A method for micro-determination of wheat starch particle size distribution

Abstract

The application discloses a method for measuring the size distribution of wheat starch granules. The method comprises the following steps: selecting wheat seeds to be measured, soaking the seeds to release starch granules, and then performing dyeing; adding a solvent to dilute the dyed sample, performing sheet preparation to obtain a sample sheet; determining a suitable shooting area of the sample sheet by using a microscope and image processing software; setting color counting of the suitable shooting area, segmenting and coloring the image, obtaining the number of the selected image, and marking; re-segmenting the image which is not completely segmented in the segmented and colored image to obtain radius data of the corresponding image; reordering the radius data to complete the measurement of the size distribution of the starch granules of the wheat seeds to be measured, and the size distribution of the starch granules of the wheat can be calculated. The application has the advantages of small sample amount, simple instrument, simple operation process, full visual control, and high accuracy, and detailed data of the diameter of each starch granule are contained in the result.

Description

Technical Field

[0001] This invention belongs to the technical field of wheat starch particle size distribution research, specifically relating to a method for micro-determining the particle size distribution of wheat starch. Background Technology

[0002] wheat( Triticum aestivum Wheat (L.) is one of the world's three major food crops, a primary source of energy and protein in the human diet, and one of the most important cereal crops. China is a major wheat producer, with a total wheat output exceeding 137 million tons in 2022, ranking first in the world. Wheat flour products such as steamed buns, noodles, biscuits, bread, and cakes are common foods on people's tables. Wheat is also a major raw material for beer, spirits, alcohol, animal feed, and biofuels.

[0003] Currently, a prominent problem in my country's wheat production is the lack of high-yield and high-quality specialty wheat varieties. Steamed buns and noodles account for 33% and 35% of my country's flour products, respectively, but varieties with a comprehensive score of 90 or above account for only 0.06% and 0.3% of these products. Research and improvement of flour dough quality is a pressing issue for wheat industry professionals. Studies have found that the particle size distribution of wheat starch granules has a significant impact on flour quality. Wheat starch consists of two different types of granules: type A (AS) with a diameter greater than 10 μm and type B (BS) with a diameter less than 10 μm. AS granules account for over 70% of the total starch weight but less than 10% of the total granules, while BS granules account for over 90% of the total starch granules but less than 30% of the total starch weight. AS and BS granules are produced in two independent granulation events. AS production begins 3-5 days after wheat flowering, reaching its final number after 4 days, at which point each starch granule contains one starch granule. As the grain develops, starch granules increase in size, eventually reaching a diameter between 10 and 45 μm. BS (saccharide granules) begin to form in starch plastids containing only one AS (aspergillus granule). As the endosperm develops, the size of BS granules gradually increases, but their diameter in mature seeds generally does not exceed 10 μm. Therefore, each endosperm plastid in a mature wheat grain typically contains one AS and several BS granules. Thus, during the post-flowering starch accumulation stage, the proportion of starch granules with a diameter greater than 10 μm should first increase, then gradually decrease and remain stable.

[0004] Starch particle size detection is a key step in starch research, but current detection methods and instruments have high requirements for the amount of material to be tested, and the operation is relatively complicated, leading to limited instrument availability. Summary of the Invention

[0005] To overcome the problems in the prior art, this invention provides a method for determining the particle size distribution of wheat starch in trace quantities. This invention utilizes a microscope, an electronic eyepiece, and relevant software, using a single wheat seed as the material, to obtain a new method for determining the particle size of wheat starch and simplifies the particle size detection process.

[0006] To achieve the above-mentioned objectives, the present invention employs the following technical solution: This invention provides a method for determining the particle size distribution of wheat starch in trace quantities, comprising the following steps: S1. Select wheat seeds to be tested, soak them to release starch granules, and then stain them; S2. After diluting the stained sample in S1 with solvent, prepare a slide to obtain a sample slide. S3. Use a microscope and image processing software to determine the appropriate shooting area for the sample in S2; S4. Set the color count for the appropriate shooting area in S3, segment and color the image, obtain the number of selected images, and mark them. S5. Re-segment the incompletely segmented images in the image segmented and colored in S4 to obtain the radius data of the corresponding images; S6. Reorder the radius data in S5 to complete the determination of the starch particle size distribution of the wheat seeds to be tested, and be able to calculate the starch particle size distribution of this wheat variety.

[0007] Furthermore, in step S1, the soaking time of the wheat seeds to be tested is not less than 36 hours.

