Soil behaviour of sulfur natural fumigants used as methyl bromide substitutes
Bibliographic record
Abstract
Methyl bromide is the most widely used and most effective fumigant and is used extensively for soil fumigation. According to the Montreal Protocol of 1991, methyl bromide is categorised as an ozone-depleting chemical and its use is prohibited from 2005. Many substitutes, such as methyl isothiocyanate and methyl iodide, are not applied as widely as methyl bromide. Moreover, crushed Alliumspp. plants (garlic, leek and onion) produce thiosulfinates (Ti, R–S–SO–R′) and related compounds like disulfides, which have the same pesticide activity as methyl bromide. Therefore Allium tissues or extracts can be used in biological control and Integrated Pest Management in agriculture. The successful application of these compounds, and Allium tissues and extracts, for biological soil disinfection requires more specific knowledge regarding their subsequent fate in the soil. To obtain this, appropriate analytical methods using IR spectroscopy, SPME (solid-phase micro-extraction) and GC-MS techniques were developed and applied in the laboratory on pure compounds and on Allium tissues or extracts. The experiments revealed that thiosulfintes are stable in the atmosphere but in soil they are rapidly degraded into disulfides, which are very stable in soil. For that reason and for their general pesticide effect, disulfides are a promising alternative to methyl bromide.
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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) | 0.001 | 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) | 0.002 | 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".