Row spacing, seeding depth, seeding rate, and trinexapac‐ethyl effects on oat yield and lodging
Bibliographic record
Abstract
Abstract Lodging can reduce the yield and quality of oats ( Avena sativa L.). Root lodging, as opposed to stem lodging, is the predominant form of lodging in oats. Therefore, identifying management practices that enhance root lodging resistance should be prioritized. The objective of this study was to investigate the effect of four management practices on oat grain yield, yield components, grain quality, observed lodging, and plant traits that contribute to root lodging resistance. Row spacing and seeding depth were tested in three oat cultivars across two environments in Ontario, Canada. Seeding rate and the application of the plant growth regulator trinexapac‐ethyl (TE) at different nitrogen (N) fertilizer rates were tested in two‐to‐three oat cultivars across four environments. Lodging occurred naturally in all environments, with root lodging always occurring, sometimes in combination with stem lodging. Under high lodging pressure, shallow seeding increased lodging. Similarly, lodging increased with greater seeding rates when lodging pressure was high. Reducing row spacing had no effect on lodging but was the only management practice to consistently increase grain yield. TE reduced lodging in some environments, especially as N rates increased. Root plate spread, root plate depth, and root safety factor were minimally affected by the management practices studied and had complex interactions with genotype and environment. Among the measured crop traits, plant height had the strongest and most consistent relationship to observed lodging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".