Cultivation of native plants for seed and biomass yield
Bibliographic record
Abstract
Abstract Establishing native perennial plants on the agricultural landscape can improve ecosystem services and provide marketable products, such as seed for restoration plantings and biomass for renewable energy. Native perennials of economic and ecological interest should be examined in different planting configurations over time to determine their suitability for sustained production. Canada milk vetch (Astragalus canadensis L.), purple coneflower (Echinacea purpurea L.), and showy tick trefoil (Desmodium canadense L.) were established at two locations in Minnesota to evaluate seed and vegetative biomass yields. These forbs were established in six different agronomic designs: three strip designs (one‐row, three‐rows, and six‐rows) and three community designs (monoculture, low‐richness polyculture, and high‐richness polyculture). Seed yield averaged 2995, 950, and 1157 kg ha−1 for Canada milk vetch, purple coneflower, and showy tick trefoil in the first year and declined for all species over time. Biomass yields averaged 6743, 2725, and 2869 kg ha−1 in the first year for Canada milk vetch, purple coneflower, and showy tick trefoil, respectively. Canada milk vetch biomass yields declined by 98% over time, and showy tick trefoil biomass yields increased by 40%. Seed and biomass yields were the lowest in one‐row strip design and greatest in the community designs, with little difference between monocultures and polycultures. Results suggest that production is maximized in community designs and that purple coneflower and showy tick trefoil have the potential for multiyear yields.
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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) | 0.001 | 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".