CN106296436A - Quantitative evaluation method for tobacco variety breeding - Google Patents
Quantitative evaluation method for tobacco variety breeding Download PDFInfo
- Publication number
- CN106296436A CN106296436A CN201610698124.0A CN201610698124A CN106296436A CN 106296436 A CN106296436 A CN 106296436A CN 201610698124 A CN201610698124 A CN 201610698124A CN 106296436 A CN106296436 A CN 106296436A
- Authority
- CN
- China
- Prior art keywords
- index
- tobacco
- tobacco bred
- breeding
- main constituent
- 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
Links
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 56
- 241000208125 Nicotiana Species 0.000 title claims abstract description 53
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000009395 breeding Methods 0.000 title claims abstract description 21
- 230000001488 breeding effect Effects 0.000 title abstract description 5
- 238000011158 quantitative evaluation Methods 0.000 title abstract 3
- 201000010099 disease Diseases 0.000 claims abstract description 12
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 12
- 239000000470 constituent Substances 0.000 claims description 18
- 241000196324 Embryophyta Species 0.000 claims description 5
- 235000019504 cigarettes Nutrition 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 3
- 238000000513 principal component analysis Methods 0.000 claims description 3
- 241000193738 Bacillus anthracis Species 0.000 claims description 2
- 241000221785 Erysiphales Species 0.000 claims description 2
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 claims description 2
- 239000011159 matrix material Substances 0.000 claims description 2
- 238000005303 weighing Methods 0.000 claims description 2
- 241000723873 Tobacco mosaic virus Species 0.000 claims 1
- 238000012935 Averaging Methods 0.000 abstract 1
- 238000012163 sequencing technique Methods 0.000 abstract 1
- 238000011156 evaluation Methods 0.000 description 4
- 244000061176 Nicotiana tabacum Species 0.000 description 3
- 244000025254 Cannabis sativa Species 0.000 description 1
- 208000035240 Disease Resistance Diseases 0.000 description 1
- 241000607479 Yersinia pestis Species 0.000 description 1
- 230000009418 agronomic effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000003595 mist Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Breeding Of Plants And Reproduction By Means Of Culturing (AREA)
- Manufacture Of Tobacco Products (AREA)
Abstract
The invention discloses a quantitative evaluation method for tobacco variety breeding, which comprises the following steps: 1) acquiring biological characters, economic characters and disease index indexes of the bred tobacco variety; 2) calculating the average value of each index, and carrying out averaging treatment; 3) calculating the optimal resolution coefficient of all indexes of the tobacco variety characters; 4) calculating the correlation coefficient of each index of different varieties respectively; 5) calculating the weight of each index; 6) calculating the comprehensive score of the bred tobacco varieties and sequencing; the quantitative evaluation method for tobacco variety breeding accurately quantifies and scores tobacco varieties, and quickly selects ideal flue-cured tobacco varieties.
Description
Technical field
The invention belongs to tobacco bred selection-breeding field, be specifically related to the method for quantitatively evaluating of a kind of tobacco bred selection-breeding.
Background technology
At present, China Nicotiana tabacum L. (Nicotiana tabacum L.) kind plantation unification problem is serious, Yun yan85, cloud and mist
The cultivated area of 3 kinds such as 87 and K326 reaches more than 70%, causes pest and disease damage to take place frequently, and tobacco style characteristic is single, serious shadow
Ring the quality of Nicotiana tabacum L..In consideration of it, China tobacco breeding worker constantly introduces characteristic product from the country such as the U.S. and Zimbabwe
Kind, develop self-fertile kind, try hard to the demand meeting Cigarette Industrial Enterprise to high-quality characteristic raw material.
During new product of tobacco selection-breeding, generally require filter out from tens or tens new flue-cured tobacco varieties several
The preferable improved seeds of Comprehensive Traits, carry out plot experiment and field demonstration the most again.Existing breed breeding evaluation, is usually
The factors such as selection Agronomic trait, economic characters, disease resistance and aesthetic quality, some key index in the analyzing influence factor,
Such as yield and disease index etc..This method can catch the principal character of new varieties, but there is deficiency: one is easily to ignore newly
Some details of kind, it is impossible to reflect whole trait information of this kind;Two is that some trait expression of new varieties is preferable, and another
When some trait expression outer is poor, easily bring puzzlement to people, it is difficult to the quality of this kind of accurate evaluation;Three is the most energetic product
Plant and evaluate score, bigger by experience influence fluctuation.
