Plant Growth, Antioxidative Enzymes, Lipid Peroxidation and Organic Solute Contents in Mulungu Seedlings (Erythrina velutina) Under Different Field Capacities
Bibliographic record
Abstract
Erythrina velutina (mulungu) is an endemic species of caatinga found in Northeast Brazil. As a result of its rapid plant growth, the species may be an alternative for the recovery of degraded areas. Thus, the present study aimed to analyze the effects of irrigation with different field capacilities (FC): 20, 50 and 80% on plant growth, antioxidative enzyme activities, membrane lipid peroxidation and organic solute contents in mulungu seedlings under greenhouse conditions. The experiment was carried out at Instituto Federal Educação, Ciência e Tecnologia do Ceará (IFCE)-Campus Maracanaú, Ceará, Brazil. Under the presented experimental conditions, E. velutina plants showed higher growth variables (dry matter yield and leaf area) when submitted to daily irrigation of 50% of FC. Irrigation at 20% of FC caused a small water deficit. However, 80% of FC watering may have resulted in an excess of water. In general, despite the reduction in plant growth in plants irrigated at 20% of FC, the activities of the antioxidant enzymes did not differ substantially between treatments. In general, the lowest organic solute contents were detected in irrigations at 20 or 80% of FC.
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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 | 0.001 |
| 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".