Effect of iron and nitrogen on the development of<i>Helminthosporium solani</i>and potato silver scurf
Bibliographic record
Abstract
Silver scurf is a surface blemish disease of potato (Solanum tuberosum L.) tubers caused by Helminthosporium solani Durieu & Mont. Silver scurf is becoming a disease of high economic impact. In this study, the effect of different iron (FeSO4, FeCl2) and nitrogen (NaNO2, NaNO3, NH4Cl, NH4NO3) salts on H. solani conidial germination and on potato silver scurf development was evaluated. The results show that iron and nitrogen salts affect in vitro germination of H. solani conidia. Conidia were particularly sensitive to FeSO4 and FeCl2. These salts completely inhibited conidial germination and were shown to be toxic at a concentration of 0.9 mM. Among the nitrogen salts tested, conidia were most affected by NaNO2 and NH4Cl, which almost completely inhibited their germination at a concentration of 169.7 mM. NaNO2 was also toxic to conidia. Among the salts tested, only FeSO4, FeCl2 and NaNO2 reduced the development of silver scurf. Comparison of the effect of the different tested salts leads to the conclusion that ions Fe++ and NO2 − have toxic effects on the conidia and repressive effects on silver scurf development while NO3 − and NH4 + have no toxic effect on conidia and no repressive effect on silver scurf development.
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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".