Effect of Trichoderma on Growth and Sporangia Production of Phytophthora capsici
Bibliographic record
Abstract
Phytophthora capsici is the main agent of chili pepper root rot, causing significant yield losses in commercial fields worldwide. Management of this plant pathogen has been difficult due to its ability to develop fungicide resistance, therefore biocontrol of P. capsici appears to be a promising alternative. In this study we evaluated the effects of three species of Trichoderma: T. harzianum (Th-7), T. koningiopsis (Tk NRRL50190) and T. asperellum (Ta NRRL50191) on two mexican isolates of P. capsici (RDP-1 and RDP-2) obtained from commercial pepper fields in Aguascalientes, Mexico. The ability to inhibit mycelia growth of P. capsici was tested with in vitro assays, followed by the quantification of sporangia after dual confrontations. All Trichoderma isolates inhibited the mycelia growth of the phytopathogen, but only Ta and Tk showed mycoparasitism. Sporangia production of P. capsici RDP-1 and RDP-2 was significantly reduced by Trichoderma isolates, compared to the non-confronted control, except for the Th-RDP-2 confrontation. Sporangia of RDP-1 significantly decreased by 95.6%, 81.3% and 78% after confrontations with Tk, Ta and Th, respectively; and by 76% and 85.4% in RDP-2 by Tk and Ta, respectively. The results suggest that Ta, Tk and Th could be used as potential biocontrol agents of Phytopthora root rot, however, further studies are necessary to test the in vivo protection of Ta, Tk and Th and their synergistic effects against Phytophthora root rot of chile peppers and other P. capsici susceptible solanaceous and cucurbitaceous crops such as tomatoes, squash, melons, and cucumbers.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".