Criteria for the definition of similarity thresholds for identifying essentially derived varieties
| Autor: | Enrico Noli, Sergio Conti, Maria Soccorsa Teriaca |
|---|---|
| Přispěvatelé: | Enrico Noli, Maria Soccorsa Teriaca, Sergio Conti |
| Rok vydání: | 2013 |
| Předmět: |
Percentile
molecular markers Basis (linear algebra) business.industry Calibration (statistics) essentially derived varietie Pattern recognition Plant Science intellectual property Biology Expression (computer science) Set (abstract data type) Fragment (logic) Similarity (network science) Genetics genetic similarity Artificial intelligence Variety (universal algebra) business Agronomy and Crop Science plant breeders’ right |
| Zdroj: | Plant Breeding. 132:525-531 |
| ISSN: | 0179-9541 |
| DOI: | 10.1111/pbr.12109 |
| Popis: | The concept of essential derivation refers to cases where a new variety is obtained from an initial variety (IV), of which it retains the expression of the essential characteristics resulting from the genotype or combination of genotypes of the IV. Protecting plant breeder’s rights can be facilitated by identifying a species-specific threshold level of similarity above which the new variety could be suspected as essentially derived (EDV). Amplified fragment length polymorphisms and simple sequence repeats proved suitable for measuring genetic similarity. Three approaches have been proposed for the definition of thresholds. According to the calibration principle’, the critical level to discriminate EDVs is defined based on similarities among closely related genotypes. Adopting the ‘tail principle’, the threshold is placed at a given percentile of the distribution of the similarities within a reference population of independent genotypes. Finally, with the ‘pedigree principle’, the thre shold is set starting from the a priori definition of breeding techniques that lead to EDVs. The tools and the approaches described in this review represent the basis for developing protocols useful in handling disputes of essential derivation. |
| Databáze: | OpenAIRE |
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