A method for positioning cinnabar cigarette grades based on glutinous rice aroma characteristics

Abstract

The present invention relates to the technical field of cinnabar cigarette classification, and in particular to a method for grading cinnabar cigarettes based on glutinous rice aroma characteristics. The method comprises the following steps: standard establishment: selecting a number of cinnabar cigarette leaf samples and detecting the content of polyphenolic chemicals in each leaf sample; determining a number of grades based on the content of polyphenolic chemicals; photographing the leaf samples and calculating the cinnabar index of the leaf samples; and obtaining the cinnabar index range of each grade based on the cinnabar index of a number of leaf samples belonging to different grades. Grading of the cinnabar cigarette leaves to be tested: taking the cinnabar cigarette leaves to be tested and determining the grade of the cinnabar cigarette leaves to be tested by the cinnabar index. The present application provides a cinnabar cigarette grade standard and a method for determining the grade of cinnabar cigarettes by judging the appearance characteristics of cinnabar cigarette leaves. The glutinous rice aroma characteristics of cinnabar cigarettes of different grades vary, providing a direction for the application of cinnabar cigarettes in cigarette formulations.

Description

Technical Field

[0001] The present invention relates to the technical field of cinnabar cigarette classification, and in particular to a cinnabar cigarette grade positioning method based on glutinous rice aroma characteristics. Background Art

[0002] Cinnabar (red) tobacco refers to a naturally occurring mutation of a premium tobacco variety during its growth. During the curing process, demethylnicotine reacts with quinones to produce a red substance, giving the front of the leaves a vermilion or red leopard pattern. This is why it's called "Cinnabar" tobacco, and it's also known as "Cherry-Red" tobacco abroad. Research on red tobacco began in the 1950s. Its red color is primarily due to a mutation in the CYP82E4 gene, which converts nicotine to demethylnicotine, accounting for over 50% of the total alkaloid content. This results in a pleasant, pleasant smoke with a moderate kick, a rich, rounded smoke, a low kick, and a low irritation. It also has a distinctive "glutinous rice" aroma, making it a unique and high-quality tobacco raw material.

[0003] The glutinous rice aroma characteristic of cinnabar tobacco determines its grade. Cinnabar tobacco with a more pronounced glutinous rice aroma is rated higher and more suitable for high-end cigarette formulations. Conversely, tobacco with a less pronounced glutinous rice aroma is rated lower and suitable for lower-end cigarette formulations. Currently, the grade classification of cinnabar tobacco remains unclear, and there is no scientific and rapid method for assigning the grade of unknown cinnabar tobacco. Therefore, how to scientifically and rationally classify cinnabar tobacco leaf raw materials based on their glutinous rice aroma, so that they can be accurately used in the production of corresponding cigarette products, has become an urgent issue. Summary of the Invention

[0004] The present invention aims to solve the above problems and provides a method for positioning the grades of cinnabar cigarettes based on the characteristics of glutinous rice aroma.

[0005] The technical solution to the problem solved by the present invention is to provide a method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma, comprising the following steps:

[0006] (1) Standard establishment:

[0007] A. Select several leaf samples of Nicotiana cinnabarifolia and test the polyphenol content of each leaf sample; determine several grades based on the polyphenol content.

[0008] Polyphenols contribute to the aromatic flavor of tobacco smoke. Under appropriate conditioning and aging conditions, plant polyphenols degrade through a series of reactions to produce a range of substances. These degradation products impart an elegant aroma to tobacco products, increasing their aroma volume. Therefore, the content of polyphenols influences the characteristic glutinous rice aroma. Cultivating cinnabar tobacco grades based on this characteristic glutinous rice aroma can accurately determine its grade.

[0009] Preferably, the polyphenolic chemical substances include one or more of chlorogenic acid, scopoletin, and rutin. The measurement of these polyphenolic chemical substances can be carried out in accordance with the standard "Determination of Chlorogenic Acid, Scopoletin, and Rutin as Polyphenolic Compounds in Tobacco and Tobacco Products" (YC / T 202-2006).

[0010] The inventors found in actual operation that the content of scopoletin is positively correlated with the characteristics of glutinous rice aroma, and the positive correlation is the highest. Therefore, as a preferred embodiment of the present invention, scopoletin is selected as the polyphenol chemical substance.

