G and delta B, converting the color change degree into a numerical value and performing linear discriminant analysis, wherein the linear discriminant analysis is that a data set obtained by using the colorimetric array sensor for different sugars is a given training set, and the training set is projected onto a straight line through a dimension reduction thought of the linear discriminant analysis, so that the projection points of the same kind of sugar data set are as close as possible, and the projection points of the different kind of sugar data sets are as far as possible. And (4) deriving a linear discriminant function, arranging the eigenvalues from large to small, and taking the eigenvectors corresponding to the two former eigenvalues, namely the linear discriminant function. Reducing the data of the training set to a two-dimensional space by using the two linear discriminant functions, namely an obtained score map, and realizing the identification and distinguishing work of eleven saccharides through the score map;

(3) and distinguishing and detecting the carbohydrate substances in the actual sample: adding six commercially available drinks with different sugar contents and sugar types into the 3-nitrophenylboronic acid/phosphate buffer solution in the step (1) respectively, wherein the reaction time is 1-5 minutes. Reading the change of the red, green or blue value of the colorimetric array sensor, namely delta R, delta G and delta B, converting the color change degree into a numerical value and performing linear discriminant analysis, wherein the linear discriminant analysis is that different saccharides use a data set obtained by the colorimetric array sensor as a given training set, and the training set is projected onto a straight line through the dimension reduction thought of the linear discriminant analysis, so that the projection points of the same kind of saccharide data sets are as close as possible, and the projection points of the different kind of saccharide data sets are as far away as possible. And (4) deriving a linear discriminant function, arranging the eigenvalues from large to small, and taking the eigenvectors corresponding to the two former eigenvalues, namely the linear discriminant function. And reducing the data of the training set to a two-dimensional space by using the two linear discriminant functions, namely obtaining a score map, and realizing the identification and distinguishing work of six kinds of commercially available beverages with different sugar types and contents through the score map.

Example 1 identification and differentiation of eleven saccharides

Adding 100mM fructose, xylose, D-arabinose, mannitol, D-sorbitol, xylitol, galactose, D-ribose, sucrose, maltitol and D-anhydrous glucose solution into the 3-nitrophenylboronic acid/phosphate buffer solution, reacting for 1-5 minutes, respectively adding each sensing unit (anthocyanin extract) of the colorimetric array sensor, and reacting in a 1mL centrifuge tube. The sensing units of the colorimetric array sensor for detecting the sugar react with different sugars to generate different color changes respectively. The centrifugal tubes of the same group of experiments are arranged on the same plane of the photographic box. The smart phone is placed in front of a dark box, and an array image is collected. Pre-reaction image information (blank analyte solution) was obtained as initial image information. Photoshop CC is used for reading red, green and blue (RGB) values in the image as characteristic signals for representing the change of chemical properties before and after reaction. Reading RGB values of each mixed reaction system through Photoshop CC, carrying out 5 times of experiments in parallel, carrying out digital processing on anthocyanin color change caused by reaction of different sugars and 3-nitrophenylboronic acid, importing obtained data into SPSS software for linear discriminant analysis, obtaining a composition diagram of the different sugars as shown in figure 1 by taking a first factor as a horizontal coordinate and taking a second factor as a vertical coordinate, wherein characteristic vectors of the first two linear discriminant functions obtained through analysis are a first factor and a second factor, and a sugar alcohol is taken as a polyhydric alcohol and contains more than two hydroxyl groups, so that the reaction is relatively strong due to the polyhydric alcohol structures of the sugar alcohols and the second factor, and the sugar alcohol can be gathered in the same area and positioned on the right side in an LDA score diagram, and the classification of the sugars and the sugar alcohol is distinguished. Further, different sugars can be correctly identified and distinguished, and no overlapping or misjudgment phenomena occur. Among the sugars, sucrose was the least reactive and was located at the far left of the LDA score plot.

Example 2 achieving differentiation of carbohydrates in actual samples

Adding the 3-nitrophenylboronic acid/phosphate buffer solution in the step (1) into six commercially available beverages respectively, wherein the reaction time is 1-5 minutes. Then anthocyanin as described above was added and mixed well. The reaction solution was placed in 1ml centrifuge tubes, and the centrifuge tubes in the same set of experiments were placed on the same plane of the camera box. The smart phone is placed in front of a dark box, and an array image is collected. Pre-reaction image information (blank analyte solution) was obtained as initial image information. Photoshop CC is used for reading red, green and blue (RGB) values in the image as characteristic signals for representing the change of chemical properties before and after reaction. Reading RGB values of each mixed reaction system through Photoshop CC, paralleling experiments for 5 times, carrying out digital processing on anthocyanin color change caused after reaction, introducing obtained data into SPSS software for linear discriminant analysis, obtaining score maps of different drinks by taking characteristic vectors of the first two linear discriminant functions obtained by analysis as a first factor and a second factor, taking the first factor as a horizontal coordinate and the second factor as a vertical coordinate, and as shown in figure 2, according to different contents and types of added carbohydrate, commercially available drinks with various carbohydrates mixed can also be successfully distinguished by using the constructed colorimetric array sensor, and can be successfully applied to a food system.

