Calla lily production in enrofloxacin-contaminated soil and manure: An attractive alternative coupling income generation with antimicrobial removal from the environment
Bibliographic record
Abstract
Enrofloxacin (Enro) is often detected in soil and animal manure used for crop production and phytotoxic responses have been observed in plants grown under antimicrobial presence. In the present paper, we investigated the effects of the presence of Enro in soils (1.9 mg kg -1 ) and manure (50.4 mg kg -1 ) in growth and flower production of calla lily plants ( Zantedeschia aethiopica ). We also reported the accumulation and distribution of Enro between plant tissues aiming to evaluate the safety of commercializing plants produced under Enro-contaminated conditions. The presence of Enro in soils and manure did not affect plant growth and flower production and did not induce any physiological effects in plants (as evaluated by photosynthetic pigment, hydrogen peroxide concentration, superoxide dismutase and catalase activity in leaves). Plants accumulated Enro mainly in their roots, restraining its translocation to shoots, which contributes to the safety of the commercialization of their flowers. However, when commercialized as pots, the amount of Enro carried by plants is a matter of concern, and therefore, selling pot plants must be avoided. Due to their tolerance and capacity to remove Enro (up to 14.76% of Enro from contaminated soil and/or manure), plants are indicated for phytoremediation programs.
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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 | 0.001 | 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".