[0011] After classifying several leaf samples into different grades using step A, the inventors discovered that leaf samples of different grades differed in appearance, primarily manifested in varying shades of cinnabar color (from light to dark, including light red, red, crimson, and purple-red) and varying cinnabar areas. The general pattern was: the darker the cinnabar color, the higher the proportion of dark cinnabar blocks, and the larger the total cinnabar area, the higher the grade. However, visual observation alone cannot accurately evaluate cinnabar appearance, and the order in which these factors influence grade is unclear. Based on this, the inventors performed the following operations to explore the corresponding relationship between leaf sample appearance characteristics and grade.

[0012] B.b1. After flattening the leaf sample, take a photo of the leaf sample under the same collection environment.

[0013] The preferred collection environment for this invention is a darkroom with a solid-color background and a D65 light source. D65 is the most commonly used artificial daylight among standard light sources. D65 simulates artificial daylight, ensuring that the color of objects observed indoors or on rainy days resembles that observed under sunlight.

[0014] As a preferred embodiment of the present invention, the pure color background is white or black. The white background is preferably selected from a whiteboard, white paper, and a white wall, and its RGB value range under the D65 standard light source is 250-255; the black background is preferably selected from a blackboard, black cloth, and black paper, and its RGB value range under the D65 standard light source is 0-5.

[0015] b2. The darkest cinnabar area ratio S in the leaf sample i Calculation: First, perform tonal separation processing on the photo with a color level of 2, then perform threshold processing with a color level of 128, and then calculate the ratio of the black block area on the leaf sample to the total area of ​​the leaf sample, which is recorded as the darkest cinnabar area ratio S of the leaf sample. i ;

[0016] b3. Total cinnabar area ratio S in leaf samples jCalculation: First, perform a color separation process on the photo with a color level of 2, then perform a decolorization process, and then calculate the ratio of the gray block area and the black block area on the leaf sample to the total area of ​​the leaf sample, which is recorded as the total cinnabar area ratio S of the leaf sample. j ;

[0017] b4. Through S i / S j Calculate the ratio of the darkest cinnabar area to the total cinnabar area S i / j ;

[0018] Through the above operation, all cinnabar areas and the darkest cinnabar areas on the cinnabar smoke can be well revealed. By calculating the area of ​​the color block representing cinnabar, the cinnabar area can be effectively calculated.

[0019] Tone separation, threshold, decolorization and other operations can be completed by PS software. As a preferred embodiment of the present invention, the darkest cinnabar area ratio S is calculated by the histogram of PS software. i and the total area ratio of cinnabar j The histogram of PS software can count the percentages of different levels of color in the photo to calculate the area of ​​the cinnabar color block.

[0020] Since gray has different shades, the color scale value of the gray block is unclear, while the color scale value of the black block is clearly 0. Therefore, it is more accurate to calculate the area of ​​the black block. As a preferred embodiment of the present invention, the total area S of the cinnabar in step b3 is j In the calculation, after decolorization, a threshold process of 128 is performed, and then the ratio of the black area of ​​the leaf sample in the photo to the total area of ​​the leaf sample is calculated, which is recorded as the total cinnabar area ratio S of the leaf sample. j .

[0021] Since the color blocks representing cinnabar are unevenly distributed, in order to improve computational convenience, as a preferred embodiment of the present invention, a pixelation filter process may be performed after threshold processing and / or decolorization processing. As a preferred embodiment of the present invention, the pixelation filter process includes one of color block processing and point processing.

[0022] As a preferred embodiment of the present invention, in steps b2 and b3, before performing the tone separation process, the photo is subjected to contrast adjustment processing to adjust the contrast to 80-100.

[0023] As a preferred embodiment of the present invention, in steps b2 and b3, before performing the tone separation process, shadow / highlight adjustment process is performed on the photo, adjusting the highlight to 0 and the shadow to 80%-100%.

[0024] The above operations can all improve the contrast between the cinnabar part and the ordinary part of the leaf sample, so that after photo processing, the cinnabar area can be better distinguished, making the calculated cinnabar area more accurate.

[0025] b5. Weight calculation: Use AHP to calculate S i The weight Z i 、S j The weight Z j 、S i / j The weight Z i / j ; Vermillion index of leaf sample = S i ×Z i +S j ×Z j +S i / j ×Z i / j .

[0026] b6. Based on the cinnabar indexes of several leaf samples belonging to different grades, obtain the cinnabar index range of each grade.

[0027] Through weight calculation, we can obtain the influence weights of the darkest cinnabar area, the total cinnabar area, and the ratio of the darkest cinnabar area to the total cinnabar area on the grade, and then the cinnabar index calculated can effectively correspond to the grade.

