Effects of Oat (Avena sativa) and Hairy Vetch (Vicia villosa) Cover Crops on Nitrate Leaching, Soil Water, and Maize Yield in Subtropical Islands in Japan
Bibliographic record
Abstract
<p>We determined the effects of oat (<em>Avena sativa</em>) and hairy vetch (<em>Vicia villosa</em>) winter cover crops on subsequent maize growth, soil erosion, water run-off, and nitrate leaching. Separate or combined plots of oat and hairy vetch cover crops were grown in winter, and maize was subsequently planted in all plots in the following summer season. The half-recommended N fertilizer (50 kg ha<sup>-1</sup>) applied to zero-tillage maize produced the same biomass and yield as the control (i.e., natural fallow-maize with tillage and fertilizer application of 100 N kg ha<sup>-</sup><sup>1</sup>) when cultivated after hairy vetch (9.6 t ha<sup>-</sup><sup>1</sup>). In contrast, maize grown after oat showed 40.4% lower biomass and 65.4% lower yield. Compared to the control, runoff and soil erosion were 85.3-92.9% (<em>P</em> &lt; 0.001) and 68.6-98.7% lower with cover crop mulch irrespective of cover crop species (<em>P</em> &gt; 0.05), respectively. Cumulative nitrate leaching 60 cm below the soil surface was highest in the control, followed by (in descending order) hairy vetch-maize, hairy vetch + oat-maize, and oat-maize. NO<sub>3</sub>-N release showed a twin-peak pattern in hairy vetch-maize plots at 18 and 37 days after sowing (DAS). Meanwhile, a single peak was observed in the control at 32 DAS immediately after top dressing at 31 DAS. The synchrony of N supply and crop demand were better in hairy vetch-maize than oat-maize or conventional cultivation owing to rapid maize growth under lower rainfall conditions.<strong></strong></p>
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".