Forage Production and Selection for Vigor in Meadow and Hybrid Bromegrass in the Northern Great Plains
Bibliographic record
Abstract
Meadow bromegrass (Bromus riparius Rehmann) is an important forage crop in Canada and the Intermountain West, but it has not been extensively evaluated in the northern Great Plains (NGP). Our objectives were to 1) evaluate meadow, smooth, and hybrid bromegrasses for forage production under intensive management in eastern South Dakota, and 2) evaluate the effect of selection for vigor in multiple environments on forage production of meadow bromegrass. Thirteen populations (7 meadow bromegrass, 5 hybrid bromegrass, and 1 smooth bromegrass) were evaluated for 4 yrs (2005-2007, 2009) at Brookings, SD. Biomass at anthesis was greater for smooth (6.75 Mg ha-1) than for meadow or hybrid brome (5.4 Mg ha-1) in 2005, but production at anthesis during 2006 and 2007 was similar for meadow and smooth bromegrass. Regrowth harvested during July and October 2005 and November 2006 was greater for meadow than smooth or hybrid bromegrass. Forage production at anthesis in 2009, after rest (i.e., no cutting) and fertilization in 2008, was 4.2 Mg ha-1 for meadow bromegrass compared with 3.3 Mg ha-1 and 2.6 Mg ha-1 for hybrid and smooth bromegrass, respectively. Smooth and hybrid bromegrasses had more leaves·tiller-1 than meadow bromegrass. After 6 yrs, meadow bromegrass had higher tiller density and greater potential for tolerating multiple harvests during a growing season than did smooth or hybrid bromegrass. Selection for vigor in multiple environments in North America resulted in experimental populations of meadow bromegrass with superior forage yield compared with ‘Fleet’ on marginal crop land in the northern Great Plains.
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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".