Use of Organo-Mineral Fertilizers in Grain Sorghum as Reverse Logistics of Organic Residues
Bibliographic record
Abstract
Organo-mineral fertilizers are an opportunity for technological innovation, because allow the correct disposal of waste from various agroindustrial sectors, which is a global problem, in order to add value to the by-product generated, as prioritized in reverse logistics. In this sense, the objective of this work was to evaluate the effect of organic matter sources on the composition of organo-mineral fertilizers in relation to the exclusive use of mineral fertilizers in cultivation of grain sorghum. The experiment was carried out at the Experimental Farm of the Federal Institute of the Triângulo Mineiro, located in the municipality of Campina Verde, State of Minas Gerais, Brazil. The experimental design was a randomized block with eight treatments and four replications arranged in a 4 × 2 + 2 factorial scheme, corresponding to: four levels of organo-mineral fertilizers (70, 100, 130 and 160% of the recommended dose of phosphorus), two sources of organo-mineral fertilizers (sewage sludge and filter cake), and two controls (without and with recommended mineral fertilization). The evaluations were: height of stem, number of leaves and stem diameter at 30, 60, and 90 days after sowing (DAS); total plant height; dry mass of plant shoot at 90 DAS, in vitro digestibility of organic matter at 90 DAS; the relationship of leaf area/ leaf and leaf area/ plant at 90 DAS. All parameters obtained a significant effect for the levels of organo-mineral fertilizer, independent of organic source, except to number of leaves and stem diameter. However, the relationship between the two organic sources was not significant just to plant height at 60 DAS. Interaction between fertilizer levels and organic source occurred to plant height at 90 DAS, dry mass per plant at 90 DAS and in vitro digestibility of organic matter. There was good adjustment in the quadratic regression equation for sorghum growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".