Claims

1. a method for distinguishing saccharides based on natural extract anthocyanin, is characterized in that natural molecule builds array sensor, can distinguish saccharide, and concrete steps are as follows:

(1) Preparation of array sensor: The anthocyanins extracted from five different anthocyanin extraction sources are mixed in different proportions as the sensing units of the colorimetric array sensor to prepare a colorimetric sensor with multiple sensing units array;

(2), Differential detection of different carbohydrates: add the prepared 3-nitrophenylboronic acid solution to the 11 kinds of sugar solutions respectively, the response time is 1-5 minutes, and add the 3-nitrophenylboronic acid solution described in step (1). In the colorimetric sensor array of the sensing unit, the reaction solution was placed in a 1 ml centrifuge tube, and the centrifuge tubes of the experiments in the same group were placed on the same plane in the photo box; the smartphone was placed in front of the dark box, and the array image was collected; the reaction was obtained. The previous image information was used as the initial image information; the changes of red, green and blue (RGB) values in the image were read with Photoshop CC as the characteristic signal characterizing the chemical property changes before and after the reaction, and the obtained data were imported into SPSS software for linear discriminant analysis. The obtained eigenvectors of the first two linear discriminant functions are used as the first factor and the second factor, respectively, with the first factor as the abscissa and the second factor as the ordinate, and the score map of the 11 sugars is obtained. Different types of 11 sugar solutions are distinguished;

Differential detection of saccharides in actual samples: select commercially available beverages with different sugar content and types of added sugars, add buffers of 3-nitrophenylboronic acid and phosphate with pH 7.4, and the reaction time is 1-5 minutes , and then added to the colorimetric sensor array with multi-sensing units described in step (1), and mixed thoroughly; the reaction solution was placed in a 1 ml centrifuge tube, and the centrifuge tubes of the experiments in the same group were placed on the same plane of the photo box Put the smartphone in front of the dark box to collect the array image; obtain the image information before the reaction as the initial image information; use Photoshop CC to read the changes in the red, green, and blue (RGB) values in the image as a characterization of the chemical property changes before and after the reaction The obtained data is imported into SPSS software for linear discriminant analysis, and the eigenvectors of the first two linear discriminant functions obtained by the analysis are taken as the first factor and the second factor respectively, with the first factor as the abscissa and the second factor as The ordinate is to obtain the score chart of six commercially available sugar-sweetened beverages, through which different types of commercially available drinks can be distinguished;

Wherein, the anthocyanins described in the step (1) are mixed in different proportions, as follows:

2. a kind of carbohydrate distinguishing method based on natural extract anthocyanin as claimed in claim 1, is characterized in that, the anthocyanin extract described in step (1), extraction source is black wolfberry dried fruit, Dried carnation flower tea, forget-me-not dried flower tea, dried mulberry fruit or dried flower tea of Chinese rose; the specific extraction method is to pulverize the raw materials separately, and the obtained dry powdery raw materials are placed in a brown bottle and stored in the dark, and the mass fraction of 70% is selected. Anhydrous ethanol is used as a leaching agent, and is mixed with raw materials according to a material-to-liquid ratio of 1-2: 20-30g/ml, and then placed in a water bath for leaching at 50 °C for 3-5 hours, and then taken out and filtered by vacuum. The pigment leaching solution was obtained by suction filtration of the device, concentrated by rotary evaporation at 50° C., fixed to volume according to a material-to-liquid ratio of 2:5 (wt%), and stored at low temperature in the dark for future use.

3. a kind of carbohydrate distinguishing method based on natural extract anthocyanin as claimed in claim 1 is characterized in that, the anthocyanin that the different anthocyanin extraction sources described in step (1) is extracted is black Lycium barbarum anthocyanin, carnation anthocyanin, forget-me-not anthocyanin, mulberry anthocyanin and rose anthocyanin.

4. a kind of carbohydrate distinguishing method based on natural extract anthocyanin as claimed in claim 1, is characterized in that, described anthocyanin leaching solution is added in reaction system of black wolfberry anthocyanin 1.5 %-2%(V/V%), Carnation anthocyanin 1.5%-2%(V/V%), Forget-me-not anthocyanin 3%-4%(V/V%), Mulberry anthocyanin 1.5%- 2% (V/V%), rose anthocyanin 1.5%-2% (V/V%); the reaction system refers to the system composed of sugar solution and 3-nitrophenylboronic acid/phosphate buffer solution.

5. A method for distinguishing saccharides based on natural extract anthocyanin as claimed in claim 1, wherein the eleven sugars in step (2) are fructose, xylose, D-arabinose, mannose alcohol, D-sorbitol, xylitol, galactose, D-ribose, sucrose, maltitol, and D-anhydroglucose; of which, fructose, xylose, D-arabinose, galactose, D-ribose, sucrose, maltose Alcohol and D-anhydroglucose are sugars, and mannitol, D-sorbitol, xylitol, and maltitol are sugar alcohols.

6. a kind of carbohydrate distinguishing method based on natural extract anthocyanin as claimed in claim 1, is characterized in that, described in step (2), the sugar solution concentration is 25-100mM, and described prepared 3- The nitrophenylboronic acid solution is 50-200mM 3-nitrophenylboronic acid dissolved in 1-10mM phosphate buffer, and the pH of the solution is adjusted to 7.4 with 0.5M NaOH;

The buffer solution of 3-nitrophenylboronic acid and phosphate with pH of 7.4 is 150-200mM 3-nitrophenylboronic acid is dissolved in 1-10mM phosphate buffer, and the pH of the solution is adjusted with 0.5-1M NaOH to 7.4.