Summary of the invention
The present invention is directed to prior art problem, it is provided that tobacco bred is carried out quantifying marking by one accurately, quickly selects
Select the method for quantitatively evaluating of the tobacco bred selection-breeding of preferable flue-cured tobacco cultivars.
Technology and method in order to solve the employing of the above-mentioned problem present invention are as follows:
The method for quantitatively evaluating of a kind of tobacco bred selection-breeding, comprises the following steps:
1) biological character of educated tobacco bred, Economic Characters and disease index index are obtained;
2) calculate the meansigma methods of each index, and carry out equalization process;
3) calculate tobacco bred character and all refer to the optimal resolution ratio of target;
Wherein, x0(k)、xiK () is index x0、xiFirst value sequence, k=1,2 ..., n, represent kth index;I=
1,2 ..., m;Represent i-th kind;It it is the average of all absolute difference;ΔmaxAbsolute value for maximum difference;ρ is
Good resolution ratio;
4) coefficient of association of each index of different cultivars is calculated respectively;
Wherein, ξi(k)It it is the coefficient of association of i-th kind kth index;
5) weight of each index is calculated;
6) calculate the comprehensive score of educated tobacco bred, and be ranked up.
Further, described biological character includes plant height, plant height of pinching, the actual number of blade, the number of blade of pinching, has
The effect number of blade, stem girth, pitch, maximum leaf length and maximum width of blade.
Further, described Economic Characters includes yield, the output value, average price and better-than-average cigarette ratio.
Further, described disease index includes climacteric spot disease, anthrax, rust, powdery mildew, tobacco ordinary flower
Leaf disease, balck shank and root black rot index.
Further, in step 5) in, the weighing computation method of each index is as follows:
Data principal component analysis after equalization is carried out factorial analysis, analyzes the characteristic root of main constituent and each main constituent
Equation contribution rate, extract main constituent, obtain being rotated into sub matrix;By factor loading divided by the characteristic root of main constituent, obtain each
Index coefficient in main constituent linear combination, is normalized, and calculates the weight of each index;
Zj=β1j*X1+β2j*X2+…+βnj*Xk
Wherein, ZjFor main constituent linear combination (j=1,2 ..., p), X1、X2、…、XnFor each index, β1j、β2j、
β3j、……、βnjFor the principal component scores of each index, γjRepresent ZjEquation contribution rate, QiIt it is index XiWeight.
Further, in step 6) in, the comprehensive score computation method of tobacco bred is as follows;
Di=ξi(1)*Qi+ξi(2)*Qi+…+ξi(k)*Qi
Wherein, DiComprehensive score by educated tobacco bred.
The invention have the benefit that according to gray system theory, it is provided that a kind of based on optimum resolution ratio objective
All character of educated tobacco bred, before quality of tobacco overall merit, are carried out Comprehensive Assessment and quantitatively marking by evaluation methodology,
The field growing situation of institute's selection-breeding tobacco bred can be judged, quickly select preferable flue-cured tobacco cultivars.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the present invention.
Fig. 2 is the schematic flow sheet of each index weights computational methods in the present invention.
Detailed description of the invention
Below in conjunction with embodiment, the present invention is described in further detail with accompanying drawing, but they are not to skill of the present invention
The restriction of art scheme, based on present invention teach that any conversion made, all falls within protection scope of the present invention.
Refering to shown in Fig. 1-2, the method for quantitatively evaluating of a kind of tobacco bred selection-breeding, comprise the following steps:
1) biological character of educated tobacco bred, Economic Characters and disease index index are obtained;
2) calculate the meansigma methods of each index, and carry out equalization process;
3) calculate tobacco bred character and all refer to the optimal resolution ratio of target;
Wherein, x0(k)、xiK () is index x0、xiFirst value sequence, k=1,2 ..., n, represent kth index;I=
1,2 ..., m;Represent i-th kind;It it is the average of all absolute difference;ΔmaxAbsolute value for maximum difference;ρ is
Good resolution ratio;
4) coefficient of association of each index of different cultivars is calculated respectively;
Wherein, ξi(k)It it is the coefficient of association of i-th kind kth index;
5) weight of each index is calculated;
6) calculate the comprehensive score of educated tobacco bred, and be ranked up.
