Molecular detection, virulence, and mycelial compatibility of <i>Macrophomina phaseolina</i> isolates associated with chickpea wilt in Sinaloa and Sonora, Mexico
Bibliographic record
Abstract
Three Macrophomina species (M. phaseolina, M. pseudophaseolina, and M. euphorbiicola) associated with various crops worldwide have been distinguished to date by DNA sequence analysis; however, no studies have been conducted to identify Macrophomina species occurring on chickpea in Mexico. The aims of this study were to identify Macrophomina isolates associated with chickpea wilt through the use of species-specific primers, as well as to determine their virulence and mycelial compatibility. During the 2019 growing season, 58 Macrophomina isolates were obtained from symptomatic plants collected from 19 chickpea crops distributed in the states of Sinaloa and Sonora, Mexico. The identity of all 58 isolates was determined by PCR using three sets of primers specific to three Macrophomina species (M. phaseolina, M. pseudophaseolina, and M. euphorbiicola). Virulence was determined by inoculating chickpea seedling roots with a mycelial suspension and disease severity was assessed 30 days after inoculation. Molecular detection with species-specific primers indicated that all isolates belong to M. phaseolina, with significant differences found in their virulence. Mycelial compatibility testing showed that there are at least six mycelial compatibility groups of M. phaseolina distributed in chickpea fields in Sinaloa and Sonora. This information will serve as a basis for future studies on the epidemiology and management of the disease caused by M. phaseolina on chickpea in Mexico.
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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".