Cutting Height of Mombasa Grass Under Silvopastoral and Monoculture Systems
Bibliographic record
Abstract
This study aimed to evaluate the production of Mombasa grass cultivation under two different systems: monoculture and silvopastoral, with heights of 70, 80, 90, and 100 cm. Two seasons were evaluated: rainy period (December to March) and rain/drought transition (March to June). The variables evaluated were: total dry mass (TDM), dry mass (DM) of the morphological components, number of tillers, efficiency of nitrogen use, DM content, number of harvest cycles and cutting intervals. The experimental design was a randomized block design with five replications. The monoculture system presented the highest yields of TDM, number of tillers and DM of the morphological components in the two evaluated periods. The main variable affected by shading was the number of tillers per area, which directly affects all variables linked to production. In addition to the type of system, the time of the year also influenced the production of DM of the grass. The evaluation of grass productivity in silvopastoral system evidenced that the plant tends to respond differently to cutting management when compared to the monoculture system. In the monoculture system, the recommended height for greater TDM yield and better leaf/stem ratio in the rainy period and the rainy/drought transition period was 80 cm, maintaining the residue height at 40 cm. As for SSP, cutting height of 70 cm presented the highest TDM and leaf/stem ratio for the two evaluated periods, maintaining the residue height at 40 cm.
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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".