Embodiment 1
1. the meansigma methods that 10 are participated in representational 8 character of selection-breeding tobacco lines is listed in the table below.
2. with DPS7.05, initial data is carried out equalization process
When being modeled by gray system, owing to data volume level difference is bigger, it is necessary to carry out nondimensionalization process, make because of
Prime sequences planningization, just can calculate.Just value algorithm is applicable to process stable economics phenomenon, and equalization is usually used in place
Manage the data sequence without visible trend, therefore initial data is carried out equalization process.Additionally due to disease index value is the biggest, cigarette
Grass Performance of cultivar is the poorest, and therefore to such index first inverseization, then equalization processes.
3. calculate optimal resolution ratio
3.1 differences calculating tobacco bred character
3.2 calculate optimal resolution ratio
According to formula (1), draw ΔX=0.1366, Δmax=0.9553;Now will affect the whole of tobacco bred character
Index, as a gray system, according to formula (2), draws ρ=0.2145.
4. calculate the coefficient of association of each index of different cultivars
According to formula (3), draw the coefficient of association ξ of each index of different cultivarsi(k)。
Strain 1 | 0.6446 | 0.5988 | 0.8609 | 0.5181 | 0.5322 | 0.6053 | 0.75582 | 0.1766 |
Strain 2 | 0.9706 | 0.7177 | 0.9976 | 0.7782 | 0.7085 | 1 | 1 | 1 |
Strain 3 | 1 | 1 | 0.9976 | 1 | 0.8753 | 0.8457 | 0.722 | 1 |
Strain 4 | 0.6385 | 0.5615 | 0.9642 | 0.5416 | 0.9156 | 0.9421 | 0.66527 | 1 |
Strain 5 | 0.8809 | 0.5859 | 0.8952 | 0.572 | 0.534 | 0.4492 | 0.5535 | 0.232 |
Strain 6 | 0.6322 | 0.5902 | 0.8555 | 0.536 | 0.8183 | 0.5599 | 0.52179 | 0.1808 |
Strain 7 | 0.7617 | 0.5714 | 0.8394 | 0.5288 | 1 | 0.8154 | 0.64233 | 0.5273 |
Strain 8 | 0.6805 | 0.6515 | 0.9242 | 0.5266 | 0.7063 | 0.5296 | 0.50984 | 0.3173 |
Strain 9 | 0.6503 | 0.6077 | 0.9416 | 0.4932 | 0.619 | 0.9557 | 0.86603 | 0.1858 |
Strain 10 | 0.6869 | 0.6241 | 1 | 0.6037 | 0.6925 | 0.9526 | 0.83361 | 0.2507 |
5. calculate the weight of each index
5.1 extract main constituent
Analyze software with SPSS16.0, the data after equalization carried out principal component analysis, draw the population variance table of explanation,
Analyze characteristic root > main constituent of 1, find that the characteristic root of composition 1,2,3 is 4.078,1.563 and 1.366 respectively, and accumulative contribution
Rate reaches 87.581%, more than 85%, determines that main constituent is 1,2,3.
5.2 obtain main constituent linear combination
By factor loading divided by the characteristic root of main constituent, obtain each index coefficient in main constituent linear combination, draw
Formula (4)
Z1=0.458X4+0.452X1+0.433X2+0.078X7+0.002X6+0.256X3+0.013X5+ 0.256X8;
Z2=0.187X4+0.008X1+0.156X2+0.751X7+0.705X6+0.526X3+0.019X5+ 0.161X8;
Z3=0.172X4+0.049X1+0.082X2-0.107X7+0.385X6+0.083X3+0.836X5+ 0.628X8;
5.3 draw weight
According to formula (5), draw the weight of each index:
6. calculate the comprehensive score of educated tobacco bred
According to formula (6), draw the Comprehensive Traits score of educated tobacco bred, and be ranked up.
