Effect of boron nutrition on American ginseng in field and in nutrient cultures
Bibliographic record
Abstract
Field and nutrient cultures of American ginseng (Panax quinquefolius L.) were used to establish foliar symptoms related to boron (B) concentration in leaves and soils, and to evaluate radish as a time-saving model system for B nutrition. Application of excess B, 8 kg/ha versus the recommended 1.5 kg/ha, to field plantings of 2-, 3-, and 4-yr-old American ginseng plants just prior to crop emergence caused, within 4 wk after crop emergence, leaf symptoms of chlorosis followed by necrosis starting at the tips and progressing along the margins. The B concentration in leaves of 2-4-yr-old plants receiving 1.5 kg/ha B was 30 μg/g dry mass compared to 460 μg/g dry mass where 8 kg/ha B was applied. Similarly, B concentration in soils receiving the lower B concentration was 1.8 μg/g dry mass and 2.2-2.8 μg/g dry mass where the higher B concentration was applied. Application of 8 kg/ha B reduced the dry yield of 3rd-yr roots by 20% from 2745 kg/ha to 2196 kg/ha and 4th-yr roots by 26% from 4130 kg/ha to 3071 kg/ha. Ginseng seedlings and radish were grown under greenhouse conditions in nutrient culture with four B concentrations ranging from 0 mg/L to 10 mg/L. At 5 mg/L and 10 mg/L ginseng and radish developed typical leaf B toxicity symptoms similar to those described above for field-grown plants. Increasing B in the nutrient solution from 0.5 mg/L to 10 mg/L decreased, in a linear fashion, the root and leaf dry mass of ginseng, but not radish. Given the many similarities of ginseng and radish to B utilization, radish might be used as a time-saving model system for the study of B, and other micronutrients, in the slow-growing perennial ginseng.
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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) | 0.001 | 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".