Association mapping of germinability and seedling vigor in sorghum under controlled low-temperature conditions
Bibliographic record
Abstract
Sorghum is one of the world's most important food, feed, and fiber crops as well as a potential feedstock for lignocellulosic bioenergy. Early-season planting extends sorghum's growing season and increases yield in temperate regions. However, sorghum's sensitivity to low soil temperatures adversely impacts seed germination. In this study, we evaluated the 242 accessions of the ICRISAT sorghum mini core collection for seed germination and seedling vigor at 12 °C as a measure of cold tolerance. Genome-wide association analysis was performed with approximately 162,177 single nucleotide polymorphism markers. Only one marker locus (Locus 7-2) was significantly associated with low-temperature germination and none with vigor. The linkage of Locus 7-2 to low-temperature germination was supported by four lines of evidence: strong association in three independent experiments, co-localization with previously mapped cold tolerance quantitative trait loci (QTL) in sorghum, a candidate gene that increases cold tolerance and germination rate when its wheat homolog is overexpressed in tobacco, and its syntenic region in rice co-localized with two cold tolerance QTL in rice. This locus may be useful in developing tools for molecular breeding of sorghums with improved low-temperature germinability.
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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".