CN108875304A - A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii - Google Patents

A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii Download PDF

Info

Publication number
CN108875304A
CN108875304A CN201710332024.0A CN201710332024A CN108875304A CN 108875304 A CN108875304 A CN 108875304A CN 201710332024 A CN201710332024 A CN 201710332024A CN 108875304 A CN108875304 A CN 108875304A
Authority
CN
China
Prior art keywords
herba dendrobii
sample
confidence interval
value
stem diameter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201710332024.0A
Other languages
Chinese (zh)
Inventor
赵田
张国强
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Lanbiao Yicheng Technology Co Ltd
Original Assignee
Beijing Lanbiao Yicheng Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Lanbiao Yicheng Technology Co Ltd filed Critical Beijing Lanbiao Yicheng Technology Co Ltd
Priority to CN201710332024.0A priority Critical patent/CN108875304A/en
Publication of CN108875304A publication Critical patent/CN108875304A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures

Landscapes

  • Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Peptides Or Proteins (AREA)

Abstract

The present invention relates to foundation, judgment criteria and the judgment methods of a kind of method for judging the purebred phase recency of Herba Dendrobii, and the establishment process of the judgment method is S1:Acquisition and the consistent Herba Dendrobii sample of gene sequencing conclusion, measure second internode stem diameter of each sample;S2:Test of normality is carried out to second internode stem diameter variable of sample;S3:Standard section:If obtained result is Normal Distribution in step S2,95% confidence interval of mean value and 95% confidence interval of standard deviation are obtained according to normal distribution totality calculation formula;The confidence interval just can be as the critical field for identifying unknown sample degree of purity.It is according to the judgment criteria that the data of actual acquisition are established:95% confidence interval of mean value and 95% confidence interval of standard deviation are respectively:(4.0515,4.4661) and (1.0178,1.3137), tested Herba Dendrobii sample only need to compare with the section.The present invention can identify the degree of purity of its kind by the relevant feature of Herba Dendrobii morphology, so as to simply judge its value of the Herba Dendrobii of artificial growth or whether there is;Its accuracy rate identified is high, has important practical significance.

