Characterization of newly recorded <i>Pythium mamillatum</i> AJA, causing cucumber root rot in Iraq: Implications for disease management in sustainable agriculture
Bibliographic record
Abstract
Pythium mamillatum is an emerging pathogen responsible for root rot and wilt diseases in cucumber (Cucumis sativus), resulting in significant crop losses in Iraq. The present study examined the occurrence, distribution, pathogenicity, and genetic characterization of P. mamillatum strain AJA in Iraq, with broader implications for sustainable agricultural practices. Field surveys were conducted to collect symptomatic cucumber root samples from Al-Tahiria, Al-Azizia, and Al-Badah districts revealed disease incidences of 37%, 35%, and 21%, respectively. Infected plants exhibited symptoms of root rot and wilting. According to molecular research, the Iraqi strain, Pythium mamillatum AJA, accession No. MN460315.1 was 100% genetically related to strains from China, the USA, and Canada, indicating a shared evolutionary origin. Through inhibiting seed germination from 10% on the third day to 90% on the seventh day of inoculation, P. mamillatum (strain AJA) demonstrated significant losses to local Iraqi cucumber crops. The rapid spread of agriculture, its valuable genetic similarity with strains established in other regions worldwide, and its pathogenic viewpoint highlight its increasing threat. The study emphasizes the importance of employing effective disease control techniques within the framework of sustainable agriculture. Reducing the effect of this infection mostly depends on early identification, seed treatments, and constant pathogen monitoring. Maintaining crop health and guaranteeing long-term agricultural resilience also depend on sustainable farming methods that reduce the use of chemical pesticides and advance integrated pest management (IPM).
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".