[0028] The AHP method for calculating weights is a decision-making method that decomposes the elements related to decision-making into levels such as goals, criteria, and plans, and conducts qualitative and quantitative analysis on this basis. The steps for determining weights are: constructing features (features are also S) based on the scale i 、S j 、S i / j ) Importance comparison matrix, normalize the feature importance comparison matrix, calculate the eigenvector of each feature; then divide each eigenvector by the sum of all eigenvectors to obtain the weight of each feature.

[0029] The importance comparison matrix is ​​a matrix obtained by comparing the importance of each feature pairwise. Scaling is the key to constructing the importance comparison matrix. There are many types of scales, such as the 1-9 scaling method and the 0-2 three-scale method, as well as the 9 / 9-9 / 1 fractional scaling method and the 10 / 10-18 / 2 fractional scaling method that improve the accuracy of the 1-9 scaling method, the -1-1 three-scale method and the -2-2 five-scale method that improve the 0-2 three-scale method, etc. Since the more scale values ​​there are, the more accurate the measurement of things is, but there are only three features in this application, as the preferred embodiment of the present invention, the feature importance comparison matrix is ​​constructed according to the 9 / 9-9 / 1 fractional scaling method. The construction standards of the 9 / 9-9 / 1 scaling method are as follows: p and q are equally important, with a scale of 9 / 9; p is slightly more important than q, with a scale of 9 / 7; p is significantly more important than q, with a scale of 9 / 5; p is strongly more important than q, with a scale of 9 / 3; p is extremely more important than q, with a scale of 9 / 1.

[0030] After determining the grades of cinnabar tobacco leaves and the standards for each grade, any unknown cinnabar tobacco leaves can be graded.

[0031] (2) Grade positioning of the cinnabar tobacco leaves to be tested:

[0032] Take the cinnabar tobacco leaf to be tested, take a photo of the cinnabar tobacco leaf to be tested under the same collection environment as step B, and process the photo in the same way as step B to obtain the darkest cinnabar area ratio and the total cinnabar area ratio, and calculate its cinnabar index. Determine the grade of the cinnabar tobacco leaf to be tested by the cinnabar index.

[0033] Beneficial effects of the present invention:

[0034] 1. In this application, a cinnabar cigarette grade standard is provided. Different grades of cinnabar cigarettes have different glutinous rice aroma characteristics, which provides direction for the application of cinnabar cigarettes in cigarette formulas.

[0035] 2. In this application, a method is provided for determining the grade of cinnabar tobacco by judging the appearance characteristics of cinnabar tobacco leaves, which is simple and accurate for locating the grade of unknown cinnabar tobacco. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a common photograph of a sample of cinnabar tobacco leaves;

[0037] Figure 2 yes Figure 1 Schematic diagram after tone separation and threshold processing;

[0038] Figure 3 yes Figure 1 Schematic diagram after toning and desaturation processing;

[0039] Figure 4 yes Figure 1 Schematic diagram after toning, desaturation, and thresholding;

[0040] Figure 5 This is a schematic diagram of the leaf sample cutting; DETAILED DESCRIPTION

[0041] The following are specific embodiments of the present invention, which are combined with the accompanying drawings to further describe the technical solutions of the present invention, but the present invention is not limited to these embodiments.

[0042] Example 1

[0043] A method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma comprises the following steps:

[0044] (1) Standard establishment:

[0045] A. Select 15 upper cinnabar tobacco leaf samples and 15 lower cinnabar tobacco leaf samples, and cut each leaf sample into the tip, middle, and base. The cutting standard is as follows: Figure 5 As shown, the leaf tip: gradually extends from the edge of the tobacco leaf at a certain angle at the tip of the tobacco leaf, and ends at the upper and lower edges of the tobacco leaf that are almost parallel; the leaf mid: the middle part of the tobacco leaf, the upper and lower edges of the middle of the tobacco leaf are almost parallel; the leaf base: extends upward from the bottom of the tobacco stem, and ends when the leaf edges are almost parallel.

[0046] The scopoletin content of each part of each leaf sample was tested:

[0047] Sample Extraction: Weigh approximately 100 mg of sample, accurate to 0.1 mg, into a 50 mL conical flask. Add 20.0 mL of 50% methanol / water solution and extract using an ultrasonic oscillator (frequency: 40 kHz) for 20 minutes. Filter 2 mL of the extract through a 0.45 μm aqueous filter.