Description

A kind of foundation of method judging the purebred phase recency of Herba Dendrobii, judgment criteria and Judgment method
Technical field
The present invention relates to field of medicaments and field of biology, and in particular to a kind of side for judging the purebred phase recency of Herba Dendrobii The foundation of foundation, judgment criteria and the judgment method of method, i.e. Herba Dendrobii morphological feature and gene sequencing conclusion relevance The discrimination method etc. of method and tested Herba Dendrobii kind degree of purity.
Background technique
Dendrobium nobile is a kind of common tonic Chinese herbal medicine, predominantly Dendrobium Sw.Dendrobium Sw is maximum in orchid A category, including multiple kinds such as Herba Dendrobii, Dendrobium fimbriatum Hook, dendrobium candidum, HERBA DENDROBII, dendrobium, Dendrobium Chrysotoxum Lindl. In the world, there are about more than 1100 kinds of dendrobium nobiles, wherein having nearly hundred kinds in China's discovery.The medicinal history of dendrobium nobile is long, early ?《Sheng Nong's herbal classic》In be just listed in nourishing top grade, for a long time, with the development of the times, dendrobium nobile is considered as treasure by people always Expensive Chinese herbal medicine has highly important nourishing effects.Clinically, dendrobium nobile be used to treat a variety of diseases, and there is enhancing to exempt from The pharmacological effects such as epidemic disease power, anti-oxidant, hypoglycemic and inhibition cancer.Dendrobium nobile including Herba Dendrobii is led in traditional Chinese medicine and health care Domain has extremely important value.
However, since artificial long-term uncontrolled excavation and irrational utilization dendrobium nobile, wild resource are reduced increasingly, artificial kind It plants situation gradually to increase, or even becomes the source of main supply Herba Dendrobii.However, long-term artificial growth is also Herba Dendrobii The phenomenon that mixing the spurious with the genuine, adulterating is brought, this is because 1. artificial growth changes the growth ring of wild Herba Dendrobii Border;2. largely applying various types of fertilizer, lesion, applying the artificial application of pesticide, the new appearance of kinds of Diseases etc. On Herba Dendrobii;3. and since dendrobium species are more, it is interracial hybridization so that the kind of its nearly edge there are character intersections Phenomenon;4. other uncontrollable or immesurable factors, to sum up reason result in some artificial growths Herba Dendrobii its it is medicinal at Point changed or even important medicinal ingredient disappears, correspondingly, the folded sheath stone that these medicinal ingredients change or disappear Also there is substantive difference with original wild gene order in its gene order of dry measure used in former times.Once and the medicinal valence of these Herba Dendrobiis Value weakens or disappears, and this field also continues to apply what is do not known, then its consequence is very serious, and works as the feelings that people do not know Herba Dendrobii is caused to disappear under condition from field of medicaments, then its consequence is even more serious.
The applicant by long-term, very big workload the study found that certain Herba Dendrobii morphology correlated characteristics and its Gene sequencing conclusion has very close relationship, and gene sequencing conclusion is exactly that the standard with traditional medicinal/nutritive value is folded The gene sequencing of sheath dendrobium nobile is as a result, wild Herba Dendrobii is substantially consistent with gene sequencing conclusion.That is can pass through The morphologic feature of Herba Dendrobii judges the degree of association of itself and gene sequencing conclusion, the degree of association or its higher kind of phase recency Degree of purity it is higher, it is easier to keep traditional medicinal, health-care efficacy, the degree of purity of the degree of association or its lower kind of phase recency A possibility that lower, i.e., it is bigger with the substantive difference of gene sequencing conclusion, and medicinal efficacy reduces or disappears is bigger.
What gene sequencing conclusion reflected is the kind of sample, for the degree of purity or gene phase recency of differential variety, in base Because on the basis of sequencing conclusion how efficiently by the measurement to morphology correlated characteristic, can judgement sample kind it is pure Degree, the problem of must be taken into consideration when being our practical applications.
Summary of the invention
In view of the above-mentioned problems in the prior art, it is a primary object of the present invention to solve the defect of the prior art, The present invention provides foundation, judgment criteria and the judgment method of a kind of method for judging the purebred phase recency of Herba Dendrobii.
The purpose of the present invention is mainly achieved through the following technical solutions.
A kind of foundation for the method judging the purebred phase recency of Herba Dendrobii, the establishment process include the following steps:
S1:Standard data acquisition:Acquisition and the consistent Herba Dendrobii sample of gene sequencing conclusion, sample size n, measurement Second internode stem diameter of each sample, obtains the measurement numerical value of second internode stem diameter variable;
S2:Test of normality:Test of normality is carried out to second internode stem diameter variable of sample;
S3:Standard section:If obtained result is Normal Distribution in step S2, totally counted according to normal distribution It calculates formula and obtains 95% confidence interval of mean value and 95% confidence interval of standard deviation;
If second internode stem diameter variable test of normality result of Herba Dendrobii is to disobey normal state point in step S2 Cloth, then if sample size exceeds 30, according to central-limit theorem it is found that the sample still is able to the public affairs according to normal population Formula calculates 95% confidence interval of its mean value and 95% confidence interval of standard deviation;
95% confidence interval of mean value obtained above and 95% confidence interval of standard deviation just can be unknown as identifying The critical field of sample degree of purity.
Further, after step S1 obtains the measurement numerical value of second internode stem diameter variable, according to second internode The measurement numerical value of stem diameter variable calculates the basic statistics amount of second internode stem diameter variable, and the basic statistics amount includes flat Horizontal and dispersion degree, then determining data according to basic statistics amount, whether there is or not exceptional values, are checked if having exceptional value, such as Fruit belongs to measurement error or record fault then suppressing exception point, if not because of error, then should retain this data.
Further, the average level includes at least one of mean value, median and mode, the dispersion degree packet Include standard deviation, mean absolute deviation and the coefficient of variation;
The basic statistics amount further include according to the measurement numerical value production histogram of second internode stem diameter variable and/or Data visualization is made its more convenient determining wrong exceptional value by box diagram.
Further, the test of normality includes at least one of visual image analysis and hypothesis testing.
Further, the test of normality includes visual image analysis and hypothesis testing.
Further, the method for the visual image analysis is:
1. according to normal state empirical distribution functionDraw the normal state experience of Herba Dendrobii Distribution function curve;
According to normal probability density functionDraw the normal probability density curve of Herba Dendrobii; As μ=0, σ=1, normal distribution just becomes standardized normal distribution:
2. the measurement numerical value of second internode stem diameter variable according to obtained in step S1, and be according to formulaEmpirical distribution function draw true empirical distribution function;
The measurement numerical value of second internode stem diameter variable according to obtained in step S1, and be according to formulaProbability density function draw trues probability density functional arrangement;
