CN113228878A - Modeling method for measuring wheat seed vitality - Google Patents
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- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
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- A01C1/00—Apparatus, or methods of use thereof, for testing or treating seed, roots, or the like, prior to sowing or planting
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Abstract
The invention provides a modeling method for measuring wheat seed vigor, and particularly relates to the technical field of seed vigor measurement. The invention provides a modeling method for measuring wheat seed vigor, which comprises the following steps: carrying out vitality measurement on the seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight; using tetrazole solution to dye the activated seeds to obtain dyed seeds; after the dyed seeds are scanned, removing background colors and endosperm parts from the scanning result, and extracting phenotype characteristic data of the embryo part area of the seeds to obtain scanning data; and analyzing the scanning data and the vitality index data and establishing a regression model. The model constructed by the modeling method can reduce the problem of strong subjectivity of manual judgment, and has the advantage of simple operation.
Description
Technical Field
The invention relates to the technical field of seed vitality determination, in particular to a modeling method for determining wheat seed vitality.
Background
The vitality of the seeds is an important index of the quality of the seeds and the quality, and is related to the germination rate and the emergence rate of the seeds, the growth potential of seedlings, the stress resistance of plants and the production potential. The determination of the seed vitality is an indirect method for rapidly identifying the germination capacity of the seeds, and the accurate vitality determination method can truly reflect the germination capacity and the maximum germination potential of the seeds and is particularly suitable for the seeds with long dormancy period.
At present, conventional germination tests are adopted to measure the germination capacity, so that the time required for measuring the germination capacity is long, the service life of seeds is different, and in order to determine whether the seeds can be used for sowing or not and determine the sowing quantity, efficient measurement of the seed viability is required. Therefore, it is of great significance to research the determination method suitable for the viability of different seeds. The rapid determination method for the seed viability is the most widely applied to a tetrazolium staining method, which indicates whether the seed is viable or not by using the principle that red triphenylformazan is generated through the reduction reaction of TTC and living cells, and can also judge the reason why the seed loses viability through the staining condition of the embryo of the seed. However, the traditional tetrazole dyeing method is complex to operate, is only recognized by human eyes, is easily influenced by human subjectivity, and is poor in repeatability.
Disclosure of Invention
In order to solve the problems, the invention provides a modeling method for measuring the activity of wheat seeds. The model constructed by the method can reduce the problem of strong subjectivity of manual judgment, and has the advantage of simple operation.
In order to achieve the above purpose, the invention provides the following technical scheme:
the invention provides a modeling method for measuring wheat seed vigor, which comprises the following steps:
carrying out vitality measurement on the seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight;
using tetrazole solution to dye the activated seeds to obtain dyed seeds;
scanning the dyed seeds, removing background colors and endosperm parts from the scanning results, and extracting phenotype characteristic data of the embryo parts of the seeds to obtain scanning data; the phenotypic features include texture features and color features; the texture features comprise gray values, contrast, dissimilarity, homogeneity, energy, correlation, angular second moment and entropy; the color features include R, G, B, H, S, V, L, a and b;
and analyzing the scanning data and the vitality index data and establishing a regression model.
Preferably, during the dyeing, the activated seeds are longitudinally cut and then placed in a tetrazole solution for dyeing, and the mass percentage of tetrazole in the tetrazole solution is 1%; the dyeing time is 1-2 h, and the temperature is 35 ℃.
Preferably, the activation is soaking at 25 ℃ for 24 h.
Preferably, the longitudinal cutting mode is cutting along the seed groin line.
Preferably, the analysis includes analysis of variance, correlation analysis and multiple linear regression analysis.
Preferably, the vitality index data used for data analysis includes germination rate, germination vigor, fresh weight and easy vitality index.
Preferably, the resolution of the scanning is 300dpi to 600 dpi.
