Phytopythium vexans Associated with Apple and Pear Decline in the Saïss Plain of Morocco
Bibliographic record
Abstract
An extensive survey conducted in the Saïss plain of Morocco during the 2017–2018 growing season revealed that 35 out of 50 apple and pear orchards were infested with a pathogen that causes the decline disease. Morphological and phylogenetic tree analyses using the cox II gene allowed us to identify the pathogen as Phytopythium vexans. Interestingly, no Phytophthora and Pythium species were isolated. The occurrence and prevalence of the disease varied between locations; the most infested locations were Meknes (100%), Imouzzer (83%), and Sefrou (80%). To fulfill Koch's postulate, a greenhouse pathogenicity test was performed on the stem and collar of one-year-old healthy seedlings of apple rootstock M115. Symptoms similar to those observed in the field were reproduced in less than 4 months post-inoculation with root rot disease severity ranging from 70 to 100%. The survey results evidenced that apple rootstocks, soil type, and irrigation procedure may contribute significantly to the occurrence of the disease. The disease was most prevalent in drip water irrigation and sandy-clay soil on wild apple rootstock. Accordingly, a rational drip advanced watering system and good sanitation practices could eliminate water stagnation and help prevent the onset of this disease. It was concluded that Pp. vexans occurrence may be strongly influenced by irrigation mode and type of soil. Therefore, the obtained findings of this study could help to better understand the recurrence of this disease and to develop a reliable integrated strategy for its management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".