Residue Removal and Nitrogen Fertilization Affects Tiller Development and Flowering in Meadow Bromegrass
Why this work is in the frame
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Bibliographic record
Abstract
Flowering and seed yield in many temperate grasses are dependent on floral induction in the previous fall. Field experiments were conducted in Saskatchewan to determine the effect of crop residue removal and N fertilization on tiller and panicle development in meadow bromegrass ( Bromus riparius Rehm.). Four residue removal treatments (none, after harvest, October, and after harvest + October) and three N treatments (0, 50, and 100 kg N ha −1 ) were applied in each of 2 yr. Tiller density and leaf stage were determined in fall and spring; panicle density was determined just before seed harvest each year. Removing crop residue generally increased tiller and panicle density. However, fall tiller density decreased at Saskatoon in 1996 due to dry conditions, regardless of residue removal. Because fewer tillers were present in the fall when conditions that promote flowering prevailed, panicle density was reduced by 62% compared with the previous year. Nitrogen generally did not affect tiller density or development. However, in the spring of 1996, 100 kg N ha −1 with a single residue removal increased leaf stage from 2.4 to 2.6 leaves tiller −1 . This rate of N with double residue removal reduced leaf stage to 2.2 leaves tiller −1 due to winter injury. Fall tiller density and panicle production were similarly affected. As a result of winter injury and drought, fall tiller density and development were not highly or frequently correlated with panicle or seed production. Hence, fall tiller density and development in the prior year cannot be used as a tool to predict seed yield.
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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 | 0.000 |
| 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) | 0.000 | 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 it