[0048] High performance liquid chromatography: Chromatographic conditions are as follows: mobile phase A: water + methanol + acetic acid = 88 + 10 + 2 (volume fraction); mobile phase B: water + methanol + acetic acid = 10 + 88 + 2 (volume fraction); column temperature: 30°C; column flow rate: 1 mL / min; injection volume: 10 μL; gradient: 0 min: A: 100%; 16.5 min: A: 80%, B: 20%; 30 min: A: 20%, B: 80%; detector: detection wavelength: 340 mm, reference wavelength: 480 mm; analysis time is 40 min.

[0049] Determination: A series of scopoletin calibration solutions were determined by high performance liquid chromatography to obtain the integrated peak area of ​​scopoletin. A calibration curve was established using the peak area as the ordinate and the concentration as the abscissa. The calibration curve was subjected to linear regression (R 2 >0.99). The extracted sample was then measured, and the concentration of scopoletin in the sample was calculated from the peak area of ​​scopoletin.

[0050] According to the content of scopoletin, five grades are determined from high to low, namely very high, high, medium, low and none.

[0051] The test data and classification results are shown in Table 1 below.

[0052] Table 1.

[0053]

[0054] Cinnabar cigarettes are divided into 5 grades, based on the characteristics of glutinous rice fragrance, from high to low, namely ultra-high-end, high-end, mid-range, low-end and no grade.

[0055] B. After the leaf sample is flattened, a D65 light source is used as the lighting source and a black table is used as the background color to photograph the leaf sample to obtain a photo.

[0056] A screenshot of a high-grade leaf sample with more cinnabar was taken and enlarged. Figure 1 As shown ( Figure 1 After black and white adjustment processing, it is not the original color of cinnabar smoke). The calculation is explained using this leaf sample as an example.

[0057] Calculation of the area of ​​the entire leaf sample:

[0058] Using Photoshop, select the Magic Wand tool and adjust the Tolerance to 100. Use the Magic Wand tool to select the leaf sample in the image, then Edit > Fill and adjust it to white. Right-click to invert the selection, then Edit > Fill to adjust the area outside the leaf sample to black. Open Window > Histogram and select Level 255 in the histogram. The percentile value on the histogram is the percentage of white area in the entire image, which is recorded as the area of ​​the entire leaf sample. This leaf sample is 39.48.

[0059] The darkest cinnabar area ratio S i calculate:

[0060] Using PS software, first perform color separation processing on the original color photo with a color level of 2, and then perform threshold processing with a color level of 128; take a screenshot of the part with more cinnabar in the photo and enlarge it as shown below Figure 2 As shown. Open the Histogram window and select the 255th level in the histogram. The percentile value on the histogram now represents the percentage of white area in the entire image. For this leaf sample, it is 27.69. Therefore, the area of ​​the black block on this leaf sample is 39.48 - 27.69 = 11.79; the ratio of the black block area to the total area of ​​the leaf sample is 11.79 / 39.48 = 0.299.

[0061] Cinnabar total area ratio S j calculate:

[0062] Using PS software, the photo was first subjected to a color separation process with a color level of 2, and then to a color removal process. The part with more cinnabar in the photo was screenshoted and enlarged. Figure 3 As shown; then perform threshold processing with a color level of 128, take a screenshot of the part with more cinnabar in the photo and enlarge it as shown below Figure 4As shown. Open the Histogram window and select the 255 level in the histogram. The percentile value on the histogram now represents the percentage of white area in the entire image, which is 14.84. Therefore, the area of ​​the black block on the leaf sample is 39.48 - 14.84 = 24.64; the ratio of the black block area to the total area of ​​the leaf sample is 24.64 / 39.48 = 0.624.

[0063] The ratio of dark cinnabar area to total cinnabar area S i / j calculate:

[0064] It is 0.299 / 0.624=0.479.

[0065] Weight calculation:

[0066] According to the 9 / 9~9 / 1 score scaling method, the feature importance comparison matrix is ​​constructed, and it is believed that S i Than S j Obviously important, S i Than S i / j Slightly more important, S i / j Than S j Slightly important; and the importance matrix is ​​normalized and the weights are calculated as shown in Table 2 below.

[0067] Table 2.

[0068]

[0069] The cinnabar index of the leaf sample = S i ×Z i +S j ×Z j +S i / j ×Z i / j =0.299×0.4296+0.624×0.2456+0.479×0.3248=0.437.

[0070] The area and cinnabar index of 30 leaf samples are shown in Table 3.

[0071] Table 3.

[0072]

[0073] According to the cinnabar index of 30 leaf samples belonging to different grades, the cinnabar index range of each grade was obtained.

