Photosynthetic Activities, Phytohormones, and Secondary Metabolites Induction in Plants by Prevailing Compost Residue
Bibliographic record
Abstract
Compost residue enriches soil health with the potential to enhance plant metabolism and hormonal balance, but has not yet been studied. A study was performed to determine how prevailing compost residue induces tomato (Solanum lycopersicum ‘Scotia’) plant morpho-physiology, phytohormones, and secondary metabolites. Plants were grown in soils with a previous history of annual (AN) and biennial (BI) compost amendments. The controls were soil without compost (C) amendment and municipal solid waste compost (MSWC) alone. The MSWC- and AN-plants had similar and significantly (p < 0.05) highest growth and photosynthetic activities compared to the BI- or C-plants. Total phenolics and lipid peroxidase activity were significantly (p < 0.001) high in BI-plants, while hydrogen peroxide and antioxidant capacity were significantly (p < 0.001) high in AN-plants. MSWC-plants recorded the highest cis-abscisic acid, followed by AN-, and then BI- and C-plants. Cis-zeatin, trans-zeatin, and isopentenyladenine ribosides were detected in the MSWC- and AN-plants but not in the BI- or C-plants. Furthermore, gibberellins GA53, GA19, and GA8 were high in the MSWC-plants, but only GA8 was detected in the AN plants and none in the others. Besides, MSWC plants exhibited the highest content of 1-aminocyclopropane-1-carboxylic acid. Conjugated salicylic acid was highest in the BI-plants, while jasmonic acid-isoleucine was highest in MSWC-plants and C plants. In conclusion, prevailing compost chemical residues upregulate plant growth, phytohormones, and metabolic compounds that can potentially increase plant growth and abiotic stress defense. Future work should investigate the flow of these compounds in plants under abiotic stress.
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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 | 0.000 |
| 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".