Characterization of <i>Trichoderma</i> spp. and their antagonistic activity against soilborne fungi associated with chickpea wilt in Sinaloa, Mexico
Bibliographic record
Abstract
Chickpea wilt, caused by a complex of soilborne fungi (Fusarium spp. Macrophomina phaseolina, Rhizoctonia solani, Sclerotium rolfsii, and Sclerotinia sclerotiorum), is the most important disease of chickpeas (Cicer arietinum) in Mexico. The aims of this study were to characterize Trichoderma isolates using a combination of phenotypic and molecular approaches and to evaluate their antagonistic activity against soilborne fungi associated with chickpea wilt. A total of 30 Trichoderma isolates were obtained from rhizospheric soil samples collected from chickpea fields in different locations of Sinaloa, Mexico. Dual confrontation assays showed the potential antagonistic effect of Trichoderma isolates against F. languescens, M. phaseolina, R. solani, S. rolfsii, and S. sclerotiorum. Five Trichoderma isolates (FAVF335, FAVF340, FAVF345, FAVF349, and FAVF351) exhibited mycelial growth inhibition of the five pathogens that ranged from 56 to 71%. These isolates were characterized using cultural, morphological, and molecular studies and tested in vivo for their ability to control soilborne pathogens in two chickpea cultivars (Blanco Sinaloa-92 and P2245) under greenhouse conditions. Phylogenetic analysis based on a combined ITS, EF-1α, and rpb2 sequence dataset identified T. afroharzianum (FAVF345, FAVF349, and FAVF351) and T. longibrachiatum (FAVF335 and FAVF340). Coating of chickpea seeds with T. longibrachiatum (FAVF335 and FAVF340) significantly reduced the disease severity and improved the plant growth-promoting attributes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".