Fertilizer micro-dosing and harvesting time of indigenous leafy vegetables affect in vitro antioxidant activities
Bibliographic record
Abstract
Plant nutrient management can influence the type and level of polyphenolic compounds within leafy vegetables. Therefore, we investigated the effects of fertilizer micro-dosing and harvest time on antioxidant activities of aqueous polyphenolic extracts from Amaranthus cruentus, Ocimum gratissimum and Solanum macrocarpon. Plants were cultivated using urea alone or combined with cattle manure for three staggered harvest periods. Polyphenolics profile (RP-HPLC), DPPH, hydroxyl and superoxide radical scavenging activities, ferric ion reducing power, ferrous ion chelation and inhibition of linoleic acid oxidation were determined. Polyphenolic contents of A. cruentus (caffeic acid, myricetin, quercetin and rutin) and O. gratissimum (catechin and gallic acid) as well as antioxidant activities of the vegetables extracts (except hydroxyl radical scavenging by A. cruentus) were fertilizer micro-dose and harvest timedependent. Thus, combination of both factors highlighted the screening of optimal farming conditions for these vegetables in order to get leaf extracts possessing higher polyphenolic contents and antioxidant activities.
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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".