Preferably, the contrast includes a contrast in grayscale and a contrast in an R channel; the dissimilarity degree comprises dissimilarity degree under gray scale and dissimilarity degree under an R channel; the homogeneity includes homogeneity under gray scale and homogeneity under R channel; the energy comprises energy in grayscale and energy in an R channel; the correlation includes a correlation in grayscale and a correlation in an R channel; the angular second moment comprises an angular second moment under the gray scale and an angular second moment under the R channel; the entropy includes entropy in grayscale and entropy in the R channel.
The model constructed by the method is applied to rapid detection of wheat seed vigor.
Has the advantages that: the invention provides a modeling method for measuring wheat seed vigor, which comprises the following steps: carrying out vitality measurement on the seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight; using tetrazole solution to dye the activated seeds, scanning the dyed seeds, removing background color and endosperm parts from the scanning result, and extracting the phenotypic characteristics of the embryo part area of the seeds to obtain scanning data; and analyzing the scanning data and the vitality index data and establishing a regression model. The method provided by the invention can reduce the problem of strong subjectivity caused by manual judgment, and has the advantages of simple operation and good predictability.
Drawings
FIG. 1 shows the vitality of wheat seeds after artificial aging treatment;
FIG. 2 is a tetrazolium staining pattern (original drawing) of wheat seed embryo;
FIG. 3 is a tetrazolium staining pattern of wheat seed embryo (after treatment);
FIG. 4 is a scatter distribution diagram of true values and predicted values, with the abscissa being the seed number and the ordinate being the germination percentage;
FIG. 5 is a stepwise regression model verification of morphological characteristics of embryo of artificially aged wheat seeds, with the abscissa being the seed number and the ordinate being the germination percentage;
FIG. 6 is a tetrazolium staining pattern (original drawing) of wheat seed embryo;
FIG. 7 is a tetrazolium staining pattern of wheat seed embryo (after treatment).
Detailed Description
The substances and reagents used in the present invention are, if not specifically required, those conventionally purchased by those skilled in the art.
The invention provides a modeling method for measuring wheat seed vigor, which comprises the following steps:
carrying out vitality measurement on the seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight;
using tetrazole solution to dye the activated seeds to obtain dyed seeds;
scanning the dyed seeds, removing background colors and endosperm parts from the scanning results, and extracting phenotype characteristic data of the embryo parts of the seeds to obtain scanning data; the phenotypic features include texture features and color features; the texture features comprise gray values, contrast, dissimilarity, homogeneity, energy, correlation, angular second moment and entropy; the color features include R, G, B, H, S, V, L, a and b;
and analyzing the scanning data and the vitality index data and establishing a regression model.
The state or variety of the seeds is not particularly limited, and the seeds can be normal seeds or aged seeds, and the aging comprises artificial aging and natural aging. In the invention, the temperature of the artificial aging is preferably 41-45 ℃, and more preferably 41 ℃; the relative humidity of the artificial aging is preferably 98% to 100%, more preferably 98%. In the invention, the artificial aging can ensure that the seed materials with different activity gradients can be obtained, and can also accelerate the experimental process. In the embodiment of the present invention, the wheat variety preferably includes jimai 22, but it is not considered as the full protection scope of the present invention.
The method comprises the steps of carrying out vitality measurement on seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight. The method for determining the activity of the present invention is not limited at all, and may be performed in a manner known to those skilled in the art.
The invention uses tetrazole solution to dye the activated seed, to obtain the dyed seed. The activation is preferably carried out for 24 hours at 25 ℃, so as to obtain the activated seeds with softened seed coats and activated enzyme; the soaking is preferably distilled water soaking.
The mass percentage of the tetrazole in the tetrazole solution is preferably 1%; in the present invention, the method for preparing the tetrazole solution is not particularly limited, but preferably the tetrazole powder and the phosphate buffer solution are mixed in a ratio of 1 g: mixing 1L.
