Effect of host genotype on biocontrol of white root rot in <i>Pyrus communis</i> L. rootstocks by <i>Trichoderma harzianum</i> and <i>Bacillus</i> spp.
Bibliographic record
Abstract
Abstract A collection of Bacillus and Trichoderma isolates from Iran was investigated for the biological control of pear white root rot caused by Rosellinia necatrix . Among the isolates, B. amyloliquefaciens AP4, B. siamensis AP8 and T. harzianum T20a were selected based on their growth inhibition of R. necatrix in dual cultures, as well as by volatiles, diffusible extracts and culture filtrates. Four pear rootstocks (Pyrodwarf, OHF40, OHF60 and Williams) were assessed for white rot in the greenhouse following soil amendment with the three isolates. For OHF40 rootstock, none of the three isolates significantly reduced disease severity, whereas all three isolates significantly reduced disease severity for OHF69 rootstock. For Pyrodwarf rootstock, only T. harzianum T20a and B. amyloliquefaciens AP4 significantly reduced root rot, but all three isolates significantly reduced leaf fall. For Williams rootstock, all three isolates significantly reduced root rot, but only T. harzianum T20a significantly reduced leaf fall. Thus, the effectiveness of both the Bacillus and Trichoderma isolates was highly dependent upon the pear genotype. The lowest levels of white rot symptoms were observed in the Williams‐ T. harzianum T20a interaction resulting in root rot severity of 46.6% and leaf fall of 4.7% at 70 dpi. While the effect of plant genotype on biocontrol activity has been reported frequently for Trichoderma , this is one of the first to report such an effect with a Bacillus biocontrol agent. Both Bacillus and Trichoderma can be effective biocontrol agents of pear white rot, but the plant genotype can have a major impact on their effectiveness.
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.
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) | 0.001 | 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".