Rust-spotted North American Ginseng Roots: Phenolic, Antioxidant, Ginsenoside, and Mineral Nutrient Content
Bibliographic record
Abstract
Rusty root is a major problem in ginseng production worldwide as it reduces root quality. Full characterization of rusty root is unavailable, and necessary for development of effective control measures. A comparison of phenolics, antioxidants, ginsenosides, and mineral nutrient content of rusted and non-rusted tissue from disease-free roots is reported. Periderm and adjacent tissues of 4-year-old North American ginseng roots ( Panax quinquefolius L.) had a total phenolic content of 3.05 mg·g -1 dry weight (as gallic acid equivalents), which was increased 53% by rust-spotting. Antioxidant activity increased with phenolic content and was 33% higher (3.6 vs. 2.7 mg·g -1 dry weight as ascorbic acid equivalents) in rust-spotted tissue. Total ginsenoside content was higher (139.1 vs. 119.4 mg·g -1 ) in healthy than in rust-spotted tissue, the latter reflecting a significant decrease in four of the major ginsenosides (Rb 2 , Rc, Rd, and Re). The Rg group was higher (38.0 vs. 29.9 mg·g -1 ) in healthy than in rust-spotted tissue. The mineral elements N, P, Ca, Mg, Zn, Mn, and Fe were higher, and K lower (21%) in rust-spotted tissue than in healthy tissue.
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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 | 0.001 | 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".