Fertilization With Nitrogen, Phosphorus and Potassium on Soil Fertility and Nutritional Status of Yellow Passion Fruit Plants
Bibliographic record
Abstract
The research had as objective to study the influence of the doses of nitrogen, phosphorus and potassium on soil fertility and nutritional status of yellow passion fruit plants. The experimental design was in randomized blocks in an incomplete fractioned factorial 1/2 (4 × 4 × 4), with four doses of N (150, 300, 600 and 1200 Kg-1 ha-1 yr-1 N); four doses of P2O5 (200, 400, 800 and 1600 kg-1 ha-1 yr-1) and four doses of K2O (100, 300, 500 and 700 kg-1 ha-1 yr-1). The fertilizers used were the ammonium nitrate = 32% N; triple superphosphate = 44% P2O5 and potassium chloride = 60% K2O. In the fertility of the nitrogen fertilization increased the content of phosphorus and sulfur. The doses of P2O5 increased the concentration of P in the soil. The doses of K2O influenced the increase in the content of K in the soil in the harvest 2013/2014. There was an interaction of the doses of N and K2O in the availability of K in the soil in the harvest 2012/13 with the maximum levels of K, in the doses of 200-400 kg N ha-1 and 600 to 700 kg ha-1 of K2O. In the nutritional state the yellow passion fruit plants was influenced by the doses of N for the sulfur content of the leaves. The maximum content of S leaf concentration of 3.63 g kg-1 was obtained in the dose estimated at 1120 kg ha-1 of P2O5.
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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".