Decay of Root Debris after Harvesting American Ginseng (Panax quinquefolius) and Changes in Soil Chemistry and Microbiology
Bibliographic record
Abstract
Commercial harvesting of American ginseng (Panax quinquefolius) results in root debris in the soil, but the rate of decay is unknown. In this study, post-harvest root debris decayed mostly over the fall and winter, with almost no ginseng debris remaining in the soil by late spring of the following year. However, a small number of intact pencil-shaped roots were able to survive after harvest and sprout the following spring without any evidence of root decay. Root rot lesions were observed, which included many associated with the root rot pathogen Ilyonectria mors-panacis, with disappearing root rot symptoms observed in the following spring. Ginsenosides in soil were highest just prior to harvest, declining until an increase the following spring. Soil bacterial and fungal populations changed over time after harvest with several peaks in bacterial populations mostly in the fall, but this was less clear for fungal populations, which were dominated by only a few taxa. Harvesting ginseng can leave considerable debris in the soil, impacting its chemistry and microbiota. Ginseng replant disease, where the second crop shows high levels of root rot due to I. mors-panacis infection compared to low levels in the first crop, could be related to the decay of post-harvest crop debris, but additional research is needed to demonstrate this.
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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".