Mapping and Quantitative Trait Loci Analysis of Drought Tolerance in a Spring Wheat Population Using Amplified Fragment Length Polymorphism and Diversity Array Technology Markers
Bibliographic record
Abstract
ABSTRACT Water availability is commonly the most limiting factor for crop production. This study was conducted to map wheat ( Triticum aestivum L.) quantitative trait loci (QTL) involved in drought tolerance. Using amplified fragment length polymorphisms (AFLPs) and Diversity Array Technology (DArT) markers, a population of 122 F 7 –derived recombinant inbred lines from a cross between ‘Dharwar Dry’ and ‘Sitta’ was reanalyzed to identify previously unknown QTL associated with drought tolerance traits and to further saturate known QTL regions. A linkage map of 48 groups was created from the combined data of DArT, AFLP, and previously reported simple sequence repeat (SSR) and expressed sequence tag (EST) markers. Quantitative trait loci were found in 24 of the 48 groups. Groups could be anchored on chromosomes 1D, 2B, 3A, 3B, 4A, 4B, 5A, 5B, 6A, 6D, 7A, and 7B. While four additional AFLP markers were added to the major QTL for drought tolerance on chromosome 4AL, a second major locus was found on chromosome 7B. QDt.ksu‐7B spans 34.7 cM with three associated markers. Simple sequence repeat marker Xbarc172 and DArT marker XwPt‐4230 explained 11.9% of the variation for harvest index under reduced irrigation in 1999 while AFLP marker XGTGG284 explained 10.7%. XwPt‐6463 explained 11.9 and 11.2% of the variation for drought susceptibility index for spike number and yield, respectively. The locus QDt.ksu‐4A now spans 21.9 cM and AFLP marker XCCGA110 explained 27.8 and 39.9% of the variation for grain fill rate and yield under reduced irrigation in 1999, respectively.
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 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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".