GB/T 19557.1-2026Guidelines for the tests of distinctness, uniformity and stability for plant varieties - General (English PDF)

5.1 Selection of traits

5.1.1 Traits used for DUS testing and variety description must meet the following basic conditions for trait expression.

a) It is the result of the action of a specific genotype or combination of genotypes;

b) It exhibits sufficient consistency and repeatability under specific conditions;

c) The varieties exhibit sufficient differences to determine specificity;

d) It can be accurately defined and identified;

e) Meets consistency criteria;

f) Meets stability criteria.

Note. The inherent commercial value of traits is generally not considered as a trait for DUS testing, but certain economic traits, special traits, or novel traits may be excluded if they meet the above criteria. If the above conditions are met, they will be considered as DUS test traits.

5.1.2 The traits used for testing of substantial derivative varieties should meet the conditions in 5.1.1.

5.2 Expression status of traits The DUS testing guidelines divide the trait into a series of different expression states, each described by a numerical code. Correspondingly. To better define expression status, the DUS testing guidelines provide standard varieties or legends as a reference for determining trait expression status. Basis. When testing the same plant species in different ecological zones, standard varieties adapted to the specific ecological zone can be used.

5.3 Types of trait expression In the DUS test, traits are classified into three types. qualitative traits, quantitative traits, and pseudo-qualitative traits.

5.4 Observation of traits The DUS testing guidelines should clearly specify the observation period, observation site, observation method, and sample size to facilitate the assessment of sexuality. To accurately observe and compare the conditions. If mixed samples are required for trait observation, refer to the UPOV document on specificity testing (TGP/9) and the document on consistency testing. (TGP/10) provides detailed instructions.

5.5 Special Characteristics

5.5.1 Traits induced by external factors Traits expressed due to external factors must meet the conditions in 5.1.Such traits can be accurately defined, and appropriate testing methods can be selected. This method ensures consistency in testing.

5.5.2 Quality Characteristics The traits expressed under the influence of chemical components must meet the conditions in 5.1.Such traits can be accurately defined, and appropriate testing methods can be selected. This method ensures consistency in testing.

5.5.3 Composite traits Biologically significant composite traits can be directly used as DUS test traits and subjected to specificity and consistency tests in the same way as other traits. And stability testing. Sometimes, these combined traits can be tested using techniques such as image analysis. Combinatorial traits should not be confused with the application of statistical methods, such as "multivariate analysis".

5.6 New Types of Traits New types of traits, including molecular traits, can be used during testing.

5.7 Functional classification of traits The functional classification of traits is shown in Table 1.

6.3.1 Differentiating varieties based on phenotypic differences

6.3.1.1 Consistent Differences 6.3.1.1.1 To ensure consistency in the differences of traits tested in planting trials, this trait is usually tested under two independent conditions. The condition. Annual and perennial varieties can be tested by planting two different growth cycles, or perennial varieties can be planted once and then tested in two different growth cycles. Tests can be conducted at different growing seasons, or through planting at multiple points over a year. If the differences in traits cannot be determined, an additional test can be performed. Test cycle. See UPOV for specificity testing (TGP/9). 6.3.1.1.2 Traits less affected by the environment, if the growing environment is always consistent, such as in a greenhouse with controlled temperature and light. There's no need to test two cycles. 6.3.1.1.3 For varieties requiring testing over two or more cycles, if the planting trial includes screening of traits via molecular markers and technical questionnaires... The selected similar varieties, after a period of testing, showed that the phenotypic expression of the applied variety and the similar varieties was normal and the differences were very significant, and no abnormalities were found. Other known varieties that are more similar to the applied variety, and which meet the consistency and stability standards, do not need to be tested in a second cycle. 6.3.1.1.4 The DUS testing guidelines for each relevant plant variety should specify the number of independent testing weeks required to demonstrate sufficient consistency in intervarietal differences. Period (e.g., several years or several separate locations or different environments under specific circumstances).

6.3.1.2 Significant differences 6.3.1.2.1 Types of Trait Expression Determining whether the difference between two varieties is significant depends on many factors, especially the type of expression of the tested trait, i.e., qualitative. Is it a qualitative trait, a quantitative trait, or a pseudo-qualitative trait? For composite traits, if the individual traits constituting the composite and the composite trait themselves satisfy the consistency criterion... The combined trait can be used as a specific trait. 6.3.1.2.2 Quality Properties For quality traits, according to the DUS testing guidelines, if one or more traits are expressed in different states, then the two varieties are considered to be in different states. There are significant differences in this trait. If the trait is expressed in the same state, the difference is considered not significant. 6.3.1.2.3 Quantitative traits For quantitative traits, specificity is determined based on the variety's propagation method and observation method, as specified in 6.3.2.2.2, 6.3.3.3.2, and 6.3.3.4. Other methods were used. 6.3.1.2.4 Pseudo-quality traits For pseudo-quality traits, the DUS testing guidelines may be insufficient in determining specificity using different expression states of the trait. Specific situations... The description of traits may differ significantly between varieties in the same expression state, see 6.3.2.2.3.

