The critical period of cover crop management: A framework for maximizing biomass potential and minimizing volunteers with buckwheat
Bibliographic record
Abstract
Abstract Buckwheat ( Fagopyrum esculentum Moench) is a short‐duration high‐biomass cover crop often grown in potato ( Solanum tuberosum ) rotations to provide select agroecosystem services. However, buckwheat's short generation time challenges its continued viability as a cover crop as seed is rapidly produced, resulting in volunteer issues in subsequent crops with limited control options. Field studies were conducted in Atlantic Canada over two seasons to model buckwheat biomass production and viable seed yield as a function of planting and termination time with the goal of providing a framework to maximize biomass production while minimizing seed return, termed the critical period of cover crop management. The model demonstrated that maximum buckwheat total (979 g m −2 ) and vegetative (565 g m −2 ) biomass production could be attained when planted by 2 and 3 growing degree days base 5 (GDD 5 ) accumulation and grown for 1680 and 2110 GDD 5 , respectively. Viable seed production rapidly increased with earlier planting dates and later termination dates up to a maximum of 3653 and 5974 seeds m −2 , respectively. Viable seed production could be minimized to 25% of the total if terminated by 696 GDD 5 or sown after 861 GDD 5 had accumulated. Values below this threshold could not be modeled in the termination study. Overall, our results provide a framework for producers to time cover crop planting and termination time to maximize the provision of agroecosystem services while minimizing the return of viable seed to their cropping systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".