The effect of nitrogen treatment on the anthacyanine and polyphenols content and ORAC factor of <i>Aronia melanocarpa</i> grown in Maryland (1042.5)
Bibliographic record
Abstract
Black chokeberry or Aronia melanocarpa is a small fruit‐bearing shrub in the rose family. Although it is native to Maryland, its range nowadays is from Newfoundland, west to Ontario, south into Alabama, and east to Georgia, and hardy to Zone 3. Aronia is a landscape quality plant, susceptible to few pests and diseases that persist in soils and temperate climatic conditions. It is an ideal candidate for organic fruit production. The Aronia fruit has nutraceutical qualities, heightening its marketability and sales potential as a value‐added product. There is currently great interest in fruits and vegetables that contain high concentrations of flavonoids, considered potent antioxidants. Some recent studies have implicated the relationship between in‐field plant nutrient fertility and antioxidant production in aronia. Here we present the data for the antioxidant content of Aronia melanocarpa as a function of the difference of age, amount of time spent in the sun or shade, and nitrogen treatment levels of crops. We have shown that the level of nitrogen treatment in the soil influences the antioxidant capacity significantly. Detailed measurements and analysis of anthocyanin and polyphenols as well as ORAC factor will be presented and discussed. The aim of the project is to determine the treatment that produces the highest capacity of antioxidants in aronia. Grant Funding Source : Supported by Grant T34GM008411, from the National Institute of General Medical Sciences
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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".