Cover crops and nitrogen fertilization effects on soil carbon and nitrogen and tomato yield
Bibliographic record
Abstract
Cover crops can influence soil properties and crop yield. We examined the influence of legume [hairy vetch (Vicia villosa Roth) and crimson clover (Trifolium incarnatum L.)] and nonlegume [rye (Secale cereale L.)] cover crops and N fertilization (0, 90, and 180 kg N ha −1 ) on the short- and long-term effects on soil C and N and tomato yield and N uptake. We measured organic C and N (long-term effects), potential C and N mineralization (PCM and PNM) and inorganic N (short-term effects) periodically on a Greenville fine sandy loam (fine-loamy, kaolinitic, thermic, Rhodic Kandiudults) planted with tomato (Lycopersicum esculentum Mill) from April to August in 1996 and 1997 in Georgia USA. Soil C and N concentrations increased early in the growing season with cover crop residue incorporation, but decreased as the residue decomposed. Rye increased organic N and maintained greater levels of organic C and PCM after 3 yr than other treatments. In contrast, hairy vetch and crimson clover increased PNM and inorganic N soon after residue incorporation into the soil and produced tomato yield and N uptake similar to that produced by 90 and 180 kg N ha –1 . Nitrogen fertilization increased PNM and inorganic N after split application and tomato yield and N uptake but decreased organic C and N and PCM compared with rye. Compared with 0 kg N ha –1 , nonlegume cover crops, such as rye can increase organic C and N and PCM but legume cover crops, such as hairy vetch and crimson clover, can enrich soil N and produce tomato yield and N uptake similar to that produced by 90 and 180 kg N ha −1 . Key words: Cover crops, nitrogen fertilization, soil carbon, soil nitrogen, tomato yield
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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 | 0.000 | 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) | 0.000 | 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".