Tracking the Release of Soil Nitrate and Labile C in A Legume-Maize Rotation in Zimbabwe
Bibliographic record
Abstract
This study compared the effect of a weedy fallow (5.2 t/ha biomass), a velvet bean (Mucuna pruriens) cut for hay (7.2 t/ha biomass) and a green-manured M. pruriens (6.49 t/ha biomass) on the dynamics of soil N and C in a maize crop. An on-farm, farmer participatory experiment was established on a farmer’s field in Wedza District, Zimbabwe. Soil mineral N and labile carbon were determined at intervals upto 120 cm depth, at maize planting and at 1 and 2 weeks after planting. Before planting, the soil mineral N content ranged from 28 kg N/ha after weed fallow to 107 kgN/ha following M. pruriens. Total nitrate concentration was highest in the 0-15 cm depth of the M. pruriens treatments in the pre-planting sampling, but following rainfall and maize planting, nitrate concentration declined rapidly. By 2 weeks after planting, 7.5 and 13.5 kg N/ha remained in the 0-120 cm soil depth of the weedy fallow and green-manured M. pruriens, respectively. Improving synchrony of nutrient release and uptake is critical when applying high quality residues which breakdown relatively slowly. This could result in significant inputs of C, release nutrients more slowly and reduce soil nutrient losses.
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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) | 0.000 | 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 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".