6.3.2 Specificity evaluation without using statistical methods

6.3.2.1 Adjacent Comparison Method Specificity evaluation is based on direct visual comparison between varieties that are adjacent or closely related to each other in planting trials. This method requires one variety. The traits can be visually observed and the trait expression can be represented by a test record. If the variation within a variety is minimal, then specificity should be determined by visual inspection of adjacent plants. If the variation within a variety is significant, such as in cross-pollination... For varieties and certain types of hybrids, this method should be used with caution to evaluate specificity.

6.3.2.2 Code Comparison Method 6.3.2.2.1 Quality Properties Codes or records that allow direct comparison of trait expression states. If two varieties have one or more quality traits whose expression states are... The two different codes in the DUS testing guidelines indicate that the two varieties are significantly different. 6.3.2.2.2 Quantitative traits The difference between the two codes usually indicates a significant difference, but this can vary depending on the variety's testing location, year, environment, or the degree of trait expression. Influenced by factors such as, the difference may be greater or less than two codes. When using codes to determine specificity, it is advisable to consider the range of trait expression states and the experimental The impact of environmental change. 6.3.2.2.3 Pseudo-quality traits Determining specificity solely based on different expression states of a trait is insufficient; sometimes, two varieties with the same expression state exhibit significant differences, even in adjacent varieties. Visual comparisons should take into account variations within the variety. 6.3.2.2.4 Evaluation of varieties with the same code For varieties with the same code, if the expression status and code of all varieties are obtained from the same planting trial, they are generally considered not to have the same expression status. Significant differences exist. Specificity may be determined in subsequent planting trials through adjacent comparisons or statistical analysis. Statistical methods can be used to classify... The specificity of a variety must meet the requirements of 6.3.3.

6.3.2.3 Evaluation of Individual Variety Records The DUS testing guidelines, based on individual test records (non-code) for each variety, determine the magnitude of the trait difference required for specificity, which is different from the code method. This depends on factors such as the test location, year, environmental changes, and the range of trait expression in the variety library.

6.3.3 Specificity evaluation using statistical methods

6.3.3.1 Selection of Statistical Methods The test data structure and scale type (ordinal, interval, or ratio, etc.) determine the appropriate statistical method selection. The data structure depends on the evaluation method. Methods (visual inspection or measurement, population or individual observation) are influenced by trait type, reproductive method, experimental design, and other factors. When using statistical methods... Before applying the law, it is advisable to understand some basic statistical rules, see UPOV document TGP/8.

6.3.3.2 Test Data Traits observed through visual inspection or measurement methods can be evaluated for specificity using statistical methods.

a) Using statistical methods requires sufficient test records for each variety.

---Records of individual plants or plant parts obtained by measurement (MS) or visual inspection (VS);

---Multiple replicates or multiple plots, or more than one growth experiment, can yield multiple records, and the test data conforms to the specific requirements. Conditions for statistical procedures.

b) In most cases, a single test record is obtained by visual inspection (VG) or by measuring a group of plants (MG), since only one test record is obtained for each variety. There is a record that it is impossible or unnecessary to assess specificity using statistical methods.

c) Commonly used for measuring traits in cross-pollinated varieties and some hybrids.

6.3.3.3 Visual inspection 6.3.3.3.1 Quality Properties For visually assessed quality traits, statistical analysis of the results is often unnecessary in most cases. 6.3.3.3.2 Quantitative traits In addition to measurement and counting, visual inspection can also be used to directly compare the quantitative traits of the applied variety with those of similar varieties in pairs. If the differences between varieties are significant and reproducible (for example, in the expression of the trait of plant height, variety A is always higher than variety B), then it indicates that... The differences are obvious. 6.3.3.3.3 Pseudo-quality traits Whether to use statistical methods to evaluate pseudo-quality traits depends on the specific circumstances.

6.3.3.4 Measurement of traits 6.3.3.4.1 Self-pollinating and asexually propagated varieties At the appropriate time for trait observation and at the specified probability level, if the trait difference between varieties is greater than or equal to the minimum significant difference... (LSD) Even if the trait expression state is the same code, it is considered to have significant differences. 6.3.3.4.2 Cross-pollinated varieties The following are commonly used statistical analysis methods for evaluating the specificity of cross-pollinated varieties.

a) Specific multi-year comprehensive analysis method For evaluating the specificity of cross-pollinated varieties, including hybrid varieties, analysis of variance should be used to assess the variation between years. See details below. UPOV recommends the "Specific Multi-Year Integrated Analysis Method" (COYD).

b) 2×1% Standard Analytical Method The specificity of two varieties can be determined using the 2×1% standard analysis method. This means that if both varieties show specificity for at least two out of three years of testing, they are considered to have specificity. One or more measured traits are significantly different at the 1% level and exhibit the same direction of expression.

c) Other statistical methods Variety specificity can be determined using other statistical methods such as analysis of variance and multiple comparison tests, provided that appropriate statistical methods are available. The model conforms to the basic statistical assumptions of the UPOV document TGP/

8.If these conditions are met, in one or more quantities... Varieties that exhibit significant differences in traits can be considered to possess specificity. 6.3.3.4.3 Hybrids Specificity can be determined using parental combinations, provided that the differences between the parents are sufficient to ensure that the hybrids obtained from these parents possess specificity. Sexuality. Refer to the UPOV procedure for specificity testing (TGP/9) for further information.

