Hormesis of 2,4-D Choline Salt in Biometric Aspects of Cotton
Bibliographic record
Abstract
Plant hormesis is a phenomenon that involves the presence of toxic compounds at high doses but can be beneficial at low doses. Thus, the aim of this study was to use dose-response curves to assess the effect of hormesis caused by sub-toxic of 2,4-D choline herbicide on biometric variables of cotton plants. The study adopted a completely randomized experimental design with seven replications, and the treatments consisted of nine fractions of the average rate indicated on the 2,4-D choline salt herbicide label: 0 (control); 0.4275; 0.855; 1.71; 3.42; 8.55; 17.1; 34.2 and 68.4 g ae ha-1 applied at phenological stages V4 or B4 of cotton plants. The plants were assessed for the main morphological parameters. The results were subjected to analysis of variance and, when significant, the hormesis model was tested aiming to describe the dose-response curves with low rates stimulation. The maximum hormesis effect for the variables plant height and number of leaves in cotton plants at stage V4 was estimated, in due order, for sub-doses between 1.14 and 3.02 and 1.37 and 5.54 g ae ha-1 of 2,4-D choline. The hormesis effect was not significant for total dry matter production when 2,4-D choline was applied at stage V4, irrespective of the year of study. Sub-doses between 0.855 and 1.71 g ae ha-1 of 2,4-D choline salt applied at stage B4 caused hormesis in the height, number of leaves, shoots dry matter and total dry matter of cotton plants.
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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".