Strain | Comprehensive score | Sequence |
Strain 1 | 0.574755 | 9 |
Strain 2 | 0.895245 | 2 |
Strain 3 | 0.9469 | 1 |
Strain 4 | 0.767041 | 3 |
Strain 5 | 0.589473 | 8 |
Strain 6 | 0.572031 | 10 |
Strain 7 | 0.687694 | 4 |
Strain 8 | 0.600968 | 7 |
Strain 9 | 0.640903 | 6 |
Strain 10 | 0.686003 | 5 |
The invention have the benefit that according to gray system theory, it is provided that a kind of based on optimum resolution ratio objective
All character of educated tobacco bred, before quality of tobacco overall merit, are carried out Comprehensive Assessment and quantitatively marking by evaluation methodology,
The field growing situation of institute's selection-breeding tobacco bred can be judged, quickly select preferable flue-cured tobacco cultivars.
The above, the only detailed description of the invention of the present invention, but protection scope of the present invention is not limited thereto, and any
The change expected without creative work or replacement, all should contain within protection scope of the present invention, therefore, and the present invention's
Protection domain should be as the criterion with the protection domain that claims are limited.
Claims (6)
1. the method for quantitatively evaluating of a tobacco bred selection-breeding, it is characterised in that: comprise the following steps:
1) biological character of educated tobacco bred, Economic Characters and disease index index are obtained;
2) calculate the meansigma methods of each index, and carry out equalization process;
3) calculate tobacco bred character and all refer to the optimal resolution ratio of target;
Wherein, x0(k)、xiK () is index x0、xiFirst value sequence, k=1,2 ..., n, represent kth index;I=1,
2 ..., m;Represent i-th kind;ΔXIt it is the average of all absolute difference;ΔmaxAbsolute value for maximum difference;ρ is optimal
Resolution ratio;
4) coefficient of association of each index of different cultivars is calculated respectively;
Wherein, ξi(k)It it is the coefficient of association of i-th kind kth index;
5) weight of each index is calculated;
6) calculate the comprehensive score of educated tobacco bred, and be ranked up.
The method for quantitatively evaluating of tobacco bred selection-breeding the most according to claim 1, it is characterised in that: described biological character
Including plant height, plant height of pinching, the actual number of blade, the number of blade of pinching, effective blade number, stem girth, pitch, maximum leaf length and
Great Ye width.
The method for quantitatively evaluating of tobacco bred selection-breeding the most according to claim 2, it is characterised in that: described Economic Characters
Including yield, the output value, average price and better-than-average cigarette ratio.
The method for quantitatively evaluating of tobacco bred selection-breeding the most according to claim 3, it is characterised in that: described disease index bag
Include climacteric spot disease, anthrax, rust, powdery mildew, tobacco mosaic virus (tmv), balck shank and root black rot index.
5. according to the method for quantitatively evaluating of the tobacco bred selection-breeding according to any one of claim 1-4, it is characterised in that: in step
Rapid 5), in, the weighing computation method of each index is as follows:
Data principal component analysis after equalization is carried out factorial analysis, analyzes characteristic root and the side of each main constituent of main constituent
Journey contribution rate, extracts main constituent, obtains being rotated into sub matrix;By factor loading divided by the characteristic root of main constituent, obtain each index
Coefficient in main constituent linear combination, is normalized, and calculates the weight of each index;
Zj=β1j*X1+β2j*X2+…+βnj*Xk
Wherein, ZjFor main constituent linear combination (j=1,2 ..., p), X1、X2、…、XnFor each index, β1j、β2j、β3j、……、
βnjFor the principal component scores of each index, γjRepresent ZjEquation contribution rate, QiIt it is index XiWeight.
