Salicylic acid-mediated growth promotion, pigment enhancement, and secondary metabolite augmentation in <i>Brassica juncea</i> L. plants under thiamethoxam pesticide stress
Bibliographic record
Abstract
Thiamethoxam (TMX) is a second-generation insecticide and belongs to the neonicotinoid class of pesticides. These synthetic compounds are applied to food crops to eliminate pests, particularly insects, and to maintain yields. Consequently, due to their higher solubilities in water, these systemic compounds get incorporated into the edible plant tissues and show impaired growth and developmental aspects. The objective of the present study was to evaluate the harmful effects of TMX pesticide on Brassica juncea L. and to uncover the defense responses exerted by the salicylic acid (SA) to curtail the losses and maintain the integrity of B. juncea field plants for 30, 45, and 60 days after growth. Experimentation with field plants was conducted, and some of the morphophysiological, biochemical, and secondary metabolites associated parameters were investigated in the B. juncea crop. The morphological metrics were found to be lowered in TMX stress conditions. Whereas the contents of photosynthetic pigments, including total chlorophyll content, were lowered, on the contrary, carotenoid and xanthophyll contents were enhanced under the TMX stressed conditions. The gaseous exchange parameters also showed a decline in the observed values. Subsequently, the enzymatic antioxidants and phenolic contents were marked by an increase under the TMX-stressed plants. Notably, the activities of antioxidative enzymes, such as superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APOX), were significantly enhanced in plants supplemented with exogenous SA. The highest concentration of SA, such as SA3 (1mM), showed significant stress ameliorative potentials in all the studied parameters.
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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".