Evaluation of different salts for the control of lettuce varnish spot: when phytotoxicity rules
Bibliographic record
Abstract
Five generally recognised as safe (GRAS) salts with antimicrobial activity were investigated for their potential use as bactericides for the control of lettuce varnish spot [Pseudomonas cichorii (Swingle) Stapp]. The phytotoxicity of salts was first assessed using greenhouse and in vitro assays. Greenhouse assays revealed that salts showed different levels of phytotoxicity. Potassium sorbate, sodium benzoate, and sodium carbonate at higher concentrations caused a noticeable decrease of growth along with foliar phytotoxicity symptoms while sodium metabisulfite and sodium bicarbonate caused exclusively foliar symptoms. Based on the phytotoxic doses 5% determined in vitro, salts can be ranked in ascending order of phytotoxicity as follows: sodium bicarbonate, potassium sorbate, sodium carbonate, sodium benzoate, and sodium metabisulfite. When applied at concentrations causing mild to moderate foliar symptoms of phytotoxicity and no noticeable effect on growth, salts did not significantly affect (p ≤ 0.01) survival of P. cichorii on lettuce leaf tissue and did not significantly reduce (p ≤ 0.01) varnish spot severity. Although sodium metabisulfite was applied at concentrations higher than the minimum inhibitory concentration and minimum bactericidal concentration, it did not affect P. cichorii survival on leaf 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".