Pea-based cover crop mixtures have greater plant belowground biomass, but lower plant aboveground biomass than a pure stand of pea
Bibliographic record
Abstract
In eastern Canada, organic grain producers have a rising interest in using cover crop mixtures instead of pure stands to maximize ecosystem services. Yield stability and belowground biomass of cover crop mixtures have however received limited attention in the scientific literature, although they do affect ecosystem services. The aims of this study were to evaluate the aboveground and belowground biomass and yield stability of pea-based cover crop mixtures, and to assess species-specific contributions to aboveground biomass . In a field experiment conducted at three site-years in Quebec, Canada, a pure stand of field pea ( Pisum sativum L.) and cover crop mixtures of 2, 6, and 12 species, all including field pea, were compared to a weedy control (without cover crop). The mixtures were seeded according to a substitutive unbalanced design. The proportion of field pea ranged from 45% to 93% of the aboveground plant biomass within all mixtures. Among all site-years, pure stand of field pea provided the highest aboveground biomass (2636 kg ha −1 ), followed by the 2-species mixture (2320 kg ha −1 ) and both multi-species cover crop mixtures (mean of 1849 kg ha −1 ). Aboveground biomass was inversely correlated to cover crop diversity (Pearson coefficient of −0.73), and inversely correlated to weed biomass (Pearson coefficient of −0.54). Pure stand of field pea had the lowest belowground biomass and stability (693 kg ha −1 , CV of 28%) when compared to mixtures (886 kg ha −1 , CV of 14% on average). This study confirms that the value of pea-based mixtures, compared to a pure stand of field pea, lies mainly below the soil surface rather than above it. This could likely enhance many soil-related ecosystem services.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".