Relationships of Campanian olive cultivars: comparative analysis of molecular and phenotypic data
Bibliographic record
Abstract
Estimation of the genetic relatedness of traditional olive cultivars with genetic markers and phenotypic data enables progress in plant breeding, management of genetic resources, and protection of both breeders' rights and certified premium products. We used amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), and quantitative and qualitative morphological traits, including characteristics recommended for variety registration, to study genetic diversity and relationships in the olive at different levels. The 14 varieties analyzed, which are used for the production of Protected Denomination of Origin extra-virgin olive oil, represent the most important cultivars in the Campania region of Italy and typify a regional diversity characteristic of traditional olive cultivation. The genetic distances obtained with the two DNA marker systems were significantly correlated, as were those obtained by quantitative and qualitative traits. A lower but significant correlation was also observed between distances based on molecular markers and quantitative traits, but qualitative traits, even if sampled in high numbers, failed to describe the pattern of molecular similarity. Our data imply that the type and the number of phenotypic traits scored can greatly influence the outcome of the analysis, and care should be taken when qualitative and quantitative data are combined. Furthermore, the data indicate that the two molecular marker systems are useful for investigating genetic relationships, but they may also be used to complement and assist the traditional registration of varieties. We propose that since the information provided by molecular and morphological marker systems in olive is different, they should serve different purposes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".