Phosphorus Sources and Rates Associated with Nitrogen Fertilization in Mombasa Grass Yield
Bibliographic record
Abstract
Nitrogen (N) and phosphorus (P) deficiency is one of the important causes of degradation of cultivated pasture under tropical conditions. The aim of this study was to evaluate phosphate rates and sources, and N rates on the concentration and uptake of N and P, and shoot dry mass (SDM) yield of Megathyrsus maximum grass cv Mombasa in an Ultisol. The trial was carried out in a greenhouse in pots with 4.0 dm−3 of soil. The experiment was arranged in a completely randomized design with four replicates. The 3 × 3 × 3 factorial treatments consisted of phosphorus sources [reactive rock phosphate from Morocco (RPM), reactive rock phosphate from Algeria (RPA) and triple superphosphate (TSP)], three phosphorus rates (0, 150, and 300 mg kg−1), and three N rates (0, 250, and 500 mg kg−1). The SDM and tillering of Mombasa grass were significantly influenced with the TSP, RPM, and RPA application associated with N fertilization. The RPM, RPA, and TSP met the nutritional demands of Mombasa grass. The three P sources showed the same effect on the total N uptake by Mombasa grass. The P use efficiency (PUE) when fertilizer-P sources were added alone by Mombasa grass was <12% of the added P, and PUE decreased as follows: TSP > RPA > RPM. When P and N-fertilizer were added together, the fertilizer-N use efficiency (NUE) was 62%. The reactive phosphate (RPM and RPA) is an efficient P sources for Mombasa grass, but requiring higher rate of application compared to TSP source.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".