BIOFUMIGATION: PROSPECTS FOR CONTROL OF SOIL BORNE PLANT DISEASES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One of the biggest worries for farmers is the spread of pathogens through the soil. These diseases are difficult to control because they are often tiny in size, buried in the soil, and frequently highly harmful even in small numbers. The Montreal Protocol on Substances that Deplete the Ozone Layer, to which the majority of countries are signatories, has restricted the use of residual pesticides for the management of soil-borne infections, and the demand for food that is free of blemishes is rising. However, it has become urgently necessary to find suitable substitutes as a result of the phase-out of methyl bromide, a significant chemical. After introducing plants that contain glucosinolate, which is digested to produce isothiocyanates (ITC) in the soil, biofumigation has emerged as a crucial procedure to control plant diseases. The existence of glucosinolates and the byproducts of their hydrolysis in soil illustrate the effectiveness and environmental impact of biofumigation. The most significant producers of bioactive chemicals are Brassica species, which makes them suitable for biofumigation applications. This review focuses on the concept, the effective application of biofumigants against soil-borne diseases, and offers several case examples to highlight upcoming difficulties for the concept's continued advancement.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it