Fermentation of Foc TR4-infected bananas and Trichoderma spp
Bibliographic record
Abstract
Fusarium wilt (also known as Panama disease) is one of the most destructive banana diseases, and greatly hampers the global production of bananas. Consequently, it has been very detrimental to the Chinese banana industry. An infected plant is one of the major causes of the spread of Fusarium wilt to nearby regions. It is essential to develop an efficient and environmentally sustainable disease control method to restrict the spread of Fusarium wilt. We isolated Trichoderma spp from the rhizosphere soil, roots, and pseudostems of banana plants that showed Fusarium wilt symptoms in the infected areas. Their cellulase activities were measured by endoglucanase activity, β-glucosidase activity, and filter paper activity assays. Safety analyses of the Trichoderma isolates were conducted by inoculating them into banana plantlets. The antagonistic effects of the Trichoderma spp on the Fusarium pathogen Foc tropical Race 4 (Foc TR4) were tested by the dual culture technique. Four isolates that had high cellulase activity, no observable pathogenicity to banana plants, and high antagonistic capability were identified. The isolates were used to biodegrade diseased banana plants infected with GFP-tagged Foc TR4, and the compost was tested for biological control of the infectious agent; the results showed that the fermentation suppressed the incidence of wilt and killed the pathogen. This study indicates that Trichoderma isolates have the potential to eliminate the transmission of Foc TR4, and may be developed into an environmentally sustainable treatment for controlling Fusarium wilt in banana plants.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".