QTLs Location of Calyx-related Traits in Tetraploid <i>Dendrobium</i>
Bibliographic record
Abstract
In order to identify QTL locus of calyx-related traits in Dendrobium, 190 F1 individuals derived from the crossbreed of tetraploid Dendrobium cultivars D. Mangosteen x D. Burana Pink No.2 were used as materials. Through three years observation of four characteristics of calyx (length of dorsal sepal, width of dorsal sepal, length of lateral sepal, width of lateral sepal), the QTL was located on the two genetic maps of parents which had been already constructed. The result showed that the four characteristics were quite different among the individuals of F1 generation, and the observed values of all the characteristics were all positive distribution, which was suitable for QTL analysis. Nine QTLs were detected on the maternal ‘D. Mangosteen’ genetic linkage map, including 1 QTL for dorsal sepal length, 3 QTLs for dorsal sepal width, 2 QTLs for lateral length and 3 QTLs for lateral width, with the genetic contribution rate ranging from 11.9% to 16.8%. Also, two tight linkage markers were acquired (M10E3-146, M8E8-284). A total of 6 QTLs were detected on the paternal ‘D. Burana Pink No.2’ linkage map, including 2 QTLs for dorsal sepal length, 1 QTL for dorsal sepal width, 2 QTLs for lateral length and 1 QTL for lateral width, with the genetic contribution rate ranging from 11.8% to 17.3%. This result of study could provide reference for Dendrobium molecular marker assisted breeding and precise location of correlation gene.
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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 | 0.000 | 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) | 0.001 | 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".