3. true empirical distribution function figure and the distribution function curve of normal distribution are compared, pass through judgment curves deviation journey The size of degree comes whether preliminary judgement sample data meets normal distribution;By the general of trues probability density functional arrangement and normal distribution The comparison of rate density curve, also according to extent of deviation size and the curve shape degree of consistency, come determine sample data whether be Normal Distribution;
If the distribution function figure or true empirical probability density functional arrangement of true empirical distribution function figure and normal distribution It is small with the deviation of the probability density function figure of normal distribution and shape is consistent, then second internode stem of Herba Dendrobii sample to be detected Diameter meets normal distribution, if the deviation obviously very big and different cause of shape, second, Herba Dendrobii sample section to be detected Between stem diameter do not meet normal distribution.
Further, the hypothesis testing includes any one during JB inspection, KS inspection and Lilliefors are examined.
Further, the hypothesis testing is that Lilliefors is examined, the Lilliefors test statistics T=sup | F*(x)-S (x) |, in formula, T is Liffiefors test statistics, F*It (x) be mean value is 0, the normal distribution that standard deviation is 1 is tired Product distribution function, S (x) areEmpirical distribution function value, under the significance of α, when test statistics T is super When crossing inspection critical value, refuse null hypothesis H0;Otherwise, null hypothesis cannot be refused.
A kind of judgment criteria of the purebred phase recency of Herba Dendrobii, the judgment criteria include the following steps:
(1):Acquisition and consistent 120, the wild Herba Dendrobii sample of gene sequencing conclusion, measure the second of each sample A internode stem diameter, measurement result are as follows:Second internode changes in stem diameter range of Herba Dendrobii is 1.56mm~7.72mm, The result that average level obtains after 3.87mm~4.29mm, calculating is:Mean value:4.26mm median:4.29mm mode: 3.87mm, the standard deviation of second internode stem diameter fluctuation are 1.15mm, mean absolute deviation:0.87mm, the coefficient of variation: 0.27;(2):Visual image analyzes normal distribution:Empirical distribution function figure and probability density are drawn according to the data in step (1) The result that true empirical distribution function figure is compared with normal state empirical distribution function curve is by functional arrangement:The curve of the two It is almost the same;It is by the result that trues probability density functional arrangement is compared with normal probability density curve:The curve of the two Shape is roughly the same;
By the intuitive analysis to the above figure it is found that second internode stem diameter sample data of Herba Dendrobii is very possible Meet normal distribution;
(3):Lilliefors is examined:Null hypothesis is H0:Data Normal Distribution;Alternative hypothesis H1:Data are disobeyed Normal distribution;It is by the inspection result that the data in step (1) obtain:
Statistic Critical value P value Level of significance α Whether null hypothesis is received
0.0578 0.0814 0.4045 0.05 It is
The value of statistic is 0.0578, is less than critical value 0.0814;P value be equal to 0.4045, be greater than significance (α= 0.05), so receiving null hypothesis, then it can confirm Herba Dendrobii sample data Normal Distribution;
(4):Then second internode stem diameter sample data of Herba Dendrobii is calculated according to normal distribution totality calculation formula 95% confidence interval of 95% confidence interval of mean value and standard deviation, respectively:
Mean value 95% confidence interval of mean value Standard deviation 95% confidence interval of standard deviation
4.2588 (4.0515,4.4661) 1.1469 (1.0178,1.3137)
95% confidence interval of above-mentioned mean value and 95% confidence interval of standard deviation are respectively:(4.0515,4.4661) and (1.0178,1.3137), the section are just the standard section for judging the purebred phase recency of Herba Dendrobii.
A kind of judgment method of the purebred phase recency of Herba Dendrobii, the method are:
A. acquire second internode stem diameter data of Herba Dendrobii sample to be detected, exclude in sample due to measurement error or Recording error causes caused exceptional value;
B. the 95% confidence area of mean value of second internode stem diameter data of Herba Dendrobii sample to be detected in step A is calculated Between and 95% confidence interval of standard deviation, if the two (standard section in the obtained standard section of above-mentioned steps (4) For:95% confidence interval of mean value and 95% confidence interval of standard deviation are respectively:(4.0515,4.4661) and (1.0178, 1.3137)), then the purebred phase recency of Herba Dendrobii to be detected is high, i.e., the degree of purity of Herba Dendrobii to be detected is high;If to be detected In 95% confidence interval of 95% confidence interval of mean value and standard deviation of second internode stem diameter data of sample of Herba Dendrobii extremely Rare one not in the obtained standard section of above-mentioned steps (4), then the purebred phase recency of Herba Dendrobii to be detected is low, i.e., The degree of purity of Herba Dendrobii to be detected is low.
The present invention at least has the advantages that:
The morphological feature of Herba Dendrobii is established with Herba Dendrobii gene sequencing conclusion and is connect by method of the invention, is led to Its gene degree of purity can be known by crossing morphological feature.It can be reflected by second internode stem diameter data of Herba Dendrobii Not Bei Ce Herba Dendrobii kind degree of purity;This method can be very simple, succinct the Herba Dendrobii for judging artificial growth Value, even with the presence or absence of value.
The present invention establishes the standard for judging degree of purity, passes through 95% confidence interval of mean value and 95% confidence of standard deviation Section can judge the purebred phase recency of tested Herba Dendrobii, and this method is simple and accurate, in the applicant largely studies Know, the method for the present invention can judge Herba Dendrobii sample degree of purity with 90% or more accuracy rate, apply valence with important Value.
The medical value that can judge certain a collection of Herba Dendrobii substantially by the method for the invention, is reacted by morphological feature Its substantive characteristics has far-reaching significance entire the world of medicine and plant kingdom.In addition, the present invention is also possible to open a kind of update , more accurate morphology sort out theory or thinking.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of histogram described in the embodiment of the present invention;
Fig. 2 is the structural schematic diagram of box diagram described in the embodiment of the present invention;
Fig. 3 is the structural schematic diagram of empirical distribution function curve described in the embodiment of the present invention;
Fig. 4 is the structural schematic diagram of probability density curve described in the embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with of the invention specific real It applies example technical solution of the present invention is clearly and completely described, it is clear that described embodiment is that a part of the invention is real Example is applied, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creation Property labour under the premise of every other embodiment obtained, shall fall within the protection scope of the present invention.
Embodiment 1
A kind of foundation for the method judging the purebred phase recency of Herba Dendrobii, the method for building up include the following steps:
S1:Standard data acquisition:Acquisition all meets the Herba Dendrobii sample of the morphology description of Herba Dendrobii, that is, acquires With the consistent Herba Dendrobii sample of gene sequencing conclusion, sample size n measures second internode stem diameter of each sample, Obtain the measurement numerical value of second internode stem diameter variable;
