Utilization of physiological traits for selection of high-yielding double haploid barley
Bibliographic record
Abstract
There is an increased interest in developing high-yielding hulless feed barley (Hordeum vulgare L.) with low fibre content for swine rations. However, little information on physiological basis to select for high-yielding hulless barley was available. Approximately 400 double haploid barley lines were derived from a Kunlun No. 1/CIMMYT No. 6 cross using the bulbosum method. Both parental lines were six-row feed barley types differing in seed type, leaf type, leaf area distribution, tillering, time to heading and maturity and grain yield. Although Kunlun No. 1 yielded abou t 66% of CIMMYT No. 6, its seed was hulless with a grain weight 21% larger than covered CIMMYT No. 6 seed. Hulless barley, with its reduced fibre content, is desirable in swine rations. Selected double haploid lines (100 covered lines in 1995 and 100 hulless lines in 1996), parental lines and an adapted check, Chapais were evaluated at Ottawa, ON, and Charlottetown, PEI. We found that grain yields were significantly correlated with leaf area index (LAI), dry matter (DM), length and width of flag leaves, and plant height. All of the highest yielding lines in both hulless and covered populations common to both sites were similar to the parent Kunlun No. 1 with broader, shorter and greener leaves than the parent, CIMMYT No. 6. The best covered lines yielded more than the check cv. Chapais and some of the hulless lines were similar to the check. This study suggests that selection of high-yielding low fibre double haploid barley lines based on physiological traits has potential to increase grain yield for feed barley. Key words: Hulless barley, physiological traits, yield, feed quality, double haploid
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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".