Seed yield variation in plains rough fescue (<i><scp>F</scp>estuca hallii</i> (<scp>V</scp>asey) <scp>P</scp>iper) populations and its relation with phenotypic characteristics and environmental factors
Bibliographic record
Abstract
Abstract Plains rough fescue (Festuca hallii (Vasey) Piper) is a dominant grass in the endangered Fescue Prairie of North America. Infrequent and unpredictable seed production presents a challenge for the use of this species in restoration and rangeland seeding. The objective of this study was to compare seed yield of different plains rough fescue populations and to determine the dependence of seed yield on phenotypic characteristics. Effect of weather conditions during the floral induction and initiation period of different years of the study was also compared. In 2007, a completely randomized field plot experiment was established from eleven populations of plains rough fescue at Swift Current, SK, Canada. In 2007, 2010 and 2011, individual plant seed yield, reproductive tillers, above‐ground biomass, plant height and crown diameter were measured, and plant vigour was scored. All measured variables differed significantly (P ≤ 0·05) among populations. Four populations were identified as having higher seed yield potential. Plants in these four populations also had characteristics of good plant vigour, taller stems, more reproductive tillers and greater biomass. Seed yield increased linearly with increasing plant height, crown diameter, above‐ground biomass and number of reproductive tillers (r2 ranged 0·17–0·67, P < 0·001), but number of reproductive tillers (r2 = 0·53–0·67, P < 0·001) was a better predictor for selection of lines with higher seed yield. Although seed yield varied among years, populations with higher seed yield tended to produce greater amounts of seed over the period of the study.
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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 | 0.000 |
| 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 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".