[0008] Furthermore, the staining solution used in S1 is iodine-potassium iodide, and the amount used is 200-250 μL of staining solution for one wheat seed.

[0009] Furthermore, the diluting solvent in S2 is a 40% glycerol solution, with a dilution concentration of 1-2.5 mL of glycerol solution added per wheat seed.

[0010] Furthermore, in S2, the sample volume for preparing the slide is 10-20 μL.

[0011] Furthermore, the suitable shooting area in S3 is specifically: in the starch granule aggregation area of ​​the sample, select an area where the starch granules are relatively dense but without starch granule accumulation and overlap, and where there is little connection between starch granules.

[0012] Furthermore, the specific steps for setting the appropriate number of color bits for the shooting area in S4 are as follows: After capturing the appropriate shooting area, click "Processing", select "Segmentation and Counting", select "Auto Options" to display the "Counting" column; click "Add" in the counting column, select "Color Blocks" to display the "Color" column, and enter starch or any number in the "Category" box; click "Options" in the color column to display the "Counting Settings" column, where the "Area (Pixel) Lower Limit" needs to be changed to a smaller value in 200x magnification images, but in 400x or higher magnification images, the lower limit pixels need to be increased according to the data size to avoid tiny fragments being counted as starch particles and affecting the data.

[0013] Furthermore, the specific steps for image segmentation and coloring in S4 are as follows: After the color count of the appropriate shooting area is set, the "color picker tool" is selected. Clicking on the starch granules dyed black in the image will set the average value of the color in the neighborhood of the currently clicked point as the base value. The image is segmented by selecting pixels within the range of the base value ± tolerance color and marked with the currently selected color. Repeatedly clicking on the target pixel in the image will continuously add new pixels within the range of the base value ± tolerance to the previously selected object, thereby achieving continuous image segmentation and coloring.

[0014] Furthermore, during the image segmentation and coloring process, when unwanted pixels are added to the segmentation data, the unwanted pixels can be removed using the "subtractive eyedropper tool".

[0015] Furthermore, the specific steps for re-segmenting the incompletely segmented image in S5 are as follows: After selecting all the segmentation data, click "OK". At this time, the software will automatically calculate the number of selected images and mark them. Clicking "Segmentation and Counting" will display the selected graphic number and size data. After clicking "Settings", select "No Fit" for "Fitting", select "Fill" for "Contour Style", uncheck "Hole", select "Yes" for "Marking Method", select "Sequence Number" for "Type", and click "OK". At this time, the marks in the image are the original contours of the unfitted starch granules. When marking, if there is no gap between two marks, they will be judged as a single target by the software. At this time, click the "Segmentation Icon" in the "Segmentation and Counting" column, and then draw a segmentation line at the connecting part. After releasing, the software will recognize the segmentation and re-count. After all the images are segmented, click "Settings", change "Fitting" from "No Fit" to "Circle", and click "OK" to obtain the radius data of the corresponding image.

[0016] Furthermore, the image processing software is ImageView software.

[0017] Compared with the prior art, the present invention has the following advantages and beneficial effects: The method for determining the particle size distribution of wheat starch according to this invention requires a small sample amount, only one wheat seed is needed to complete the determination; the instrument used is simple, requiring only a microscope and ImageView software, and the operation process is simple, requiring only simple operation in ImageView software; the entire determination process is visual and controllable, and the results include detailed data on the diameter of each starch particle, with high accuracy. Attached Figure Description

[0018] Figure 1 The morphological structure of wheat starch granules obtained by grinding (left) and soaking (right) under a 400x microscope.

[0019] Figure 2 The images show microscopic images of wheat starch granules at different dilution concentrations under a 200x microscope; Figures A, B, C, and D show microscopic images after the addition of 1.5 mL, 2 mL, 2.5 mL, and 3 mL of glycerol solution, respectively.

[0020] Figure 3 The diagram shows starch granules in the sparser region (A), the moderate region (B), and the denser region (C) of the same slide under a 50x microscope.

[0021] Figure 4 is a flowchart illustrating the segmentation and counting operations in ImageView software; where... Figure 4A , Figure 4B , Figure 4C , Figure 4D , Figure 4E , Figure 4F , Figure 4G and Figure 4H These are all screenshots of the ImageView software window.

[0022] Figure 5 The images show the microstructure of seeds and starch granules at different post-flowering stages; Figure A shows the morphology of seeds at different stages, and Figures B, C, D, E, and F show the microstructure of starch granules in seeds with 10 DAA, 15 DAA, 20 DAA, 25 DAA, and 30 DAA, respectively.

