Agronomic Efficiency of Phosphorus Fertilizers With Associate Technology in Soy Crop in Cerrado Soil
Bibliographic record
Abstract
For commercial soybean production, the presence of phosphorus in the soil is essential, not only to increase productivity but also because it affects basic functions in plant metabolism. Phosphate fertilizers have low efficiency in Cerrado soils. For this reason, the use of technologies associated with phosphate fertilizers is important to increase their efficiency in the soil. The experiment was conducted at Fazenda Rio Brilhante in Coromandel, MG. The experiment was laid out in a randomized block design in a 4 × 4 + 1 factorial arrangement. Treatments consisted of four phosphate fertilizer sources (MAPCONVENCIONAL, MAPpol 1, MAPpol 2, and FOM), four P2O5 doses (40, 80, 120, and 160 kg ha-1), and the control treatment (no phosphorus application). The soybean cultivar RK8115 IPRO with a plant population of 340 thousand plants per hectare was used. The experimental plots consisted of five planting lines with a spacing of 0.5 meters and a length of 7 meters. In the experiment, phosphorus leaf, morphological evaluation of plant height, stem diameter, number of stems, and pods were measured. For plant biomass, the dry matter of leaves, stems, and pods were determined. For yield evaluation, the calculation of productivity and RAE was compared with MAPCONVENCIONAL. For sources, data were subjected to analysis of variance, and means were separated by Tukey’s rate test (p < 0.05). For P2O5 doses, regression model fitting was performed using the ExpDes.pt package of R Studio software. Morphological assessments responded linearly to P doses, except for DPM. Leaves and pods P content and yield were affected by P dosage and P sources, with a quadratic response to P dosage. Maximum yield efficiency was achieved at P2O5 doses of 122.73; 145.07; 112.03; and 94.71 kg ha-1, with yields of 3818.30; 4064.67; 4089.03; and 3952.63 kg ha-1 for MAPCONVENCIONAL, MAPpol 2, MAPpol 1, and FOM, respectively. However, MAPpol 1 and FOM provided a dose reduction of 26 and 15 compared to the maximum yield of MAPCONVENCIONAL, respectively.
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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".