Induced resistance and control of charcoal rot in <i>Cicer arietinum</i> (chickpea) by <i>Pseudomonas fluorescens</i>
Bibliographic record
Abstract
Pseudomonas fluorescens isolate 4-92 induced systemic resistance against charcoal rot disease in chickpea (Cicer arietinum L.) caused by Macrophomina phaseolina (Tassi) Goidanich. Time-course accumulation of pathogenesis-related (PR) proteins (chitinases and glucanases) in chickpea plants inoculated with P. fluorescens was significantly (P = 0.05) higher than in control plants. The level of chitinases and glucanases increased by 6.6- to 7-fold up to 4 days postinoculation; thereafter, little decrease in the activity of PR proteins was observed. Root-colonizing populations of P. fluorescens were at a maximum 2 days after transplantation at different inoculum concentrations, and decreased over time. Inoculation of root tips of chickpea by P. fluorescens, 2,6-dichloroisonicotinic acid, and o-acetylsalicylic acid induced systemic resistance against charcoal rot. Disease was 33 to 55.5% higher in control plants than in plants inoculated with chemical inducers or P. fluorescens. Single treatment of plants with P. fluorescens increased disease resistance by 33%, whereas combined application of P. fluorescens with either of the chemical inducers was most effective in inducing the resistance by 2- to 2.25-fold. The time-course study shows that an interval of at least 2 days was required between induction treatment and challenge inoculation. Biocontrol efficacy of P. fluorescens against charcoal rot disease in chickpea was demonstrated under greenhouse conditions.Key words: biological control, induced resistance, Macrophomina phaseolina, Pseudomonas fluorescens.
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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 | 0.000 | 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".