Obtaining Triploid Hybrids by Means of Open Pollinations and Controlled Crosses Involving Diploids Parental
Bibliographic record
Abstract
The creation of triploid hybrids is an important genetic improvement strategy for the development of new commercial citrus scion varieties. The objective of this work was to quantify the frequency of triploids obtained from natural and controlled crosses of different mandarin varieties under varying environmental conditions in the state of Bahia. The experiments were conducted in the municipalities of Cruz das Almas (Recôncavo Baiano region) and Mucugê (Chapada Diamantina region). The first experiment was based on fruits from open pollinations of the varieties ‘Page’, ‘Ortanique’, ‘Ellendale’, ‘Clemenules’, ‘Swatow’, ‘Piemonte’, ‘Fortune’, ‘South Africa’, ‘Montenegrina’, ‘Kincy’, ‘Span Americana’, ‘Fremont, ‘Nova’, ‘Dancy’ and ‘Murcott’, and the second involved fruits from controlled crosses of female parents ‘Nova’, ‘Fortune’ and ‘Ortanique’ and male parents ‘Page’, ‘Montenegrina’, ‘Swatow’, ‘Fremont’ and ‘Kincy’. The seeds selected were inoculated in test tubes containing approximately 10 mL of Woody Plant Medium (WPM). When the plants reached circa 60 days of age, leaf samples were removed for quantification of the DNA by the flow cytometry technique. In Mucugê, three triploids were identified from open pollinations, ‘Clemenules’ (1) and ‘Ortanique’ (2), while in Cruz das Almas, no triploids were obtained. In the controlled crosses, triploids were only obtained in Mucugê: ‘Ortanique’ × ‘Montenegrina’ (4), ‘Ortanique’ × ‘Kincy’ (1) and ‘Ortanique’ × ‘Swatow’ (2). Based on the data, it is suggested that the environmental conditions of Mucugê favored the formation of triploids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".