[0023] Figure 6 Figure 1 shows the calculated statistical distribution of starch granule size at different post-flowering stages. Figures A, B, C, D, and E are histograms of starch granule size distribution in seeds with 10 DAA, 15 DAA, 20 DAA, 25 DAA, and 30 DAA, respectively. Figure F is a line graph showing the change in the ratio of A and B starch in seeds 30 days after flowering. Detailed Implementation

[0024] The technical solution of the present invention will be further described in detail with reference to the following specific examples.

[0025] Materials and instruments required: A microscope with a magnification of 800 to 1000x. The microscope used in this invention is an OLYMPUS BX53, manufactured by Olympus Corporation; the electronic eyepiece is an E3ISPM06300KPB, manufactured by Suzhou Jingkai Instrument Equipment Co., Ltd.; the graphics analysis software used is ImageView, version 4.11.21522.20221011.

[0026] Materials, reagents and consumables: wheat seeds, glycerin, potassium iodide, iodine, coverslips, glass slides, 2 mL centrifuge tubes. Example 1

[0027] 1. Sampling Wheat seeds of moderate size and relatively uniform shape were selected as the test samples. This embodiment compares the advantages and disadvantages of grinding and soaking methods for starch extraction to select the most suitable extraction method.

[0028] Grinding method: Use a mortar and pestle to grind individual seeds into powder. The advantage is that it is quick, but the disadvantage is that the increase in broken starch granules in the starch granule image will affect the accuracy of the results.

[0029] Soaking method: First, disinfect the seeds to be tested with alcohol, then place them in a pre-marked centrifuge tube and soak them in water for 36 hours until the seeds fully absorb water and swell. Use tweezers to break the seed coat to release starch. The advantage is that the starch granules are relatively intact with less damage, but the disadvantage is that the soaking time required is relatively long.

[0030] The morphology and structure of starch granules obtained by the two methods described above were observed under a 400x microscope. For example... Figure 1 As shown, the starch granules in the soaking method image are more intact, reducing the number of broken starch granules and resulting in higher data accuracy. Therefore, this embodiment uses the soaking method to extract starch.

[0031] 2. Sample staining Unstained starch granules are white and transparent, making them difficult to separate from other impurities in the solution, such as lipids and air bubbles. Therefore, starch needs to be stained. Iodine-potassium iodide staining solution is used for staining.

[0032] Preparation of solution: Dissolve 8 g of potassium iodide in 40 mL of purified water. After complete dissolution, add 1 g of iodine and shake to dissolve. After dissolution, add water to make up to 100 mL and store in a brown bottle for later use.

[0033] After soaking, the seeds were punctured in a clean centrifuge tube to release starch, and then 200 μL of staining solution was added. The tubes were shaken and stained for 1 hour.

[0034] 3. Diluted solution, i.e., solvent There are specific requirements for selecting a starch solvent: the solvent must be colorless and transparent for easy observation; the starch granules must be able to remain suspended in the solvent for a certain period of time to facilitate sampling; the solvent evaporation rate must be slow; and the solvent evaporation must be avoided to prevent sample failure when observing a large number of samples or for a long period of time. Therefore, this example selects a 40% glycerol solution as the solvent. Take 40 mL of glycerol and dilute it with water to a final volume of 100 mL.

[0035] 4. Dilution factor When observing the images, a suitable concentration range is needed to ensure that as many particles as possible are visible in the field of view without significant stacking or adhesion, thus avoiding excessive errors in counting and measurement. In this example, 1.5 mL, 2 mL, 2.5 mL, and 3 mL of glycerol solution were added to each seed to observe and determine the optimal dilution concentration.

[0036] Microscopic observation reveals that ( Figure 2 When diluted to 2 mL, the starch granules are more abundant and less overlapping and adhering, making it suitable for observing a larger area. Therefore, adding 2 mL of glycerol solution to each wheat seed is the most suitable dilution concentration. The specific procedure is as follows: After soaking, the seed coat of one seed is broken in a clean centrifuge tube to release the starch. Then, 200 μL of staining solution is added and the mixture is shaken for 1 hour for staining. After thorough staining, 1800 μL of glycerol solution is added and the mixture is shaken thoroughly to mix.

[0037] 5. Sampling and film preparation The sample volume should generally not be too large, as excessive amounts will cause starch granules to have a longer flow time and be more prone to aggregation after slide preparation. Therefore, a sample volume of 10-20 μL is sufficient. In this example, a sample volume of 10 μL is used for slide preparation. The steps are as follows: After shaking the solution well, quickly insert the pipette tip to one-third of the liquid surface to draw 10 μL of sample solution, then drop it onto the center of the glass slide and cover it with a coverslip. The slide should always be kept horizontal. At this time, a small black shadow area can be observed on the slide, which is the area where starch granules aggregate.