[0074] File-level verification:

[0075] Five sensory evaluation experts from Hubei China Tobacco Technology Center were invited to conduct a smoking evaluation on the above 30 leaf samples, mainly scoring the glutinous rice aroma in the fragrance. The evaluation results are shown in Table 4 below.

[0076] Table 4.

[0077] Leaf samples Expert A Expert B Expert C Expert D Expert E Upper part-1 4.5 4.7 4.6 4.3 4.7 Upper part-2 4.9 4.5 4.8 4.1 4.3 Upper part-3 4.3 4.1 4.3 4.9 4.5 Central-1 4.9 4.5 4.3 4.2 4.6 Central-2 4.7 4.7 4.2 4.3 4.6 Central-3 4.3 4.8 4.3 4.8 4.4 Upper part-4 3.7 3.4 3.4 3.3 3.6 Upper part-5 3.7 3.4 3.8 3.7 3.5 Upper part-6 3.5 3.8 3.5 3.7 3.2 Central-4 4.0 3.9 3.8 3.0 3.2 Central-5 3.5 3.5 3.3 3.1 3.1 Central-6 3.6 4.0 3.8 3.0 3.3 Upper part-7 2.9 2.5 2.4 2.8 2.4 Upper part-8 2.1 2.1 2.3 2.8 2.8 Upper part-9 2.5 2.6 2.6 2.8 2.1 Central-7 2.5 2.4 3.0 2.5 2.5 Central-8 2.1 2.5 2.2 2.7 2.4 Central-9 2.9 2.4 2.4 2.7 2.7 Upper -10 1.2 1.2 1.0 1.9 1.5 Upper part-11 1.7 1.6 1.3 1.4 1.0 Upper part-12 1.7 1.7 1.6 1.4 1.1 Central-10 1.3 1.5 1.9 1.2 1.1 Central-11 1.0 1.8 1.5 1.6 1.2 Central-12 1.3 1.8 2.0 1.1 1.1 Upper part-13 0.9 0.8 0.3 0.1 0.1 Upper part-14 0.4 0.9 0.6 0.2 0.7 Upper part-15 0.8 0.9 0.1 0.3 0.9 Central-13 0.8 0.3 0.1 0.6 0.9 Central-14 0.6 0.9 0.6 1.0 0.1 Central-15 0.7 0.9 0.8 0.8 0.9

[0078] The suction evaluation results are consistent with the grade classification results, proving the accuracy of the grade classification of this application.

[0079] (2) Grade positioning of the cinnabar tobacco leaves to be tested:

[0080] Take the cinnabar tobacco leaf to be tested, flatten it, use D65 light source as the lighting source, and a black table as the background color, take a photo of the cinnabar tobacco leaf to be tested, and process the photo in the same way as step (1) to obtain its darkest cinnabar area and total cinnabar area, and calculate its cinnabar index. The calculated cinnabar index is 0.261, which is judged to be mid-range.

[0081] Verification of evaluation results:

[0082] Observe the cinnabar tobacco leaves to be tested. The cinnabar content in their appearance is distributed in patches with more patches, and the cinnabar spots are mostly ordinary red.

[0083] The total concentration of scopoletin in the Nicotiana tabacum leaf was calculated using the method in step (1) to be 0.45 mg / g.

[0084] A sensory evaluation expert was asked to conduct a smoking evaluation, mainly scoring the glutinous rice aroma in the fragrance, with a score of 2.7.

[0085] All of them meet the standards of mid-range cinnabar cigarettes.

[0086] Example 2

[0087] This embodiment is basically the same as the first embodiment, and the only difference is that:

[0088] When calculating the darkest cinnabar area ratio Si:

[0089] Using Photoshop software, first perform contrast adjustment on the original color photo, adjusting the contrast to 100. Then perform shadow / highlight adjustment on the photo, adjusting the highlights to 0 and the shadows to 100%. Then perform toning with a color level of 2, followed by a thresholding process with a color level of 128. Finally, perform filter-pixelation-color block processing. Open the window-histogram, select the color level 255 in the histogram. The percentile value on the histogram is the percentage of white area in the entire image. For this leaf sample, the percentile value is 27.77, which is only 0.08 different from the statistical result of Example 1. The area of ​​the black block on the leaf sample is 39.48-27.77=11.71; the ratio of the black block area on the leaf sample to the total area of ​​the leaf sample is 11.71 / 39.48=0.299.