The dyeing of the invention is preferably to soak the half-grain activated seeds after the longitudinal cutting in a tetrazole solution, and the dosage of the tetrazole solution is preferably based on the submerged seeds. In the present invention, the longitudinal cutting is preferably performed along the seed groove line. The dyeing is preferably carried out under the dark condition, and the dyeing time is preferably 1-2 h, more preferably 2 h; the temperature of the dyeing is preferably 35 ℃. After the dyeing treatment, the invention preferably further comprises washing the dyed seeds; the number of the rinsing is preferably 3 times; the rinsing is preferably with clear water.
Scanning the dyed seeds, removing background colors and endosperm parts from the scanning results, and extracting phenotype characteristic data of the embryo parts of the seeds to obtain scanning data; the phenotypic features include texture features and color features; the texture features comprise gray values, contrast, dissimilarity, homogeneity, energy, correlation, angular second moment and entropy; the color characteristics include R, G, B, H, S, V, L, a and b. In the present invention, the contrast preferably includes a contrast in grayscale and a contrast in the R channel; the dissimilarity preferably includes dissimilarity in grayscale and dissimilarity in an R channel; the homogeneity preferably includes homogeneity in grayscale and homogeneity in the R channel; the energy preferably includes energy in grayscale and energy in the R channel; the correlation preferably includes a correlation in grayscale and a correlation in an R channel; the angular second moment preferably comprises an angular second moment in grayscale and an angular second moment in the R channel; the entropy preferably includes entropy in grayscale and entropy in the R channel.
The conventional methods at the present stage comprise a method of visual observation and a method of mainly observing or calculating the depth and the position of a dyeing (red) area, wherein the method adopts artificially aged seeds with different degrees or seeds of the same variety with different storage times; the method can simultaneously consider other color indexes and texture indexes, the adopted information is richer, and indexes with strong correlation with the seed vitality are screened out through correlation analysis to perform regression analysis and prediction. Wherein, the wheat seeds adopt a plurality of different varieties, and the universality of the experimental result on the production is stronger.
The present invention preferably performs the scanning by placing the embryo of the seed face down on the glass plate of the scanner. In the invention, the scanning resolution is preferably 300 dpi-600 dpi, which can ensure that the image is clear and the file is not too large.
The invention analyzes the scanning data and the vitality index data and establishes a regression model. In the present invention, the analysis includes analysis of variance, correlation analysis, and multiple linear regression analysis.
The model constructed by the method can reduce the problem of strong subjectivity of manual judgment, so that the model constructed by the method can predict the activity of the seeds.
The model constructed by the method is applied to rapid detection of wheat seed vigor.
For further illustration of the present invention, the following detailed description of a modeling method for determining wheat seed vigor provided by the present invention is provided in conjunction with the accompanying drawings and examples, which should not be construed as limiting the scope of the present invention.
Example 1
1. Artificially accelerated aging test
The Jimai 22 wheat seeds are put into nylon mesh bags, 500 grains are put into each bag, 16 bags are labeled, and the nylon mesh bags are put into a blast drying oven at the temperature of 41 ℃ (the relative humidity RH is 98%). Aging for 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15 days, taking out the seeds after aging, and drying at room temperature to the original weight.
2. Standard Germination test
300 of each of the treatments were counted, 100 were repeated, and the seeds were sterilized with 1% sodium hypochlorite for 5min and washed 3 times.
The test uses a paper bed germination method, a germination box and a sponge are cleaned, germination paper (the specification of 25cm by 38cm, manufactured by Anchor company in America) and the sponge are soaked, and the germination paper is placed on the sponge and is placed in the germination box.
The sterilized wheat seeds were placed on germination paper, 100 grains per box. And (4) sticking a label on the top end of the germination box, and writing the name of the variety, the aging days, the bed setting time and the repetition times. The germination box is placed in a germination room at 25 ℃ under the illumination condition for culture.