[0038] 6. Microscopic observation to determine the imaging range Place the sample image on the observation platform, connect the computer to the electronic eyepiece via a data cable, open the ImageView software, select the camera, and the image will appear on the screen. First, observe with a 50x scope, such as... Figure 3 As shown, the starch granules in the sample are not uniform, and there is a certain aggregation effect between them. In the aggregation area, look for regions where the starch granules are relatively dense but without overlap or overlap, and where there are few connections between them. This area is relatively large when preparing the sample by diluting the solution by 2 mL, making observation easier. After finding a suitable area, click the "Capture" option to take a picture. Note that the software needs to be calibrated under different magnifications before use.

[0039] 7. Image Processing and Data Analysis (1) After selecting the appropriate area and capturing it, click "Process", select "Segmentation and Counting", and select the "Automatic" option to display the counting bar. Figure 4A ).

[0040] (2) Click "Add" in the count bar, select the color block, and the "Color" bar will appear. Figure 4B In the category box, you can enter starch or any number instead.

[0041] (3) Click "Options" in the color bar to bring up the "Counting Settings" section. Figure 4C The lower limit of the area (pixels) represents the minimum area of ​​a point that can be counted. In a 200x magnification image, this can be changed to a smaller value, meaning even smaller starch grains will be counted. However, at 400x magnification or higher, the lower limit should be increased based on the data size to prevent tiny fragments from being counted as starch grains and affecting the data. The lower limit of the area must remain consistent across the same batch of comparative materials at the same magnification.

[0042] (4) At this point, the "Color Eyedropper Tool" (i.e., the one with the plus sign icon in the image) is selected. Clicking on a starch grain dyed black in the image will set the average color of the neighborhood at the current click point as the base value. The image will then be segmented by selecting pixels within the base value ± tolerance color range, and marked with the currently selected color (the default color is red). Repeatedly clicking on the target pixel in the image will continuously add new pixels within the base value ± tolerance range to the previously selected object, achieving continuous segmentation and coloring. Figure 4D When unwanted pixels are added to the segmentation data, the "subtractive eyedropper tool" (the one with the minus sign icon in the image) can be used to remove them. The process is the same as with the additive eyedropper tool: use the average color value in the neighborhood of the clicked area as the base value, and then remove segmentation data whose color values ​​are within the base value ± tolerance range. After selecting all, as shown... Figure 4E As shown.

[0043] (5) After selecting all images, click "OK". The software will automatically calculate and mark the number of selected images. Click "Segmentation and Counting" in the lower left corner to display the selected image number and size data. Click "Settings". At this time, select "No Fit" for the fitting option, "Fill" for the contour style, uncheck the hole option, select "Yes" for the marking method, and select "Serial Number" for the type. Figure 4F As shown, click "OK".

[0044] At this point, the red markers in the image represent the original outlines of the unfitted starch granules. During the selection process, some starch granules will inevitably be close together. If there is no gap between two red markers, the software will identify them as a single target. In this case, click the second "Segmentation Icon" on the left side of the "Segmentation and Counting" column, then hold down the left mouse button and draw a segmentation line at the connecting point. After releasing the left button, the software will recognize the segmentation and re-count. After all segments are completed, click Settings to change the fitting option from "No Fit" to "Circle". After confirming, the "Segmentation and Counting" column will display the sequence number of the fitted image and the radius of the corresponding image in a table. Figure 4G ).

[0045] Clicking the radius column header will reorder all data according to the radius in ascending order. Then click the Excel icon on the left. Figure 4H The data and images were exported to a new Excel spreadsheet, renamed, and saved to obtain the radius data of all starch granules in the selected images. Based on the distribution of starch granule radii in this spreadsheet, the grain size distribution of this wheat variety can be calculated. For data reliability, images with at least five field-of-view images or more than 2000 starch granules were selected as the standard, and the calculated data after meeting the conditions showed good repeatability.

