Yield and nutritive value of irrigated tall fescue compared with orchardgrass: In monocultures or mixed with alfalfa
Bibliographic record
Abstract
Thompson, D. J. 2013. Yield and nutritive value of irrigated tall fescue compared with orchardgrass: in monocultures or mixed with alfalfa. Can. J. Plant Sci. 93: 799-807. Orchardgrass (Dactylis glomerata L.) is commonly grown for irrigated forage production in interior British Columbia. Tall fescue [Schedonorus phoenix (Schop.) Holub.] is also adapted to the area but no comparative trials have been reported. Three varieties of each grass species were grown in monocultures or in mixtures with alfalfa at three irrigated sites throughout southern interior British Columbia. Study objectives included comparing the forage yield and nutritive value of the following groups: (1) tall fescue and orchardgrass monocultures, (2) tall fescue and orchardgrass mixtures with alfalfa and (3) grass-alfalfa mixtures with monocultures. In monoculture, tall fescue yield was 9% greater than orchardgrass (significantly greater yield at 3 of 6 site-years), though forage nutritive values were similar. Mixtures of the two grasses with alfalfa had similar yields, but those containing tall fescue had superior nutritive value. Alfalfa contributed a greater percentage to total yield and had higher survival when mixed with tall fescue. Tall fescue is a viable alternative to orchardgrass for irrigated forage production in monoculture and may be more suitable for mixtures with alfalfa. Our findings demonstrate a functional diversity effect; grass-alfalfa mixtures over-yielded the mean of the alfalfa, orchardgrass, and tall fescue monocultures by 12%.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".