Does the presence of the gene for glabrous hull in annual canarygrass affect the response to chloride fertilizer?
Bibliographic record
Abstract
May, W. E., Holzapfel, C. B., Lafond, G. P. and Schoenau, J. J. 2013. Does the presence of the gene for glabrous hull in annual canarygrass affect the response to chloride fertilizer? Can. J. Plant Sci. 93: 109–118. Annual canarygrass is an important cereal crop in western Canada with a unique niche market as feed for caged birds. Chloride (Cl) fertilizer has been shown to increase seed yield in annual canarygrass; however, the response was only tested in one glabrous cultivar. Currently, glabrous cultivars created through mutagenesis, are lower yielding than cultivars with trichomes on their lemma, palea and glumes. The objective of this study was to determine if the mutagenic process which created cultivars that lack trichomes on their lemma, palea and glumes also affected the response of annual canarygrass to chloride fertilizer. A two-way factorial study was conducted across 7 site-years. The first factor was Cl applied at two rates (0 and 18.2 kg Cl ha−1) and the second factor was four cultivars (Keet, Cantate, CDC Togo (glabrous) and CDC Bastia (glabrous). The application of Cl increased the seed yield of annual canarygrass by 25% and most of this increase was due to a 21% increase in seeds per panicle. Kernel weight also contributed to increased seed yield. Chloride did not interact with the presence or absence of trichomes and therefore growers can expect to receive a yield increase from the application of Cl regardless of the annual canarygrass cultivar grown. Growers should apply 9 kg ha−1 of Cl when growing annual canarygrass. In conclusion, Cl is not involved in the physiology of the lower yield in glabrous cultivars compared with cultivars with trichomes, and Cl could not explain the seed yield differences between the two types of annual canarygrass.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".