[0090] Cinnabar total area ratio Sj calculate:

[0091] Using Photoshop software, first perform contrast adjustment on the original color photo, adjusting the contrast to 100. Then perform shadow / highlight adjustment on the photo, adjusting the highlights to 0 and the shadows to 100%. Then perform toning with a color scale of 2, desaturation, and thresholding with a color scale of 128. Finally, perform filter-pixelation-color block processing. Open the window-histogram, select the color scale of 255 in the histogram. The percentile value on the histogram at this time, which is the percentage of white area in the entire image, is 15.84, which is only 1 different from the statistical result of Example 1. The area of ​​the black block on the leaf sample is 39.48-15.84=23.64; the ratio of the black block area on the leaf sample to the total area of ​​the leaf sample is 25.64 / 39.48=0.599.

[0092] The ratio of dark cinnabar area to total cinnabar area S i / j calculate:

[0093] It is 0.299 / 0.599=0.499.

[0094] The cinnabar index of this leaf sample is 0.438, which is close to the calculated result in Example 1.

[0095] Therefore, through the photo processing method of this embodiment, the grades of cinnabar cigarettes can also be divided into: ultra-high grade: cinnabar index > 0.5; high grade: 0.35 < cinnabar index ≤ 0.5; mid-range: 0.25 < cinnabar index ≤ 0.35; low grade: 0.15 < cinnabar index ≤ 0.25; no grade: cinnabar index ≤ 0.15.

[0096] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Persons skilled in the art may make various modifications, additions, or substitutions to the described specific embodiments without departing from the spirit of the present invention or exceeding the scope of the appended claims.

Claims

1. A method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma, characterized by: The following steps are involved: (1) Standard establishment: A. Select several leaf samples of Nicotiana tabacum, test the polyphenol content of each leaf sample, and determine several grades based on the polyphenol content; B.b1. After flattening the leaf samples, photograph each leaf sample individually under the same collection environment. b2. First, perform toning on the photo at a color scale of 2, then threshold processing at a color scale of 128. Then calculate the ratio of the black area of ​​the leaf sample to the total area of ​​the leaf sample, and record it as the darkest cinnabar area ratio S of the leaf sample. i ; b3. First, perform a color separation process on the photo at a color level of 2, then perform a decolorization process, and then calculate the ratio of the gray block area and the black block area on the leaf sample to the total area of ​​the leaf sample, which is recorded as the total cinnabar area ratio S of the leaf sample. j ; b4. Through S i / S j Calculate the ratio of the darkest cinnabar area to the total cinnabar area S i / j ; b5. Use AHP to calculate S i The weight Z i 、S j The weight Z j 、S i / j The weight Z i / j ; Vermillion index of leaf sample = S i ×Z i +S j ×Z j +S i / j ×Z i / j ; b6. According to the cinnabar index of several leaf samples belonging to different grades, the cinnabar index range of each grade is obtained; (2) Grade positioning of the cinnabar tobacco leaves to be tested: Take the cinnabar tobacco leaf to be tested, take a photo of the cinnabar tobacco leaf to be tested under the same collection environment as step B, and process the photo in the same way as step B to obtain the darkest cinnabar area ratio and the total cinnabar area ratio, and calculate its cinnabar index. Determine the grade of the cinnabar tobacco leaf to be tested by the cinnabar index.

2. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: The polyphenolic chemical substances include one or more of chlorogenic acid, scopoletin and rutin.

3. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 2, characterized in that: The polyphenol chemical substance is scopoletin.

4. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: The collection environment is: in a dark room, with a pure color background and D65 light source as the lighting source.

5. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: The darkest cinnabar area ratio S was calculated by the histogram of PS software. i and the total area ratio of cinnabar j .

6. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 5, characterized in that: In step b3, after the decolorization process, a threshold process with a color scale of 128 is performed, and then the ratio of the black block area on the leaf sample to the total area of ​​the leaf sample is calculated, which is recorded as the total cinnabar area ratio S of the leaf sample. j .

7. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: After the threshold processing and / or the desaturation processing, a pixelation filter processing is also performed.

8. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 7, characterized in that: The filter pixelation process includes one of color block and dot.

9. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: In steps b2 and b3, before performing the tone separation process, the contrast of the photo is adjusted to 80-100.

10. The method for locating the grade of cinnabar cigarettes based on the characteristics of glutinous rice aroma according to claim 1, characterized in that: In steps b2 and b3, before performing the tone separation process, perform shadow / highlight adjustment on the photo, adjusting the highlights to 0 and the shadows to 80%-100%.

Images