S2:The confirmation of data:It is straight that second internode stem is calculated according to the measurement numerical value of second internode stem diameter variable The basic statistics amount of diameter variable, the basic statistics amount include average level and dispersion degree, the average level include mean value, At least one of median and mode, the dispersion degree include standard deviation, mean absolute deviation and the coefficient of variation;And according to Correspondingly data visualization can be become apparent from clear observation, analysis, judgment variable point by data creating histogram and box diagram Cloth situation and exceptional value.Then determine the wrong exceptional value of data, checked if having exceptional value, if belong to measurement error or Record fault then suppressing exception point, if not because of error, then this data should be retained, if not because of error, that This data should be retained.
S3:Test of normality:Test of normality is carried out to second internode stem diameter variable of sample;The test of normality Including at least one of visual image analysis and hypothesis testing, preferably both of which is used, can be in terms of subjectivity and objective two It tests.
The method of visual image analysis is:
1. according to normal state empirical distribution functionDraw the normal state experience of Herba Dendrobii Distribution function curve;X in formula is stochastic variable, that is, the sample observations of Herba Dendrobii;μ is the sample observation acquired The mean value of value;σ is the standard deviation of sample observations;E is natural constant, and value is about 2.71828;The function of the normal distribution is bent Line has given, and goes out normal state empirical distribution curve by computer also analog, acquires, draw not according to initial data Make the normal state empirical distribution function curve be desirable to by the distribution function curve of initial data and the function curve of normal distribution into Row compare, come examine initial data whether Normal Distribution.
According to normal probability density functionThe normal probability density curve of Herba Dendrobii is drawn, As μ=0, σ=1 (mean value 0, standard deviation 1), normal distribution just becomes standardized normal distribution: X in formula is stochastic variable, that is, the sample observations of dendrobium nobile;E is natural constant, and value is about 2.71828.Equally The probability density function curve on ground, normal distribution has given, and it is bent to go out the distribution of normal state experience by computer also analog Line acquires not according to initial data.The normal probability density curve is drawn to be desirable to the probability density letter of initial data Number curve is compared with normal probability density function curve, come examine initial data whether Normal Distribution.
Above-mentioned initial data is data obtained in the step S1 of summary of the invention.
2. the measurement numerical value of second internode stem diameter variable according to obtained in step S1, rule of thumb distribution function (EDF, Empirical Distribution Functions) draws true empirical distribution function;
The empirical distribution function formula is:If x1,x2,...,xnIt is the sample measures that one group of overall sample size is n Value, n measured value is rearranged for by sequence from small to largeFor any real number x, (x is i.e. for sample This measured value x1, x2 ..., xn), defined function
Then claim Fn(x) empirical distribution function for being totality X.It can be abbreviated as Fn(x)=1/n*{x1,x2,...,xn, Wherein*{x1,x2,...,xnIndicate x1,x2,...,xnIn be not more than x number.Another common representation is
Wherein, I is indicative function, i.e.,
Therefore, empirical distribution function F is soughtn(x) value at x on one point, as long as finding out the n observation x of stochastic variable x1, x2,...,xnIn be less than or equal to the number of x, then divided by observation frequency n.It can be seen that FnIt (x) is exactly only in n times repetition The frequency that event { X≤x } occurs in vertical experiment.
The measurement numerical value of second internode stem diameter variable according to obtained in step S1, and drawn according to probability density function Trues probability density functional arrangement processed;
The formula of the probability density function (probabi l ity dens ity function, PDF) is:If right In the distribution function F (x) of stochastic variable X, there are nonnegative function f (x), so that having for any real number Then claiming X (measured value x1, x2 ..., xn that x is i.e. sample) is random variable of continuous type, wherein f (x) be known as X probability it is close Spend function, abbreviation probability density.The probability density function of random data indicates that instantaneous amplitude falls in the probability in certain specified range, It therefore is the function of amplitude.It changes with the amplitude of taken range.
Probability density function has the following property: Since the probability density function is from distribution function, the figure of probability density function can be directly according to sample measurement number According to each data x1, x2 ..., what xn was calculated.
3. true empirical distribution function figure and normal state empirical distribution function curve are compared, pass through judgment curves deviation The size of degree comes whether preliminary judgement sample data meets normal distribution;Trues probability density functional arrangement and normal probability paper is close Line of writing music compares, also according to extent of deviation size and the curve shape degree of consistency, come determine sample data whether be Normal Distribution;
If the distribution function figure or true empirical probability density functional arrangement of true empirical distribution function figure and normal distribution It is small with the deviation of the probability density function figure of normal distribution and shape is consistent, then second internode stem of Herba Dendrobii sample to be detected Diameter meets normal distribution, if the deviation obviously very big and different cause of shape, second, Herba Dendrobii sample section to be detected Between stem diameter do not meet normal distribution.
By drawing sample empirical distribution function figure and sample empirical probability density functional arrangement, and by itself and normal distribution phase Functional arrangement is answered to compare, the intuitive difference degree for observing two curves, so that second internode stem diameter variable of judgement sample is It is no to come from normal distribution.
Hypothesis testing
The hypothesis testing includes any one during JB inspection, KS inspection and Lilliefors are examined, preferably Lilliefors is examined.
The Lilliefors test statistics T=sup | F*(x)-S (x) |, in formula, T is Liffiefors inspection statistics Amount, F*It (x) be mean value is 0, the normal distribution cumulative distribution function that standard deviation is 1, S (x) isExperience be distributed letter Numerical value, when test statistics T is more than to examine critical value, refuses null hypothesis H under the significance of α0;Otherwise, it cannot refuse Exhausted null hypothesis.
By Lilliefors normal distribution hypothesis testing method can more objective judgement sample whether from one Normal distribution is overall.
S4:Standard section:If obtained result is Normal Distribution in step S3, totally counted according to normal distribution It calculates formula and obtains 95% confidence interval of mean value and 95% confidence interval of standard deviation;
If second internode stem diameter variable test of normality result of Herba Dendrobii is to disobey normal state point in step S3 Cloth, it is contemplated that Infinite-Sample Properties are that is, when sample size is bigger, i.e., general to require>30, then according to central-limit theorem it is found that The sample still is able to calculate 95% confidence area of 95% confidence interval of its mean value and standard deviation according to the formula of normal population Between.
95% confidence interval of mean value obtained above and 95% confidence interval of standard deviation just can be unknown as identifying The critical field of sample degree of purity.
Embodiment 2
A kind of judgment criteria of the purebred phase recency of Herba Dendrobii, mainly includes the following steps that:
(1):Acquisition and the consistent wild Herba Dendrobii sample of gene sequencing conclusion, sample size are 120, and measurement is each Second internode stem diameter of sample, measurement result are as follows:Second internode changes in stem diameter range of Herba Dendrobii substantially exists 1.56mm~7.72mm, the result that average level substantially obtains after 3.87mm~4.29mm, calculating are:Mean value:In 4.26mm Digit:4.29mm mode:3.87mm, the standard deviation of second internode stem diameter fluctuation are 1.15mm, mean absolute deviation: 0.87mm, the coefficient of variation:0.27.
