Dicamba and growth condition effects on doubled haploid production in durum wheat crossed with maize
Bibliographic record
Abstract
Abstract Doubled haploid plants are useful in genetic studies and plant breeding, but a consistent and satisfactory frequency of production has been difficult to achieve in durum wheat. Triticum turgidum L., using the maize pollen method. The objective of this study was to develop an objective method of producing doubled haploids in durum wheat. Plant growing and handling conditions, aspects of hormone treatments, wheat genotype and pollen source were considered. The number of caryopses, embryos, haploids, doubled plants and doubled plants that set seed were measured. Although growth conditions, pollen source, method of handling plants and wheat genotype are important considerations, the type of hormone was found to be most significant in the production of doubled haploid plants. When 50mg/l dicamba was substituted for 100 mg/l 2,4‐D the number of doubled haploids per spike increased from 0.2 for the best 2,4‐D treatment to 1.3 for the dicamba treatment. This increased frequency was largely attributed to an increase in the number of caryopses generated for each spike emasculated and from an increased frequency of germination of embryos to haploid plantlets. The best production of caryopses was 0.41 caryopses per florest with 2,4‐D. The best production of haploids per 100 florets was 12 with dicamba and 1.65 with 2,4‐D. The frequency of one doubled haploid per emasculated spike through the use of dicamba is a practical level for generating populations for genetic studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".