Genetic linkage mapping for molecular dissection of chilling requirement and budbreak in apricot (<i>Prunus armeniaca</i>L.)
Why this work is in the frame
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Bibliographic record
Abstract
Commercial production of apricot is severely affected by sensitivity to climatic conditions, an adaptive feature essential for cycling between vegetative or floral growth and dormancy. Yield losses are due to late winter or early spring frosts and inhibited vegetative or floral growth caused by unfulfilled chilling requirement (CR). Two apricot cultivars, Perfection and A.1740, were selected for high and low CR, respectively, to develop a mapping population of F1 individuals using a two-way pseudo-testcross mapping strategy. High-density male and female maps were constructed using, respectively, 655 and 592 markers (SSR and AFLP) spanning 550.6 and 454.9 cM with average marker intervals of 0.84 and 0.77 cM. CR was evaluated in two seasons on potted trees forced to break buds after cold treatments ranging from 100 to 900 h. A total of 12 putative CR quantitative trait loci (QTLs) were detected on six linkage groups using composite interval mapping and a simultaneous multiple regression fit. QTL main effects of additive and additive x additive interactions accounted for 58.5% +/- 6.7% and 66.1% +/- 5.8% of the total phenotypic variance in the Perfection and A.1740 maps, respectively. We report two apricot high-density maps and QTLs corresponding to map positions of differentially expressed transcripts and suggested candidate genes controlling CR.
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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 it