Markers associated with stalk number and suckering in sugarcane colocate with tillering and rhizomatousness QTLs in sorghum
Bibliographic record
Abstract
Two important factors influencing sugar yield, the primary focus of sugarcane plant breeding programs, are stalk number and suckering. Molecular markers linked to both of these traits are sought to assist in the identification of high sugar yield, high stalk number, low-suckering sugarcane clones. In this preliminary mapping study, 108 progeny from a biparental cross involving two elite Australian sugarcane clones were evaluated at two sites for two years for both stalk number and suckering. A total of 258 DNA markers, including both restriction fragment length polymorphisms (RFLPs) and radio-labelled amplified fragments (RAFs), were scored and evaluated using single-factor analysis. Sixteen (7 RFLPs and 9 RAFs) and 14 (6 RFLPs and 8 RAFs) markers were identified that were significantly associated (P < 0.01) with stalk number and suckering, respectively, across both years and sites. The seven and six RFLP markers associated with stalk number and suckering, respectively, were generated by eight different RFLP probes, of which seven had been mapped in sorghum and (or) sugarcane. Of significant interest was the observation that all seven RFLP probes could be shown to be located within or near QTLs associated with tillering and rhizomatousness in sorghum. This observation highlights the usefulness of comparative mapping between sorghum and sugarcane and suggests that the identification of useful markers for stalk number and suckering in sugarcane would be facilitated by focussing on sorghum QTLs associated with related traits.
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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 | 0.001 | 0.001 |
| 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".