Detection of High Concentrations of Organic Acids in Fish Emulsion and Their Role in Pathogen or Disease Suppression
Bibliographic record
Abstract
Fish emulsion (FE) added to a sandy-loam soil at 1 and 2% rates reduced the viability of Verticillium dahliae microsclerotia by 39 and 74% in 1 day, 87 and 98% in 3 days, and 95 and 99% in 6 days, respectively. The immediate kill of microsclerotia indicated that FE contains toxic substances. We found in FE high concentrations (400 mmol/liter) of organic acids, including some known toxicants. Glycolic, acetic, formic, n-butyric, and propionic acids were the major organic acids detected in FE at the proportions of 52.5, 26.9, 7.9, 7.2, and 4.7%, respectively. In solution assays, the viability of V. dahliae microsclerotia treated for 24 h in 1, 2, 5, and 10% FE (pH 3.6 to 3.0) or a mixture of organic acids (pH 4.1 to 3.9) equivalent to the proportions in FE was reduced by 74, 94, 97, and 99% or 81, 91, 98, and 99%, respectively. The viability of microsclerotia was increased when the treatment solutions were buffered to pH 6.0. The organic acids mixtures and formic (0.025%) and acetic (0.1%) acids were toxic to Pythium ultimum. A mixture of organic acids (1, 2, and 4%) provided immediate protection of cucumber seedlings from damping-off in P. ultimum-infested muck and sandy-loam soils but not in peat-based mix. FE (1 and 2%) provided immediate protection of cucumber seedlings from damping-off in an infested muck soil, and disease protection was consistent when planting was delayed for 7, 14, and 28 days after adding FE. FE (1, 2, and 4%) did not provide immediate protection of cucumber seedlings from damping-off in a P. ultimum-infested peat-based mix; however, disease suppression was evident when planting was delayed for 7, 14, and 21 days after adding FE. Real-time polymerase chain reaction analyses of the peat-based mix indicated that the P. ultimum populations in the FE-amended mix declined over time. This study suggests that these organic acids in FE played a major role in pathogen or disease suppression, depending on the soil and substrate.
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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".