Wheat germination vigor was recorded on day 4 of germination, wheat germination percentage was recorded on day 8 and seedling fresh weight was weighed (four decimal places were kept), and the Simple Vigor Index (SVI) was calculated and the results of the survey are shown in table 1 and fig. 1. Wherein, the formula of the germination rate is as follows: the germination rate of wheat (number of normal germination seeds/number of test seeds on day 8) is multiplied by 100 percent, and the formula I is shown in the specification; the Simple Vitality Index (SVI) formula is: simple Vigor Index (SVI) germination rate × fresh weight of individual plant, formula ii.
TABLE 1 germination percentage, fresh weight, simple vigor index and germination vigor of the different treatments
As is clear from the test data shown in table 1 and fig. 1, the vigor of the wheat seeds gradually decreased with the aging time, and the germination percentage was close to 0 after 15 days of aging. And selecting the Jimai 22 wheat seeds artificially aged for 0, 1, 5, 7 and 9 days through analysis of variance to perform a tetrazole staining experiment, wherein the germination rates and the simple vitality indexes of the wheat seeds on different aging days are significantly different.
3. Tetrazolium staining assay
The average number of the artificially aged 0, 1, 5, 7 and 9 days of the Jimai 22 wheat seeds is 50 seeds with uniform size and no damage, and the steps are repeated for 3 times. Placing the seeds into a conical flask, adding sufficient distilled water, soaking for 24h at room temperature based on the water consumption for completely submerging the seeds to obtain activated seeds.
Cutting the activated seeds along the ventral sulcus line, taking half of the seeds, keeping the seeds in a wet state, putting the seeds into a clean culture dish, sticking a label, and adding a tetrazole solution with the concentration of 0.1 wt.% according to the standard that the seeds are submerged. The plates were placed in a light incubator (35 ℃ C., dark conditions) and stained for 2 h. The tetrazole solution having a concentration of 0.1% was prepared by weighing 1g of tetrazole powder and dissolving in 1L of phosphate buffer (5.45 g of sodium dihydrogen phosphate and 3.79g of disodium hydrogen phosphate were added to 1L of distilled water and sufficiently dissolved), and the tetrazole powder, sodium dihydrogen phosphate and disodium hydrogen phosphate were purchased from national pharmaceutical group chemical Co., Ltd.
And after dyeing is finished, pouring out the tetrazole solution in the culture dish, and washing the wheat seeds for 3 times by using clear water to obtain the dyed seeds. Note that the tetrazole solution should be ready for use and care should be taken to avoid light.
4. Machine vision and image segmentation
The tetrazolium-stained wheat seed embryos of each treatment replicate were placed face down on a glass plate of a scanner and scanned at a resolution of 300dpi to yield a PNG format file (fig. 2). The wheat tetrazolium staining images obtained by scanning were processed using Adobe Photoshop CS9 software to remove the background of the images and to wipe off the endosperm portion leaving only the embryo of the seed (fig. 3).
And (3) removing the black background except the seeds by Photoshop image processing, and extracting the phenotypic characteristics of the seeds by using PhonoSeed software. Wherein the texture features in the phenotype features comprise gray values and gray levels, and 15 of contrast, dissimilarity, homogeneity, energy, correlation, angular second moment and entropy in the R channel, the color features in the phenotype features comprise R, G, B, H, S, V, L, a and b, and the detection data are shown in Table 2.
TABLE 2 PhenoSeed software extraction of phenotypic characteristics of seed-stained embryos
Note: different lower case letters indicate significant differences between different treatments, p < 0.05.
5. Data processing
WPS Office 2019 is used as a table, and IBM SPSS statistics 20 software is used for carrying out variance analysis (one-factor variance analysis), correlation analysis (bivariate correlation analysis) and regression model establishment.
The data of the correlation analysis are shown in Table 3, and the data of the anova are shown in Table 4.
TABLE 3 correlation analysis of phenotypic characteristics of seed-stained embryos extracted by PhenoSeed software
Note: indicates significant correlation at 0.05 level (bilateral); significant correlation at 0.01 level (double-sided).
As can be seen from table 3, in the phenotype characteristics of the embryo part of the wheat after tetrazolium staining, which are extracted by the PhenoSeed software, the textural characteristics have no significant correlation with the germination vigor, the germination rate and the simple vitality index; in the color characteristics, R, V has a significant correlation with germination percentage and simple vigor index, and a and H have significant correlations with germination vigor, germination percentage and simple vigor index. Therefore, the seed vigor is predicted by using the color characteristics of the dyed embryo part, and the wheat seed vigor standard measurement based on the tetrazole dyeing image is realized.
The color features extracted by the PhenoSeed software were used for stepwise regression, and the data are shown in tables 4 and 5.
TABLE 4 summary of stepwise regression model of wheat seed embryo color characteristics
Note: predictor variable- (constant), R; a; b.
TABLE 5 wheat seed embryo color feature stepwise regression model coefficients
Note: dependent variable-germination rate.
As can be seen from tables 4 and 5, after the adjustment of the multiple linear regression models of R, a, b 3 variables and germination percentage selected by stepwise regression, the R is 0.943, the expansion factors of the 3 variables are all less than 10, no collinearity exists, and the regression model y is obtained as-3.045 +0011R +0.127a-0.063 b; wherein y represents germination percentage, R represents red of the three primary colors, a represents a range from red to green, and b represents a range from blue to yellow.
6. Verification of stepwise regression model of wheat seed embryo color characteristics
The standard germination test is carried out on 80 parts of naturally stored wheat seeds (180 parts of wheat seeds with different ages under natural conditions in a laboratory), and the germination rate is distributed from 2.0% to 93.3% and conforms to normal distribution. And (4) extracting the phenotype characteristic data of the embryo part of the wheat after tetrazolium staining from PhenoSeed software, and removing abnormal values by using a box diagram.
The accuracy of the regression model y-3.045 +0011R +0.127a-0.063b established by the artificial aging wheat 22 seeds was verified by using the 80 wheat seeds, and the result is shown in fig. 4: and comparing the true value of the germination rate of the 80 parts of wheat seeds with the predicted value to obtain a correlation coefficient of 0.483 which is extremely obviously correlated, but the correlation coefficient is low, and then, the model establishment is still carried out by utilizing the data of the 80 parts of wheat seeds.
The correlation analysis of the color characteristics of the dyed embryo of the naturally aged 80 parts of wheat seeds was carried out, and the results are shown in Table 6.
TABLE 6 correlation analysis of color characteristics of seed dyed embryo extracted by PhenoSeed software
Note: indicates significant correlation at 0.05 level (bilateral); significant correlation at 0.01 level (double-sided).
As can be seen from Table 6, in the color characteristics of the embryo part of 9 triticale after dyeing extracted by the PhenoSeed software, R, G, a, H and S have significant correlation with germination vigor, germination rate and simple vigor index.
Carrying out stepwise regression on the color characteristics extracted by utilizing PhenoSeed software, and mixing 80 parts of wheat seeds according to the weight ratio of 7: the proportion of 3 is divided into a modeling set and a test set, namely 56 parts of wheat seeds are randomly extracted to carry out stepwise regression to obtain a regression equation, 24 parts of wheat seeds are used for verifying the accuracy of the equation, and the result is shown in tables 7 and 8.
TABLE 7 summary of stepwise regression model of wheat seed embryo color characteristics
Note: the predictor variable- (constant), S mean is the average of the saturation, R mean is the average of the red in the tri-primary light, G mean is the average of the green in the tri-primary light.
TABLE 8 wheat seed embryo color feature stepwise regression model coefficients
Note: dependent variable-germination percentage, B is the regression coefficient and intercept, and the left corresponds to a constant representing the intercept and to a variable representing the regression coefficient.
As is clear from tables 7 and 8, the multiple linear regression model of R, G, S and germination percentage was adjusted to have an R-side of 0.513, and the regression model y was 4.012+ 0.051R-0.065G-0.041S.
The accuracy of the regression model y-4.012 +0.051R-0.065G-0.041S was verified using 24 wheat seeds not involved in the modeling, and the results are shown in table 9 and fig. 5.
FIG. 9 Germination data for 24 wheat seeds not involved in modeling
| Numbering | Actual germination percentage (%) | Predicted germination percentage (%) |
| 1 | 4 | 18 |
| 2 | 7.3 | 15 |
| 3 | 9.3 | 8 |
| 4 | 9.3 | 21 |
| 5 | 9.3 | 32 |
| 6 | 10.7 | 36 |
| 7 | 26 | 42 |
| 8 | 26 | 80 |
| 9 | 37.3 | 27 |
| 10 | 41.3 | 58 |
| 11 | 41.3 | 91 |
| 12 | 46 | 51 |
| 13 | 47.3 | 34 |
| 14 | 48.7 | 30 |
| 15 | 49.3 | 35 |
| 16 | 50 | 77 |
| 17 | 55.3 | 32 |
| 18 | 57.3 | 26 |
| 19 | 59.3 | 60 |
| 20 | 61.3 | 68 |
| 21 | 62.7 | 72 |
| 22 | 64 | 62 |
| 23 | 68 | 76 |
| 24 | 88.7 | 66 |
As can be seen from table 9 and fig. 5, the absolute value of the difference between the actual germination rate of the wheat variety having a real germination rate of about 60% and the predicted germination rate of the regression equation was small in the 24 seeds. The real value of the 24 wheat seeds is compared with the predicted value, and the obtained correlation coefficient is 0.583, which shows very significant correlation. Therefore, the model can be used for predicting the germination rate of the wheat variety.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (9)
1. A modeling method for measuring wheat seed vigor is characterized by comprising the following steps:
carrying out vitality measurement on the seeds to obtain vitality index data; the vitality index data comprise a germination rate, a germination vigor, a simple vitality index and a fresh weight;
using tetrazole solution to dye the activated seeds to obtain dyed seeds;
scanning the dyed seeds, removing background colors and endosperm parts from the scanning results, and extracting phenotype characteristic data of the embryo parts of the seeds to obtain scanning data; the phenotypic features include texture features and color features; the texture features comprise gray values, contrast, dissimilarity, homogeneity, energy, correlation, angular second moment and entropy; the color features include R, G, B, H, S, V, L, a and b;
and analyzing the scanning data and the vitality index data and establishing a regression model.
2. The method according to claim 1, characterized in that the activated seeds are longitudinally cut and placed in a tetrazole solution for dyeing, and the tetrazole content in the tetrazole solution is 1% by mass; the dyeing time is 1-2 h, and the temperature is 35 ℃.
3. The method according to claim 2, wherein the activation is soaking at 25 ℃ for 24 h.
4. The method of claim 2, wherein the slitting is along the seed groin line.
5. The method of claim 1, wherein the analysis comprises analysis of variance, correlation, and multiple linear regression.
6. The method of claim 1, wherein the vitality indicator data used for data analysis comprises germination rate, germination vigor, fresh weight, and simple vitality index.
7. The method of claim 1, wherein the scan has a resolution of 300dpi to 600 dpi.
8. The method of claim 1, wherein the contrast comprises a contrast in grayscale and a contrast in an R-channel; the dissimilarity degree comprises dissimilarity degree under gray scale and dissimilarity degree under an R channel; the homogeneity includes homogeneity under gray scale and homogeneity under R channel; the energy comprises energy in grayscale and energy in an R channel; the correlation includes a correlation in grayscale and a correlation in an R channel; the angular second moment comprises an angular second moment under the gray scale and an angular second moment under the R channel; the entropy includes entropy in grayscale and entropy in the R channel.
9. Use of the model constructed by the method of any one of claims 1 to 8 in rapid detection of wheat seed vigor.
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