Initial Growth of Corn Using Human Urine, Cassava Wastewater and Cattle Manure as Source of Nutrients
Bibliographic record
Abstract
The present study aimed to analyze the initial growth of the corn hybrid AG 1051 cultivated in soil fertilized with human urine, cassava wastewater and cattle manure. The experimental design was completely randomized with four replicates and eight treatments: T1 (Control – without fertilization), T2 (HU – Human urine), T3 (CW – Cassava wastewater), T4 (BM – Cattle manure), T5 (BM + HU – Cattle manure + Human urine), T6 (BM + CW – Cattle manure + Cassava wastewater), T7 (HU + CW – Human urine + Cassava wastewater) and T8 (HU + CW + BM – Human urine + Cassava wastewater + Cattle manure). ESI (emergence speed index) and E% (emergence percentage) were determined by daily counting all seedlings emerged in a period of seven days and, at 15 DAS (days after sowing), plant height was measured. The use of cattle manure led to higher ESI and E% compared with the other treatments, as well as the variable plant height. For production variables, T5 caused highest increment in shoot dry phytomass and there were no significant differences between treatments for shoot dry phytomass. It was concluded that T4, T6 and T5 led to higher performance in the initial growth stage.
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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".