6.4 Number of Specific Observation Samples

6.4.1 Quality Properties For qualitative traits, a small number of plants is sufficient to identify the expression of a variety. The number of plants typically used to evaluate specificity is not the number of plants planted. Limiting factors on the number of plants in the experiment.

6.4.2 Quantitative traits and pseudo-massive traits For quantitative traits and pseudo-qualitative traits, the number of plants or plant parts required for specificity evaluation must meet the minimum requirement.

a) Observation of the entire cell (VG/MG).

b) Observations on subsamples of the cell (VG/MG).

c) Observation of individual plants (VS/MS).

---The number of plants is important for the accuracy of the records;

---It is advisable to specify the number of observations;

---The number of observation samples in the testing guidelines.

6.4.3 Number of similar varieties The number of test plants specified in the DUS testing guidelines applies to both the applicant variety and similar varieties. If varietal consistency is not required, this should be considered separately. To reduce the number of similar plants in planting trials, the minimum number required for specific analysis must be met.

7.2.1 Heteromorphic strain method

7.2.1.1 Visual inspection method for identifying heteromorphic plants In DUS testing, if the expression of a plant's overall or partial traits differs significantly from the trait expression of a typical plant of that variety, then that plant... The plant is a heterotypic plant. In assessing consistency, the difference between the heterotypic plant and the applicant variety is compared with the difference between the applicant variety and other varieties. The standards are the same, see 6.3.2.

7.2.1.2 Measurement Methods for Identifying Heteromorphic Plants Statistical analysis is performed on individual records obtained from a single measurement of a group of plants or plant parts. Methods for processing measurement data from each plant are described. See UPOV's conformance testing document (TGP/10).

7.2.1.3 Determination of the number of heteromorphic plants Based on population criteria and acceptable probability, determine the maximum permissible value for heteromorphic plants of different sample sizes. If it is possible to observe a variety... For all plants, the population standard is the percentage of acceptable off-type plants. Varieties that correctly accept the specified percentage of off-type plants exhibit uniformity. The rate is called the acceptance probability. Appropriate population criteria, acceptance probabilities, and the maximum permissible number of heteromorphic plants within a specified sample size range should be determined using the DUS assay for the relevant plant varieties. The test guidelines make clear provisions.

7.2.1.4 Consistency Evaluation Based on the Multi-Test-Period Heterogeneous Strain Method 7.2.1.4.1 Independent Testing Cycle Two independent testing cycles can be conducted in different years at the same location, or in the same year at different locations. The following guidelines do not apply. This method is suitable for evaluating varietal uniformity using the heteromorphic method on the same plant in two testing cycles, and for testing different batches of plant propagation material. The results cannot be combined. 7.2.1.4.2 Evaluation of consistency between test results from two cycles If the results of two testing cycles for a variety meet the consistency criteria, the variety is considered consistent; otherwise, the variety is considered inconsistent. The species lacks consistency. 7.2.1.4.3 Test the third cycle If a variety's test results are inconsistent at the end of two testing cycles, and one testing cycle meets the consistency criteria, while the other testing cycle does not, then... If the first test cycle does not meet the consistency criteria, a third test cycle can be performed. If the third test cycle passes and the results meet the consistency criteria... If the consistency criteria are met, the variety is considered to have consistency; if the consistency criteria are not met, the variety is considered to lack consistency. 7.2.1.4.4 Evaluation based on the combined results of two test cycles If a variety's test results are inconsistent at the end of two testing cycles, and one testing cycle meets the consistency criteria, while the other testing cycle does not, then... If the test cycle does not meet the consistency standard, but the total number of atypical strains does not exceed the allowable total number of samples combined from two test cycles, then the product is considered acceptable. If a variety is considered to be incompatible, then the total number of heteromorphic plants exceeds the allowable total number of samples combined over two testing periods. 7.2.1.4.5 Outlier Confirmation If there are significant differences in the results across different testing periods, for example, when the number of a certain variant strain significantly exceeds the allowable limit in one testing period. If a variant is found in one test period but not in another, a consistency statistical test should be performed at an appropriate time to determine the number of variant strains between test periods. It is important to determine whether the differences are due to environmental factors or sampling.