[0046] This method not only provides a simple and rapid way to determine the particle size distribution of different varieties, but also has significant advantages in detecting starch accumulation and particle size distribution in wheat at different days after flowering (DAA). It eliminates the need for milling and other additional treatments. Grains are collected at different stages and stored at ultra-low temperatures. For testing, one grain is taken from each of the different DAA stages and analyzed using the method described above. It is even possible to collect grains from the same ear at different stages for analysis. However, it should be noted that the amount of starch in the grains varies significantly due to different grain-filling times. Specifically, the dilution volume should be 1 mL for 5-15 DAA grains and 1.5 mL for 15-25 DAA grains. The observation results are as follows: Figure 5 .

[0047] The calculation results are as follows Figure 6 In the early stage of grouting, due to the early development of type A starch granules, the number of type A granules larger than 10 μm accounts for as high as 35%. Later, as type B starch gradually develops, the proportion of type A granules gradually decreases to about 10%. This result is consistent with existing studies, indicating that the detection method of the present invention has good accuracy.

[0048] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions claimed by the present invention.

Claims

1. A method for determining the particle size distribution of wheat starch in trace quantities, characterized in that, Includes the following steps: S1. Select wheat seeds to be tested, soak them to release starch granules, and then stain them. The staining solution used is iodine-potassium iodide, and the amount is 200~250 μL of staining solution for one wheat seed. S2. After diluting the stained sample from S1 with solvent, prepare a slide to obtain a sample slide; the diluent is a 40% glycerol solution, with a dilution concentration of 1~2.5 mL of glycerol solution added to each wheat seed. S3. Use a microscope and image processing software to determine the appropriate shooting area of ​​the sample in S2; the image processing software is ImageView software; the appropriate shooting area is specifically: in the starch granule aggregation area of ​​the sample, select an area where the starch granules are relatively dense but without starch granule accumulation and overlap, and where there are few connections between starch granules; S4. Set the color count of the appropriate shooting area in S3, and segment and color the image of the appropriate shooting area to obtain and mark the number of starch granules in the selected image. S5. Re-segment the incompletely segmented images in the image segmented and colored in S4 to obtain the radius data of the corresponding images; S6. Reorder the radius data in S5 to complete the determination of starch particle size distribution in the wheat seeds to be tested.

2. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 1, characterized in that, In step S1, the soaking time of the wheat seeds to be tested is not less than 36 hours.

3. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 1, characterized in that, In step S2, the sample volume for preparing the slide is 10-20 μL.

4. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 1, characterized in that, The specific steps for setting the color count for a suitable shooting area in S4 are as follows: After capturing the suitable shooting area, click "Processing", select "Segmentation and Counting", select the "Automatic" option to display the "Counting" column; click "Add" in the counting column, select "Color Block" to display the "Color" column, and enter starch or any number in the "Category" box; click "Options" in the color column to display the "Counting Settings" column, where the "Lower Limit Area" needs to be changed to a smaller value in 200x magnification images, but in 400x or higher magnification images, the lower limit pixel points need to be increased according to the data size to avoid tiny fragments being counted as starch particles and affecting the data.

5. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 1, characterized in that, The specific steps for image segmentation and coloring in S4 are as follows: After the color count of the appropriate shooting area is set, the "color picker tool" is selected. Clicking on the starch granules dyed black in the image will set the average value of the color in the neighborhood of the currently clicked point as the base value. The image is segmented by selecting pixels within the range of the base value ± tolerance color and marked with the currently selected color. Repeatedly clicking on the target pixels in the image will continuously add new pixels within the range of the base value ± tolerance to the previously selected objects, thereby achieving continuous image segmentation and coloring.

6. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 5, characterized in that, During the image segmentation and colorization process, when unwanted pixels are added to the segmentation data, the unwanted pixels can be removed using the "subtractive eyedropper tool".

7. The method for determining the particle size distribution of wheat starch in trace amounts according to claim 1, characterized in that, The specific steps for re-segmenting the incompletely segmented image in S5 are as follows: After selecting all the segmentation data, click "OK". The software will automatically calculate and mark the number of selected images. Clicking "Segmentation and Counting" will display the selected graphic number and size data. After clicking "Settings", select "No Fit" for "Fitting", select "Fill" for "Contour Style", uncheck "Hole", select "Yes" for "Marking Method", select "Sequence Number" for "Type", and click "OK". At this time, the marks in the image are the original contours of the unfitted starch granules. When marking, if there is no gap between two marks, they will be judged as a single target by the software. At this time, click the "Segmentation Icon" in the "Segmentation and Counting" bar, and then draw a segmentation line at the connecting part. After releasing, the software will recognize the segmentation and re-count. After all the images are segmented, click "Settings", change "Fitting" from "No Fit" to "Circle", and click "OK" to obtain the radius data of the corresponding image.

Images