And according to above-mentioned data creating histogram and box diagram by data visualization, as illustrated in fig. 1 and 2.By box diagram 1~ It is found that there are abnormal points in numerical value collected in 2, learn the abnormal point not due to measurement error or note by checking again Caused by record fault, therefore the point also belongs to normal value, retains this data.(2) identify Herba Dendrobii sample degree of purity to be determined Standard section
According to the quantitative value of each plant of second internode stem diameter in 120 samples measured, and rule of thumb divide Cloth function draws the curve of true empirical distribution function, as shown on the solid line in figure 3;The curve of empirical distribution function is one in jump Jump onto the step curve risen.Smooth curve is the figure of the theoretic distribution function of overall X in figure.
According to the quantitative value of each plant of second internode stem diameter in 120 samples measured, and it is close according to probability It spends function and draws trues probability density function curve, as shown in solid in Fig. 4.
It is drawn according to the data of the second of Herba Dendrobii internode stem diameter, and according to the formula of normal state empirical distribution function The normal state empirical distribution function curve of Herba Dendrobii, as shown in Figure 3.
It is drawn according to the data of the second of Herba Dendrobii internode stem diameter, and according to the formula of normal probability density function The normal probability density function curve of standard Herba Dendrobii, as shown in Figure 4.
The ordinate of Fig. 3 indicates the cumulative probability that event { X≤x } occurs in 120 repetition independent experiments, and ordinate indicates Be the sum of probability that sample event is less than or equal to some numerical value, by accumulating experience, distribution function can be unified at one The probability distribution that variable is described under angle, for normal distribution, cumulative distribution function has a fixed curve, So difference of accumulate experience the distribution function figure and normal cumulative empirical distribution function figure of the drafting of comparative sample data, Ji Kezhi It sees ground and finds out whether sample data meets normal distribution.Fig. 4 ordinate indicates that the density of probability, density are bigger at the range Probability is also bigger.The abscissa of Fig. 3 and Fig. 4 indicates the value range of stochastic variable, i.e. abscissa is Herba Dendrobii second The quantitative range of a internode stem diameter, the ordinate of Fig. 3 indicate that sample data accumulates it less than or equal to the probability of some numerical value The density of probability is indicated with the ordinate of, Fig. 4, the bigger probability at the range of density is also bigger.
According to the empirical distribution function figure and probability density function figure drawn, it is more intuitive come from subjective angle from the Whether the distribution of two internode stem diameter sample datas obeys normality.Empirical distribution function curve can be used to assess distribution with The degree of fitting of data estimates percentile and the different sample distribution of comparison.Herba Dendrobii can be intuitive to see by Fig. 3 The distribution situation of two internode stem diameter data.
Specifically, it can see from the empirical distribution function figure of Fig. 3, true empirical distribution function curve and normal state experience Distribution function curve is almost the same;From the probability density function figure of Fig. 4 as can be seen that trues probability density curve shape with The shape of normal probability density curve is roughly the same.By being believed that Herba Dendrobii substantially to the intuitive analysis of upper curve Second internode stem diameter sample data probably meets normal distribution.
Since in real life, many data all meet the feature of normal distribution, so we can first pass through the above method To judge that the true distribution of initial data can not be adopted with normal distribution comparable situation for obviously meeting the data of normal distribution Use hypothesis testing.
Next, by assuming that whether the method judgement sample examined really is from a normal distribution totality.
It is verified using the Lilliefors method of inspection, null hypothesis H0:Data Normal Distribution;Alternative hypothesis H1:Data disobey normal distribution.
Test statistics and P are calculated according to the data of second internode stem diameter in Herba Dendrobii sample collected Value, inspection result are as shown in table 1.
1 Lilliefors inspection result of table
Statistic Critical value P value Level of significance α Whether null hypothesis is received
0.0578 0.0814 0.4045 0.05 It is
Critical value in table 1 is not subjective given, but determined by the method for inspection and sample size.The work of P value With being exactly to decide whether refusal null hypothesis, if P value is less than significance (generally taking 0.05), we just refuse Null hypothesis thinks that data disobey normal distribution.The value that can be seen that statistic from the inspection result in table 1 is 0.0578, Less than critical value 0.0814;P value is equal to 0.4045, is greater than significance (α=0.05);So receiving null hypothesis, it is believed that folded Second internode stem diameter sample data Normal Distribution of sheath dendrobium nobile.
The calculation formula of above-mentioned P value is:When alternative hypothesis H1 is μ ≠ μ0When, p=21- Φ (Z0)];When alternative hypothesis H1 is μ > μ0When, p=1- Φ (Z0);When alternative hypothesis H1 is μ < μ0When, p=Φ (Z0).Wherein, Φ (Z0) it is normal distribution experience letter Number, be by tabling look-up to obtain, and μ is the statistic being calculated, μ0It is the assumption value of the statistic,The P value can be directly calculated by software, such as Matlab software.
Its confidence interval is calculated according to second internode stem diameter data of the Herba Dendrobii to be detected of the present embodiment acquisition Deng concrete outcome is as shown in table 2.
Mean value, the calculated result of standard deviation and confidence interval of 2 second internode stem diameter of Herba Dendrobii of table
Mean value 95% confidence interval of mean value Standard deviation 95% confidence interval of standard deviation
4.2588 (4.0515,4.4661) 1.1469 (1.0178,1.3137)
95% confidence interval of mean value and 95% confidence interval of standard deviation are respectively:(4.0515,4.4661) and (1.0178,1.3137), the section are just the standard section for judging the purebred phase recency of Herba Dendrobii, i.e., the section is just to identify to fold The standard section of sheath dendrobium species degree of purity.
Embodiment 3
A kind of judgment method of the purebred phase recency of Herba Dendrobii, the method are:
A. acquire second internode stem diameter data of Herba Dendrobii sample to be detected, exclude in sample due to measurement error or Recording error causes caused exceptional value;
B. the 95% confidence area of mean value of second internode stem diameter data of Herba Dendrobii sample to be detected in step A is calculated Between and 95% confidence interval of standard deviation, if the two in the standard section that embodiment 2 obtains, Herba Dendrobii to be detected it is pure The phase recency of kind is high, i.e., the degree of purity of Herba Dendrobii to be detected is high;If second internode stem of the sample of Herba Dendrobii to be detected is straight The standard that at least one in 95% confidence interval of 95% confidence interval of mean value and standard deviation of diameter data is not obtained in embodiment 2 In section, then the purebred phase recency of Herba Dendrobii to be detected is low, i.e., the degree of purity of Herba Dendrobii to be detected is low.
As further preferred embodiment, in step A, can by histogram described in embodiment 1 or embodiment 2 and Box diagram carrys out auxiliary judgment, and whether there is or not exceptional values.
Embodiment 4
