Interaction between chloride and both macro- and micronutrients in annual canarygrass
Bibliographic record
Abstract
Annual canarygrass (Phalaris canariensis L.) has a larger response to chloride (Cl − ) fertilizer than other cereal crops. This unexpected response prompted further research for unexpected interactions between Cl − and other nutrients in annual canaryseed. The objective of this study was to compare the interaction of macronutrients and micronutrients with Cl − on the development and grain yield of annual canarygrass. Thirteen fertilizer combinations were applied to determine the effect of macro- and micronutrients on annual canarygrass. A field study was conducted at six locations across Saskatchewan over a 4 yr period using a randomize complete block design. Grain yield had a strong chloride response at 7 of the 21 site years with a 70% increase in grain yield over the 7 site-years. A sideband application or surface application of Cl − were both effective. At the responsive sites without the addition of Cl − , the addition of other nutrients is not effective while at the non-responsive sites, responses to the nutrients can be achieved without the addition of Cl − . Chloride impacted canarygrass during reproductive development. Nitrogen is the major nutrient Cl − interacted with in this study. Canarygrass is not more responsive to phosphorus, potassium, sulfur, zinc, copper, manganese, and boron than other cereals. In conclusion, at Cl − -responsive sites the application of nutrients are ineffective in the absence of Cl − fertilizer. In addition, the sensitivity of annual canarygrass to Cl − indicates that it could be used to investigate the role of Cl − in cereal crop development and grain yield.
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 | 0.001 | 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 | 0.001 | 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".