Winter Cover Crop Seeding Rate and Variety Affects during Eight Years of Organic Vegetables: I. Cover Crop Biomass Production
Bibliographic record
Abstract
Long‐term research on cover crops (CC) is needed to design optimal rotations. Winter CC shoot dry matter (DM) of rye (Secale cerealeL.), legume–rye, and mustard was determined in December to February or March during the first 8 yr of the Salinas Organic Cropping Systems trial focused on high‐value crops in Salinas, CA. By seed weight, legume–rye included 10% rye, 35% faba (Vicia fabaL.), 25% pea (Pisum sativumL.), and 15% each of common vetch (V. sativaL.) and purple vetch (V. benghalensisL.); mustard included 61% Sinapis albaL. and 39% Brassica junceaCzern. Cover crops were fall‐planted at 1x and 3x seeding rates (SR); 1x SR were 90 (rye), 11 (mustard), and 140 (legume–rye) kg ha−1. Vegetables followed CC annually. Cover crop densities ranged from 131 to 854 plants m−2and varied by CC, SR, and year. Year, CC, and SR affected DM production, however, the effects varied across the season and interactions occurred. Averaged across years, final DM was greater in rye and legume–rye (7 Mg ha−1) than mustard (5.6 Mg ha−1), and increased with SR through January. Dry matter production through the season was correlated significantly with growing degree days (GDD). Legumes contributed 27% of final legume–rye DM. Season‐end legume DM was negatively correlated with GDD at 30 d, and legume DM in the 3x SR increased during years with frequent late‐season rainfall. Seed costs per Mg of final CC DM at 1x SR were approximately three times higher for legume–rye than rye and mustard.
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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".