Abscisic Acid Sprayed on Olive Tree (Olea europaea L.) Affects the Phenolic Composition of Olive Fruit Cultivars
Bibliographic record
Abstract
The aim of this research was to study the effect of abscisic acid pre-harvest treatment on the phenolic composition of olive fruits. To that end we applied abscisic acid (i.e., 50 mg/L and 100 mg/L) on Arbequina and Picual olive trees. Two different days of harvesting (i.e., day 3 and 6 after treatment) were also included in the study. Although the results obtained depended on the cultivar and on the day of harvesting a general trend was established. The treatment with 50 mg/L of abscisic acid resulted in higher total phenol content but significant decrease in the DPPH activity. In contrast, olives treated with 100 mg/L abscisic acid resulted in higher total phenol content, DPPH activity and contents of oleuropein, hydroxytyrosol and phenolic acids as compared with controls. The best values of total phenol content and IC50 were obtained for treated Picual olives (727.75 mg gallic kg-1 and 889.72 µg/ml, respectively) whereas the highest values of oleuropein and hydroxytyrosol were measured for treated Arbequina olives (508.94 and 559.67 mg kg-1, respectively). Phenolic acid content was also higher in Picual olives treated with 100 mg/L of abscisic acid. Particulary, values ranged from 7.26 mg kg-1 for caffeic acid to 92.38 mg kg-1 for chlorogenic acid. Exogenous abscisic acid applied to olive trees is a promising agronomic practice to obtain olives enriched in antioxidants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".