Yield of Brachiaria in Function of Natural Phosphate Application and Liming in Pará Northeast
Bibliographic record
Abstract
Forage plants of the genus Brachiária show excellent adaptation to poor soils with high acidity in the region. They present good response to phosphate fertilization and tolerant to soil with higher humidity. The soils of Amazonia are characterized mainly by high acidity, low availability of phosphorus and high saturation of aluminum. Under these conditions, aluminum tends to fix the phosphorus, making it necessary to apply higher doses to supply the need for fodder, justifying the need to apply corrective acidity material. The objective was to evaluate the pH of the behavior and productivity of Brachiaria brizantha cv. Xaraés by using Arad rock phosphate and limestone dolomite in a yellow Latosol of medium texture collected from the 0-20 cm layer. The treatments were: soil only (T1); soil with the addition of lime (T2); soil with added Arad 30 days before planting (T3); soil with the addition of Arad on planting (T4); soil with the addition of Arad and liming 30 days before planting (T5); and soil with the addition of Arad and liming on planting (T6), distributed in five replications, totaling 30 experimental units. At 45 days of germination, evaluated the plant height (HP) and number of leaves (NL), culminating with the courts to obtain the shoot fresh matter (SFM) and dry matter (FDM), the other cuts made every 30 days. pH variations responded positively to the treatments using lime to increase the pH to levels close to 6.5. For HP variables, NL, SFM and SDM the highest increases were obtained for treatments under the influence of limestone (T2) and limestone + Arad 30 days before planting (T5). The natural phosphate fertilizer in combination with liming showed significant results for all parameters.
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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".