Bibliographic record
Abstract
Abstract Methyl bromide (MeBr) has been used for several decades for preplant (PRE) soil fumigation in high-value agricultural and horticultural crops because it can provide broad-spectrum control of insects, nematodes, pathogens, and weeds. However, MeBr has been identified as an ozone-depleting chemical and is associated with hazards to human heath, plants, and animals. Therefore, a global agreement to gradually phase-out ozone depleting chemicals was made with the signing of the 'Montreal Protocol' in 1987 and research for effective and sustainable alternatives to MeBr has been a priority since 1995. Several alternative fumigants and non-chemical alternatives for weed control have been tested. In many agricultural systems the phase-out of MeBr presents a critical challenge because alternative pest control measures are ineffective, costly, or pose hazards to the environment and human health. In this paper, we review the status of MeBr alternatives with a focus on weed control in high-value cropping systems. It is concluded that no currently available alternative chemical or management practice has the same broad-spectrum efficacy and consistency as MeBr. Because the development of a single alternative to MeBr is unlikely, weed control in many high-value fruit, vegetable, and ornamental crops will become an even greater challenge in the absence of MeBr. Development of crop- and region-specific integrated pest management systems that include appropriate fumigants, herbicides and cultural practices will be necessary to maintain productivity at levels and prices that meet current grower and consumer expectations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".