The associated research of the morphological feature and kind degree of purity of the present inventor's long campaigns Herba Dendrobii, with research It was found that Herba Dendrobii being affected for certain morphological features that degree of purity is low, by a large amount of wild Herba Dendrobii and The data of the sample of artificial growth and summary, comparison, the research of sample etc., obtain substantially:Degree of purity is high, and (i.e. purebred is close Degree is high) the empirical distribution function curve of Herba Dendrobii its second internode stem diameter, probability density function curve etc. and normal state The deviation and shape of distribution function curve are almost the same, and 95% confidence interval of mean value and 95% confidence interval of standard deviation are in reality It applies in the standard section that example 2 obtains, and its mean value of Herba Dendrobii sample to be measured of degree of purity lower (i.e. purebred phase recency is low) 95% confidence interval and 95% confidence interval of standard deviation at least one not in the standard section that embodiment 2 obtains, standard regions Between i.e. mean value 95% confidence interval (4.0515,4.4661) and standard deviation 95% confidence interval (1.0178,1.3137).
In addition, in the past ten years, the present inventor has carried out sample collection many times, meter in the multiple places in the whole nation Calculate, comparison etc., and repeatedly carry out gene sequencing, compared and found by big data, the judgment method in the present invention it is accurate Rate is 90% or more.If 95% confidence interval of mean value and 95% confidence interval of standard deviation of Herba Dendrobii sample to be measured be not in standard In section, then the gene order similarity of Herba Dendrobii and real Herba Dendrobii is tested 95% hereinafter, and in above-mentioned mark Tested Herba Dendrobii sample in quasi- section, with the gene order similarity of real Herba Dendrobii substantially 95% with On.
Some tested Herba Dendrobii samples placed on record are now randomly selected, as described in Example 3 to its mean value 95% confidence interval of 95% confidence interval and standard deviation is calculated, as shown in table 3 below.
3 part case of table illustrates situation table (second internode stem diameter)
In upper table, place is province where tested sample, and 95% confidence interval of mean value and 95% confidence interval of standard deviation are equal Refer to the tested obtained section of Herba Dendrobii sample, if whether be the value of tested Herba Dendrobii sample in standard section at this Invent obtained 95% confidence interval of mean value;Phase recency is tested quantity and sample size of the Herba Dendrobii sample in section The percentage of ratio.
For above-mentioned sample, by practical measurement it is found that the accuracy rate of the application method is high, with important application reference Value.
When it is implemented, the formula that the present invention needs to use is as follows:
Mean value:Here mean value is arithmetic mean of instantaneous value (mean), and calculation method isWherein n is dendrobium nobile Sample size.
Median:It, can be by finding out one of middle after all observed values height are sorted for limited manifold Usually take the average of most intermediate two values as median if observed value has even number as median.
When N is odd number, m0.5=X(N+1)2;When N is even number,
Mode:Generally use M0It indicates, is exactly that number that accounting example is most in one group of data.
Standard deviation:Standard deviation is a kind of measurement of one group of statistical average degree of scatter, and a biggish standard deviation represents It differs greatly between most of numerical value and its average value;One lesser standard deviation represents these numerical value and is closer to average value.Meter Calculating formula isWherein μ is average value.Because what we largely contacted is sample, generally calculate Be sample standard deviation, sample standard deviation can be understood as a unbiased esti-mator to given population standard deviation, calculation formula ForWhereinFor sample average.
Mean absolute deviation:It is usually denoted as MAD (MeanAbsolute Deviation), calculates each observed value and average value Apart from summation, then take its average.Calculation formula is
The coefficient of variation:When needing to compare two groups of data discrete degree sizes, if the measurement scale of two groups of data Too big or data dimension difference is differed, is directly compared using standard deviation improper, should just eliminate measurement at this time The influence of scale and dimension, and the coefficient of variation (CV, Coefficient of Variation) can accomplish this point, for original The ratio of beginning data standard difference and initial data average.The calculation formula of the coefficient of variation is
Confidence interval:Mean value and standard deviation that front calculates are the point estimate of parameter, are with counted one, sample Value removes estimation unknown parameter.But point estimate is only an approximation of unknown parameter, it does not reflect this approximation The error range of value, the form that range leads to conventional section provide.It is desirable that determine a section, it can be with relatively high reliable journey Degree believes that it includes true parameter value, this degree of reliability is commonly referred to as confidence level, is denoted as 1- α, and α is known as the level of signifiance here, It is the positive number of a very little, usually takes α=0.025,0.05,0.1 etc..
Work as variances sigma2When known, statistic isThe confidence interval of mean μ is:
Work as variances sigma2When unknown, statistic isThe confidence interval of mean μ is:
When mean μ is unknown, statistic isThe confidence interval of standard deviation sigma is:
Lilliefors is examined:
Hypothesis testing is for judgement sample and sample, and sample and overall difference are to be caused by sampling error or essence Statistical Inference caused by difference.The basic principle is that first making certain it is assumed that then grinding by sampling to overall feature The statistical inference studied carefully should be rejected this hypothesis or receive to draw an inference.Normal distribution-test in hypothesis testing includes Three classes:Whether JB is examined, KS is examined, Lilliefors is examined, for test samples from a normal distribution totality.
Wherein, Liffiefors inspection is the improvement that KS is examined, and KS inspection is that sample and standardized normal distribution is (equal Value is 0, variance 1) it compares, and the target not instead of standard normal that Liffiefors is examined, have identical as sample The normal distribution of mean value and variance.It is suitable for the normal distribution-test of small sample, unknown parameters, therefore for dendrobium nobile sample number According to test of normality for, Liffiefors inspection be most suitable.
Inspection principle and method are as follows:
1. null hypothesis:H0:Data Normal Distribution;H1:Data disobey normal distribution.Level of significance α= 0.05。
2. test statistics:
T=sup | F*(x)-S(x)|
In formula, T is Liffiefors test statistics, F*(x) be mean value be 0, standard deviation be 1 normal distribution iterated integral Cloth function, S (x) areEmpirical distribution function value.It just needs to use sample size and initial data when calculating S (x) Value.
Judgment principle:Under the significance of α, when test statistics T is more than to examine critical value, refuse null hypothesis H0;Otherwise, null hypothesis cannot be refused.
When it is implemented, the applicant is studied by being engaged in gene sequencing conclusion and Herba Dendrobii morphological feature for many years, It has obtained second internode stem diameter of Herba Dendrobii and its degree of purity is closely related, for guarding, the accuracy rate of judgement exists 90% or more
In the present invention, second internode refers to is started counting by the lowermost end of Herba Dendrobii stem, the second section and first segment Between just be second internode, the greatest measure of i.e. second Internode diameter of second internode stem diameter.
Finally it should be noted that:Above-described embodiments are merely to illustrate the technical scheme, rather than to it Limitation;Although the present invention is described in detail referring to the foregoing embodiments, those skilled in the art should understand that: It can still modify to technical solution documented by previous embodiment, or to part of or all technical features into Row equivalent replacement;And these modifications or substitutions, it does not separate the essence of the corresponding technical solution various embodiments of the present invention technical side The range of case.

