Drip application of methyl bromide alternative chemicals for control of soilborne pathogens and weeds
Bibliographic record
Abstract
BACKGROUND: Producers of several high-value crops in California have traditionally used preplant soil fumigation with methyl bromide/chloropicrin combinations. Although methyl bromide has been phased out since 2005, several crop industries, including cut flower producers, have continued methyl bromide use under Critical Use Exemptions, a provision of the Montreal Protocol. This research was conducted to evaluate newer, emerging methyl bromide alternative chemicals. RESULTS: Two field trials were conducted to test several emerging chemicals in combination with metam sodium as replacements for methyl bromide. Emerging chemicals included 2-bromoethanol, dimethyl disulfide, furfural, propylene oxide and sodium azide. Weed and pathogen populations were measured after chemical application, and seed viability was assessed from weed seed previously buried in the plots. In the first trial, the emerging chemicals did not improve pest control compared with metam sodium alone. However, in the second trial, several of these chemicals did improve the pest control performance of metam sodium. CONCLUSIONS: The emerging alternative chemicals have the potential to provide better control of soilborne pathogens and weeds when used with metam sodium than metam sodium alone. Registration of these materials could provide California growers with a broader choice of tools compared with the limited methyl bromide alternatives now available.
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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 | 0.001 | 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".