6. according to the method for quantitatively evaluating of the tobacco bred selection-breeding according to any one of claim 1-4, it is characterised in that: in step
Rapid 6), in, the comprehensive score computation method of tobacco bred is as follows;
Di=ξi(1)*Qi+ξi(2)*Qi+…+ξi(k)*Qi
Wherein, DiComprehensive score by educated tobacco bred.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610698124.0A CN106296436A (en) | 2016-08-22 | 2016-08-22 | Quantitative evaluation method for tobacco variety breeding |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610698124.0A CN106296436A (en) | 2016-08-22 | 2016-08-22 | Quantitative evaluation method for tobacco variety breeding |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106296436A true CN106296436A (en) | 2017-01-04 |
Family
ID=57661013
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610698124.0A Pending CN106296436A (en) | 2016-08-22 | 2016-08-22 | Quantitative evaluation method for tobacco variety breeding |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106296436A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109993413A (en) * | 2019-03-04 | 2019-07-09 | 中国地质大学(武汉) | A kind of flue cured tobacco quality benefit integrated evaluating method and system based on data-driven |
CN113433012A (en) * | 2021-07-28 | 2021-09-24 | 陕西科技大学 | Health assessment method for ceramic cultural relics |
-
2016
- 2016-08-22 CN CN201610698124.0A patent/CN106296436A/en active Pending
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109993413A (en) * | 2019-03-04 | 2019-07-09 | 中国地质大学(武汉) | A kind of flue cured tobacco quality benefit integrated evaluating method and system based on data-driven |
CN113433012A (en) * | 2021-07-28 | 2021-09-24 | 陕西科技大学 | Health assessment method for ceramic cultural relics |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Domínguez et al. | Determination of optimal regulated deficit irrigation strategies for maize in a semi-arid environment | |
Mohammadi et al. | The use of AMMI model for interpreting genotype× environment interaction in durum wheat | |
Voltas et al. | Genotype by environment interaction for grain yield and carbon isotope discrimination of barley in Mediterranean Spain | |
Verhaegen et al. | What is the genetic origin of teak (Tectona grandis L.) introduced in Africa and in Indonesia? | |
Mohammadi et al. | Interpreting genotype× environment interactions for grain yield of rainfed durum wheat in Iran | |
Mollasadeghi et al. | Important morphological markers for improvement of yield in bread wheat | |
Mourice et al. | Maize cultivar specific parameters for decision support system for agrotechnology transfer (DSSAT) application in Tanzania | |
Osorio et al. | Age trends of heritabilities and genotype-by-environment interactions for growth traits and wood density from clonal trials of Eucalyptus grandis Hill ex Maiden | |
Azimi et al. | Multivariate analysis of morphological characteristics in Iris germanica hybrids | |
Gömöry et al. | Effective population number estimation of three Scots pine (Pinus sylvestris L.) seed orchards based on an integrated assessment of flowering, floral phenology, and seed orchard design | |
Jamilu et al. | Factors influencing the adoption of Sasakawa Global 2000Maize production technologies among smallholder farmers in Kaduna State | |
Boussakouran et al. | Genetic advance and grain yield stability of moroccan durum wheats grown under rainfed and irrigated conditions | |
CN106296436A (en) | Quantitative evaluation method for tobacco variety breeding | |
Dumont et al. | Sugarcane breeding in reunion: challenges, achievements and future prospects | |
Molenaar et al. | Selection for production-related traits in Pelargonium zonale: improved design and analysis make all the difference | |
Lopez et al. | Tree breeding model to assess financial performance of pine hybrids and pure species: deterministic and stochastic approaches for South Africa | |
Poupon et al. | Genotype x environment interaction and climate sensitivity in growth and wood density of European larch | |
Hirano et al. | Propagation management methods have altered the genetic variability of two traditional mango varieties in Myanmar, as revealed by SSR | |
Karadavut et al. | Genotype-environment interaction and phenotypic stability analysis for yield of corn cultivar | |
Faux et al. | Modelling approach for the quantitative variation of sex expression in monoecious hemp (Cannabis sativa L.) | |
He et al. | China-CIMMYT collaboration enhances wheat improvement in China | |
Kalivas et al. | Genetic diversity and structure of tobacco in Greece on the basis of morphological and microsatellite markers | |
Dijoux et al. | Effects of orange rust on sugarcane yield traits in a multi-environment breeding program | |
Mohammadi | Phenotypic plasticity of yield and related traits in rainfed durum wheat | |
TAHIR et al. | Assessment of heritability estimates for some yield traits in winter wheat (Triticum aestivum L.) |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170104 |
|
RJ01 | Rejection of invention patent application after publication |