Biofumigation: Opportunities and Challenges for Control of Soilborne Diseases in Nursery Production
Bibliographic record
Abstract
Soilborne diseases reduce crop performance, increase costs to the nursery producers, and can cause potential ecological damage to the natural environment. In particular, soilborne diseases caused by Phytophthora nicotianae and Rhizoctonia solani are the most economically important problems of southeastern U.S. nursery producers. Methyl bromide was widely used as a standard treatment in many parts of the world until the implementation of the Montreal Protocol. Since then, many chemical and nonchemical soilborne disease management methods have been tested but are not yet providing effective and consistent results like methyl bromide. Cover crops that belong to the Brassicaceae family can be incorporated into the soil to control soilborne diseases, and this process is widely known as biofumigation. Glucosinolates that are available inside Brassicaceae plant cells can be hydrolyzed into isothiocyanates, and these compounds are proven to be highly biocidal to many microorganisms (including fungi, oomycetes, nematodes, and bacteria), insects, and germinating weed seeds. The use of biofumigant cover crops is a newer area of research in woody ornamental nursery production that has been previously explored most extensively in row crop, vegetable, fruit, and flower production. This review article compiles previous research observations in biofumigation while emphasizing the potential of biofumigation to control diseases in nursery production caused by soilborne pathogens.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".