Use of Salines Waters and Biofertilizers in Quality of the Seedlings From Passiflora edulis Evaluated by the Dry Phytomass
Bibliographic record
Abstract
The objective of this study was to evaluate the effects of the biofertilizers (common and enriched) in substrate irrigated with saline waters on the quality of the seedlings evaluated by the phytomass from yellow Passiflora edullis. In this sense, an experiment was carried in a greenhouse at the Center of Agricultural Sciences and Biodiversity CCAB/UFCA, Crato-CE, from October/2017 to March/2018. The substrate used was a material of the first 20 cm to depth of a Red Yellow Latosol. The experimental design was completely randomized in a factorial scheme of type 5 × 3, with three replications, referring to the electrical conductivity values of the irrigation water: 0.5; 1.0; 2.0; 3.0 and 4.0 dS m-1, in the soil without the bovine biofertilizer; in treatments with common biofertilizer and, evaluated in the soil with enriched biofertilizer, conditioned in black polyethylene bags with it a maximum capacity of 5.0 kg, totaling 60 treatments. The fermented bovine biofertilizer after dilution in non-saline and non-chlorinated water (0.5 dS m-1), in the proportion of 1:3, was applied only once to 10% of the substrate volume, two days before sowing. The salinity increase of the irrigation water affected negatively the phytomass production, but with less intensity in the treatments with enriched biofertilizer. The enriched and common biofertilizer provided higher growth and consequently higher phytomass production of passion fruit seedlings in relation to the soil without the respective input, independently of the level of salinity of irrigation water.
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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) | 0.001 | 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 | 0.001 |
| 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".