Apple Scab Disease Severity in the Sais Region of Morocco and its Sensitivity to Three Commercial Fungicides
Bibliographic record
Abstract
Apple scab, Venturia inaequalis (Cooke) G. Winter, results in numerous fungicide applications in the Sais region of Morocco. We conducted the study to determine the susceptibility of cultivars through field survey and to evaluate the sensitivity of V. inaequalis to three fungicides using both in vitro and in vivo methods. We surveyed 100 apple orchards and collected two samples. Disease survey showed that the cultivars were highly susceptible to apple scab (grand mean of leaf scab: Golden Delicious, 40.31%; Starking Delicious, 20.45%; and Gala, 18.92%). Results underlined no significant differences between isolates in term of inhibition rate of mycelial growth and averaged disease severity. However, both treatment and concentration were statistically significant. EC50 values ranged from 2.33 µg/ml to 7.40 µg/ml and resistance factor (RF) values of 0.55, 1.02 and 1.79 were obtained for difenoconazole, trifloxystrobin and thiophanate-methyl, respectively. In vivo tests at a concentration of 10 µg/ml on the isolate ViIF using a curative method showed a high efficacy of trifloxystrobin (96.38%), and low efficacy of thiophanate-methyl (29.65%) and difenoconazole (24.62%). V. inaequalis was most sensitive to trifloxystrobin followed by difenoconazole and thiophanate-methyl, respectively. From this work, it was recommended testing more isolates and contact fungicides in order to develop a baseline sensitivity of the pathogen population against commonly used fungicides to treat the disease, as continued usage over time and the introduction of new fungal races may result in a decrease in fungicide efficacy.
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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".