Claims (10)

1. a kind of foundation for the method for judging the purebred phase recency of Herba Dendrobii, it is characterised in that:The establishment process includes following Step:
S1:Standard data acquisition:Acquisition and the consistent Herba Dendrobii sample of gene sequencing conclusion, sample size n, measurement are each Second internode stem diameter of sample, obtains the measurement numerical value of second internode stem diameter variable;
S2:Test of normality:Test of normality is carried out to second internode stem diameter variable of sample;
S3:Standard section:If obtained result is Normal Distribution in step S2, totally calculated according to normal distribution public Formula obtains 95% confidence interval of mean value and 95% confidence interval of standard deviation;
If second internode stem diameter variable test of normality result of Herba Dendrobii is to disobey normal distribution in step S2, If sample size exceeds 30, according to central-limit theorem it is found that the sample still is able to the formula meter according to normal population Calculate 95% confidence interval of its mean value and 95% confidence interval of standard deviation;
95% confidence interval of mean value obtained above and 95% confidence interval of standard deviation just can be as identification unknown samples The critical field of degree of purity.
2. the foundation of the method for the judgement purebred phase recency of Herba Dendrobii according to claim 1, it is characterised in that:Step S1 After obtaining the measurement numerical value of second internode stem diameter variable, calculated according to the measurement numerical value of second internode stem diameter variable The basic statistics amount of second internode stem diameter variable, the basic statistics amount include average level and dispersion degree, then root Determining data according to basic statistics amount, whether there is or not exceptional values, are checked if having exceptional value, if belonging to measurement error or record mistake Accidentally then suppressing exception point, if not because of error, then this data should be retained.
3. the foundation of the method for the judgement purebred phase recency of Herba Dendrobii according to claim 2, it is characterised in that:It is described flat Horizontal includes at least one of mean value, median and mode, the dispersion degree include standard deviation, mean absolute deviation and The coefficient of variation;
The basic statistics amount further includes the measurement numerical value production histogram and/or box-like according to second internode stem diameter variable Data visualization is made its more convenient determining wrong exceptional value by figure.
4. the foundation of the method for the judgement purebred phase recency of Herba Dendrobii according to claim 1, it is characterised in that:It is described just It includes at least one of visual image analysis and hypothesis testing that state property, which is examined,.
5. the foundation of the method for the judgement purebred phase recency of Herba Dendrobii according to claim 4, it is characterised in that:It is described just It includes visual image analysis and hypothesis testing that state property, which is examined,.
6. the foundation of the method for the judgement purebred phase recency of Herba Dendrobii according to claim 5, it is characterised in that:It is described straight See image analysis method be:
1. according to normal state empirical distribution functionThe normal state experience for drawing Herba Dendrobii is distributed letter Number curve;
According to normal probability density functionDraw the normal probability density curve of Herba Dendrobii;Work as μ When=0, σ=1, normal distribution just becomes standardized normal distribution:
2. the measurement numerical value of second internode stem diameter variable according to obtained in step S1, and be according to formulaEmpirical distribution function draw true empirical distribution function;
The measurement numerical value of second internode stem diameter variable according to obtained in step S1, and be according to formulaProbability density function draw trues probability density functional arrangement;
3. true empirical distribution function figure and the distribution function curve of normal distribution are compared, pass through judgment curves extent of deviation Size comes whether preliminary judgement sample data meets normal distribution;The probability of trues probability density functional arrangement and normal distribution is close Curve comparison is spent, also according to extent of deviation size and the curve shape degree of consistency, to determine whether sample data is to obey Normal distribution;
If the distribution function figure or true empirical probability density functional arrangement of true empirical distribution function figure and normal distribution and just The deviation of the probability density function figure of state distribution is small and shape is consistent, then second internode stem diameter of Herba Dendrobii sample to be detected Meet normal distribution, if the deviation obviously very big and different cause of shape, second internode stem of Herba Dendrobii sample to be detected Diameter does not meet normal distribution.
7. the method for the judgement purebred phase recency of Herba Dendrobii according to claim 5 establishes method, it is characterised in that:It is described Hypothesis testing includes any one during JB inspection, KS inspection and Lilliefors are examined.
8. the method for the judgement purebred phase recency of Herba Dendrobii according to claim 7 establishes method, it is characterised in that:It is described Hypothesis testing is that Lilliefors is examined, the Lilliefors test statistics T=sup | F*(x)-S (x) |, in formula, T is Liffiefors test statistics, F*It (x) be mean value is 0, the normal distribution cumulative distribution function that standard deviation is 1, S (x) isEmpirical distribution function value, under the significance of α, when test statistics T be more than examine critical value when, refuse Exhausted null hypothesis H0;Otherwise, null hypothesis cannot be refused.
9. a kind of judgment criteria of the purebred phase recency of Herba Dendrobii, it is characterised in that:The judgment criteria includes the following steps:
(1):Acquisition and consistent 120, the wild Herba Dendrobii sample of gene sequencing conclusion measure second section of each sample Between stem diameter, measurement result is as follows:Second internode changes in stem diameter range of Herba Dendrobii is 1.56mm~7.72mm, average The result that level obtains after 3.87mm~4.29mm, calculating is:Mean value:4.26mm median:4.29mm mode: 3.87mm, the standard deviation of second internode stem diameter fluctuation are 1.15mm, mean absolute deviation:0.87mm, the coefficient of variation: 0.27;(2):Visual image analyzes normal distribution:Empirical distribution function figure and probability density are drawn according to the data in step (1) The result that true empirical distribution function figure is compared with normal state empirical distribution function curve is by functional arrangement:The curve of the two It is almost the same;It is by the result that trues probability density functional arrangement is compared with normal probability density curve:The curve of the two Shape is roughly the same;
By the intuitive analysis to the above figure it is found that second internode stem diameter sample data of Herba Dendrobii probably meets Normal distribution;
(3):Lilliefors is examined:Null hypothesis is H0:Data Normal Distribution;Alternative hypothesis H1:Data disobey normal state Distribution;It is by the inspection result that the data in step (1) obtain:
Statistic Critical value P value Level of significance α Whether null hypothesis is received 0.0578 0.0814 0.4045 0.05 It is
The value of statistic is 0.0578, is less than critical value 0.0814;P value be equal to 0.4045, be greater than significance (α= 0.05), so receiving null hypothesis, then it can confirm Herba Dendrobii sample data Normal Distribution;
(4):The mean value of second internode stem diameter sample data of Herba Dendrobii is then calculated according to normal distribution totality calculation formula 95% confidence interval of 95% confidence interval and standard deviation, respectively:
Mean value 95% confidence interval of mean value Standard deviation 95% confidence interval of standard deviation 4.2588 (4.0515,4.4661) 1.1469 (1.0178,1.3137)
95% confidence interval of above-mentioned mean value and 95% confidence interval of standard deviation are respectively:(4.0515,4.4661) and (1.0178,1.3137), the section are just the standard section for judging the purebred phase recency of Herba Dendrobii.
10. a kind of judgment method of the purebred phase recency of Herba Dendrobii, it is characterised in that:The method is:
A. second internode stem diameter data of Herba Dendrobii sample to be detected are acquired, are excluded in sample due to measurement error or record Error causes caused exceptional value;
B. calculate step A in second internode stem diameter data of Herba Dendrobii sample to be detected 95% confidence interval of mean value and 95% confidence interval of standard deviation, if the two, in standard section, the purebred phase recency of Herba Dendrobii to be detected is high, i.e., to The degree of purity for detecting Herba Dendrobii is high;If the mean value 95% of second internode stem diameter data of the sample of Herba Dendrobii to be detected is set At least one in section and 95% confidence interval of standard deviation is believed not in standard section, then Herba Dendrobii to be detected is purebred Phase recency is low, i.e., the degree of purity of Herba Dendrobii to be detected is low;The standard section is:95% confidence interval and standard deviation of mean value 95% confidence interval be respectively:(4.0515,4.4661) and (1.0178,1.3137).
CN201710332024.0A 2017-05-11 2017-05-11 A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii Pending CN108875304A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710332024.0A CN108875304A (en) 2017-05-11 2017-05-11 A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710332024.0A CN108875304A (en) 2017-05-11 2017-05-11 A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii

