Competitive Ability in Mixtures of Small Grain Cereals
Why this work is in the frame
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Bibliographic record
Abstract
Morphological and physiological differences in competitive ability among species and genotypes can affect the growth, development, and subsequent composition and value of feedstuffs produced from small grain cereal mixtures. Our objective was determine the final grain yields of the components of mixtures and compare these yields with those expected based on the yields of the monocrops. Three field studies were conducted to evaluate the productivity of barley ( Hordeum vulgare L.), oat ( Avena sativa L.), triticale (× Triticosecale rimpaui Wittm.), and rye ( Secale cereale L.) grown as monocrops and mixtures. Seeding rates ranging from 250 seeds m −2 to 750 seeds m −2 were evaluated to determine their effect on competitive ability of genotypes and species of small grains. Differences in competitive ability were found. The semi‐dwarf barley ‘Kasota’ was less competitive than the standard‐height ‘AC Lacombe’ and ‘Seebe’. ‘Noble’ barley was more competitive than ‘AC Mustang’ oat or ‘Wapiti’ triticale. ‘Prima’ winter rye was more competitive than ‘Pika’ winter triticale. Relative grain yields were generally not different than 1.0 g g −1 , but when significantly different they were usually higher than one, indicating that the yields of those mixtures were better than expected based on yields when the cultivars were grown as pure stands. Seeding rates had little effect on competitive ability. The specific factors that lead to better than expected grain yields of mixtures and to good competitive ability of cultivars and species are difficult to predict and must be evaluated on a case‐by‐case basis.
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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 | 0.001 | 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) | 0.001 | 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 it