Relationships and influence of yield components on spaced‐plant and sward seed yield in perennial ryegrass
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Adequate seed production is essential for cultivar success in perennial ryegrass turf and forage industries, but improvement is limited by the complexity of yield components and low‐rank correlations between selection and production environments. This study examined seed yield components among 20 perennial ryegrass entries in both spaced plantings (selection environment) and swards (production environment) at two locations in Minnesota. Competitive (23 plants/m 2 ) and non‐competitive (3 plants/m 2 ) spaced‐plant nurseries were tested. Competitive spaced‐plant total yield was highly correlated with sward yield ( r s = 0.64 and 0.66, p < 0.01) at both locations, whereas the non‐competitive environment showed no correlation. Structural equation modelling ( SEM ) was used to explore the indirect and direct relationship of fall vegetative growth, winterkill, and yield components on total seed yield in all environments. Fertile tiller number (spikes plant −1 /m −2 ) exhibited both strong direct and indirect influence on total seed yield in all environments. However, the importance of fertile tiller number in the SEM was reduced with increased plant competition. The SEM showed that both weight per spike and seed yield per spike influenced total yield in spaced plants; however, neither consistently predicted total sward yield. The ratio of these two traits (g seed spike −1 /g spike −1 ) gave an index of fertility that was easy to measure and had a superior correlation with sward yield at two locations ( r s = 0.81 and 0.54, p < 0.05) when spaced plants were under competition. Results suggest that increasing competition in spaced plantings and selecting for spike fertility may more accurately identify superior plant material compared to lower competition environments.
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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 | 0.001 |
| 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