Publications (1)

Publication Number Publication Date
CN108875304A true CN108875304A (en) 2018-11-23

Family

ID=64319909

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710332024.0A Pending CN108875304A (en) 2017-05-11 2017-05-11 A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii

Country Status (1)

Country Link
CN (1) CN108875304A (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101894215A (en) * 2010-07-06 2010-11-24 厦门大学 Likelihood ratio test error detection method
CN103823933A (en) * 2014-02-26 2014-05-28 大连理工大学 Method for processing metal cutting simulation data
CN104765945A (en) * 2015-02-09 2015-07-08 广东电网有限责任公司电力科学研究院 Device failure rate detecting method based on quantity confidence coefficient
CN105069030A (en) * 2015-07-20 2015-11-18 赵蒙海 Hospitalization expense estimation and judgment method for single disease
CN105205736A (en) * 2015-10-14 2015-12-30 国家电网公司 Rapid detection method for power load abnormal data based on empirical mode decomposition
CN106201829A (en) * 2016-07-18 2016-12-07 中国银联股份有限公司 Monitoring Threshold and device, monitoring alarm method, Apparatus and system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101894215A (en) * 2010-07-06 2010-11-24 厦门大学 Likelihood ratio test error detection method
CN103823933A (en) * 2014-02-26 2014-05-28 大连理工大学 Method for processing metal cutting simulation data
CN104765945A (en) * 2015-02-09 2015-07-08 广东电网有限责任公司电力科学研究院 Device failure rate detecting method based on quantity confidence coefficient
CN105069030A (en) * 2015-07-20 2015-11-18 赵蒙海 Hospitalization expense estimation and judgment method for single disease
CN105205736A (en) * 2015-10-14 2015-12-30 国家电网公司 Rapid detection method for power load abnormal data based on empirical mode decomposition
CN106201829A (en) * 2016-07-18 2016-12-07 中国银联股份有限公司 Monitoring Threshold and device, monitoring alarm method, Apparatus and system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
贾怀勤: "《应用统计》", 31 March 2005, pages: 178 - 198 *
郭鹏: "《数据、模型与决策》", pages: 59 - 63 *

Similar Documents

Publication Publication Date Title
CN108875308A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of HERBA DENDROBII
Smith Systematics and the fossil record: documenting evolutionary patterns
Jantzen et al. Pap-smear benchmark data for pattern classification
Shipton et al. Handaxe reduction and its influence on shape: An experimental test and archaeological case study
CN101996329B (en) Device and method for detecting blood vessel deformation area
CN107169145A (en) A kind of method of user&#39;s stealing menace level detection based on clustering algorithm
CN101460976A (en) &#39;In vitro&#39; diagnostic method for diseases affecting human or animal tissues
Reitalu et al. Plant species segregation on different spatial scales in semi‐natural grasslands
Barbosa et al. Discrimination of soybean seed lots by multivariate exploratory techniques
CN110010202A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Dendrobium fimbriatum Hook
CN108874732A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Dendrobium aphyllum (Roxb.) C. E. Fisch.
Vilhar et al. Genome size and the nucleolar number as estimators of ploidy level in Dactylis glomerata in the Slovenian Alps
Ingrouille The construction of cluster webs in numerical taxonomic investigations
CN108875313A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of dendrobium candidum
CN108875304A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Herba Dendrobii
Sandoval et al. Probability distributions in high-density dendroenergy plantations
CN108875309A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Dendrobium loddigesii
CN108874746A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Dendrobium Chrysotoxum Lindl
CN108875101A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of dendrobium devonianum
CN108875303A (en) A kind of foundation, judgment criteria and the judgment method of the method judging the purebred phase recency of Dendrobidium huoshanness
CN110222459B (en) Individual height analysis method, system, readable storage medium and terminal
STILES Industrial taxonomy in the early stone age of Africa
CN108109675A (en) A kind of Good Laboratory controls data management system
Shaw et al. Evaluating the accuracy of ground-based hemlock dwarf mistletoe rating: a case study using the Wind River Canopy Crane
CN108108864A (en) A kind of Good Laboratory controls data managing method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination