Cover crops and nitrogen fertilization effects on soil aggregation and carbon and nitrogen pools
Bibliographic record
Abstract
Cover crops and N fertilization rates may influence soil aggregation and associated C and N pools, thereby affecting soil quality and productivity. We compared the effects of legume [hairy vetch (Vicia villosa Roth) and crimson clover (Trifolium incarnatum L.)] and nonlegume [rye (Secale cereale L.)] cover crops and N fertilization rates {half N rate [HN: 90 kg N ha-1 yr-1 for 3 yr of tomato (Lycopersicon esculentum Mill.) followed by 80 kg N ha-1 yr-1 for eggplant (Solanum melogena L.)]} and full N rate [FN: 180 kg N ha-1 yr-1 for 3 yr of tomato followed by 160 kg N ha-1 yr-1 for eggplant]} on soil aggregation and C and N pools in whole-soil and aggregates. The pools were organic C, total N, potential C mineralization and potential N mineralization (PCM and PNM), microbial biomass C and microbial biomass N (MBC and MBN), and particulate organic C and particulate organic N (POC and PON). Field experiment was conducted in a Greenville fine sandy loam (fine-loamy, kaolinitic, thermic, Rhodic Kandiudults) from 1995 to 2000 in Fort Valley, Georgia, USA. While the amount of soil present in aggregates decreased with decreasing size class, the amount was greater with nonlegume and FN than with HN and legume cover crops in the 2.00- to 0.85-mm size class. Organic C, PCM, and MBC contents in whole-soil were greater with nonlegume, but MBN and PON were greater with legumes than in the control with no cover crop or N fertilization. Organic C and total N concentrations in aggregates were greater in 2.00- to 0.50-mm than in 4.75- to 2.00-mm, <0.25-mm, or <4.75-mm (whole-soil) size classes, but PNM and MBN were greater in <0.50- or <4.75-mm than in 4.75- to 2.00-mm size classes. As POC and PON decreased with decreasing aggregate-size class, POC in the <0.85-mm size class was greater with nonlegume and PON in the 2.00- to 0.85-mm size classes was greater with legumes than with the control and N rates. Nonlegume may increase soil aggregation, microbial activities, and C sequestration, but legumes may increase N mineralization in the soil compared with no cover crop. Nitrogen fertilization also may improve soil aggregation. Nitrogen mineralization and C and N sequestration may be greater in aggregates <2.00 mm diameter. Cover crops and N fertilization may improve soil quality and productivity, particularly in intermediate and small size (<2.00 mm) aggregates. Key words: Cover crop, nitrogen fertilization, soil aggregation, soil carbon, soil nitrogen
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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".